Psychology Handbook Volume VI
Daphne Hopkins
Psychology Handbook Volume VI
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Psychology Handbook Volume VI Edited by Daphne Hopkins
Published by College Publishing House, 5 Penn Plaza, 19th Floor, New York, NY 10001, USA
Psychology Handbook: Volume VI Edited by Daphne Hopkins
© 2017 College Publishing House International Standard Book Number: 978-1-9789-2817-6
This book contains information obtained from authentic and highly regarded sources. Copyright for all individual chapters remain with the respective authors as indicated. A wide variety of references are listed. Permission and sources are indicated; for detailed attributions, please refer to the permissions page. Reasonable efforts have been made to publish reliable data and information, but the authors, editors and publisher cannot assume any responsibility for the validity of all materials or the consequences of their use. Copyright of this ebook is with College Publishing House, rights acquired from the original print publisher, Clanrye International. The publisher’s policy is to use permanent paper from mills that operate a sustainable forestry policy. Furthermore, the publisher ensures that the text paper and cover boards used have met acceptable environmental accreditation standards. Trademark Notice: Registered trademark of products or corporate names are used only for explanation and identification without intent to infringe.
Contents Preface
Chapter 1 Comparing the Sensitivity of the MMPI-2 Clinical Scales and the MMPI-RC Scales to Clients Rated as Psychotic, Borderline or Neurotic on the Psychodiagnostic Chart Robert M. Gordon, Ronald W. Stoffey, Bethany L. Perkins
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Chapter 2 Illusory Upward Self-Motion Results in a Decrease in Perceived Room Temperature Takeharu Seno, George H. Van Doorn
Chapter 3 Designing Effective CME—Potential Barriers to Practice Change in the Management of Depression: A Qualitative Study Mandana Shirazi, Sagar V. Parikh, Ideh Dadgaran, Charlotte Silén
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Chapter 4 Investigating Cognitive Processes Underlying Reading in Arabic: Evidence from Typical and Poor Reading Performance Haitham Taha
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Chapter 5 But You Promised: Children’s Judgments of Broken Promises Karen Hussar, Jared Horvath
Chapter 6 Benefits of Combined Mental and Physical Training in Learning a Complex Motor Skill in Basketball Andrea Gaggioli, Luca Morganti, Maurizio Mondoni, Alessandro Antonietti
Chapter 7 The Best Route Is Not Always the Easiest One: Spatial References in Heuristics of Route Choice Wen Wen, Hideaki Kawabata
Chapter 8 Neural Substrates of Forward and Backward Associative Priming: A Functional MRI Study Sarah Terrien, Fabien Gierski, Stéphanie Caillies, Véronique Baltazart, Christophe Portefaix, Laurent Pierot, Chrystel Besche-Richard
Chapter 9 Socio-Emotional Status, Education, and Time-Discounting in Japanese Non-Smoking Population: A Multi-Generational Study Shoko Yamane, Taiki Takahashi, Akiko Kamesaka, Yoshiro Tsutsui, Fumio Ohtake
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Chapter 10 Do Positive School Experiences and Preference for American Culture Moderate the Association between School-Based Ethnic Discrimination and Mental Health for Filipino American Adolescents? Tzu-Fen Chang, Eun-Jin Han, Esther E. Onaga, M. Brent Donnellan
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Chapter 11 Competitive Orientations and Men’s Acceptance of Cosmetic Surgery Bill Thornton, Richard M. Ryckman, Joel A. Gold
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Chapter 12 Neuropsychological Profile of Anti-NMDA Receptor Encephalitis Laura Marcos-Arribas, Justino Jiménez Almonacid, Alberto Marcos Dolado
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Chapter 13 The Effects of Family Structure on the Development of Bilinguality Lily Halsted
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Chapter 14 The Role of Parental Involvement in Classroom Life in Greek Primary and Secondary Education Yota Xanthacou, Thomas Babalis, Nektarios A. Stavrou
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Chapter 15 A Novelty-Induced Change in Episodic (NICE) Context Account of Primacy Effects in Free Recall Eddy J. Davelaar
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Chapter 16 Does System 1 Process both Local and Nonlocal Information in Intuitive Judgment and Decision Making? Available Evidence and a Research Agenda Proposal Patrizio Tressoldi Chapter 17 Perceptions of Diversity: Global versus Local Perceptions Gizelle L. Gilbert, Candace Myers, M. Diane Clark, Shelley Williams, Angela McCaskill Chapter 18 Behavioral and Experiential Self-Regulations in Psychological Well-Being under Proximal and Distal Goal Conditions Peter Horvath, Vanessa McColl Chapter 19 The Beliefs and Attitudes about Deaf Education (BADE) Scale: A Tool for Assessing the Dispositions of Parents and Educators M. Diane Clark, Sharon Baker, Song Hoa Choi, Thomas E. Allen Chapter 20 How Emotional Context Influences Facial Preferences and Impressions Satomi Hara, Kentaro Katahira, Kazuo Okanoya Chapter 21 Profile Performance of Working Memory in Children of Elementary Schools Rita de Cássia Coutinho Vieira Fornasari, Tais Ferreira De Lima, Sylvia Maria Ciasca
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Contents
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Chapter 22 Left-Right and Up-Down Mirror Image Confusion in 4-, 5- and 6-Year-Olds Izumi Uehara
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Chapter 23 The Relationship between Consciousness of Professional Role and Work Autonomy of Rural Teachers from Sichuan Province Tianmei Zhou, Jiewei Chen, Li Luo
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Chapter 24 Development of Deterministic Thinking Scale Based on Iranian Culture Jalal Younesi, Akram Alsadat Mirafzal
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Chapter 25 Development and Evaluation of the Posttraumatic Growth Status Inventory Tatjana Alexander, Rainer Oesterreich
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Chapter 26 Interpersonal Dependency Inventory: Its Construct Validity and Prediction of Dysphoric Mood and Life Functioning via Negative Life Events Masayo Uji, Yukihiro Takagishi, Keiichiro Adachi, Toshinori Kitamura Chapter 27 Construction and Validation of the Gender Apperception Test-GAT for Children Silvana B. Gaino, Francisco Baptista Assumpção Jr., Gerson Silva Santos Neto, Victor Galvao Chapter 28 Teachers’ Knowledge and Misconceptions of Attention Deficit/Hyperactivity Disorder Keetam D. F. Alkahtani
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Permissions List of Contributors
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Preface The term Psychology is derived from 2 words, ‘psyche’ meaning soul and ‘logous’ meaning study. Through explanation, prediction and control of behavior, it helps study how humans and animals think and perceive their environment. Though it is categorized as a Humanities subject, Psychology is scientific in nature because it relies on physical evidence. The origins of this branch can be traced to Wilhelm Wundt who set up the first laboratory of Psychology at the University of Leipzig in Germany and has been fondly nicknamed as ‘The father of psychology’. He explained psychology as the study of structures of consciousness. This was followed by different perspectives by Sigmund Freud, Rogers and Maslow and Watson. An integral component of Psychology is psychotherapy, which helps ensure the well-being of people. From the conventional psychotherapies such as psychodynamic therapy to creative ways of treating the clients through music therapy, the book is well updated and illustrates all these modes in detail. The popular streams of Psychology include clinical psychology, counseling psychology and organizational behavior among numerous other disciplines. Each of these streams have a specific significance of its own and this book attempts to provide a balanced insight to its readers on all the three streams. I would like to thank all the contributors of this work who have worked tirelessly to provide us with their valuable researches and insights. Editor
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1 Comparing the Sensitivity of the MMPI-2 Clinical Scales and the MMPI-RC Scales to Clients Rated as Psychotic, Borderline or Neurotic on the Psychodiagnostic Chart Robert M. Gordon1, Ronald W. Stoffey2, Bethany L. Perkins3 1
Independent Practice, Allentown, USA Psychology Department, Kutztown University, Kutztown, USA 3 Department of Education and Human Services, Lehigh University, Bethlehem, USA 2
The purpose of this study was to assess the differences between the MMPI-2 and the MMPI-RC scales in sensitivity to levels of psychopathology. Ninety-eight clients from forensic, disability and psychotherapy evaluations were evaluated on the MMPI-2 and RC scales and rated for personality organization (neurotic, borderline or psychotic) on the Psychodiagnostic Chart. The results over-all showed support that most of the MMPI-2 scales have more clinical sensitivity than the RC scales at all levels of psychopathology and particularly at the less pathological levels. K correction does not account for the elevation differences. Most of the RC scales add little to no incremental validity to the MMPI-2 Clinical scales except for RC 1, RC 2, and RC 9 and these may be used as supplemental scales. Keywords: MMPI-2; MMPI-RC; MMPI-RF; Psychodiagnostic Chart; PDM; Psychopathology
Introduction Tellegen, Ben-Porath, McNulty, Arbisi, Graham, and Kaemmer (2003) first produced the Restructured Clinical scales (RC) to improve measurement of the core constructs of the MMPI-2 Clinical scales, but then went on to develop a separate competing form of the MMPI. Rouse, Greene, Butcher, Nichols, and Williams (2008) looked at a sample of 78,159 respondents across diverse clinical settings and found that each RC scale was highly correlated with the existing MMPI-2 contents scales; higher, in fact, than the correlation between the RC scale and its parent scale concluding that the RC scales added nothing new to the MMPI-2 scales. Binford and Liljequist (2008) compared the behavioral correlates of RCd, RC 2, and RC 4 with their original Clinical scale counterparts (Scale 2, Scale 4), and conceptually related Content scales (DEP, ASP, CYN) in an outpatient clinical sample (N = 150). The results indicated that RC 4 is a stronger predictor of several antisocial behaviors than Clinical Scale 4 or the Content Scales ASP and CYN. In contrast, RC 2 demonstrated significantly lower correlations with several behaviors conceptually related to depression than its Clinical scale counterpart or DEP. Bolinskey, and Nichols (2011) concluded that RC 4, RC 7, and RC 9 are not necessarily equivalent to those assessed by the original scales. The RC scales have higher internal consistency and discriminant validity than the original MMPI-2 clinical scales, which the authors believe, would lead to greater clinical utility. However, Gordon (2008) warned that the high internal consistency of the RC scales violates a basic assumption of complex
psychopathology. Whereas some unitary symptoms such as anxiety or anger can be assessed with scales of high internal consistency, such homogenized scales will not work well for complex diagnostic conditions such as Hysteria, Post Traumatic Stress Disorder and Borderline Personality. For example, Tellegen, et al. (2003) eliminated the Hysteria scale and replaced it with the RC 3 Cynicism scale. Dahlstrom, Welsh, and Dahlstrom (1972) stated that the items on the Hysteria scale seem mutually contradictory. The Hysteria scale has such seemingly unrelated issues such as somatic complaints, naiveté, denial of aggressive motives, unhappy home life and sexual conflicts. The RC researchers removed from the Hysteria scales the demoralization and somatic complaints items and assigned them to their own distinct scales, leaving mainly the items of naively trusting. Naiveté is an aspect of hysteria. The researchers reversed the scoring of the naiveté items and produced the RC 3 scale of Cynicism. Cynicism is neither an aspect of nor a substitute for Hysteria. The authors found that RC 3 poorly correlated with the MMPI-2 Hysteria scale; −.24 for females and −.18 for males. The RC 3 scale serves as an excellent example of the failure of the behavioral assumption that psychopathology is simply the sum of additive correlated symptoms. The RC scales have been criticized for having less clinical sensitivity than the MMPI-2 Clinical Scales. Wallace (2005) found that the majority of client MMPI-2 profiles (56%) had fewer scale elevations on the RC scales as compared to the MMPI-2 Clinical scales. In Nichols’ (2011) review of the issue, he concluded “upon the presently available weight of the evidence, the RC scales, like the MMPI content scales, the sub-
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Psychology Handbook
stantive MMPI-2-RF scales, and other content-based measures lack sensitivity and therefore may underestimate the presence, significance, and magnitude of clinical problems, a liability that may render them less than suitable for screening purposes (e.g., employment screening) for which maximal sensitivity is desirable...” (p. 16). Sellbom, Ben-Porath, McNulty, Arbisi, and Graham (2006) felt that the demoralization items, subtle items, and K correction contributed substantially to elevation differences between the MMPI-2 and RC scales. Though the item diversity of clinical syndromes would contribute to greater sensitivity of the MMPI-2 over the RC scales, it is unlikely that K is a cause of the differences. K is often lower with greater psychopathology and would not be adding to the elevation. There are currently no known published studies comparing the sensitivity of the MMPI-2 Clinical scales and the MMPIRC scales with a population of individuals diagnosed through the full dimension of psychopathology (psychotic, borderline and neurotic). Lanyon and Thomas (2013) did look at the MMPI-RF and Psychological Screening Inventory (PSI) noting that the 3 Higher Order (HO) scales of the MMPI-RF and the 3 core clinical scales of the PSI/PSI-2 were developed to broadly represent the 3 traditional categories of mental disorder: major psychiatric disorder (“psychotic”), general psychological distress (“neurotic”), and significant antisocial characteristics (“character disorder”). Their research found support for using these basic personality organizations, but the authors did not compare the sensitivity of these tests to these categories. Gordon and Bornstein (2012) developed the Psychodiagnostic Chart (PDC)1,2 to operationalize the Psychodynamic Diagnostic Manual (2006). The first axis of the PDC measures personality organization with the Overall Personality Organization scale (OPO), which helps categorized individuals as mainly operating on a psychotic, borderline or neurotic to healthy level (Bornstein & Gordon, 2012). A preliminary study of the OPO scale and PDC indicted good reliability and validity (Gordon & Stoffey, 2013).
senting a wide range from psychotic to neurotic personality organizations.
Results Hypothesis One For Hypothesis 1, we predicted that the MMPI-2 scales should show more clinical sensitivity than the RC scales at: 1) all levels of psychopathology and 2) particularly at the less pathological levels. To test this hypothesis, we calculated a series of paired-samples t tests using 8 MMPI-2 scale scores (Hs, D, Hy, Pd, Pa, Pt, Sc, Ma) and 8 corresponding MMPI-RC scale scores (RC 1, RC 2, RC 3, RC 4, RC 6, RC 7, RC 8, RC 9) within each of the three levels or categories of the Overall Personality Organization (OPO) scale. The categories were derived by dividing the 10-point OPO scale into psychotic (ratings 1 - 3, n = 13), borderline (4 - 6, n = 51), and neurotic (7 - 10, n = 33) levels. (There were no “healthy” levels of individuals in this sample so this category was labeled “neurotic.”). Within the psychotic level, the first 3 paired-samples t tests comparing MMPI-2 Hs, D, and Hy scales with the corresponding MMPI RC 1, RC 2, RC 3 scales were not significant. The paired-samples t tests comparing MMPI-2 Pd, Pa, Pt, and Sc with the MMPI RC 4, RC 6, RC 7, and RC 8 were all significant. Finally, the paired-samples t test comparing the MMPI-2 Ma scale with the MMPI RC 9 scale failed to reach significance. Taken together, within the psychotic level of the OPO, 50% of the paired-samples t tests were significant in the predicted direction (see Table 1 for a summary of the scale means, standard deviations, t values, p values and d values within the psychotic level of the OPO). Within the borderline level, the first paired-sample t test comparing the MMPI-2 Hs scale with the MMPI RC 1 scale was not significant. The paired-samples t tests comparing Table 1. The MMPI-2 vs. RC sensitivity at psychotic level of overall personality organization.
Method Scale
Participants Thirty-eight psychologists who are MMPI-2 experts were contacted by email and asked to rate their last ten psychotherapy patients, disability or forensic clients on the PDC. They were advised to share no other identifying data other than the client’s initials, gender, ethnicity, age and years of education. They were given a manual as to how to use the Psychodiagnostic Chart (PDC) and asked to rate each client without looking at their MMPI-2s. Of the 38 psychologists, 15 sent in 98 PDCs with MMPI-2s. The overall sample of 104 clients consisted of 43 women, 61 men (93% Caucasian, mean age = 40.65, age range: 18 - 74 years, mean years of education = 15.54, education range: 6 - 22 years). The client sample included people from forensic, disability and psychotherapy evaluations, repre1
Parts of these findings were presented at the American Psychoanalytic Association National Meeting at New York Discussion on January 17, 2013, “Research in Psychoanalysis: Creating the Psychodynamic Diagnostic Manual, Version 2 (PDM-2): Conceptual and Empirical Issues.” The session was co-organized by the American Psychoanalytic Association and the Psychodynamic Psychoanalytic Research Society. 2 For free copies of the PDC search online for “Psychodiagnostic Chart” or email
[email protected].
M
SD
t
p
d
Hs
65.69
17.12
−1.95
.075
−.54
RC 1
69.31
19.31
D
71.23
17.54
1.29
.223
.36
RC 2
67.38
18.87
Hy
72.69
18.46
1.91
.08
.53
7.4
.001
2.06
3.99
.002
1.11
6.27
.001
1.74
4.4
.001
1.22
−.318
.756
−.09
RC 3
60
9.8
Pd
79.46
12.07
RC 4
56.54
5.75
Pa
80.46
18.67
RC 6
66.08
15.07
Pt
78
19.43
RC 7
54.38
10.28
Sc
85.77
19.55
RC 8
67.54
16.88
Ma
61.38
14.06
RC 9
62.23
10.13
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Comparing the Sensitivity of the MMPI-2 Clinical Scales and the MMPI-RC Scales to Clients Rated as Psychotic, Borderline or Neurotic on the Psychodiagnostic Chart
MMPI-2 D, Hy, Pd, Pa, Pt, and Sc with the corresponding MMPI RC 2, RC 3, RC 4, RC 6, RC 7, and RC 8 were all significant. The final paired-sample t test comparing the MMPI-2 Ma scale with the MMPI RC 9 scale failed to reach significance. Taken together, 75% of the paired-sample t tests within the borderline level were significant in the predicted direction (see Table 2 for a summary of the scale means, standard deviations, t values, p values and d values within the borderline level of the OPO). The last set of paired-sample t tests examined mean differences between the MMPI-2 and MMPI RC scales within the neurotic level of the OPO. The only paired-samples t test that failed to reach significance was between the MMPI-2 D and MMPI RC 2 scale. Within the neurotic level, a total of 88% of the paired-samples t tests were significant in the predicted direction (see Table 3 for a summary of the scale means, scale standard deviations, t values, p values and d values within the neurotic level of the OPO). Across all three levels of the Overall Personality Organization (OPO) scale a total of 71% of the paired-samples t tests were significant. Taken together, the above analyses lend strong support to Hypothesis 1 (a). In support of Hypothesis 1 (b), the neurotic level of the OPO contained the largest percentage of significant pair-sample t tests (88%), followed by the borderline level (75%), and lastly the psychotic level (50%).
Hypothesis Two For Hypothesis 2, we predicted that the added K correction does not account for the differences in elevation between the MMPI-2 scales versus the MMPI RC scales. To test this hypothesis, we calculated means and standard deviations both within each level of the Overall Personality Organization (OPO) scale and an overall mean and standard deviation across all three levels of the OPO. The level means and standard deviations were: psychotic (M = 40.08, SD = 7.16), borderline (M = 48.44, SD = 8.65) and neurotic (M = 55.88, SD = 9.33). The Table 2. The MMPI-2 vs. RC sensitivity borderline level of the overall personality organization. M
SD
t
p
d
Hs
Scale
58.86
13.36
1.34
.185
.19
RC 1
57.63
13.98
D
66.57
16.01
3.43
.001
.48
RC 2
61.94
15.91
Hy
64.31
13.98
5.23
.001
.73
RC 3
50.24
10.13
Pd
66.06
11.2
7.15
.001
1
RC 4
54.04
10.13
Pa
63.33
11.71
5.6
.001
.78
RC 6
53.94
11.9 7.69
.001
1.08
6.02
.001
.84
1.21
.234
.17
Pt
63.67
12.98
RC 7
50.86
10.98
Sc
62.08
12.39
RC 8
52.86
11.78
Ma
50.63
8.57
RC 9
49.35
8.31
Table 3. The MMPI-2 vs. RC sensitivity neurotic level of the overall personality organization. M
SD
t
p
d
Hs
Scale
56.67
11.24
3.21
.003
.56
RC 1
52.85
11.55
D
54.73
9.92
1.1
.279
.19
RC 2
52.85
7.44
Hy
59.85
12.15
4.49
.001
.78
RC 3
46.79
8.31
Pd
59.7
8.87
4.41
.001
.77
52
9.68
Pa
56.97
9.85
5.9
.001
1.03
RC 6
46.48
8.02
Pt
57.27
10.07
6.15
.001
1.07
RC 7
45.97
8.04
Sc
56.18
9.28
4.91
.001
.85
RC 8
45.91
7.84
Ma
49.24
6.49
2.67
.012
.46
RC 9
45.76
6.76
RC 4
overall mean and standard deviation across all levels of the OPO was M = 49.80 and SD = 10.30 indicating that the greater elevations in the MMPI-2 Clinical scales are not due to the K correction.
Hypothesis Three For hypothesis 3, we predicted that for each clinical scale, the RC scale adds very little incremental validity to the MMPI2 clinical scales in predicting the level of severity in the Overall Personality Organization (OPO) scale. In testing hypothesis 3, a series of multiple regressions were conducted where an MMPI2 scale was entered first, followed by its corresponding RC scale. In the first regression, Hs was entered first followed by RC 1. For the first model, Hs accounted for 3.80% of the variance in the OPO scale (R2 = .038). When RC 1 is included (model 2), this value increases to .149 or 14.9% of the variance in the OPO scale (R2 = .149), an increase of 11.1%. The F change for model 2 was significant, F(1,94) = 12.303, p = .001, indicating that adding RC 1 significantly improved the prediction of the OPO scale compared to using Hs as a single predictor. In the second regression, D was entered first followed by RC 2. For model 1, D accounted for 15% of the variance in the OPO scale (R2 = .150). When RC 2 was entered in model 2, this value increased to .153 or 15.3% (R2 = .153), an increase of only .30%. The F change for model 2 was not significant, F(1,94) = .382, p = .538, indicating that adding the RC 2 scale did not significantly improve the prediction of the OPO scale compared to using only D. The third regression entered Hy followed by RC 3. For model 1, Hy accounted for 7.30% of the variance in the OPO scale (R2 = .073). For model 2, this value increased to .247 or 24.7% (R2 = .247), an increase of 17.4%. The F change was significant, F(1,94) = 21.68, p = .001, indicating the adding RC 3 did significantly improve the prediction of the OPO scale above and beyond what was predicted using only Hy. However,
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RC 3 is a measure of Cynicism and not hysterical personality traits and therefore cannot be considered a substitute for the MMPI-2 Hy scale. In the next regression, model 1 contained Pd, with RC 4 added in model 2. For model 1, Pd accounted for 23.9% of the variance in the OPO scale (R2 = .239). For model 2, this value increased to .241 or 24.1% (R2 = .241), an increase of only .2%. This change in R2 produced a non-significant F(1,94) = .249, p = .619, indicating no predictive improvement with the inclusion of RC 4. The fifth regression entered Pa followed by RC 6. For the first model with Pa entered alone, Pa accounted for 24.2% of the variance in the OPO scale (R2 = .242). When RC 6 was added in model 2, this value increased to .289 or 28.9%, producing a significant F(1,94) = 6.228, p = .014, indicating improvement in predicting the OPO scale compared to using only Pa. An examination of the beta values for these two predictors in model 2 suggests, however, that Pa predicts more of the variance in the OPO scale than does RC 6 (−.317 vs. −.279). That is, while RC 6 predicts additional variance above and beyond that predicted by Pa alone, the amount predicted is small relative to Pa. We next entered Pt in model 1 followed by RC 7 in model 2. For model 1, Pt accounted for 18.2% of the variance in the OPO scale (R2 = .182). For model 2, this value increased to .184 or 18.4 (R2 = .184), an increase of only .2%. This change in R2 produced a non-significant F(1,94) = .306, p = .582, indicating no predictive improvement with the inclusion of RC 7. The next regression entered Sc in model 1 and RC 8 in model 2. For model 1, Sc accounted for 28.3% of the variance in the OPO scale (R2 = .283). For model 2, this value increased to .320 or 32.0.1% (R2 = .320), an increase of 3.7%. This change in R2 produced a significant F(1,94) = 5.036, p = .027, indicating improvement in predicting in the OPO scale with the inclusion of RC 8. However, the beta values indicate the Sc predicts more of the variance in the OPO scale than does the RC 8 scale (−.366 vs. −.253). In the final regression, Ma was entered first, followed in model 2 with RC 9. For model 1, Ma accounted for 11.3% of the variance in the OPO scale (R2 = .113). Adding RC 9 in model two increased this value to 24.1% (R2 = .241), producing a significant F(1,94) = 15.809, p = .001. In this regression, the beta values indicate that RC 9 in comparison to MA also predicts more of the variance in the OPO scale (−.476 vs. −.021). In summary, 5 of the 8 RC scales (RC 1, RC 2, RC 6, RC 8, and RC 9) added incremental validity to the MMPI-2 clinical scales in predicting the level of severity in the Overall Personality Organization (OPO) scale. However, an examination of the beta values indicates that for 2 of the 5 RC scales (RC 6 and RC 8) the amount of additional predicted variance is relatively small in comparison to the amount predicted by their corresponding MMPI-2 scales (Pa and SC). Taken together, in terms of predictive utility, the results suggest that only 3 of the 8 or 37.5% of the RC scales contribute incrementally in predicting the level of severity in the OPO scale, lending support to hypothesis 3.
Discussion This study looked at the clinical sensitivity of the MMPI-2 Clinical scales vs. the MMPI-RC scales with 98 clients from
Psychology Handbook
forensic, disability and psychotherapy evaluations, representing a wide range from psychotic, borderline to neurotic levels of personality organization as measured by the Psychodiagnostic Chart. Since the RC scales lack a diversity of items and subtly, we hypothesized that the MMPI-2 Clinical scales would have more clinical sensitivity than the RC scales at: 1) all levels of psychopathology and 2) particularly at the less pathological levels where subtlety is more of an issue in detecting psychopathology. We found that the clients at the psychotic level of personality organization as measured by the PDC, the MMPI-2 Hs, D, Hy and Ma scales were not significantly different than the corresponding MMPI RC 1, RC 2, RC 3, RC 9 scales. The MMPI-2 Pd, Pa, Pt, and Sc were all significantly higher than the corresponding RC 4, RC 6, RC 7, and RC 8. Only 4 of the RC scales reached clinical significance (T 65 or more), while 7 of the 8 MMPI 2 Clinical scales were T 65 or more for clients at the psychotic level. For those clients rated on the PDC at the borderline level the MMPI-2, Hs and Ma scales and the RC 1 and RC 9 scales were not significantly different. The MMPI-2 D, Hy, Pd, Pa, Pt, and Sc were all significantly higher than the corresponding RC 2, RC 3, RC 4, RC 6, RC 7, and RC 8 scales. D and Pd were in the clinical range, but none of the RC scales reached the clinical range of T 65. For those clients rated on the PDC at the neurotic level, only the MMPI-2 D scale and the RC 2 scales were not significantly different. The MMPI-2 Hs, Hy, Pd, Pa, Pt, Sc and Ma were all significantly higher than the corresponding RC scales. Across all three levels of the Overall Personality Organization (OPO), the neurotic level of the OPO had 88% difference between the MMPI-2 and RC, followed by the borderline level (75%) and lastly the psychotic level (50%). The added K correction to the MMPI-2 Clinical scales does not seem likely to account for the differences in elevations. Overall, K was at the normal level (M = 49.80). K was lowest in the psychotic level and highest in the neurotic level. K functions in much the same way as the subtle items function in those scales that are not K corrected, i.e. as the defensive aspects of the psychopathology (Gordon, 1989). These diagnostically valid items are not artificially elevating the Clinical scales. Both K and the subtle items add diagnostic sensitivity to the MMPI-2 scales not found in homogenized scales. Most of the RC scales add little to no incremental validity to the MMPI-2 Clinical scales in predicting the level of severity in the Overall Personality Organization (OPO) scale. However, RC 1, RC 2, and RC 9 do have value in adding to the incremental validity of the MMPI-2 and should be considered as supplemental scales. We recommend using the MMPI-2 Clinical scales for screening psychopathology and to use the RC scales only as supplemental scales. The broader issue, however, is the value of criteria-based scales. The MMPI-2 scales were based on the complexity expressed in the conflicts of disturbed individuals. The RC scales are based on behavioral reductionistic assumptions of psychopathology which fail to capture the complexity of human conflicts.
REFERENCES Binford, A., & Liljequist, L. (2008). Behavioral correlates of selected MMPI-2 clinical, content, and restructured clinical scales. Journal of Personality Assessment, 90, 608-614.
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Comparing the Sensitivity of the MMPI-2 Clinical Scales and the MMPI-RC Scales to Clients Rated as Psychotic, Borderline or Neurotic on the Psychodiagnostic Chart
Bolinskey, P. K., & Nichols, D. S. (2011). Construct drift in the MMPI2 restructured clinical scales: Further evidence and a possible historic example. Journal of Clinical Psychology, 67, 907-917. Bornstein, R. F., & Gordon, R. M. (2012). What do practitioners want in a diagnostic taxonomy? Comparing the PDM with DSM and ICD. Division/Review: A Quarterly Psychoanalytic Forum, 6. Dahlstrom, W. G., Welsh, G. S., & Dahlstrom, L. E. (1972). An MMPI handbook: Vol. I: Clinical interpretations. Minneapolis, MN: University of Minnesota Press. Gordon, R. M. (1989). Interpreting MMPI subtle scales as representing defense mechanisms. Paper presented at the 24th Annual Symposium on Recent Developments in the Use of the MMPI, Honolulu. Gordon, R. M. (2006). False assumptions about psychopathology, hysteria and the MMPI-2 restructured clinical scales. Psychological Reports, 98, 870-872. Gordon, R. M., & Stoffey, R. W. (2013). Research in psychoanalysis: Creating the psychodynamic diagnostic manual, version 2 (PDM-2): Conceptual and empirical issues. Presented at the American Psychoanalytic Association National Meeting, New York. Lanyon, R. I., & Thomas, M. L. (2013). Assessment of global psychiatric categories: The PSI/PSI-2 and the MMPI-2-RF. Psychological Assessment, 25, 227-232.
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Nichols, D. S. (2011). Essentials of MMPI-2 assessment (2nd ed.). Essentials of psychological assessment. Hoboken, NJ: John Wiley & Sons Inc. PDM Task Force (2006). Psychodynamic diagnostic manual. Silver Spring, MD: Alliance of Psychoanalytic Organizations. Rouse, S. V., Greene, R. L., Butcher, J. N., Nichols, D. S., & Williams, C. L. (2008). What do the MMPI-2 restructured clinical scales reliably measure? Answers from multiple research settings. Journal of Personality Assessment, 90, 435-442. Sellbom, M., Ben-Porath, Y. S., McNulty, J. L., Arbisi, P. A., & Graham, J. R. (2006). Elevation differences between MMPI-2 clinical and restructured clinical (RC) scales: Frequency, origins, and interpretative implications. Assessment, 13, 430-441. Tellegen, A., Ben-Porath, Y. S., McNulty, J. L., Arbisi, P. A., Graham, J. R., & Kaemmer, B. (2003). MMPI-2 restructured clinical (RC) scales: Development, validation, and interpretation. Minneapolis, MN: University of Minnesota Press. Wallace, A., & Laura, L. (2005). A comparison of the correlational structures and elevation patterns of the MMPI-2 restructured clinical (RC) and clinical scales. Assessment, 12, 290-294.
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2 Illusory Upward Self-Motion Results in a Decrease in Perceived Room Temperature 1
Takeharu Seno1,2,3, George H. Van Doorn4
Institute for Advanced Study, Kyushu University, Fukuoka, Japan 2 Faculty of Design, Kyushu University, Fukuoka, Japan 3 Research Center for Applied Perceptual Science, Kyushu University, Fukuoka, Japan 4 School of Applied Media and Social Sciences, Monash University, Melbourne, Australia
Purpose: Stationary observers often experience illusory self-motion (vection) when they are exposed to large patterns of optic flow. The effect of different temperatures on the strength of vection was investigated. Method: Eleven participants were exposed to visual stimuli that induced illusory motion (up, down) in three room temperatures (26˚C - 27˚C, 21˚C - 22˚C, 5˚C - 6˚C). Participants rated (a) the vection magnitude, and (b) the room temperature (twice; before and after vection). Results: Upward vection was rated as stronger than downward vection in the 26˚C - 27˚C temperature. In addition, after experiencing upward and downward vection, subjective ratings of room temperature decreased and increased, respectively, when the room temperature was 26˚C - 27˚C. This effect was not observed when the room was 5˚C - 6˚C. Conclusion: These results suggest that a cross modal association exists between the direction “up” and 26˚C - 27˚C temperatures. Keywords: Vection; Temperature; Vision; Illusory Self-Motion
Introduction Exposure to a visual motion field that simulates the retinal optical flow generated by self-movement commonly causes the perception of the subjective movement of one’s own body. This phenomenon is known as “vection” (Fischer & Kornmuller, 1930). For example, when a stationary person observes a train beginning to move, they are likely to perceive that they are moving in the opposite direction to the motion of the train. This phenomenon is known as the “train illusion”, and provides a good example of vection (e.g. Seno & Fukuda, 2012). Some recent studies reported that vection can modulate aspects of perception and cognition, e.g. daydreaming (Miles, Karpinska, Lumsden, & Macra, 2010), attention (Seno, Ito, & Sunaga, 2011a), time perception (Seno, Ito, & Sunaga, 2011b), perception of numbers (Seno, Taya, Ito, & Sunaga, 2011), and visual illusions (Fukuda & Seno, 2011; Fukuda & Seno, 2012). Vection is also affected by personality traits such as narcissism (Seno, Yamada, & Ihaya, 2011). In this study, we assessed for the first time whether vection can be modulated by temperature, or can have a modulating influence on perceived temperature. Soto-Faraco, Spence and Kingstone (2004) suggested that a feature in one sensory modality can be associated with a feature in another sensory modality, i.e. a cross-modal correspondence. Although different sensory organs receive different inputs, interactions between sensory modalities occur after these inputs have been recoded at post-perceptual levels (Marks, 2004); recoding activates a representation that captures elements of each input that are common across modalities (Martino & Marks,
2000). Consequently, reaction times (RTs) to a simultaneously presented high-pitched tone and a light coming from above might be shorter, for example, than RTs to a low-pitched tone and a light coming from above; the recoded inputs of the former pair share the post-perceptual format “high”, whereas the later do not. Similar to Mark’s (2004) work, Seno, Ito, Sunaga, Hasuo, Nakajima and Ogawa (2011) recently proposed a consistency hypothesis that predicts that visually-induced self-motion will be enhanced when inputs from one (or more) of the non-visual senses are consistent with visual simulation. Consistent with the predictions of this hypothesis, somatosensory stimulation generated by adding air-flow to a stationary observer’s face significantly (p < .05) enhanced visually-simulated forward motion (Seno, Ogawa, Ito, & Sunaga, 2011). In addition, vection has been facilitated by vibrations on the body and auditory cues that are consistent with visual rotation (Riecke, Schulte-Pelkum, Caniard, & Bülthoff, 2005; Riecke, Feuereissen, & Rieser, 2008). Crossmodal correspondence, or consistency, seems to be nonarbitrary and accumulated through repeated exposure to pairs of stimuli (Williams & Bargh, 2008). As we go through life experiencing wind against our face, for example, it becomes paired with forward motion. This idea can be applied to temperatures and spatial directions (up/down) which may be semantically associated in everyday language (e.g. “hot air rises”). If a correspondence exists between “hot” temperatures and “upward” direction (and vice versa for “cold” and “down”) then vection may be influenced by temperature; specifically, upward vection would be stronger
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when the temperature of a room is hotter than usual, and vice versa for colder temperature. In addition, illusory change in room temperature may arise as a result of perceiving vection. Thus, we tested the following hypotheses: H1: In a 26˚C - 27˚C room, upward vection will be stronger than illusory self-motion in other directions. H2: Subjective ratings of room temperature will be hotter after experiencing upward vection, and cooler after downward vection.
Method Participants Eleven volunteers (seven females) took part in the experiment. The participants had a mean age of 24.8 years (SD = 3.7 years). All participants had normal or corrected-to-normal vision and none of them reported visual or vestibular abnormalities. The experiments were pre-approved by the ethics committee of Kyushu University, and written informed consent was obtained from each subject prior to participating.
Materials and Stimuli The up/down vection stimulus was a white vertical sinusoiddal grating whose luminance was horizontally modulated. Motion displays subtended a visual area of 72˚ (horizontal) × 57˚ (vertical) when viewed from 570 mm in front of a television screen. Upward/downward vection was induced by moving the grating (spatial frequency: .1 cycle/deg; mean luminance: 18 cd/m2; Michelson contrast: 80%) down/up, respectively, at a speed of ~20 deg/sec. We used virtually continuous motion in the minimum motion technique that was essentially the same as that used in Cavanagh, MacLeod and Anstis (1987). Each up/ down motion stimulus consisted of 13 images presented sequentially and repeatedly. The gratings moved in only one direction for the duration of each trial, which was fixed at 30 sec. There was also a static (i.e. control) grating condition. The experiment was conducted in a 7 m × 7 m × 2.6 m darkened room. There were three room temperature conditions, i.e. normal (21˚C - 22˚C), hot (26˚C - 27˚C), and cold (5˚C - 6˚C). Room temperature was modulated and kept constant by the two air conditioners. Room temperature was certificated by the thermometer.
Procedure Prior to the presentation of stimuli, participants were asked to sit down; they remained seated for the entire experiment. Before each stimulus combination was presented (e.g. 5˚C - 6˚C temperature/upward grating pattern) participants were asked to estimate the room temperature to one decimal point (e.g. 23.5˚C). They were also instructed to press a button during each trial if/ when they experienced vection, and were to keep the button depressed for as long as the experience lasted. If vection ceased, or became ambiguous, they were to release the button. Duration and latency of vection were recorded as dependent variables. Latency was defined as the time interval between the onset of the visual stimulus and the time at which the participant pressed the button. Duration was calculated as the total time that the button was pressed until it was released. Following the instructions a motion stimulus was presented. After the 30 sec stimulus presentation period ended, and after
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participants released the button to signify that vection had ceased, participants rated the strength of vection by verbally stating a number from 0 (no vection) to 100 (very strong vection); the experimenter recorded this number on a piece of paper. Participants then estimated the room temperature again, and the difference between pre- and post-trial estimations was calculated. There were two motion directions and three room temperature conditions. There were four trials per condition, and thus a total of 24 trials per participant. The presentation order of trials was randomized. Each temperature condition lasted approximately 20 mins. Thus the experiment had a total duration of approximately 60 mins for each participant. All conditions were interior-group design. It is known that vection can be modulated by an experimenter’s instructions or demands (Palmisano & Chan, 2004). Thus, we carefully instructed the participants regarding their task without giving them any suggestion which may lead to a cognitive bias about the consistency hypothesis. Furthermore, several control conditions were included in an attempt to negate potential extraneous variables.
Results A 3 (temperature: 21˚C - 22˚C, 26˚C - 27˚C, 5˚C - 6˚C) × 3 (grating motion: upward, downward, static) repeated-measures ANOVA on subjective ratings of vection strength revealed a significant main effect of temperature [F(2,20) = 21.62, p < .0001, η2 = .16]. Vection was weaker in the 26˚C - 27˚C condition than in the 21˚C - 22˚C and 5˚C - 6˚C cold conditions (see Figure 1). This is supported by the duration and latency data which were significantly shorter and longer, respectively, in the 26˚C - 27˚C condition relative to the 21˚C - 22˚C and 5˚C - 6˚C conditions [duration: F(2,20) = 6.83, p = .005, η2 = .06; latency: F(2,20) = 13.62, p = .0002, η2 = .21]. The main effect of the grating motion was significant [magnitude: F(2,20) = 66.62, p < .0001, η2 = .16; duration: F(2,20) = 86.29, p = .005, η2 = .70; latency: F(2,20) = 54.36, p < .0001, η2 = .55]. Bonferroni-corrected post-hoc tests revealed significant differences between the static grating and the others (p < .05). Importantly, the direction of illusory self-motion experienced by each participant was consistent with previous research (e.g. Seno, Ito, & Sunaga, 2009). The interaction between temperature and grating motion was significant [magnitude: F(4,40) = 9.36, p < .05, η2 = .10; duration: F(4,40) = 3.79, p < .05, η2 = .03; latency: F(4,40) = 12.19, p = .002, η2 = .16]. Bonferroni-correct post-hoc comparisons revealed that upward vection was stronger than downward vection in the 26˚C - 27˚C condition (p < .05), and thus H1 was supported. A second 3 (temperature) × 3 (grating motion) repeated-measures ANOVA on the difference between perceived temperatures pre- and post-stimulus presentation revealed no significant main effect of temperature [F(2,20) = 1.62, p = .22; η2 = .03] (see Figure 2). The main effect of grating motion was significant [F(2,20) = 7.17, p = .0045, η2 = .08]. Post-hoc tests (Holm’s Sequentially Rejective Bonferroni Procedure) revealed significant differences between down and the other two conditions [up vs. down, t(10) = 2.98, p = .04; Cohen’s d = .73; down vs. static, t(10) = 2.48, p = .03; d = .31]. There was also a trend towards significance between the up and static conditions, t(10) = 2.05, p = .06; d = .29. The interaction was significant [F(4,40) = 2.64, p < .05, η2 = .12]. Bonferroni-corrected post-hoc com-
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Psychology Handbook
Figure 1. Strength of vection. The unit of measurement for latency and duration were seconds, while magnitude was a rating from 0 to 100. There was no vection in any static condition, and hence the “spaces” in the figures.
Figure 2. The perceived change in temperature after vection.
parisons revealed that perceived room temperature was modulated by motion stimuli only in the 26˚C - 27˚C condition (p < .05).
Discussion Vection refers to the experience of illusory self-motion in response to large patterns of optic flow. The main issues explored in this study were whether (a) vection is influenced by changes in room temperature, and (b) perceived room temperature is changed by experiencing vection. Remarkably, the interaction between temperature and grating motion was significant, and thus vection seems to be influenced by room temperature. Further, and contrary to H2, upward vection produced a perceived
drop in room temperature and downward vection resulted in a perceived rise, but only in the 26˚C - 27˚C condition. We speculate that, as upward vection was stronger than downward vection in the 26˚C - 27˚C condition, there is a correspondence between heat and upward motion that exists in closed spaces, e.g. rooms and buildings where hot air rises. However, in the 5˚C - 6˚C condition, downward vection was not significantly stronger than upward vection. It is somewhat surprising that an association exists only between 26 - 27˚C and “up”, and not between 5˚C - 6˚C and “down”. Although speculative, this unidirectional finding may be explained by the work of Riecke et al. (2008) who showed that the possibility of actual self-motion facilitates vection. In their experiment auditory circular vection was enhanced by suspending participants above the ground. In our experiment, participants’ feet touched solid ground and they, presumably, knew that actual “downward” motion was impossible, whereas given the free space above each participant’s head it was (theoretically) possible for them to move up into this free space. To examine this hypothesis, we conducted an informal observation with 4 naïve volunteers in which their feet were kept off the ground, and thus upward and downward motion was (theoretically) possible; we, again, measured strength of vection. The results were similar to those of the main experiment, i.e. upward vection was stronger than downward vection in the 26˚C - 27˚C condition. Thus, the idea that contact between one’s feet and solid ground inhibits vection is not supported by our informal observations. That said, even though the participants’ feet did not touch the ground, their buttocks did touch the chair. Further experiments are planned to determine whether manipulating the procedure shows correspondence effects in the other conditions. The current results suggest that illusory self-motion is stronger when there is a correspondence between two stimuli and one knows that physical motion is possible. Contrary to H2, upward vection produced a perceived drop in room temperature while downward vection resulted in a perceived rise, but only in the 26˚C - 27˚C condition. It is possible that participants were aware of the fact that hot air rises and, after experiencing illusory self-motion in the 26˚C - 27˚C temperature condition, they expected an increase in room temperature. As the actual temperature remained constant after experiencing vection, because no physical positional change took place, there was a discrepancy between expected and actual room temperatures, which resulted in the room being judged colder than it actually was. However, given downward vection was weaker than upward vection in the 26˚C - 27˚C and, here, downward vection resulted in a perceived increase in room temperature, this explanation is speculative. It might be that the hot temperature (26˚C - 27˚C) and vection stimuli used here contain some unknown features that correspond, whereas the cold temperature (5˚C - 6˚C) and vection stimuli did not. There is some evidence (see Pilcher, Nadler, & Busch, 2002) that heat can be more attention-getting than can cold and, as such, it may be that a hotter room shifts attention to temperature, and thus participants became sensitive to it. It is known that exposure to visual stimuli like those used here can create nausea in participants, and common autonomic reactions are cold sweating and reduced peripheral blood flow. These reactions are especially common among healthy, young people who do not suffer from vestibular disorders. These are natural autonomic responses and a shift in the autonomic nervous system towards a sympathetic reaction. Although each ex-
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perimental trial lasted only a short time, there were repeated exposures and the autonomic response is quick, especially if trials are repeated with short inter-trial intervals. That said, for autonomic responses to have been a confounding variable the reported influence of temperature on vection would have to be explainable having found that autonomic responses occurred in the 26˚C - 27˚C temperature/downward motion (upward vection) condition but not in the 26˚C - 27˚C temperature/upward motion (downward vection) condition, and that this increased the perceived strength of vection in the former condition. There is no evidence to support such a view. In conclusion, we have demonstrated the existence of a new crossmodal correspondence, namely an association between temperature and directional up; vection modulated perceived temperature, and was modulated by actual temperature. As Parise and Spence (2012) argue, this correspondence might reflect the natural correlation between physical properties of the world, i.e. warmer air moves upwards relative to cooler air.
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Test. Experimental Brain Research, 220, 319-333. Pilcher, J. J., Nadler, E., & Busch, C. (2002). Effects of hot and cold temperature exposure on performance: A meta-analytic review. Ergonomics, 45, 682-698. Riecke, B. E., Schulte-Pelkum, J., Caniard, F., & Bülthoff, H. H. (2005). Influence of auditory cues on the visually-induced self-motion illusion (circular vection) in virtual reality. In M. Slater (Ed.), Proceedings of the 8th International Workshop on Presence 2005 (pp. 49-57). London: University College London. Riecke, B. E., Feuereissen, D., & Rieser, J. J. (2008). Auditory self-motion illusions (“circular vection”) can be facilitated by vibrations and the potential for actual motion. In S. N. Spence (Ed.), Proceedings of the 5th Symposium on Applied Perception in Graphics and Visualization 2008 (pp. 147-54). New York, NY: The Association for Computing Machinery. Seno, T., Ito, H., & Sunaga, S. (2009). The object and background hypothesis for vection. Vision Research, 49, 2973-2982.
Acknowledgements
Seno, T., Ito, H., Sunaga, S., & Nakamura, S. (2010). Temporonasal motion projected on the nasal retina underlies expansion-contraction asymmetry in vection. Vision Research, 50, 1131-1139.
This work is supported by the Program to Disseminate Tenure Tracking System, MEXT, Japan.
Seno, T., Ito, H., & Sunaga, S. (2011a). Attentional load inhibits vection. Attention, Perception, & Psychophysics, 73, 1467-1476.
REFERENCES
Seno, T., Ito, H., & Sunaga, S. (2011b). Self-motion perception compresses time experienced in return travel. Perception, 40, 497-499.
Cavanagh, P., MacLeod, D. I., & Anstis, S. M. (1987). Equiluminance: Spatial and temporal factors and the contribution of blue-sensitive cones. The Journal of the Optical Society of America, 4, 1428-1438. Fischer, M. H., & Kornmuller, A. E. (1930). Optokinetic ausgeloste Bewegungs-wahrnehmungen und optokinetinetisher Nystagmus. Journal of Comparative Neurology, 41, 273-308. Fukuda, H., & Seno, T. (2011). Shrinking neighbors: A quantitative examination of the ‘Shrinking Building’ illusion. Seeing Perceiving, 24, 541-544. Fukuda, H., & Seno, T. (2012). Healin’ groovy: Movement affects the appearance of the Healing Grid Illusion. Perception, 41, 243-246. Marks, L. E. (2004). Cross-modal interaction in speeded classification. In G. Calvert, C. Spence, & B. Stein (Eds.), The handbook of multisensory processes (pp. 85-105). Cambridge: MIT Press. Martino, G., & Marks, L. E. (2000). Cross-modal interaction between vision and touch: The role of synesthetic correspondence. Perception, 29, 745-754. Miles, L. K., Karpinska, K., Lumsden, J., & Macrae, C. N. (2010). The meandering mind: Vection and mental time travel. PLoS One, 5, e10825. Palmisano, S., & Chan, A. Y. (2004). Jitter and size effects on vection are immune to experimental instructions and demands. Perception, 33, 987-1000. Parise, C. V., & Spence, C. (2012). Audiovisual crossmodal correspondences and sound symbolism: A study using the Implicit Association
Seno, T., Ito, H., Sunaga, S., Hasuo, E., Nakajima, Y., & Ogawa, M. (2011). Consistency between modalities enhances visually induced self-motion (vection). In G. Suzuki (Ed.), Proceedings of the 12th International Multisensory Research Forum. Fukuoka: I-Perception. Seno, T., Ogawa, M., Ito, H., & Sunaga, S. (2011). Consistent air flow to the face facilitates vection. Perception, 40, 1237-1240. Seno, T., Taya, S., Ito, H., & Sunaga, S. (2011). Mental number line in depth revealed by vection. Perception, 40, 1241-1244. Seno, T., Yamada, Y., & Ihaya, K. (2011). Narcissistic people cannot be moved easily by visual stimulation. Perception, 40, 1390-1392. Seno, T., & Fukuda, H. (2012). Stimulus meanings alter illusory selfmotion (vection): Experimental examination of the train illusion. Seeing & Perceiving, 25, 631-645. Soto-Faraco, S., Spence, C., & Kingstone, A. (2004). Cross-modal dynamic capture: Congruency effects in the perception of motion across sensory modalities. The Journal of Experimental Psychology: Human Perception and Performance, 30, 330-345. Williams, L. E., & Bargh, J. A. (2008). Experiencing physical warmth promotes interpersonal warmth. Science, 322, 606-607.
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3 Designing Effective CME—Potential Barriers to Practice Change in the Management of Depression: A Qualitative Study Mandana Shirazi1,2, Sagar V. Parikh3, Ideh Dadgaran4,5*, Charlotte Silén6 1
Education Development Center, Medical Education Department, Tehran University of Medical Sciences, Tehran, Iran, 2 Departments of LIME and Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden 3 University of Toronto, Toronto, Canada 4 Medical-Surgical Nursing Department, Langroud Nursing and Midwifery School, Guilan University of Medical Sciences (GUMS), Rasht, Iran 5 Research in Medical Education, Education Development Center (EDC), Guilan University of Medical Sciences (GUMS), Rasht, Iran 6 Center for Medical Education, Department of Learning, Informatics, Medical Management and Ethics (LIME), Karolinska Institutet, Stockholm, Sweden
Aim: The main aim of the current study is to explore GPs’ micro level obstacles of behavior change which affects diagnosis and management of Depressive Disorders following attendance at a Depression CME event. Methods: In this qualitative study, semi-structured interviews exploring GPs’ perceptions and experiences regarding the diagnosis and treatment of depression were done. A purposeful sampling to obtain a broad range of views was carried out among GPs that had participated in an educational intervention study three years earlier. Eleven GPs were interviewed and their views were probed in depth to get rich descriptions to ensure trustworthiness of the data. The data were analyzed by using qualitative content analysis. Results: GPs’ beliefs regarding micro level barriers emerged as two important themes individual and workplace factors. The individual themes included: educational and professional, and the contextual themes included: psychological disorders and work place categories. The results showed different perceptions on the barriers between the two groups of GPs, those who did change and had a positive perception of the CME program they participated in three years ago, and some who did not change. Conclusion: The results of this study imply that a number of micro level obstacles were of great importance when managing patients with depression disorders. In order to improve the effectiveness of CME events they should be tailored for the individual and address workplace issues i.e. both individual and contextual factors need attention. Keywords: CME; Depression; Primary Care; Qualitative Study
Introduction Quality improvement in health care is a common concept affecting all the field professionals. Several factors such as organization, policy and education influence the quality of healthcare. Health care quality assurance is a worldwide concern in evaluating the effects of Continuing Medical Education (CME) or Continuing Professional Development (CPD), not only on the physicians’ knowledge and skills, but also on their performance and the clinical results (Davis, Thomson, Oxman, & Haynes, 1995; Oxman, Thomson, Davis, & Haynes, 1995). Grol and Weising stated that effective CME interventional events should be planned based on personal, workplace and local health care system needs. They emphasize attention on causal variables that support or hinder targeted health care tailored intervention, using appropriate theories in social cognition *
Corresponding author.
models and health care results (Grol & Wensing, 2004). The aim of all types of learning is change—changing mental models and creating new ways of thinking, so models of change are relevant. One of the applicable theories (Shirazi et al., 2011) in this field is Readiness to Change model, which underpins the necessity to match interventions with the change stage and corresponding cognitive style. This model, originally known as the “trans-theoretical model”, was developed by James Prochaska and Carlo DiClemente in the early 1980s to explain the stages of change observed in persons striving to change addictive behaviour (Prochaska, 1992). More specifically, the five stages of change are defined on the basis of people’s propensity to change a specific behaviour and understanding. In the initial stage, individuals are not aware of any problem or contemplating change; in the second stage, they begin contemplating change; in the third stage, they actively prepare, and in the fourth stage, they actually change behaviour. A fifth stage is the
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Designing Effective CME—Potential Barriers to Practice Change in the Management of Depression: A Qualitative Study
consolidation or maintenance of the new change. CME in Iran is mandatory for physicians who wish to continue their professional practice (Shirazi et al., 2004). A comprehensive project including interventions concerning education on improving General Practitioners’ (GP) knowledge, attitude, and performance in the management of depressive disorders was carried through in 2006 .The evaluation of GPs’ performance was done through the application of unannounced Standardized Patients (SP) (Shirazi et al., 2011). That study showed that some physicians changed their performance while others did not; the reason for lack of change was not identified (Figure 1) (Shirazi et al., 2011). Research in CME interventions has failed to provide reliable and effective methods to change the services and professional performance for the better. In a study from the literature, barriers to uptake of Evidence-Based Medicine were explored. That study categorized GPs’ individual practice on the micro level, commercial and consumer organizations on the meso-level (institutions, organizations) and health care policy, media and specific characteristics of evidence on the macro-level (policy level and international scientific community). Existing barriers and possible strategies to overcome these barriers were described (Hannes et al., 2005). In the current study, we were interested in the barriers to change from the individual physician’s perspective, so we used a qualitative approach for a deeper understanding of the barriers (Pope, Van Royen, & Baker, 2002). According to the literature, there are different obstacles and multifactor barriers behind the GPs’ failure to detect depression. Shortage of time, insufficient knowledge, the patients’ failure to reach appropriate mental healthcare services, social and cultural background, and the patients’ resistance to admitting their mood disorders are just some of the underlying factors (Hannes et al., 2005; Shirazi et al., 2013). These obstacles may easily be classified into the micro and macro level categories described earlier. The macro level barriers were reported in our previous publication at the micro level (personal and work place) barriers which affect doctors’ performance, ultimately in order to improve the quality of care (Diner et al., 2007). Specifically, we aim to explore GPs’ micro level obstacles of behavior change which affect diagnosis and management of Depressive Disorders following participation in a major CME program for depression. Randomization and doing Pre-assessment
96 GPs
Intervention
PostGPs’ who assessment changed their
Intervention Large 61 GPs (attitude)
performance 8 GPs
Semi‐ structure interview 4 GPs
Intervention Intervention Small (intention)
17 GPs
192 GPs
96 GPs
62 GPs
53GPs
3GPs
19 GPs
14 GPs
2 GPs
Methods This qualitative research was carried out by the use of phenomenology method. It consists of the semi-structured interviews with the data gathering method and qualitative content analysis for data analysis. The interviews were conducted between May 2010 and June 2011 (by MS). Qualitative content analysis is a method that accounts for the contradictory comments and unresolved issues concerning the meanings and application of concepts and procedures. Qualitative content analysis is used in a large number of fields, ranging from marketing and media studies to cultural studies, sociology, and cognitive science, as well as other fields of inquiry (Palmquist, 2010).
Participants and Design The participating GPs in this qualitative study originated from a previously published randomized controlled trial (RCT) where interactive teaching and learning methods were used to support GPs in their practice when diagnosing and treating patients with depression disorders (Krippendorff, 2004; Marandi, 1996; Shirazi et al., 2011; World Health Organization, 2004). In summary, in that study the participating GPs (n = 192) were randomized into an intervention group (n = 96) or into a control group (n = 96) and assessed at the follow-up (78 and 81 GPs, respectively). At the follow-up the participants in the intervention group were categorized as those who had changed their behavior and those who had not. The twelve approached GPs of the present study originated from the intervention group: all five GPs that had not changed their behavior and/or performance (i.e. GP, no change) and seven of those who had changed (i.e. GP change) their behavior and/or performance were approached but one of the latter declined to participate. The seven were randomly chosen among all those who had changed and the interviews continued until saturation of the data was reached. The choice of participants was done purposely in order to get a wide range of views about the barriers they had met (Krippendorff, 2004) (Figure 1). After signing an informed consentphysicians were asked to agree upon a convenient time and place for the interview. The principal interview questions were as follows: “What do you feel about the barriers of GPs’ behavior change? What is your perception regarding your behavior change following yourparticipation in the CME course three years ago?” The interviewer probed participant responses using questions, such as “Could you say something more about that?”, “What did you think then?”, and “When you mention-what do you mean?” (Kvåle, 2007). The GPs consisted of eight male and three female participants among whom there were three under the age of 40, five between the ages of 40 and 50, and three over 50 years of age. Nine of them had worked as a GP for 10 to 20 years and two of them for over 20 years. As an incentive, each participant received a CME credit point for his/her participation.
Collecting and Analyzing Data Control Small
Quantitative study Reference No 5
2 GPs
GPs’ who did not change their performance
Control Large
Control
3 GPs
11
Mandana shirazi
Qualitative study 3
Figure 1. The design of the project including the previous and current studies.
The interviews were recorded on a digital voice recorder and subsequently transcribed. All interviews were analyzed. The process of qualitative content analysis often begins during the early stages of data collection. This early involvement in the analysis phase assists in moving back and forth between concept development and data collection, and may help direct subsequent data collection toward sources that are more useful for
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addressing the research questions (Zhang, 2012). This process includes open coding, creating categories, and abstraction. Open coding, axial coding, and generating themes were performed during data gathering and analysis. Each category was named using content-characteristic words. Subcategories with similar events and incidents were grouped together as categories and categories were grouped as themes. The abstraction process continued as far as it was reasonable and possible (Elo & Kyngäs, 2008).
Quality Assurance of Data Analysis During the analysis of data, certain techniques can help prove our points (Westbrook, 1994). The data reliability of the current study was checked through double-coding and abstracting the data from the same transcripts which was performed by two separate persons.
Accuracy Sometimes other sources can be used to confirm inferences from data such as previous successes, contextual experiences, established theories, and representative interpreters. “A content analysis is valid to the extent that its inferences are upheld in the face of independently obtained evidence” (Westbrook, 1994). In the present study sampling method was based on the previous contextual findings of another study on “stages of change theory”. The results of the other study were confirmed through the current study which in turn supports the credibility of data.
Results The analysis of data demonstrated barriers of micro level in four categories and two themes. The micro level barrier themes focused on individual and contextual obstacles based on the GPs’ views regarding depression management. The results showed different perceptions on the barriers between the two groups of GPs, those who did change and had a positive perception of the CME program they participated in three years ago, and some who did not change. The two themes and four categories are displayed in Table 1. Table 1. Themes, Categories and Subcategories of Micro Level Barriers to Management of Depressive Disorders based on the GPs’ Perspectives. Theme
Individual factors
Category
Subcategory
Educational
Physician’s academic training CME
Professional
MICRO LEVEL BARRIERS Contextual factors (setting factor)
Psychological disorders
Motivation Past experience Competence Patients’ attitude and culture Depressive disorder characteristics Socio-Economic Colleagues’ Opinion (Interface GPs’ with other professions) Practice situation
Work place issues
Lack of time Financial issues
The main themes included: Individual factors (educational and professional categories) and contextual factors (psychological disorders and work place categories).
Individual Factors Educational Issues Academic psychiatric training: Potential barriers for diagnosis and management of depression disorders were based on the GPs’ points of view from two extremes: those who did not change their performance and behavior and those who did. The Psychiatry courses for medical students in Iranare offered for no more than a month during their internship which is admittedly insufficient (P3c2). Another participant mentioned inappropriate teaching methods, which were not applicable to doing interviews with patients during their general undergraduate courses in medicine. “It seems that one of the hindering problems regarding thedetection and treatment of depression is that we are not well trained with any proper clinical interview techniques in the general medical courses” (P4C45). CME Normally the CME program is not designed based on GPs’ needs. A participant explained: “I remember a meeting was held by a group of surgeons about different ways of operating breast cancer. What are the advantages of knowing different methods of operating breast cancer for a general practitioner (GP)? If the meeting was about different ways of diagnosis and screening of breast cancer, it would help us diagnose the disease. I only attended the meeting to gain extra CME credit points. We neither understood what the surgeons said nor did they care whether we understood their points or not. The subject is of no use to us in general” (P8c13). One of the GPs’ who did not change his performance and behavior stated: “In a regular CME program, the sessions were mere lectures and were thus uninteresting to us. They do not affect our knowledge and performance as the content will be forgotten very soon” (P4c6). “CME courses regarding one subject normally continue in an excessively big interval which in turn leads to the loss of information” (P10c6). Specific CME Program: “The specific CME course increased my knowledge and changed my view. After the course, the quality of my diagnosis and treatment improved. For instance, prior to the course I didn’t care and ask if the patients were suicidal because I thought they would not like to talk about it. But now I follow through with that point with no exception and then I try to pay attention to whether or not they are seriously considering suicide” (P3c1)? “What we read in books did not even begin to compare with the information provided by teachers in specific CME events. The provided information was more practical and gave us more useful information for our practice. Especially in the CME course when i had interviewed with Standardized Patients and get feedback from teachers I had learnt a lot” (P8). “Following my participation in the course, my motivation for self-study increased due to the useful printed materials and references that the course instructors provided regarding the management of depression” (P1C5).
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Designing Effective CME—Potential Barriers to Practice Change in the Management of Depression: A Qualitative Study
“Even though I had previously counseled depressed patients and diagnosed and treated them; after attending the CME event I am more capable of distinguishing between different types of depression and combining disorders” (P11, C11, C13). “Following my participation in the course, I have followed up with severely depressed patients who may have committed suicide or are prone to do so and referred them to a psychiatrist” (P11C12) (P8C1). “After participating in the course I began to prescribe drugs more carefully. Before our attendance in a specific course, when a patient complained about her/his difficulty to sleep at night, without asking him further questions in order to rule out depression, I would prescribe sleeping pills for him, instead of prescribing Fluoxetine or another antidepressant” (P3c19). Some of GPs’ who did not change their performance and behavior made the following statements: “I think the previous CME course (specific course) in which I participated, had no effect on my performance as there are several more important disorders than depression” (P7C1). “I do not remember crucial points of the specific CME course that you are asking of it. I just remember that Depression is an important disorder and we should pay more attention to it but I have participated in that course simply to gain CME credits” (P4C36, P4C37). “The mentioned course had no significant effect on my performance. I mean, I refer depressed patients to the psychiatrist who works in our hospital” (P4C38)?
Contextual Factors Work Place Issues The results of this study also indicated that work place and conditions can affect the GPs’ professional requirements regarding management of Depressive Disorders’. Some GPs’ who did change their performance and behavior stated the following: “I work in my private office and the number of depressed patients who consult with me has increased following my participation in the course. I may have missed some cases prior to the course” (P6C30). One of the GPs’ who did not change his performance and behavior said: “Since we have a very crowded and terrible emergency ward in the hospital…, we don’t have enough time to assess the patients’ health and to talk and consult with them to diagnose DD” (P4C4). “I closed my private clinic eight months after participating in that course so the value of what has been taught to me was reduced due to the fact that I was working in the emergency ward. In that place there is no time for treating depressed patients” (P4C40). Shortage of Time Among other problems regarding workplace is the shortage of time for consulting with depressed patients. In this regard, a physician who did change his practice and behavior claimed: “In my office normally I spent 25 - 30 minutes on consultation with a depressed patient and I remember a case in which after a 30 minute discussion, the patient refused to accept his depressive disorder. Other patients sitting in waiting room complained to my secretary saying that I am a talkative doctor. This happened to me several times and other patients became
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angry with me and complained to me when they entered my office” (P318). Even though interviewing depressed patients is a time consuming process, most of the patients will accept my diagnosis and are satisfied with it so they suggest my services to their relatives (PC20). Another participant who did not change his method of practice mentioned: “For instance, since I am working in a very crowded emergency ward, other patients have to wait there for a long time which is not possible for me to provide them with the proper services. If I had more than 10 minutes to talk to each patient, I would be able to diagnose whether the patient is depressed or not” (P4C47). Other factors such as GPs’ motivation, past experience and their competencies have been labeled as an individual theme.
Discussion The main research questions “why did some of the physicians following their participation in tailored CME intervention change their performance and others’ did not”? and “How to explore GPs’ obstacles of behavior change which effects their diagnosis and management of Depressive Disorders?” These are the main concerns of the current study which remain unanswered in almost all parts of the world (Jewell, 2003). Based on the present research findings, several factors affect GPs’ behavior change such as individual factors and setting specifications. Underpinning the andragogia view such as “Bandura”, adult learning theory depends on three important factors: personal, contextual, and behavioral factors. So our findings are in line with Bandura and stages of change theories which emphasized on individual motivation to change their behavior (Rimer & Glanz, 2005). We have found that behavior change occurs, when the personal and contextual factors are considered based on the GPs’ points of view. We interprets and show pictures of GPs’ barriers of behavior change into the context of the theoretical back ground of CME which is the base of the recent study (Figure 2).
Individual Factors Education Academic Training: The preliminary task of medical schools through a well-designed curriculum is to train medical students in order to gain adequate knowledge, skills and attitudes and graduate them as competent physicians who can guarantee the patient safety (Pellegrino, 2002). But the current case is regarding some incompetent graduate GPs’ in the field of Psychiatry due to their shortage of Psychiatry course during their undergraduate study (P3 and P4) (Lecrubier, 2007; Mitchell, Vaze, & Rao, 2009; Wilhelm, Brownhill, Harris, & Harris, 2006). It could be reflecting the educational organizational difficulties such as the medical school psychiatry curriculum: Syllabus, teaching and evaluation methods, educational environment etc. Based on the findings of the study at hand, GPs’ believed that their academic psychiatry courses and their knowledge and skill especially in the field of management of depressive disorders were insufficient. They claimed that their clinical psychiatry education period was too short P3 P4. In line with our results Wilson directed a study regarding what GPs’ essential needs are regarding the management of psychiatry
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Education Work place
GPs' as a Profession
Psychological Disorder
Figure 2. Micro level Barriers of GPs’ behavior change.
disorders based on their view points and which knowledge, skills and attitudes should be included in the current medical curriculum in the University of Aberdeen. They have found that depression is the most common psychiatry disorder for the management of which they would like to gain competence. In contrast with our findings, GPs’ in their study stated that their needs for management of depression is in the domain of knowledge but the result of our study expressed GPs’ needs in the skill and attitude domains (Wilson, Eagles, Platt, & McKenzie, 2007). Nisha Dogra et al. stated that psychiatry curriculum development for medical students is a complex process due to the fact that successful implementation should be kept in their curriculum developers’ mind (Dogra et al., 2010). Overall at present time in Iran at TUMS medical curriculum is reforming but there is still a necessity to include current study results to the curriculum. In some countries such as Iran, when a difficulty regarding physicians’ competency for management of disease happens, CME would be responsible to overcome the current barriers. CME Training General issue and Specific issues of CME: Based on our data the GPs’ had two perspectives; the first, focused on their general idea regarding the CME events and the second was related to their specific views of tailored CME courses in which they had participated. Their general idea of CME events in both groups demonstrated that they were not satisfied with regular CME events for several reasons such as: impractical topics which did not address the GPS’ main issues, and applying didactic educational methods, etc (P8, P4, P10). Their opinion of the specifically tailored CME (Shirazi et al., 2011) was totally different. Some of GPs who had changed their performance, in contrast with the other group, found it practical, interactive, and more relevant to their real needs based on the data which was extracted from interviewing the two groups of GPs’ (P1, P3, P8, P11). In accordance with our findings, applying interactive methods, Marinopolos et al. directed a systematic review for assess-
ing the physicians’ behavior change and improving their clinical outcomes through participation in a CME Intervention. They suggested that it has been successful, at least to some extent, in not only attaining, but also in sustaining the intended objectives. They illustrated shared factors throughout the studies. For instance, using printed materials was proven to be less effective than using live media and multi-media. Applying multifaceted teaching and learning methods was more effective than applying a single method. Hence the staff considered these factors in planning CME events to enhance its effectiveness (Marinopoulos et al., 2007). Another systematic review focused on “assessing barriers to physicians’ adherence to practice guidelines”. They found seven general categories of barriers such as: knowledge, attitudes, behavior, awareness, familiarity, agreement, and lack of self-efficacy. Thus our general finding regarding participants’ dissatisfaction in Iranian CME events are due to the use of didactic methods and do not consider the main attributes of an effective CME program by CME providers. Those programs should be modified and adopted to the specific design, based on GPs’ needs and applying a theoretical framework and utilizing multifaceted methods, the same as our previous studies which satisfied most attendees (Shirazi et al., 2011, 2007, 2009, 2008). Modeling CME Intervention Interestingly, those GPs’ who had changed their performance and stages of change were in intervention groups and few of them who had not changed assumed that the CME course they participated in was not sufficient for them which could be interpreted as their inadequate motivation for learning about depression management (P4). Their lack of motivation could be related to their work place since most of them were working in the emergency wards of the hospital and they did not feel that their needs were aligned with depressive disorders. In contrast, other GPs working in a primary health care setting suggested the usefulness of the previous course and its content sustainability of course content (for example some of them remember some specific educational sessions after three years, which they
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Designing Effective CME—Potential Barriers to Practice Change in the Management of Depression: A Qualitative Study
had interviewed with Standardized Patients) (SP) (P8). In line with our findings, in a review article, a writer quoted “Continuous Medical Education (CME) generally has failed to address the physicians’ educational needs”. They have emphasized that if CME providers wish to improve doctors learning translating knowledge into physicians’ practice, there is a crucial need to understand theories of physician behavior change and characteristics of effective CME interventions. The writers have then discussed the necessity of person center education in which physicians preferred independence and self-directed learning. So if these issues are overlooked, then the CME program is doomed to fail (Amin, 2000). Following CME program’s exploring the barriers of behavior change based on the participants’ view, there is also a very important component which can help us overcome the obstacles and there for design more effective CME courses in the future. It is thus highly recommended to design CME programs based on accepted theories of behavior change. Based on theoretical perspectives of “stages of change” those GPs who did not change their performance, also remained in the attitude stage after participation in CME specific courses. Data analysis showed that those GPs’ views supported “stages of change” theory, where they had participated three years ago. GPs’ who were in the attitude stage and did not change their performance did not feel they need to change their performance in the field of management of depression (P4). Based on the data they did not feel they need to participate in management depression disorder course. So, they participated in it merely to gain CME credit points. Thus CME providers and policy makers should consider these issues in designing future CME programs. They should assess GPs’ readiness to change before they participate in the courses. If participants are not ready then participating in the course is useless for them (Shirazi et al., 2011, 2007, 2009, 2008). Work place and Practice Setting: In current study the physicians’ work place played an important role. For instance, some physicians who worked in primary health care settings stated that a tailored CME course (participated three year ago) was efficient in their performance (P11). However, for some others who were working in the emergency wards from another extreme the program was not useful (P4). According to one published study work place could affect the doctors’ perceived needs for the management a depression; they have found that those doctors who work in a hospital had different psychiatric needs in comparison with those who work in the primary care (Wilson et al., 2007). Setting and workplace could be acted as a potential barriers for GPs’ behavior change. Interestingly the basement data from previous study demonstrated that GPs’ work place had direct effects on their professional needs and also on their readiness to change and learn more about specific courses (P11, P4). Shortage of time: Inadequate time is an issue that was raised by both groups of GPs’ from two extremes regarding barriers of behavior change. But their explanation of this process was varied. The ones who had changed their performance believed that due to an increased patient satisfaction the total number of their patients will increase (P3). In contrast, others who worked in the crowded work places such as emergency wards, need to spend more time to explore depression which they thoughts it impossible (P4). As confirmed in our study, time shortage is commonly described as a barrier to adherence by more than 10% of GPs’
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who participated on their study (3). Other researchers found the same issue which has been arisen as barrier, due to the nature of the depression disorder, for eliciting the symptoms from patients there is a need to dedicate more time than other disorders and it will be increased socio-economic deficit of physician (Chew-Graham, Mullin, May, Hedley, & Cole, 2002; Pierce & Gunn, 2007). Strengths and limitations of this study: This study has some limitations. Firstly, to transfer the results to other countries, the context of the Iranian healthcare system has to be taken into account. Secondly, the rather small number of participants can be seen as a limitation. The interviews were carried out until no new information was added, which can be seen as a strength, even if it is probable that the reason for reaching saturation with a rather small number of participants might be related to the fact that they were recruited from the RCT of a previous study. On the other hand, since the participants had been part of an educational intervention with a follow-up, they were engaged and their characteristics were known which guaranteed a broad view of the issues in focus. Thirdly, all participating GPs had more than 10 years’ of experience, which could be seen as a limitation even though GPs with more experience might have a deeper understanding of the questions probed in this study. One of the strengths in this study was that all authors were engaged in the analysis and their different experiences made it possible to challenge each other’s assumptions and constantly return to the data for confirmation of interpretations. An additional strength of the current study was the use of sampling method based on the previous contextual findings of previous studies according to the “stages of change theory”. The previous results were confirmed through the current study which appears to approve the credibility of the data.
Conclusion To make complex changes in the physicians’ performance, we need to overcome potential barriers at various levels (Grol & Wensing, 2004). Common CME programs do not have scientific design based on the behavior change theory and also they do not explore participants’ perceptions and performance following attending in those activities. In order to make them more effective, there is a need to deepen the understanding of GPs’ experience regarding the obstacles of behavior change. Otherwise, CME providers could not be able to estimate the potential barriers of behavior change. CME organizers should take it into account that the nature of individual and contextual factors (Micro level)—Educational, professional, Psychological disorders and Work place issues—to design a successful CME intervention and utilize underpinning and testable theories such as the “stages of change”.
REFERENCES Amin, Z. (2000). Theory and practice in continuing medical education. Annals of the Academy of Medicine, Singapore, 29, 498-502. Chew-Graham, C. A., Mullin, S., May, C. R., Hedley, S., & Cole, H. (2002). Managing depression in primary care: Another example of the inverse care law? Family Practice, 19, 632-637. Davis, D. A., Thomson, M. A., Oxman, A. D., & Haynes, R. B. (1995). Changing physician performance. JAMA: The Journal of the American Medical Association, 274, 700-705.
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Diner, B. M., Carpenter, C. R., O’Connell, T., Pang, P., Brown, M. D., Seupaul, R. A., Mayer, D., et al. (2007). Graduate medical education and knowledge translation: Role models, information pipelines, and practice change thresholds. Academic Emergency Medicine, 14, 10081014. Dogra, N., Höschl, C., Moussaoui, D., Gask, L., Coskun, B., & Baron, D. (2010). Developing a medical student curriculum in psychiatry. In L. Gask, B. Coskun, & D. A. Baron (Eds.), Teaching Psychiatry: Putting Theory into Practice (pp. 27-46), Hoboken, NJ: Wiley. Elo, S., & Kyngäs, H. (2008). The qualitative content analysis process. Journal of advanced nursing, 62, 107-115. Grol, R., & Wensing, M. (2004). What drives change? Barriers to and incentives for achieving evidence-based practice. The Medical Journal of Australia, 180, S57. Hannes, K., Leys, M., Vermeire, E., Aertgeerts, B., Buntinx, F., & Depoorter, A.-M. (2005). Implementing evidence-based medicine in general practice: A focus group based study. BMC Family Practice, 6, 37. Jewell, D. (2003). How to change clinical behaviour: No answers yet. The British Journal of General Practice, 53, 266. Krippendorff, K. (2004). Book review: Content analysis: An introduction to its methodology (2nd ed.). Organizational Research Methods, 13, 392-394. Kvåle, K. (2007). Do cancer patients always want to talk about difficult emotions? A qualitative study of cancer inpatients communication needs. European Journal of Oncology Nursing, 11, 320-327. Lecrubier, Y. (2007). Widespread underrecognition and undertreatment of anxiety and mood disorders: Results from 3 European studies. The Journal of Clinical Psychiatry, 68, 36-41. Marandi, A. (1996). Integrating medical education and health services: The Iranian experience. Med Educ, 30, 4-8. Marinopoulos, S. S., Dorman, T., Ratanawongsa, N., Wilson, L. M., Ashar, B. H., Magaziner, J. L., Qayyum, R., et al. (2007). Effectiveness of continuing medical education. Evidence Reports/Technology Assessments, 149, 1-69. Mitchell, A. J., Vaze, A., & Rao, S. (2009). Clinical diagnosis of depression in primary care: A meta-analysis. The Lancet, 374, 609-619. Oxman, A. D., Thomson, M. A., Davis, D. A., & Haynes, R. B. (1995). No magic bullets: A systematic review of 102 trials of interventions to improve professional practice. CMAJ: Canadian Medical Association Journal, 153, 1423. Palmquist, M. (2010). Writing guide: Content analysis. Fort Collins, CO: Colorado State University. Pellegrino, E. D. (2002). Professionalism, profession and the virtues of the good physician. Mount Sinai Journal of Medicine, 69, 378-384. Pierce, D., & Gunn, J. (2007). GPs’ use of problem solving therapy for depression: A qualitative study of barriers to and enablers of evidence based care. BMC Family Practice, 8, 24. Prochaska, J. O., DiClemente, C. C., & Norcross, J. C. (1992). In search of how people change. Applications to Addictive Behaviours, 47, 1102-1114. Pope, C., Van Royen, P., & Baker, R. (2002). Qualitative methods in research on healthcare quality. Quality and Safety in Health Care, 11,
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148-152. Rimer, B. K., & Glanz, K. (2005). Theory at a glance: A guide for health promotion practice. Bethesda, MD: US Department of Health and Human Services, National Institutes of Health, National Cancer Institute. Shirazi, M., Gandomkar, R., Ponzer, S., & Silén, C. (2013). Exploring the macro level barriers that affect Iranian GPs’ diagnosis and management of depression disorders. European Journal for Person Centered Healthcare, 1. (in Press) www.bjll.org/index.php/ejpch Shirazi, M., Lonka, K., Parikh, S. V., Ristner, G., Alaeddini, F., Sadeghi, M., & Wahlstrom, R. (2011). A tailored educational intervention improves doctor’s performance in managing depression: A randomized controlled trial. Journal of Evaluation in Clinical Practice, 19, 16-24. Shirazi, M., Assadi, S. M., Sadeghi, M., Zeinaloo, A. A., Kashani, A. S., Arbabi, M., Wahlstrom, R., et al. (2007). Applying a modified Prochaska’s model of readiness to change for general practitioners on depressive disorders in CME programmes: Validation of tool. Journal of Evaluation in Clinical Practice, 13, 298-302. Shirazi, M., Parikh, S. V., Alaeddini, F., Lonka, K., Zeinaloo, A. A., Sadeghi, M., Wahlstrom, R., et al. (2009). Effects on knowledge and attitudes of using stages of change to train general practitioners on management of depression: A randomized controlled study. Canadian Journal of Psychiatry, 54, 693-700. Shirazi, M., Sadeghi, M., Emami, A., Kashani, A. S., Parikh, S., Alaeddini, F., Wahlstrom, R., et al. (2011). Training and validation of standardized patients for unannounced assessment of physicians’ management of depression. Academic Psychiatry, 35, 382-387. Shirazi, M., Zeinaloo, A., Parikh, S., Sadeghi, M., Taghva, A., Arbabi, M., Wahlstrom, R., et al. (2008). Effects on readiness to change of an educational intervention on depressive disorders for general physicians in primary care based on a modified Prochaska model—A randomized controlled study. Family Practice, 25, 98-104. Shirazi, M., Zeinaloo, A., Sabouri, K., & Alaedini, F. (2004). Assessing the gap between current and desirable needs in TUMS CME Unit: Participants viewpoints. Iranian Journal of Medical Education, 5, 17-22. Westbrook, L. (1994). Qualitative research methods: A review of major stages, data analysis techniques, and quality controls. Library & Information Science Research, 16, 241-254. Wilhelm, K., Brownhill, S., Harris, J., & Harris, P. (2006). Depression—What should the doctor ask? Australian Family Physician, 35, 163-165. Wilson, S., Eagles, J. M., Platt, J. E., & McKenzie, H. (2007). Core undergraduate psychiatry: What do non-specialists need to know? Medical Education, 41, 698-702. World Health Organization (2004). Prevention of mental disorders: Effective interventions and policy options: Summary report. Geneva: World Health Organization Zhang, Y. (2012). College students’ uses and perceptions of social networking sites for health and wellness information. http://informationr.net/ir/17-3/paper523.html
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4 Investigating Cognitive Processes Underlying Reading in Arabic: Evidence from Typical and Poor Reading Performance Haitham Taha1,2 1
The Cognitive Lab for Reading and Learning-Sakhnin College for Teachers’ Education, Sakhnin, Israel 2
Safra Brain Research Center for Learning Disabilities-Haifa University, Haifa, Israel
The current study has examined by which cognitive factors at the field of phonological and visual processing, rapid automatized naming and morphological awareness, contribute to reading and decoding abilities among typical and poor native Arabic readers. In the current study, the performances of two groups of participants, typical and poor readers were compared through tasks that examined their performance with regard to the areas of functions mentioned above in addition to other tasks that examined their performance in reading meaningful and pseudo words. The study’s results have indicated that the visual and phonological processing skills play an important role in reading among typical and poor readers as well. Moreover, it was found that the visual and phonological processing skills of participants with poor reading skills were lower in comparison to participants with typical reading abilities. Keywords: Phonological Processing; Morphological Processing; Visual Processing; R.A.N; Arabic Orthography
Introduction The process of reading acquisition is regarded as complex and relies on the development of various cognitive processes. Many researchers suggest that during the process of reading acquisition, the reader learns the written representation of the phonemes of which the spoken words are composed, as during the process of reading, the reader can decode these phonemes according to the graphemes that represent them (Ziegler & Goswami, 2005). The reader can correctly pronounce written words through processes of sequential blending (Adams, 1990; Bradely & Bryant, 1978; Coltheart, 2005; Lundberg, Olofsson, & Wall, 1980; Snowling, 2001; Stanovich, 1986; Treiman, 1993). Many researchers also suggest that normal development of phonological processing skills, such as phonemic segmentation and phonemic blending, is acquired as the reader enjoys a normal phonological awareness regarding the speaking sounds which composed the spoken words (Abu-Rabia & Taha, 2004, 2006; Goswami & Bryant, 1990; Share, 1995; Snowling, Goulandris, & Defty, 1996; Stanovich, 1988; Wagner & Torgesen, 1987; Ziegler & Goswami, 2005). Those phonological processing skills are found to be main contributor to reading acquisition in several alphabetic orthographies and are affected mutually by the exposure to print (Ziegler et al., 2010; Ziegler & Goswami, 2005). Accordingly, the study at the field of the reading acquisition and its development discerns that among readers with difficulties, particularly those with reading disabil-
ity, an inadequate performance in tasks that investigate phonological awareness was found (Snowling, 2001; Stanovich, 1986; Vellutino, Fletcher, Snowling, & Scanlon, 2004). Along with the previous assumption, Snowling (2001) suggests that heterogeneity between various readers concerning the control of the processes of phonological processing distinguishes between the sub populations of readers in the extent of their reading skills. In addition, such heterogeneity illustrates that readers with reading disability suffer from inadequate development of processes of phonological processing, as the level of difficulty in reading among this group is measured by the extent of inadequacy in these processes of processing. Consistent with Snowling’s assumption, research evidence argues that individual differences in the processes of reading and spelling are related to the processes of phonological processing (Goswami & Bryant, 1990; Share, 1995; Snowling, Goulandris, & Defty, 1996; Stanovich, 1988; Wagner & Torgesen, 1987). Appropriately, different developmental models in reading development (for example: Ehri, 1999; Frith, 1985), suggest that formation of a skilled reader is a matter of a transition from logographic stage where the child can identify forms of words that are familiar in his/her surrounding as symbols (such as his/her name etc.) to the alphabetic stage where the reader learns the letter-sound relationship and that reading of words becomes a matter of a process of phonological decoding that basically relies on a phonemic processes of segmentation and blending according to the grapheme sequence (the letters) and
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the pattern of the written word. By the repeated exposure to the patterns of words in the case of normal processes of reading and a normal development of the processes of decoding at the alphabetic stage, the child stores these patterns of words to which he/she was exposed during the process of reading. Consequently as children read these words again, they can more accurately and swiftly identify the pattern of the word according to its orthographic structure. This stage is called the orthographic stage or the consolidated one (Ehri, 1999; Frith, 1985). Various researchers argue that in spite of the significant role of the phonological awareness in controlling the processes of reading, it is important to consider the contribution of other linguistic variables in achieving fluency in reading. In recent years, the research conducted in the field of reading acquisition highlights the importance of the morphological awareness and the development of the morphological lexicon among readers for the purpose of a normal acquisition of reading skills (BenDror, Bentin, & Frost, 1995; Elbro & Arnbak, 1996; Levin, Ravid, & Rapaport, 2001; Nunes & Bryant, 2009; Ravid, 2001; Senechal, 2000; Taha & Siaegh-Haddad, submitted; Treiman & Bourassa, 2000). The results of the studies that examined the reading acquisition among novice readers indicated that children eventually have a good intuitive knowledge regarding the morphology of the language (Clark & Hecht, 1982). Accordingly, Carlisle (1995) points out that the extent of the morphological awareness at kindergarten years, which was measured by tasks of morphological differentiation successfully predicts the ability in reading comprehension at the second grade. In other words, the morphological awareness strengthens the skills that are related to reading such as the identification of words and even meta-linguistic ability such as reading comprehension (Tong et al., 2011). In addition, consistent with the approach which suggests that individual differences in reading abilities are produced as a result of a variation in the extent of the control of the processes of phonological processing (Goswami & Bryant, 1990; Share, 1995; Snowling, Goulandis, & Defty, 1996; Stanovich, 1988; Wagner & Torgesen, 1987), other researchers suggest that differences in the processes of morphological processing and morphological awareness contribute to inter-personal differences in the processes of literacy skills (Nunes, Bryant, & Lindman, 2006; Rubin, 1991). Other researchers argue that in addition to the contribution of processes of phonological and morphological processing to reading, other processes also predict reading such as automatization and the speed of retrieval and naming, particularly phonological naming to repeated visually presented forms (Denckla & Cutting, 1999; Wolf, Bowers, & Biddle, 2000). The argument of researchers who advocate the approach of the speed of retrieval and naming indicates that the process of phonological naming according to visual labels as measured in tasks of rapid naming (Denckla & Rudel, 1974), is sort of analogy to the process of reading in which the reader is required to match the sound to the visual clue (The letter or the written form of words). On the other hand, such tasks can predict the success in the acquisition of skills of decoding and letter-sound relationship in the process of reading (Bowers & Newby-Clark, 2002). However, for the process of verbal retrieval according to the visual labels to occur, the verbal and visual processes need to occur simultaneously, a situation similar to the process of reading written words (for more details, see Breznitz, 2006). This
Psychology Handbook
process of timing or “synchronization” between the phonological processes and the processes of visual processing of the forms of word is considered as a fundamental process, as it may enable the reader to read words efficiently. Breznitz (2006) argues that the lack of synchronization between the processes certainly leads to a loss of the phonological and visual knowledge needed for reading words due to the limitation of the working memory. Therefore, there is a need for a “quick” work on this synchronized system to prevent inconsistency between the visual and phonological processes as the outcome could be a difficulty in reading words. This pace of work is called speed of processing (SOP) (Breznitz, 2006). Eventually, it can be inferred that similar to explanations about the variation in the reading ability based on the approach of phonological processing, mentioned above, and the approach of morphological processing and the speed of retrieval, SOP indicates that variation in the speed of processing is a possible source for variation in reading ability since it is a possible reason for disability in synchronization between the processes during the processing of words. The processes of synchronization deal with the visual-phonological synchronization in the process of processing of words, though other researchers argue that the processes of visual processing are at the center of processes of reading and proved significant and distinctive in identifying normal readers and readers with difficulties (Everatt et al., 1999; Heiervang & Hugdahl, 2003; Jaœkowski & Rusiak, 2005). A central research approach at the field of psychology of reading indicates that these processes of phonological decoding that occur during identification of words and the processing of the patterns of written words are directed through the resources of visual attention that need to be sufficiently available during the process (for more details, see Everatt, 1999). During reading, the process of words identification starts with the visual processing of the orthographic form of words. The eyes scan the written form through a series of movements of fixation and saccades. As the eyes are fixed on the word during the scanning, the situation is called fixation and as the eyes move toward the following word, the situation is called saccadic movement. These two movements of the eyes, fixation and saccades, play a significant role in centering the pattern of the scanned word at the fovea, the eye’s most sensitive position, for the purpose of increasing the possibility that the word will be processed to the maximum. The success of the process of visual scanning necessitates mobilization of sufficient resources of visual attention. On the other hand, research on the psychology of reading indicates that disabilities in the processes of visual attention disturb the movements of the eyes during the process of reading of words (Everatt, et al., 1999; Heiervang & Hugdahl, 2003; Jaœkowski & Rusiak, 2005). Besides, the research in the field of psychophysiology and neuropsychology indicates that the visual areas at parietal lobes of the brain are related to focusing the movements of the eyes and to processes of visual attention (Glickstein, 2000; Goodale & Milner, 2004; Milner & Goodale, 1995). Beside, Kinsey et al., (2004) argue that the function of visual attention is particularly important during reading new words and pseudo words. The failure of readers with reading disability in reading pseudo words can be attributed to their failure in processes of visual processing of the written words’ orthographic form (Heiervang & Hugdahl, 2003). This failure in the processes of processing that rely on processes of visual attention during reading leads to failure in de-
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Investigating Cognitive Processes Underlying Reading in Arabic: Evidence from Typical and Poor Reading Performance
tecting the position of the letter in the word, a thing that leads to reading errors of letters transposition and migration (Friedman & Gvion, 2001). Studies that compared the performances of readers with reading disability versus normal readers in tasks that examined the processes of visual attention and spatial processing indicated that readers with reading disability achieved lower performance than readers with normal reading ability (Facoetti & Turatto, 2000; Vidyasagar & Pammer, 1999). Consistent with the above mentioned review, it can be indicated that the research regarding the study of reading acquisition and the skills of recognition of words emphasizes the development of a variety of cognitive process. Accordingly and in light of the abovementioned review, the current study seeks to investigate by which phonological processing, automatized naming, morphological awareness and visual processes contribute to the ability of reading new unfamiliar words as well as familiar words in Arabic orthography which has unique characteristics. Hence, this study tries to identify the implications of the unique orthographic and linguistic characteristics of the written Arabic language on the cognitive processes related to the reading process.
Reading in Arabic Orthography Studies in the field of reading in Arabic orthography argue that the process of phonological processing is significantly related to the processes of reading in Arabic orthography (AbuRabia, 2001, 1997a, 1997b, 2007). Furthermore, other researchers argue that the development of phonological awareness, at the center of the processes of phonological processing, among native Arab readers is highly influenced from diglossia; a situation that may be clearly manifested during the acquisition of reading and spelling (Abu-Rabia & Taha, 2005; SaieghHaddad, 2003, 2004). In unique linguistic situation of the Arabic language, the distance within different linguistic domains between the spoken language and dialect to the written language acquired by children at the formal framework of school is a classic situation of diglossia (Ayari, 1996; Ferguson, 1959; Taha, 2013). Other studies also suggest that process of morphological processing have high importance regarding controlling processes of reading at the Arabic orthographic system, due to the morphological richness of the Arabic language (for more details, see Abu-Rabia, 2007; Abu-Rabia & Taha, 2005; Taha, 2013). Beside to the specific linguistic features of the Arabic language and their effect on reading, recent studies suggest that the specific orthographic features of the written Arabic may affect the process of word recognition in Arabic (Ibrahim, Eviatar, & Aharon Peretz, 2002; Taha, Ibrahim, & Khateb, 2013). Two main unique features are account within this frame, the level of connectedness of the letters within the word and the existence of dots and vowelization marks above and below the letters within the written word. A former study conducted by Ibrahim, Eviatar and Aharon-Peretz (2002) showed that the orthographic structure of the Arabic language may decelerate the pace of the visual processing during reading. While other studies found that this effect of orthographic structure on word recognition might be modulated by development and exposure to print (Khateb et al., Submitted). Yet, so far studies have not investigated the contribution of processes of visual processing and the speed of naming according to visual stimuli besides the contribution of the processes of phonologi-
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cal and morphological processing to the ability of reading and decoding, neither familiar nor unfamiliar words, in the Arabic language. Also, investigating the differences of the contribution of the abovementioned factors to reading among typical readers versus poor readers have not been conducted. It should be noted that a study conducted by Abu-Rabia, Share and Mansour, (2003) examined the processes of performance in tests of visual memory among typical readers and readers with reading disability at the same chronologic age group and reading age and their contribution to reading words, as no differences were found in the performances of participant in the tests of visual memory. The study of Abu-Rabia and his colleagues focuses on examining the process of global and analytical visual memory but it does not directly focus on examining the processes of sequential visual scanning and search. While the process of orthographic processing of the orthographic words patterns relies on processes of visual scanning and processing and sequential visual processing in addition to processes of visual identification. Accordingly, due to the fact of the orthographic complexity of the written Arabic, where letters shapes changes according to their position in the written form and according to the letters that precede and follow them. And due to the visual intensity that exists as a result of the vowelization marks above and under the letters within the written words. Accordingly, the current study assumes that the processes of visual sequential processing and distinction will have an essential contribution to achieving efficient processes of reading in the Arabic language beside to other cognitive abilities that were found to affect reading in Arabic like the phonological and morphological skills. In general, it is important to investigate the contribution of the different cognitive and linguistic skills that were reported during the abovementioned review on reading in Arabic orthography among typical and poor readers.
Methods Participants. 67 native Arab children studying at Arab school in north of Israel have participated in the study. The participants were divided into two groups according based on their performances in the test of reading words in context. From the first sample, children whose performance was below 70% at the task of reading meaningful words were defined as children with reading difficulties. The chosen words were regarded as highly frequent taken from pedagogical texts. A skilled reader can identify these words at a high level of accuracy (Taha & Saiegh-Haddad, Submitted). Thus readers whose percentage of accuracy in reading these words is below 70% can be regarded as reader with reading difficulty. The group of typical readers is those who achieve above 90% in reading meaningful words. The reading screening task included 60 meaningful punctuated words (α = 0.82). The group of poor readers included 11 boys and 21 girls whose age average was 12.04 (SD ± 0.29). The group of typical readers included 18 boys and 17 girls whose age average was 12.12 (SD ± 0.39) years old. All participants were from the middle class of socioeconomic status. The participants in the two groups took part in tasks that examined reading meaningful words, pseudo words, processes of phonological processing, automatic naming, orthographic and morphological awareness and processes of visual processing. Procedure. The testing procedures were conducted at the school in a quiet room dedicated specifically for the purpose of
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current study. Testing procedure took place during the regular school days of the week. Tests were conducted on a one-on-one basis. The order of the tests was counterbalanced across participants.
Material and Stimuli Rapid Automatized Naming (R.A.N) (Denckla & Rudel, 1974) Naming of letters. A sheet of 5 Arabic letters, ten-times randomly repeated, was presented before the participants, who was asked to name the 50 letters at the fastest possible pace. Digit naming. A sheet of 5 digits, ten-times randomly repeated was presented for each participant who was asked to name the 50 digits at the fastest possible pace. Naming of objects. A sheet of 5 pictures of objects ten-times randomly repeated was presented before each participant who was asked to name the 50 pictures at the fastest possible pace.
Phonological Processing Phonemic Deletion. The test is composed from 20 items. Within each item of the test, words were presented Auditory before the participant who was eventually asked to omit a phoneme from the word and pronounce the word without the omitted phoneme (α = 0.86). Phonemic Blending. The test is composed from 10 items. Within each item of the test, phonemes were presented before each participant who was asked to combine the phonemes sequentially and to submit the produced word (α = 0.91). Short-term phonological memory. Series of digits was presented before the participants who were asked to repeat the series again after hearing it through an immediate retrieval from their memory. Each item included two series with a same number of digits. The series begins with two digits in the first item and for each additional item one digit to each series. Each participant score was calculated as the total number of the correct series were retrieved (α = 0.93). Phonological Working memory. Audio series of digits were presented before the participants who were asked eventually (after hearing the series) to repeat it again by an immediate retrieval from their memory but in an opposite order. Each item included two series. The series starts with two digits in the first item and in each additional item one digit for each series. Each participant score was calculated as the total number of the correct series were retrieved (α = 0.91).
Morphological Awareness Morphological decision task. This task included 15 items. Each item included five words, four of which are derived from the same root and the fifth word is morphologically different but phonologically and orthographically similar to the other four words. The participant was asked to identify and circle the word which is different concerning its morphological relationship (α = 0.85).
Visual Processing Visual Perception Test (Beery, 1997). The test included 27 items. Each item has a target image and a number of other images below. The participant was asked to identify the image that exactly fit in with the target image using visual distinction
processes. The level of the test’s difficulty was at an increasing pace. Visual search test of the diamond shape (Rudel, Denckla, & Broman, 1978). The participant was asked to mark the target image in a sheet that included a lot of distractors. The target image appeared 14 times randomly in the sheet. Visual search test of a series of digits (592) (Rudel, Denckla, & Broman, 1978). The participant was asked to mark the series of digits (592) in a sheet that included a lot of distractors (series from other digits). The target series appeared 14 times randomly in the sheet.
Reading Tests Reading pseudo words. The participant was asked to read a list of 22 pseudo words connected according to common form in the Arabic orthography and conform to words at the age of orthographic exposure. The reader has never been exposed to these words, meaning that the words were regarded as new (α = 0.79). Reading meaningful words. The participant was asked to read a list that included 56 familiar, meaningful and fully-punctuated words. The words conformed to the level of difficulty and exposure according to the participant’s age (α = 0.85).
Results Using the model of stepwise regression indicates that there is a significant correlation between the processes of visual distinction as measured by the visual perception test and processes of visual search as measured by the test of searching the series of digits, but not by the test of visual searching of the visual shape, to reading meaningful and pseudo words. Calculating Person correlation indicates that in reading pseudo words there is a significant and positive correlation (r = 0.34, p < 0.01) with the processes of visual distinction measured through the Beery test. In addition, regarding the reading of pseudo words, a significant positive correlation was found with the processes of visual searching of the series of digits (r = 0.32, p < 0.01). Also concerning reading regular meaningful words, a signifycant positive correlation was found with the performance in the task of visual distinction (r = 0.51, p < 0.001). In addition, a positive correlation was found with the performance in the test of visual searching for the series of digits (r = 0.34, p < 0.01). Significant correlation was found between the processes of phonological processing as examined in the tests of phonemic blending and phonemic omission to the processes of reading. A positive and significant correlation was found between the processes of phonemic blending and phonemic omission to reading pseudo words (r = 0.28, p < 0.05 and r = 0.5, p < 0.001 respectively). Also positive and significant correlation was found between the processes of phonemic blending and phonemic omission to reading meaningful and regular words (r = 0.5, p < 0.001 and r < 0.53, p < 0.001). A positive and significant correlation was also found between the phonemic blending and working memory (r = 0.27, p < 0.03), in addition to the positive correlation that was found between the processes of phonemic omission and the processes of working memory (r = 0.4, p < 0.01). From the above analysis, based on the model of regression, it
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Investigating Cognitive Processes Underlying Reading in Arabic: Evidence from Typical and Poor Reading Performance
can be indicated that the variables which added to the regression model explain 53% of the variance in the process of reading meaningful words beyond the two populations of the study (see Table 1). The first variable is the ability of phonemic deletion (R2 = 0.29). The second variable is the performance in the test of visual distinction of Beery (R2 = 0.12). The third variable is the search for symbols (diamond test) (R2 = 0.08) and the fourth is phonemic blending (R2 = 0.04). In reading pseudo words 31.6% of the explained variance was explained by the variables of phonemic omission (R2 = 0.244) as the second variable was the visual search for series of digits (R2 = 0.072) (see Tables 1 and 2). According to the analysis conducted separately on the two groups of readers regarding reading meaningful words, 34.2% of variance within the poor readers was explained significantly by phonemic blending and visual search of digits (R2 = 0.229, and R2 = 0.113 respectively). Besides, 49.5% of variance was found among the group of participants with typical reading abilities was significantly explained by the following variables; phonemic omission, naming of objects, naming of digits and working memory (R2 = 0.161, R = 0.116, R2 = 0.141, and R2 = 0.077 respectively) (see Tables 3 and 4). Regarding reading pseudo words, among the poor readers group 29.6% of variance was significantly explained by the phonemic omission and the visual search for digits (R2 = 0.194, and R2 = 0.102 respectively) Among the groups of readers with typical reading abilities, 32.6% of variance in reading pseudo words was significantly explained by working memory and object naming (R2 = 0.185 and R2 = 0.114 (see Tables 5 and 6). The analysis of variance indicated that there was a significant Table 1. Stepwise Regression Analysis results of predictors for reading words beyond to the both groups of participants. Predictors
R2
R2 Change
F
Phonological Deletion
0.29
0.29
25**
Visual perception (distinction-Beery)
0.37
0.12
19.12**
Visual search-Diamond
0.45
0.08
16.88**
Visual search-592
0.49
0.04
14.57**
**
p < 0.001.
Table 2. Stepwise Regression Analysis results of predictors for reading pseudo words beyond to the both groups of participants. R2
R2 Change
F
Phonological Deletion
0.24
0.244
20.98**
0.072
**
0.31
14.75
**
p < 0.001.
Table 3. Stepwise Regression Analysis results of predictors for reading words within poor readers group.
*
Predictors
R2
R2 Change
F
Phonological Blending
0.229
0.229
8.8*
Visual search-(592)
0.342
0.113
7.55*
p < 0.05.
Table 4. Stepwise Regression Analysis results of predictors for reading words among typical readers group. Predictors
R2
R2 Change
F
Phonological deletion
0.161
0.161
6.31*
Speed naming of objects (R.A.N)
0.277
0.116
6.11*
Visual search-592
0.418
0.141
7.41*
Phonological working memory
0.495
0.077
7.36*
*
p < 0.05, Abbreviation: R.A.N (Rapid Automatized Naming).
Table 5. Stepwise Regression Analysis results of predictors for reading pseudo words among poor readers group.
*
Predictors
R2
R2 Change
F
Phonological deletion
0.194
0.194
7.2*
Visual search-(592)
0.296
0.102
6.1*
p < 0.05.
Table 6. Stepwise Regression Analysis results of predictors for reading psuedo words among typical readers group.
*
Predictors
R2
R2 Change
F
Phonological working memory
0.418
0.185
7.49*
Speed naming of objects (R.A.N)
0.495
0.141
7.74*
p < 0.05, Abbreviation: R.A.N (Rapid Automatized Naming).
difference between the group of typical readers and the group of poor readers in reading pseudo words [F(1, 65) = 32.62, p <0.001] (see Table 7). In addition such significant difference was also found between the two groups of participants in reading meaningful words [F(1, 65) = 64.38, p < 0.001]. Also a significant difference was found between the two groups in the performance in the tests of phonological processes that include phonemic blending and phonemic omission [F(1 , 65) = 5.71, p < 0.05, and F(1, 65) = 10.43, p < 0.05]. Also the difference was significant between the two groups in the performance of the working memory test [F(1, 65) = 7.047, p= 0.01]. The analysis of variance for the performance in the tests of visual processing indicated a significant difference between the two groups of participants in the test of visual search for series of digits and the visual distinction as was tested by the visual perception test [ F(1, 65) = 5.4, p < 0.05 and F(1 ,65)= 23.45, p < 0.01].
Discussion
Predictors Visual search-592
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The study’s findings clearly indicate that visual processing capacities and variables relevant to processes of phonemic processing predict reading in Arabic. Visual processing capacities that have been basically examined through tasks of visual distinction and visual scanning and search have significant correlation with the ability of reading pseudo words and meaningful words as well. Yet, it can be indicated that the correlation between the processes of visual distinction and reading meaningful words is higher than the correlation with reading pseudo words, but still, the correlations are significant. It can be inferred that reading pseudo words highly rests on the processes of phonological processing, generally on the processes of phonological working memory that is required in the process of
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Table 7. Averages and standard deviation for the performances in the different tasks for each group of readers and the F value for the ANOVA between the groups. Poor Readers Typical Readers Test
M
SD
F value
R.A.N objects
39.93 7.24
M
37.33
7.31
n.s
R.A.N letters
27.42 4.34
26.88
6.23
n.s
R.A.N Digits
23.31
3.1
21.41
4.63
n.s
Phonological blending
18.34 2.56
19.45
0.98
5.71*
Phonological deletion
16.28 2.14
17.85
1.84
10.43**
1.93
8.31
2.63
n.s
Phonological working memory 4.125 1.31
4.97
1.29
7.05*
Short-term phonological memory 7.78 Reading pseudowords
17.03 2.65
19.97
1.42 32.62***
Reading words
45.21 5.65
53.14
1.41 64.38***
9.87
Visual search (592)
1.82
10.57
2.7
n.s
11.12 2.23
12.25
1.73
5.39*
Visual distinction (Beery)
20.97
2.3
23.65
2.2
23.45***
Morphological awareness
13.31 2.04
13.8
2.08
n.s
Visual search-Diamond
*
SD
**
p < 0.05, p < 0.01,
***
p < 0.001, n.s = non significant.
decoding during the reading of pseudo words in particular. Though, a significant correlation was found between the proc esses of distinction and visual processing to the process of reading pseudo words. This finding clearly indicates that reading unfamiliar words in Arabic orthography is associated with visual processing and processes of phonological processing. In reading regular words, a high and significant correlation was received between the processes of visual distinction and the processes of reading, as it was also found that the variable of visual distinction significantly explains part of the variation in reading regular meaningful words. The finding indicates that there is a significant reliance on processes of visual processing of the orthographic pattern of words during reading. Accordingly, among participants in the two groups, it was found that the processes of visual processing play an important role in identifying familiar words. This finding shows that the process of reading words visually integrates processes linked to the processing of orthographic structure and the processes of phonological processing. Various theories suggest that during the reading, there is synchronization between visual and phonological process, as an efficient synchronization which is the result of typical development of the processes of processing increases the probabilities that the process of reading and word identification will occur appropriately (Breznitz, 2006). The study's result shows that readers in Arabic orthography rely on processes of visual processing when reading orthographically regular and familiar words as well as new and unfamiliar words. The results also emphasize the significant difference between the group of participants with difficulties and the group of those who succeed in the performances related to tasks that examine visual processing. Similarly, significant difference was found between the two groups in task that examine phonological processing and phonological working memory that relates to processes of reading. this finding advocates the claim that interpersonal differences in reading abilities can be explained not only through differences in the processes of visual processing (Everatt, 1999; Facoetti & Turatto, 2000; Vidyasagar & Pammer,
1999), but also, through differences in the processes of phonological processing, as many researchers have suggested (Snowling, 2001) More specifically, it can be suggested that in the case that the particular orthographic structure of the written word in the Arabic language places the reader under cognitive burden while performing the reading, a situation that necessitates him/her to try to invest visual resources for the sake of the task in addition to the processes of phonological processing that simultaneously occur (Ibrahim, Eviatar, & Aharon-Peretz, 2002; Taha & Khateb, Submitted). In the processes of synchronization terms, it can be indicated that a high level of synchronization between processes of visual and phonological processing is required by readers in the Arabic orthography for the purpose of an accurate reading. Regarding visual processing during the reading of words, it is acceptable to point at two basic eye movements that occur during the reading for the purpose of performing the visual scanning for the form of the written word. The processes of visual scanning are the first stage in the reception of the orthographic form visually before the grapheme-phonemic transduction happens. Performing the process in a controlled and sequential way may increase the possibility that the reader will succeed to read appropriately. The study provides evidence for the importance of the processes of visual scanning and processing during the reading. Yet, it is still interesting to examine whether there is sequential processing at the level of letters, while reading pseudo words, whereas the processing will be at the global level when reading familiar words. The study’s results underscore that there is a positive correlation between the sequential visual scanning and the global distinction to reading pseudo words and familiar words. Yet it can be suggested that a specific answer to such question is to be received in a study that investigates the eye movements during reading pseudo and regular words. Besides, we cannot ignore the fact that the processes of phonological processing play a primary and essential role in reading and decoding familiar and unfamiliar words as well (Goswami & Bryant, 1990; Share, 1995; Snowling, Goulandris, & Defty, 1996; Stanovich, 1998; Wagner & Torgesen, 1987). A specific look into the relation between the performances in the various tasks indicates that there is a significant correlation between the performance of tasks that examine phonological processing, phonemic omission and phonemic blending to the processes of phonological working memory. It can be suggested that the fact of the existence of this high correlation in the performance between tasks and the nature of these tasks indicates that the processes of phonological working memory are the primary factor on which the process of phonological processing relies and that tasks that examine processes of phonological processing, such as phonemic omission and phonemic blending, are actually tasks that examine phonological processing which basically relies on phonological working memory (Bradely & Bryant, 1987). This claim concerning the contribution of processes of phonological processing to the processes of reading, in particular at the Arabic orthography, is advocated by various studies (Abu-Rabia, 1997a, 1997b, 2003, 2007). Similarly, other researchers suggest that the development of phonological awareness which constitutes a basis for the processes of phonological processing among native Arab readers is evidently influenced by diglossia, a situation that may be manifested during reading and writing acquisition particularly
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Investigating Cognitive Processes Underlying Reading in Arabic: Evidence from Typical and Poor Reading Performance
among children with difficulties (Saiegh-Haddad, 2003, 2004; Taha, 2013). The study’s results reveal that there is a significant difference in the ability of phonological processing between poor and typical readers. It can be suggested that the groups of readers with reading difficulties experience difficulty in the processes of phonological processing as a result of individual developmental factors and also due to the impact of diglossia on the development of the phonological awareness among this group. Consequently, the phonological structure of the literary Arabic language which is the language studied in reading and the distance between the literary and spoken language constitutes more burden on the typical development of the processes of phonological processing, specifically among people with poor developmental potential to this skill. The main conesquences of such negative contribution of diglossia may be obviously manifested in difficulties in reading and decoding acquisition. Concerning the processes of visual processing in the same context, it can be suggested that variance in the processes of visual processing points at primary cognitive developmental difficulties that impede the success in reading, especially in orthographies that have complex structure. Moreover, the orthographic structure of written words, specially, unfamiliar words that are not stored as consolidated orthographic patterns in the orthographic lexicon constitutes a burden during the processes of decoding, as processes of visual scanning and processing of the word’s pattern are required. This situation of sequential visual processing or visual distinction that can be called the processes of visual processing may become more complex and packed during reading, decoding and orthographic processing in Arabic language due to the complexity of its orthographic features. Thus people with developmental difficultties in visual processing capacities may experience difficulties at a more significant level than those enjoying a normal functioning in these processes of processing. Thus based on the abovementioned analysis, the phonological status of the literary Arabic language and its orthographic status emphasize the developmental cognitive abilities that set the basis for the acquisition of reading skills I.e. the processes of phonological and visual processing. Besides, the current study examines the process of the speed of verbal retrieval according to grapheme, visual and numerical stimuli, the so-called “Rapid automatized naming”. However, there was no significant and sequential correlation between those processes and the processes of reading and decoding. It can bee seen that the primary components during reading in Arabic orthography are the processes of visual and phonological processing, as these processes are at the processing level and not only at the identification level. In other words, the verbal naming according to the visual stimulus basically rests on identification and retrieval, while the process of reading rests on variety of complex processing, specially reading in a complex orthography such as Arabic. Thus it is hard to confirm the claim that the processes of verbal naming according to the visual label constitute pure analogy for the processes of reading (Denckla & Cutting, 1992; Wolf & Bowers, 1999; Wolf, Bowers, & Biddle, 2000). Yet it can be suggested that the speed of processing, especially the synchronization between the processes of visual and phonological processing is responsible for reading accuracy (Breznitz, 2006). The speed of processing may bridge difficulties in the processes of working memory that are produced due to the cognitive burden during the proc-
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essing. The faster the processing is, the coordination between the two processing will be and the probability of reading accuracy increases accordingly. Though this argument need to be further investigated through specific study. The study’s results reveal that the variable of morphological awareness does not have significant correlation with the performance in the reading tasks. Yet examination the task through which the morphological awareness is studied reveals that the task that basically examines morph-orthographic awareness and that the performance among the two populations was similar. The finding indicates that the nature of the task that examines morphological awareness through the reliance on processes of deduction of semantic links between words is not that task that purely examines morphological awareness, but rather, a task that examines awareness to semantic and morphological links between words, as participants was able to rely on the semantic links between words for the purpose of deduction of words that are not morphologically related to the rest of the words. Also, given that the reader is not aware to this linguistic fact, he/she can conclude that the word that does not semantically relate to the rests of the words is the odd word also if he/she does not enjoy a good morphological awareness. It can be inferred that the lack of the task’s specificity regarding the mission fails to accurately distinguish those with good morphological awareness and those whose morphological awareness is inadequate and even loses the sensitivity of distinction people with normal abilities and those with difficulties due to the reliance on semantic clues. Thus, it can be suggested that examining the morphological awareness should occur at various levels for the purpose of ensuring the examination of the skills in a complete way. In sum, the study’s results raise a very important point suggesting that the process of reading in Arabic orthography necessitates normal functions of visual processing beside to the phonological processing abilities. This may make the process of orthographic visual processing more efficient either during a sequential decoding of new words or during the processes of identification of familiar words.
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338). New York: Routledge. Abu-Rabia, S., & Taha, H. (2006). Phonological errors predominate in Arabic spelling across grades 1-9. Journal of Psycholinguistic Research, 35, 167-188. Abu-Rabia, S., Share, D., & Mansour, M. (2003). Word recognition and basic cognitive processes among reading-disabled and normal readers in Arabic. Reading and Writing: An Interdisciplinary Journal, 16, 423-442. Adams, M. (1990). Beginning to read: Thinking and learning about print. Cambridge, MA: MIT Press. Ayari, S. (1996). Diglossia and illiteracy in the Arab world. Language, Culture and Curriculum, 9, 243-253. Beery, E. K. (1997). The Beery-Buktenica developmental test of visual motor integration with supplemental developmental tests of visual perception and motor coordination. New Jersey: Modern Curriculum Press. Ben-Dror, I., Bentin, S., & Frost, R. (1995). Semantic, phonologic, and morphologic skills in reading disabled and normal children. Reading Research Quarterly, 30(4), 876-893. http://www.jstor.org/stable/748202 Bowers, P. G., & Newby-Clark, E. (2002). The role of naming speed within a model of reading acquisition. Reading and Writing, 15, 109-126. Bradly, L., & Bryant, P. E. (1978). Difficulties in auditory organization as a possible cause of reading backwardness. Nature, 271, 746-747. Breznitz, Z. (2006). Fluency in reading: Synchronization of processes. London: Lawrence Erlbaum Associates. Carlisle, J. F. (1995). Morphological awareness and early reading achievement. In L. B. Feldman (Ed.) Morphological aspects of language processing (pp 189-209). Hillsdale, NJ: Lawrence Erlbaum. Clark, E. V., & Hecht, B. F. (1982). Learning to coin agent and instrument nouns. Cognition, 12, 1-24. Coltheart, M. (2005). Modelling reading: The dual-route approach. In: M. J. Snowling & C. Hulme (Eds.), The Science of Reading. Oxford: Blackwells Publishing. Denckla, M. B., & Cutting, L. E. (1999). History and significance of rapid automatized naming. Annals of Dyslexia, 49, 29-42. Denkla, M. B., & Rudel, R. G. (1974). Rapid automatized naming of pictured objects, colors, letters and numbers by normal children. Cortex, 10, 186-202. Ehri, L. C. (2005). Learning to read words: Theory, findings, and issues. Scientific Studies of Reading, 9, 167-188. Elbro, C., & Arnbak, E. (1996). The role of Morpheme recognition and morphological awareness in dyslexia. Annals of Dyslexia, 46, 209-240. Everatt, J. (1999). Reading and dyslexia: Visual and attentional processes. New York: Routledge. Everatt, J., McCorquodale, B., Smith, J., culverwell, F., wilks, A., Evans, D., Kay, M., & Baker, D. (1999). Association between reading ability and visual processes. In: Everatt, J (Ed.), Reading and dyslexia: Visual and attentional processes (pp 1-39). New York: Routledge. Facoetti, A., Paganoni, P., Turatto, M., Marzola, V., & Mascetti, G. G. (2000). Visual-spatial attention in developmental dyslexia. Cortex, 36, 109-123. Ferguson, C. A. (1959). Diglossia. Word, 14, 47-56. Friedmann, N., & Gvion, A. (2001). Letter position dyslexia. Cognitive Neuropsychology, 18, 673-696. Frith, U. (1985). Beneath the surface of developmental dyslexia. In: Patterson, K. E., Marashall, J. C., & Coltheart, M. (Eds.), Surface dyslexia. (pp 301-330). London: Lawrence Erlbaum Associates.
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Glickstein, M. (2000). How are visual areas of the brain connected to motor areas for the sensory guidance of movement? Trends in Neurosciences, 23, 613-617. Goodale M, A., & Milner A, D. (2004). Sight unseen: An exploration of conscious and unconscious vision. New York: Oxford University Press. Goswami, U., & Bryant, P. (1990). Phonological skills and learning to read. Hove: Erlbaum. Heiervang, E., & Hugdahl, K. (2003). Impaired visual attention in children with dyslexia. Journal of learning disabilities, 36, 68-73. Ibrahim, R., Eviatar, Z., & Aharon Peretz, J. (2002). The characteristics of the Arabic orthography slow it’s cognitive processing. Neuropsycholgy, 16, 322-326. Jaœkowski, P., & Rusiak, P. (2005). Posterior parietal cortex and developmental dyslexia. Acta Neurobiologiae Experimentalis (Wars), 65, 79-94. Khateb, A., Khateb, M., Taha, H., & Ibrahim, R. (Submitted). The effect of the internal connectedness of written Arabic words on the process of the visual recognition: A developmental study. Kinsey, K., Rose, M., Hansen, P., Richardson, A., & Stein, J. (2004). Magnocellular mediated visual-spatial attention and reading ability. Neuroreport, 15, 2215-2218. Levine, I., Ravid, D., & Rapaport, S. (2001). Morphology and spelling among Hebrew-speaking children: From kindergarten to first grade. Journal of Child Language, 28, 741-772. Lundberg, I., Olofsson, A., & Wall, S. (1980). Reading and spelling skills in the first school years predicted from phonemic awareness skills in kindergarten. Scandinavian Journal of Psychology, 21, 159-173. Milner, A. D., & Goodale, M. A. (1995). The visual brain in action. Oxford: Oxford University Press. Nunes, T., Bryant, P., & Bindman, M. (2006). The effects of learning to spell on children’s awareness of morphology. Reading and writing, 19, 767-787. Ravid, D. (2001). Learning to spell in Hebrew: Phonological and morphological factors. Reading and Writing, 14, 459-485. Rubin, H. (1991). Morphological knowledge and writing ability. In R. M. Joshi (Ed.), Written Language Disorders (pp. 43-69). Boston: Kluwer Academic. Rudel, R. G., Denckla, M. B., & Broman, M. (1978). Rapid silent response to repeated target symbols by dyslexic and nondyslexic children. Brain and Language, 6, 52-62. Saiegh-Haddad, E. (2003). Linguistic distance and initial reading acquisition: The case of Arabic diglossia. Applied Psycholinguistics, 24, 431-451. Saiegh-Haddad, E. (2004). The impact of phonemic and lexical distance on the phonological analysis of word and pseudowords in a diglossic context. Applied Psycholinguistics, 25, 495-512. Saiegh-Haddad, E., & Geva, E. (2008). Morphological awareness, phonological awareness, and reading in English-Arabic bilingual children. Reading and Writing, 21, 481-504. Senechal, M. (2000). Morphological effects in children’s spelling of French words. Canadian Journal of Experimental Psychology, 54, 7685. Share, D. L. (1995). Phonological recoding and self-teaching: Sine qua non of reading acquisition. Cognition, 55, 151-218. Snowling, M. (2001). From language to reading and dyslexia. Dyslexia, 7, 37-46. Snowling, M. J., Goulandris, N., & Defty, N. (1996). A longitudinal study of reading development in dyslexic children. Journal of Educational Psychology, 88, 653-669.
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Investigating Cognitive Processes Underlying Reading in Arabic: Evidence from Typical and Poor Reading Performance
Stanovich, K. E. (1986). Matthew effects in reading: Some consequences of individual differences in the acquisition of literacy. Reading Research Quarterly, 21, 360-406. http://www.jstor.org/stable/747612 Stanovich, K. E. (1988). Explaining the differences between the dyslexic and garden-variety poor reader: The phonological-core variabledifference model. Journal of Learning Disabilities, 21, 590-604. Taha, H. Y. (2013). Reading and spelling in Arabic: Linguistic and orthographic complexity. Theory and Practice in Language Studies, 3, 721-727. Taha, H., Ibrahim, R., & Khateb, A. (2013). How does Arabic orthographic connectivity modulate brain activity during visual word recognition: An ERP study. Brain Topography, 26, 292-302. Taha, H., & Saiegh-Haddad, E. (Submitted). Morphology and spelling in Arabic: Development and interface. Tong, X. L., Deacon, S. H., Kirby, J. R., Cain, K., & Parrila, R. (2011). Morphological awareness: A key to understanding poor reading comprehension in English. Journal of Educational Psychology, 103, 523534. Treiman, R. (1993). Beginning to spell: A study of first-grade children. New York: Oxford University Press. Treiman, R., & Bourassa, D. C. (2000). The development of spelling skills. Topics in Language Disorders, 20, 1-18.
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Vidyasagar, T. R., & Pammer, K. (1999). Impaired visual search in dyslexia relates to the role of the magnocellular pathway in attention. Neuroreport, 10, 1283-1287. Wagner, R. K., & Torgesen, J. K. (1987). The nature of phonological processing and its causal role in the acquisition of reading skills. Psychological Bulletin, 101, 192-212. Wolf, M., & Bowers, P. G. (1999). The double-deficit hypothesis for the developmental dyslexias. Journal of Educational Psychology, 91, 415-438. Wolf, M., Bowers, P. G. & Biddle, K. (2000). Naming-speed processes, timing, and reading: A conceptual review. Journal of Learning Disabilities, 33, 387-407. Ziegler, J. C., & Goswami, U. (2005). Reading acquisition, developmental dyslexia, and skilled reading across languages: A psycholinguistic grain size theory. Psychological Bulletin, 131, 3-29. Ziegler, J. C., Bertrand, D., Tóth, D., Csépe, V., Reis, A., Faísca, L., Saine, N., Lyytinen, H., Vaessen, A., & Blomert, L. (2010). Orthographic depth and its impact on universal predictors of reading: A cross-language investigation. Psychological Science, 21, 551-559.
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5 But You Promised: Children’s Judgments of Broken Promises Karen Hussar, Jared Horvath Fisher College, Boston, USA
Current conceptions regarding children’s understanding of promises (and promise breaking) rely upon absolute distinction: namely, a promise versus a non-promise. The current study expands the understanding of children’s judgments of broken promises to include more nuanced, refined descriptions. Utilizing a four-point rating scale—ranging from “OK” to “very bad”—forty children aged 6 to 10 judged story cards depicting characters breaking commitments not to engage in specific behaviors across three different domains (moral, social-conventional, and personal). Analyses indicated that children judge broken promises in the moral domain more severely than those in the social-conventional domain and broken promises in the social-conventional domain more severely than those in the personal domain. Therefore, children appear to judge broken commitments on a sliding scale in much the same way they judge actions from the moral, social-conventional and personal domains. Results from the current study also suggest an inverse pattern of judgment with regards to broken commitments. Specifically, it appears that the more severely an initial action is judged, the less severely its concurrent commitment condition is judged; and vice versa. These findings help refine our understanding of childhood interpretations of broken promises and engender several unique ideas for future research in this field. Keywords: Commitment; Promises; Morality; Social Domain Theory
Introduction A hallmark of childhood psychological research is the progression from diametric classification to a more detailed spectrum of designation. For instance, Piaget and Kohlberg, pioneers in the field of moral development, focused on a near absolute emergent moral distinction between right and wrong. Subsequent social domain theorists expanded this perception and developed a more nuanced prescriptivity scale that allowed children to judge various actions according to a spectrum, typically ranging between “OK” and “very bad”. The introduction of this refined rating system advanced research in the field of moral development by revealing the ability of young children to reliably distinguish between moral transgressions, social-conventional transgressions, and personal choices (Nucci & Turiel, 1978; Smetana, 1981; Smetana & Braeges, 1990). Similarly, early research examining lying among young children focused on the ability of these children to distinguish between lies and truth. Only when these initial boundaries were delineated were researchers able to examine children’s refined distinctions between different types of lying. Presently, there is strong evidence to support the idea that children as young as 7 can readily distinguish between antisocial lies (lies intended to conceal or mislead—“It was like that when I got here.”), prosocial lies (lies intended to be polite—“I love your new haircut.”), and trick lies (lies intended to elicit joy or laughter—“Got your nose!”). By age 9, children often judge “antisocial” lies more severely than “prosocial lies” and “prosocial lies” more se-
verely than “trick lies” (Bussey, 1999; Fu, Xu, Cameron, Heyman, & Lee, 2007; Lee, Xu, Fu, Cameron, & Chen, 2001; Xu, Boa, Fu, Talwar, & Lee, 2010). The present study continues this progression from dichotomous classification to nuanced designation with regards to children’s understandings of promises. Through the use of a sliding rating scale—similar to one employed by social domain theorists—we expand the current understanding of children’s judgments of broken promises.
Promises and Children Philosopher John Searle (1969) outlined a series of conditions that must be met in order for a successful “promise” to be made. These conditions include obligation (a “promiser” makes a commitment to undertake a certain action), controllability (a promise must be physically and/or mentally possible to perform), and advantage (a promise must prove advantageous or beneficial to the “promisee”—promise to harm is no longer a promise; it is a threat). Perhaps the most important aspect of Searle’s description of promising is the nugatory nature of outcome. Whether fulfilled or not, the very act of saying “I promise” engenders an expectation in the listener. Accordingly, the “promiser” is held accountable and the promise remains valid regardless of the outcome. For example, a mother’s failure to appear at a class play she promised to attend does not negate the previously made promise. The claim that individuals view a promise as valid irrespective of outcome has been confirmed in
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several studies using adult subjects (Astington, 1988, 1990; Gibbs & Delaney, 1987). Searle’s notion of an explicit obligation points to an important distinction between lying and promise breaking. Lying is an act of verbal and/or emotional deception meant to engender a false belief. Conversely, a broken promise reneges on a prior commitment. Whether or not a promise is kept, the initial intention to perform the promised act (obligation) is inherently different from the initial intent to deceive by lying. We highlight this point because, although there is a long tradition of research exploring children’s understanding of lying, research exploring children’s understanding of promises and their ensuing commitments did not emerge until quite recently—and, even today, the literature is quite sparse and diametric. In one of the first looks at promissory understanding, Astington (1988), through the use of utterances embedded in oral narratives, determined that children between the ages of 5 - 7 were unable to grasp the concept of obligation. As a result, the children classified a statement as a promise only if the promised event occurred. More specifically, participants in this study considered the statement, “I will take you [to the store], I promise,” as a valid promise only if the characters went to the store. Astington concluded that the ability to recognize that a promise remains valid regardless of outcome does not begin to emerge until age seven. While ultimately confirming Astington’s findings, several researchers have demonstrated that the distinction between promise and outcome is somewhat tenuous even beyond the age of 7. For instance, using stories that featured characters making and breaking promises to one another, Maas and Abbeduto (2001) found that 9-year-olds, although able to assign responsibility to the “promiser” for the outcome, often acknowledged obligation only if a clear and involuntary obstacle impeded the said “promiser” from fulfilling the promise. For example, when Nevin did not show up to play on the swings with Corrinda after he had promised he would do so, many 9-year-old participants saw this as a broken promise even when it was explained Nevin failed to show up due to illness. However, when Nevin simply went home to play alone, these same participants did not view this act as a broken promise. Similarly, Mant and Perner (1988), using oral narratives featuring characters breaking promises for various reasons (both intentionally and unintentionally in much the same manner as the Nevin character described above), concluded that the ability to consistently and accurately assign obligation to the “promiser” does not emerge until the age of 9 or 10. In order to further define the boundaries of young children’s understanding of promises, Maas (2008) used videotaped stories employing thought bubbles to reveal the inner-thoughts of characters. Utilizing this methodology, Maas examined the impact of “promiser” sincerity and intention on 4- to 6-yearolds’ ability to correctly identify promises. As an example, after promising to help rake leaves, a “sincere” character’s thought bubble might say, “I DO want to help—I ALWAYS like to help,” while an insincere character’s thought bubble might say, “I DO NOT want to help—I will NEVER want to help.” Mass determined that although children as young as 4 can—and do—successfully identify promises made with sincere intentions, the ability to identify promises regardless of intention begins to emerge by age 6. In her conclusion, Maas argued that childhood understanding of promises progresses from a focus on outcome to a focus on the belief promises create in the lis-
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tener. When combined with Maas’s earlier work, it appears promissory comprehension evolves from responsibility to obligation and ends with expectation. Unfortunately, as noted above, due to the dearth of research examining this topic, such syntheses can only be hypothesized. In addition, it is important to note that each of the aforementioned studies utilized a diametric scale rather than a more nuanced “sliding” scale. More specifically, participants were asked to categorize each scenario as a broken promise or not.
Synthesizing Moral Development and Understanding of Promises Piaget and Kohlberg’s foundational research in the field of moral reasoning focused on stage-like moral development; however, succeeding developmental psychologists—namely Turiel, Nucci and Smetana—investigated the reasoning behind children’s moralistic categorization of specific actions. Based on a series of studies (Nucci & Turiel, 1978; Nucci, 1981; Nucci, Turiel, & Encarnacion-Gawrych, 1983; Smetana, 1981; Smetana, 1985; Turiel, 1983; Turiel, 2002), these domain theorists concluded that children as young as three years old can readily differentiate between moral transgressions (actions that cause physical or psychological harm to others, such as hitting or teasing), social-conventional transgressions (actions that violate the social order, such as not sitting in an assigned seat or cutting in line), and personal choices (actions that reflect personal preference, such as wearing a certain brand of clothing or participating in a particular sport). Hussar and Harris (2009) utilized this non-diametric moral domain-theory framework to examine children’s understanding of personal “promiser” commitment. More specifically, this research examined whether children viewed a failed promise made to one’s self (in this case, “I will not eat meat.”) as a binding commitment. Using story cards in which characters made and broke promises not to eat meat for moral reasons (e.g., “Animals are my friends and I don’t want to hurt them.”) and personal reasons (e.g., “I just don’t like the taste.”), they found that both vegetarian and non-vegetarian participants did indeed judge failure to adhere to a commitment to vegetarianism as wrong. However, participants judged the breaking of a commitment more severely if it was made for moral as opposed to personal reasons. Thus children varied in their judgments of this broken commitment depending on whether the person’s initial motive for making it fell into the moral domain or the personal domain.
The Current Study The current study aimed to expand Hussar and Harris’s research (2009). Participants in the current study were asked to judge individuals who broke commitments across various domains. Specifically, participants were asked to judge individuals who broke personal commitments (e.g., a commitment to be physically active), social-conventional commitments (e.g., a commitment to be tidy) and moral commitments (e.g., a commitment to stop bullying classmates) using a scale comparable to the one utilized by social domain theorists. The authors hypothesized that children would judge broken commitments in the same manner they judge actions from the moral, socialconventional and personal domains. Specifically, participants would judge broken commitments from the moral domain more
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severely than broken commitments from the social-conventional domain and broken commitments from the social-conventional domain more severely than broken commitments from the personal domain. By establishing children’s judgments toward various broken commitments, we hope to determine if children judge the breaking of a commitment in terms of the initial grounds for making it.
Method Participants Participants were 40 middle-class children ranging from 6 to 10 years of age (M = 7 years 7 months, SD =1.37). There were an equal number of boy and girl participants; all were Caucasian. Participants were recruited in suburban neighborhoods surrounding two major northeast metropolitan areas in the United States.
Design and Procedure The first author conducted all interviews individually with each participant during a single visit to either the participant’s home or school. Before the interview began, participants were told that the researcher was “talking with kids like you to find out what things different children think are OK to do and what things children think are bad to do.” Each interview lasted between 30 - 45 minutes and was audio-taped and subsequently transcribed. To provide an initial assessment of children’s evaluation of actions falling into the moral, social-conventional, and personal domains, children were presented in a random order with twelve story cards depicting four moral transgressions (stealing a quarter from a classmate; pushing a classmate out of the way so as to be first in line; grabbing a toy from a classmate; hitting a classmate); four social-conventional transgressions (eating salad with fingers; not pushing in a chair upon dismissal from class; leaving a dirty wrapper on the table after a snack; not sitting in an assigned seat in class); and four personal choices (reading during recess; coloring a drawing with a purple crayon; eating junk food; sleeping in on a Saturday morning). The gender of the story card character matched the gender of the participant (Susan for girls, Sam for boys). Children were asked to judge each depicted action as “OK”, “a little bad”, “bad”, or “very bad”. Initially, the interviewer did not provide any background information about the story character. Thus, children were left to make their own assumptions about the individual. After this initial exercise, children were asked to judge the twelve events again; however, this time the interviewer told participants that the story character had made a commitment not to engage in the action in question before performing it (e.g., Sam promised not to take things that did not belong to him, but stole a quarter from his classmate’s desk; Susan promised to be more active, but decided to read a book during recess). Once children learned about each prior commitment, they then judged each depicted action as “OK”, “a little bad”, “bad”, or “very bad”.
Results Figure 1(a) reveals that participants judged moral transgressions more severely than social-conventional transgressions and rarely condemned personal choices. To analyze these results, a
repeated measures ANCOVA of Domain (moral, social- conventional, personal) X Age (6, 7, 8, 9, 10) was conducted with the participants’ gender included as a covariate. This analysis produced a significant main effect of Domain, F(1, 34) = 229.69, p < 0.001, but no main effect of Age, F(4, 34) = 1.25, p = 0.31. The covariate, Gender, was not a statistically significant predictor of the outcome (p = 0.14). Figure 1(b) indicates that when participants were told that the story character made a commitment (promise) not to engage in the action in question, they typically judged moral transgressions more severely than social-conventional transgressions and social-conventional transgressions more severely than personal choices. To analyze these results, a repeated measures ANCOVA of Domain (moral, social-conventional, personal) X Age (6, 7, 8, 9, 10) was conducted with the participants’ gender included as a covariate. This analysis produced a significant main effect of Domain, F(1, 34) = 288.19, p < 0.001, but no main effect of Age, F(4, 34) = 0.93, p = 0.46. The covariate, Gender, was not a statistically significant predictor of the outcome (p = 0.25). Figure 1(c) demonstrates that within each of the three domains, participants’ judgments were more severe if they were told that the story character initially made a promise not to engage in the action in question. Contrast analyses confirm that participants judged identical moral transgressions more severely when it was made explicit that the character had promised not to transgress prior to acting, F (1, 34) = 12.49, p < 0.01, identical social-conventional transgressions more severely when it was made explicit that the character had promised not to transgress prior to acting, F (1, 34) = 16.01, p < 0.001, and identical personal choices more severely when it was made explicit that the character promised not to transgress prior to acting, F (1, 34) = 43.51, p < 0.001. In summary, participants were sensitive to the domain under consideration, both when they were given no background information on the story character’s intentions and when they were told that the story character made a promise not to engage in the action in question. Nevertheless, within each of the three domains, participants consistently judged the story character more severely for his/her actions when the story character initially made a commitment not to engage in the action in question.
Discussion The goal of this study was to determine if children consider the breaking of commitments (promises) to vary in degree of wrongness. Specifically, we asked whether children would judge any form of failed commitment similarly or whether they would differentially judge broken commitments according to the initial basis for the commitment. We began our analyses by confirming that our participants judged events within the moral, social-conventional and personal domains in a pattern identical to what domain theorists have established (e.g., Smetana, 2006; Turiel, 2006). On average, participants judged moral transgressions more severely than social-conventional transgressions and judged social-transgressions more severely than personal choices. In fact, participants were reluctant to pass judgment on personal choices in general (see Figure 1(a)). With respect to commitments broken within each of these three domains, our results indicate that children judged broken promises in the moral domain more severely than those in the
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(a)
(b)
(c)
Figure 1. (a) Participants’ average judgments of three domains (moral, socialconventional, and personal) (N = 40). Responses reflect a four-point scale where 0 = OK, 1 = a little bad, 2 = bad, 3 = very bad. (b) Participants’ average judgments of three domains (moral, social-conventional, and personal) after learning that the story character promised not to transgress prior to acting (N = 40). Responses reflect a four-point scale where 0 = OK, 1 = a little bad, 2 = bad, 3 = very bad. (c) Participants’ average judgments of three domains (moral, social-conventional, and personal) across two conditions (no background information on story character and committed story character) (N = 40). Responses reflect a four-point scale where 0 = OK, 1 = a little bad, 2 = bad, 3 = very bad.
social-conventional domain and broken promises in the social-conventional domain more severely than those in the personal domain (see Figure 1(b)). Therefore, it appears that children judge broken commitments on a sliding scale in much the same way they judge actions from the three specified domains. Below, we consider two plausible explanations as to why children do not judge broken commitments in a uniform manner. A comparison of the promise/non-promise scenarios reveals that across all three domains, participants’ judgments were more severe when the story card character initially made a
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promise not to engage in the action in question (see Figure 1(c)). On average, judgments shift by approximately one rating on the ordinal scale: from “OK” to “a little bad” within the personal domain; from “a little bad” to “bad” within the socialconventional domain; and from “bad” to “very bad” within the moral domain. Under this interpretation, participants judge the breaking of all promises similarly. What differs is the initial judgment of the actions in question (as evidenced in Figure 1(a)). This explanation is reinforced by several participants’ unprompted comments. For instance, in reference to the scenario where Susan breaks her promise to be more active at recess, one child replied, “It wouldn’t have been so bad…but she breaks a promise so it goes down one [italics added].” Another participant expressed a similar viewpoint: “I guess all the ones where [Susan] promises might be one worse…because she made a promise and broke it [italics added].” These references to intensifying a judgment by “one” suggest a consistent judgment assigned to the act of breaking a promise, regardless of the associated behavior. Although this interpretation is compelling, a closer examination of the data casts doubt on this theory. If this explanation were correct, we would have expected to see a near identical judgment differential (“one”) between the non- and brokenpromise scenarios across each domain. However, when numerically calculated (as opposed to simply assigning an ordinal rank), this difference appears to shift between scenarios— reaching, on average, 1 point in the personal domain, 0.50 points in the social-conventional domain, and 0.25 points in the moral domain. Accordingly, despite the homogenous ranking method alluded to by several participants, it appears that, on average, our participants differentially judged commitment conditions according to each unique circumstance. These numerical calculations suggest an alternative explanation for our results, one we believe corresponds with the pattern of results initially established by domain theorists. As previously noted, our participants were reluctant to assign any judgment to the personal choices made by the story card characters. However, once the character made and broke a promise not to engage in the described personal action, participants negatively judged their behavior (“a little bad”, on average). Accordingly, these negative judgments can be understood to exclusively reflect the act of breaking the promise. Conversely, our participants, on average, initially judged moral transgressions as “very bad”. However, when a promise condition was introduced and broken within the moral domain, this judgment shifted only slightly (0.25 points). This small shift in judgment suggests that our participants viewed the breaking of a promise not to engage in a moral transgression as almost inconsequential, particularly as it compares to the moral transgression itself. In other words, it appears that the more severely an initial action is judged, the less severely its concurrent commitment will be judged. Accordingly, the less severely an initial action is judged, the more severely its concurrent commitment condition will be judged. Although certainly suggested by our data, we believe this “inverse commitment” theory could be better tested with a more sensitive sliding scale upon which participants judge non-promise/promise scenarios. Whereas our scale may have led to a ceiling effect within the moral domain, a five-point scale ranging from “OK” to “very, very bad” would allow researchers to better determine judgments toward broken moral commitments and perhaps confirm this relationship between original action and related commitment. Regardless, the data
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collected in the current study supports this hypothesis. In addition, it is important to note that the age range of our participants (6 - 10 years old) may have influenced participants’ judgments of the actions in question. As demonstrated by earlier researchers (i.e., Maas & Abbedutio, 2001; Mant & Perner, 1988), mature comprehension of made-, kept- and brokenpromises emerges around age 7 but remains somewhat fragile until later adolescence. Perhaps the vacillation in our procedures between traditional moral-domain judgments and broken commitment judgments is a symptom of this maturation. Future research could also determine if the aforementioned results are replicated with older children (i.e., 11 - 12 years old) or if varied judgments towards broken commitments stabilizes with age. In the end, this study has generated some unique and interesting results. It initially appeared that young children were differentially rating commitment scenarios (e.g., judging those broken commitments that result in physical or psychological harm towards others more severely than those broken commitments that result in a disruption to the social order). However, when the promise scenario is decoupled from its related event, the opposite may actually be true: young children judge broken commitments to moral transgressions less severely than broken commitments to personal choices. The message presented seems to be one of caliber: when one breaks a promise not to engage in a moral transgression, the broken promise is superseded by the moral transgression itself and, accordingly, is not judged harshly (e.g., “S/he should have known better.”). Conversely, when one breaks a promise not to engage in a personal choice, the broken promise is the only true transgression and, accordingly, is judged somewhat severely (e.g., “Why did s/he say it if s/he didn’t mean it?”). This concept implies children are sensitive to personal commitments, particularly broken personal commitments. As such, our findings suggest that educators and other professionals working with young children may need to mitigate the judgments children are likely to bestow on others when personal commitments are broken (e.g., dropping out of a school club; quitting a sports team; canceling a scheduled social activity). Therefore, with regards to our research question, children do consider the initial basis for which a commitment was made in determining the severity of their judgment of the broken commitment in question. However, their judgments appear to be more sophisticated that initially theorized. The more severely an initial action is judged, the less severely its concurrent commitment will be judged. Accordingly, the less severely an initial action is judged, the more severely its concurrent commitment condition will be judged. Although certainly suggested by our data, we believe this “inverse commitment” theory should be confirmed through future research that includes a more sensitive judgment scale as well as a wider age range of participants.
REFERENCES Astington, J. W. (1988). Children’s understanding of the speech act of promising. Journal of Child Language, 15, 157-173.
Fu, G., Xu, F., Cameron, C. A., Heyman, G., & Lee, K. (2007). Crosscultural differences in children’s choices, categorizations, and evaluations of truths and lies. Developmental Psychology, 43, 278-293. Gibbs, R. W., & Delaney, S. M. (1987). Pragmatic factors in making and understanding promises. Discourse Processes, 10, 107-126. Hussar, K. M., & Harris, P. L. (2009). Children who choose not to eat meat: A study of early moral decision-making. Social Development, 19, 627-641. Lee, K., Xu, F., Fu, G., Cameron, C. A., & Chen, S. (2001). Taiwan and Mainland Chinese and Canadian children’s categorization and evaluation of lie- and truth-telling: A modesty effect. British Journal of Developmental Psychology, 19, 525-542. Maas, F. K., & Abbeduto, L. (2001). Children’s judgments about intentionally and unintentionally broken promises. Journal of Child Language, 28, 517-529. Maas, F. K. (2008). Children’s understanding of promising, lying, and false belief. The Journal of General Psychology, 135, 301-321. Mant, C. M., & Perner, J. (1988). The child’s understanding of commitment. Developmental Psychology, 24, 343-351. Nucci, L. P., & Turiel, E. (1978). Social interactions and the development of social concepts in pre-school children. Child Development, 49, 400-407. Nucci, L. (1981). Conceptions of personal issues: A domain distinct from moral or societal concepts. Child Development, 52, 114-121. Nucci, L., Turiel, E., & Encarnacion-Gawrych, G. (1983). Children’s social interactions and social concepts: Analyses of morality and convention in the Virgin Islands. Journal of Cross-Cultural Psychology, 14, 469-487. Searle, J. (1969). Speech acts: An essay in the philosophy of language. New York: Cambridge University Press. Smetana, J. (1981). Preschool children’s conceptions of moral and social rules. Child Development, 52, 1333-1336. Smetana, J. (1985). Preschool children’s conceptions of transgressions: The effects of varying moral and conventional domain-related attributes. Developmental Psychology, 21, 18-29. Smetana, J., & Braeges, J. L. (1990). The development of toddlers’ moral and conventional judgments. Merrill-Palmer Quarterly, 36, 329-346. Smetana, J. (2006). Social domain theory: Consistencies and variations in children’s moral and social judgments. In M. Killen, & J. Smetana (Eds.), Handbook of moral development (pp. 119-154). Hillsdale, NJ: Erlbaum. Turiel, E. (1983). The development of social knowledge. Cambridge: Cambridge University Press. Turiel, E. (2002). The culture of morality: Social development, context, and conflict. Cambridge: Cambridge University Press. Turiel, E. (2006). The development of morality. In N. Eisenberg, W. Damon, & R. M. Lerner (Eds.), Handbook of child psychology: Social, emotional, and personality development (pp. 789-857). Hoboken, NJ: Wiley. Xu, F., Bao, X., Fu, G., Talwar, V., & Lee, K. (2010). Lying and truth-telling in children: From concept to action. Child Development, 81, 581-596.
Astington, J. W. (1990). Metapragmatics: Children’s conception of promising. In G. Conti-Ramsden, & C. Snow (Eds.), Children’s language: Vol. 7 (pp. 223-244). Hillsdale, NJ: Erlbaum. Bussey, K. (1999). Children’s categorization and evaluation of different types of lies and truths. Child Development, 70, 1338-1347.
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6 Benefits of Combined Mental and Physical Training in Learning a Complex Motor Skill in Basketball Andrea Gaggioli, Luca Morganti, Maurizio Mondoni, Alessandro Antonietti Università Cattolica del Sacro Cuore, Milano, Italy
Previous research in sport psychology and rehabilitation suggests that training with motor imagery (mental practice) is a potentially effective strategy to improve motor performance. The goal of the present study was to investigate the benefits of combining mental and physical training in learning a complex motor skill in basketball (the lay-up shot). To this end, sixty female university students were randomly assigned to either mental practice with physical training, or physical training alone. Motor performance was assessed before and after a four-week training period. To assess motor learning performance, a video analysis was carried out by three independent raters on the motor task before and after the training in both conditions. Results showed that mental practice condition improved coordination and movement accuracy, suggesting the potential effectiveness of this approach in training complex motor skills; furthermore, findings indicate the feasibility and accuracy of using video-based analysis of movement in the assessment of motor performance improvements. Keywords: Motor Learning; Motor Imagery; Mental Practice; Sport Performance; Complex Motor Skills
Introduction Motor imagery refers to the mental simulation of a movement without its physical execution. This process has been widely used in combination with physical practice to improve performance (for reviews see, Driskell, 1994; Allami et al., 2007; Schuster et al., 2011). Athletes often deal with new skills to be learned and in several circumstances an incorrect execution of a skill can result in a fault given to the athlete; in team sports, an error by one player can affect the whole group (e.g., travelling in basketball is punished by stopping the game and giving the ball to the opponent team). It has been proposed that mental practice with motor imagery can enhance motor learning process by allowing the explicit representation of different stages of the action (Jeannerod & Decety, 1995; Sherwood & Lee, 2003). More specifically, the mental representation of the movement can be used during mental simulation to cue the learner on temporal and spatial elements of the skill. By rehearsing this representation, the learner can use this information to monitor and improve the physical performance of the skill (Murphy & Jowdy, 1992). Starting from this background, the main objective of this study was to investigate the efficacy of mental practice to improve learning of a complex motor skill in basketball. The hypothesis formulated is that supplementing physical practice with mental practice improves specific components of a complex motor skill. Although evidence in favour of this hypothesis has been provided in several sports (Driskell et al., 1994; Cumming & Williams, 2012), efficacy of mental practice with motor imagery on a closed motor task (in this case, lay-up shot) has been less investigated. Further, this study aimed at evaluating the feasibility and accuracy of a new
methodology to assess motor learning performance in sports. This approach is based on multiple raters’ evaluation of videorecorded movements along different dimensions.
Mental Practice with Motor Imagery Richardson (1967) refers to mental practice as “the mental rehearsal of a task without any muscular movement” (in Olsson, 2008: p.133). Other recurring terms in the mental practice literature are “mental preparation” and “motor imagery”. Mental preparation is a broad term describing all the mental techniques that an athlete might use during training sessions, whereas “motor imagery” is more specifically defined as the mental rehearsal of a movement in absence of a gross muscular activetion (Jeannerod, 1994). A further distinction is made between internal (or “kinaesthetic”) and external (or “visual”) imagery (Lang, 1979). When taking an internal perspective, the subject imagines to execute the task from a first-person, body-centered frame of reference, by focusing on simulated perceptions and sensations. In the external perspective, the movement is imagined as if the subject were watching someone performing the task, like in a movie. According to Jeannerod (1994), however, only the internal perspective should be regarded as motor imagery, while the external perspective is more related to visual imagery. In particular, internal motor imagery features a kinaesthetic component that helps the subject to really “feel” the imagined movement, including not only the visual, but also the spatial and kinaesthetic characteristics of the movement. Although no real movement is performed during an imagery task, motor imagery and physical execution are characterized by common functional features. For example, the time taken to
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imagine the movement is correlated with the time needed to actually execute it (Decety et al., 1989): the link between motor imagery duration and actual motor action duration is also maintained following specific training aimed at improving the speed of the execution (Louis et al., 2008). Furthermore, the imagination of effortful action activates similar physiological changes to the actual execution of movements (e.g., increase in heart and respiratory rates; Decety et al., 1991). There is also evidence that physical constraints of the movement affect both real and imagined execution (Roure et al., 1998). At the neurological level, compelling evidence exists that the imagination and the execution of the movement share common neuronal substrates (Karni, 1995; Jackson, 2003; Miller, 2010). Drawing on this compelling evidence of the functional and neurophysiological relationship between imagined and actual movements, several authors have proposed mental practice with motor imagery as an effective strategy to improve motor learning (Feltz & Landers, 1983; Driskell et al., 1994; Guillot & Collet, 2008; Schuster et al., 2011). The efficacy of this approach in improving performance of motor function has also been investigated in neurological rehabilitation in combination with physiotherapy, with promising results (Lafleur et al., 2002; Gaggioli et al., 2006; Sun et al., 2013).
Applications of Mental Practice with Motor Imagery In Sport Mental practice with motor imagery has been applied in different sport disciplines, showing benefits in speed, performance accuracy, muscle strength, movement dynamics, and motor skill performance (for a review, see Taktek, 2004). The specialized literature provides also specific indications about how motor imagery training can be optimized (Driskell et al., 1994). As concerns the relative effectiveness of external and internal (i.e. kinaesthetic) imagery in sport applications, Hardy and Callow (1999) investigated this issue in karate. They found that external imagery was more effective in task learning, whereas internal imagery was more effective in athletes with greater level of expertise, especially with tasks involving a complex series of movements and different body parts (White & Hardy, 1995). Further, the efficacy of mental practice with motor imagery seems greater when it is applied to close as opposed to open sport skills (Coelho, 2007). In sports involving closed skills it is easier to figure out the real movement that will be performed. In open sports, conversely, athletes often have to deal with different factors that may prevent the correct execution of the task and affect the course of action. In general, most of individual sports involve closed skills, whereas most team sports involve open skills. Starting from this background, the goal of the present study was to test the effectiveness of combined mental and physical practice against physical practice alone in learning a complex motor task in basketball (lay-up shot). We selected the lay-up shot because it has a well-coded structure and accuracy is very important for its optimal execution. A mistake during the feet tapping phase, for example, may cause a foul being called to the player: each athlete has to learn the exact sequence and execute the task by coordinating the movement of arms and knees, rhythmically preparing the ending jump to the basket. The lay-up shot is performed by leaping from below, laying the ball up near the basket, and using one hand to bounce it off the backboard and into the basket. Furthermore, the accuracy of the
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movement can be measured quantitatively by focusing on selected features of the motor task.
Material and Methods Participants Sixty female university students (M = 21.25, SD = 2.73) volunteered to participate in the experiment: they all attended the first year of the course in Motor Sciences at Università Cattolica del Sacro Cuore in Milan, Italy. We decided to include only female participants to have a homogeneous sample in terms of gender. Participants were randomly assigned to either one of two conditions: mental practice combined with conventional physical training (MI) and physical training alone (C). Ten students were excluded from the analysis because they did not show up at the post-test (t2). The group that performed the MI condition included 35 students (M = 21.2; SD = 2.77); the control condition included 25 students (M = 21.3; SD = 2.73). All participants were novice players and had not received previous training in lay-up shot technique. Participants received no payment or other forms of compensation for taking part into the research. Participants signed an informed consent module for this study. The training protocol and the research design have previously obtained the institutional approval of the Department of Psychology of Università Cattolica del Sacro Cuore in Milano.
Measures Imagery ability. The “Vividness of Movement Imagery Questionnaire” (VMIQ: Isaac, Marks, & Russell, 1986) in the Italian version adapted by Antonietti and Crespi (Antonietti & Crespi, unpublished manuscript) was used to assess the participant's imagery ability. VMIQ is a 24-item questionnaire asking participants to imagine movements and rate their ability to imagine individual movements on a 5-point Likert scale ranging from 1 (very hard to see) to 5 (very easy to see). The VMIQ has been shown to have a good internal consistency for the visual subscale (r = .95) and for the kinestetic subscale (r = .97), with a test-retest coefficient over a 3-week period of r = .76 and of r = .62 over a 2-week period (Eton et al., 1998). The VMIQ has shown high (r = .81; Isaac et al., 1986) to moderate (r = .60; Eton et al., 1998) correlations with the Vividness of Visual Imagery Questionnaire (VVIQ; Marks, 1973) but low correlations with Movement Imagery Questionnaire (r = .58; Hall & Martin, 1997). No participants were excluded on the basis of their VMIQ score (see Results section). Lay-up shot. The lay-up shot performance was evaluated through 5-point Likert scales (1 = very poor, 5 = very good), which assessed five features of the movement: “Fluidity”, “Rhythm”, “Coordination”, “Step Accuracy” and “Balance Landing”. Higher values in “Fluidity” indicate a smooth movement, without interruptions and variations in speed. “Rhythm” indicates the presence of a rhythmic component in the required steps of the motor sequence. “Coordination” indicates the player’s ability to control and correctly move all the parts of the body required by the task: specifically for the lay-up shot, coordination between knees and arms is evaluated. “Step Accuracy” refers to the player’s ability alternating steps during the execution of the movement, following the right timing and the right sequence of feet hitting the floor: a balanced posture is also required. Finally, “Balance Landing” focuses on the final
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phase of the movement, when the player has to keep the balance after the shot, so that the player can immediately take part to the next action.
were right-handed.
Materials
Video Analysis
The motor imagery instructions script was encoded as Mp3 audio file and then stored on a compact disc: the audio track lasted 74 seconds. The script traces the lay-up shot from an internal perspective: the athlete was instructed to recollect the real sensations of the movement. The script used for the experiment was as follows: “Imagine that you are on the basketball field with the basket right in front of you. You receive the ball and hold it in your hands. By holding it tight, you begin your movement with a right foot step. Then you perform a quick step by moving the left and then the right foot. You feel the speed of your movement starting from feet and spreading all along your body. The ball is firmly settled on your body’s side far from a possible defender’s tackle. The horizontal strength that moves you is now loaded on the left foot that switches it vertical. You jump as high as you can feel your body fly. You flex your right knee and clearly feel the extended left leg lift off the floor just before the shot. You stare at the basket and complete the action by shooting the ball through a wrist circular movement, before landing with both feet on the court”. Some key elements of the script helped participant’s work: for example, each athlete was asked to imagine from an internal perspective through the use of the second-person singular. This was aimed at enhancing the athlete’s involvement in the task and it can help him/her through a non-familiar kind of practice. Furthermore, words have been chosen to let the participant feel the movement like if he/she is performing it: the script is not just a bare description of the correct movement.
Procedure The study consisted in three consecutive phases: pre-training, training and post-training. In the pre-training phase, a baseline measure was obtained by asking participants to execute five lay-up shots (t1) while the experimenter video-recorded their performance. In the following, training phase, players in the MI group received a Mp3 file containing audio instructions which were designed to facilitate mental rehearsal of the lay-up shot. As suggested by previous research (Olsson, 2008), participants were instructed to mentally practice three times a week. Each mental practice session consisted of five repetitions and lasted 10 minutes for a total amount of 30 minutes per week. In order to monitor compliance, participants were asked to fill a report after each mental training session in which they described their feelings during mental rehearsal. Participants assigned to the control group received half-anhour physical training, two times per week for four weeks, totalizing four hours of physical training (the same amount of physical training was received by participants assigned to the MI group). In the post-training phase (t2), each participant performed a second series of five lay-up shots and performance was again videotaped by the experimenter. All participants
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Results Participants performance was video-taped during the execution of the motor task before and after training. After, videos were collected and post-produced to obtain individual clips for each lay-out shot performed by participants. Next, these clips were recorded in random order on a DVD. The DVD was sent to three professional basketball trainers (all males, mean age = 41.5 years) who were asked to rate each single lay-out shot included in the DVD (only once at time). The three judges had extensive experience in training and evaluating young basketball players and received no monetary or other form of compensation for their evaluation. The DVD instructions included no indication concerning the scope of the research or the type of training that was received by participants. Evaluators provided their ratings on an Excel form, which was sent back per email to the experimenter. In order to test inter-rater agreement, Cronbach alpha values were calculated: high consistency (values from .83 to .87) emerged for an all the measures of the lay-up shot except for “Balance Landing”, that met lower agreement (t1 = .65, t2 = .55). Table 1 reports the mean improvement (t2 - t1) for each measure. The mental practice group showed greater improvement in performance than the control group. Five repeated-measures 2 (MI vs. C) X 2 (t1 vs. t2) ANOVAs were computed to test the statistical significance of the differences observed in the two conditions. Results of the ANOVA showed a significant effect of training condition on “Coordination” [F (1, 58) = 5.603, p < .05, η2 = .088] and an almost significant effect of training on “Step Accuracy” [F (1, 58) = 3.724, p = .059, η2 = .060], whereas the other three features of the movement (“Fluidity”, “Rhythm” and “Balance Landing”) did not significantly differ between the two conditions. Descriptive statistics for “Coordination” and “Step Accuracy” are reported in Table 2. Figure 1 shows the interaction effect between Group and Time for “Coordination”.
Vividness of Movement Imagery Questionnaire Further analyses have been conducted to assess any correlaTable 1. Mean improvement (t2 - t1) on selected performance measures. Fluidity
Rhythm
Step Accuracy
Coordination
Balance Landing
MI
0.24
0.25
0.34
0.35
0.26
C
0.11
0.12
0.03
0.09
0.18
Table 2. Coordination and step accuracy (Mean and SD). Coordination
Step Accuracy
t1
t2
t1
t2
MI
2.85 (0.94)
3.20 (0.86)
2.90 (1.07)
3.24 (0.97)
C
2.53 (0.55)
2.63 (0.64)
2.65 (0.68)
2.68 (0.76)
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Figure 1. Coordination X time interaction.
tions between VMIQ scores and performance improvement: the participants scored from 84 to 120, with a mean value on the whole sample of 99.17. The sample was split into tertiles considering their imagery ability (VMIQ score), assessed before training. Pearson correlation coefficients with performance scores (the mean improvement between t1 and t2 for each features) were calculated. No significant correlations were found.
Discussion Consistent with the main hypothesis of this study, findings indicate that combined mental and physical practice can improve performance of a closed sport task. These findings are partially in line with those obtained by related studies investigating motor imagery in basketball (Post et al., 2010; Lamirand & Rainey, 1994; Savoy & Beitel, 1996). Guillot et al. (2009) trained three attack movements with 10 national female basketball players: results showed that motor imagery improved motor performance, although mental practice was not found more effective than physical practice alone. Other research has indicated that imagery efficacy in basketball is enhanced when it is supported by visual cues (Hall & Erffmeyer, 1983) or it is performed right before the match (Post et al., 2010). In the present study, the lay-up shot technique was examined with respect to several dimensions (“Fluidity”, “Rhythm”, “Step Accuracy”, “Coordination” and “Balance Landing”). Among these features, “Balance Landing” was the only feature showing relatively low agreement among judges. Since “Balance Landing” is a crucial indicator of the relationship between the individual movement and athlete’s ability to start the next team action, this is a crucial feature to consider in future studies employing mental practice in basketball. The results showed a significant improvement in “Coordination”, and in particular evaluators considered the coordination between arms and knees. This is a difficult challenge for novices, since not only they must learn different patterns of movement involving different body parts, but they also have to synchronize them. The imagery instructions script provided by our training protocol helped novices
taking into account all the different parts of the task, and particularly how to associate them in order to perform an homogeneous movement. To our best knowledge, this is the first study showing a positive effect of motor imagery on coordination in learning a complex motor skill in sport: however, similar findings were obtained in the clinical context, in particular in the application of motor imagery in developmental coordination disorder (Wilson, 2002; Doussoulin & Rehbein, 2011). The improvement observed in Step Accuracy, although close to significance, deserves also a comment. This feature is directly linked to the cognitive dimension of motor learning: the main challenge for an athlete learning the lay-up shot is represented by the acquisition of the right sequence of steps, whose difficulty is high because the final performance must be very quick. Once again, the imagery script guided the athlete to take into account that the three steps required are not only an abstract sequence nor simply a series of rules to follow. The perceptions recalled through the imagery script allowed the athlete to feel and consider the lay-up shot as the best and fastest way to reach the basket efficiently. The imagery script was rehearsed from an internal viewpoint, so that the participant was able to learn both the correct execution and the bodily sensations and feelings, i.e. the shift of body’s weight while performing the task. Giving them a detailed script they could focus on, athletes better understood the sequence as a pattern that makes sense to the actual performance. Secondly, we have introduced a novel methodology for evaluation of the motor skill performance, based on the analysis of the video-tapes of the target movement. Recent studies have attempted to assess motor imagery effects through self-reported measures, like the Standardized Basic and Combined Movements Scale (Dossoulin & Rehbein, 2011) or the Sport Imagery Questionnaire (Hall et al., 1998). These studies aim at identifying the role of imagery training in improving psychological issues like self or collective efficacy (Shearer et al., 2009) or the imagery ability itself (Cumming et al., 2001). Other studies analyze the outcome from a mathematical perspective with a specific parametric analysis of distances and angles of the movements, e.g. in golf (Smith et al., 2008) and high jump (Olsson et al., 2008). A small number of researches in sport assess the final score of the movement or the number of successful attempts (Peynircioglu et al., 2000; Ploszay et al., 2006). However, we propose that video-analysis performed by independent raters represents a way of assessing motor performance which may reduce some of the bias usually associated with self-reports. This methodology allowed us to rate directly the performance in a simple way, besides the results highlight the specific features enhanced by the protocol instead of a general improvement. However, it should be mentioned that this study had several limitations. First, the sample involved only female participants, limiting the generalizability of findings. Further, the sample included only students; therefore it is not clear to which extent these findings are also applicable to athletes. A future goal is to investigate how to incorporate this newlydesigned imagery protocol in the training program of a team. Our training could be specifically addressed to the novices showing greater difficulties in performing a synchronized movement. For example, a coach could identify the specific strengths and weaknesses of each athlete, e.g., lack of coordination, to offer them specific motor imagery training, empowering the physical one practiced during team sessions with the help of a
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sport psychologist (or just scheduled by a specialist and then performed autonomously by the athlete). Future studies should also aim to investigate the real efficacy of mental training with younger athletes (Munroe-Chandler, 2007; Parker et al. 2009), taking into account also their ability of performing an imagery protocol based on internal perspective (Parker, 2011).
Acknowledgements We wish to thank Michele Moscardin for registering the audio tracks.
REFERENCES Allami, N., Paulignan, Y., Brovelli, A., & Boussaud, D. (2007). Visuomotor learning with combination of different rates of motor imagery and physical practice. Experimental Brain Research, 184, 105-113. Coelho, R. W., De Campos, W., Da Silva, S. G., Okazaki, F. H., & Keller, B. (2007). Imagery intervention in open and closed tennis motor skill performance, Perceptual and Motor Skills, 105, 458-468. Cumming, J. L., & Ste-Marie, D. M. (2001). The cognitive and motivetional effects of imagery training: A matter of perspective. The Sport Psychologist, 15, 276-288. Cumming, J., & Williams, S. E. (2012). Imagery: The role of imagery in performance. In S. Murphy (Ed.), Handbook of sport and performance psychology (pp. 213-232). New York, NY: Oxford University Press. Decety, J., Jeannerod, M., Germain, M., & Pastene, J. (1991). Vegetative response during imagined movement is proportional to mental effort. Behavioural Brain Research, 42, 1-5. Decety, J., Jeannerod, M., & Prablanc, C. (1989).The timing of mentally represented actions. Behavioural Brain Research, 34, 35-42. Doussoulin, A., & Rehbein, L. (2011). Motor imagery as a tool for skill training in children, Motricidade, 7, 37-43. Driskell, J., Copper, C., & Moran, A. (1994). Does mental practice enhance performance? Journal of Applied Psychology, 79, 481-492. Eton, D. T., Gilner, F. H., & Munz, D. C. (1998). The measurement of imagery vividness: A test of the reliability and validity of the vividness of visual imagery questionnaire and the vividness of movement imagery questionnaire. Journal of Mental Imagery, 22, 125136. Feltz, D. L., & Landers, D. M. (1983). The effects of mental practice on motor skill learning and performance: A meta-analysis. Journal of Sport Psychology, 5, 25-57. Gaggioli, A., Meneghini, A., Morganti, F., Alcaniz, M., & Riva, G. (2006). A strategy for computer-assisted mental practice in stroke rehabilitation. Neurorehabilitation and Neural Repair, 20, 503-507. Guillot, A., Nadrowska, E., & Collet, C. (2009). Using motor imagery to learn tactical movements in basketball. Journal of Sport Behavior, 32, 189-206. Guillot, A., & Collet, C. (2008). Construction of the motor imagery integrative model in sport: A review and theoretical investigation of motor imagery use. International Review of Sport and Exercise Psychology, 1, 31-44. Hall, C. R., & Martin, K. A. (1997). Measuring movement imagery abilities: A revision of the movement imagery questionnaire. Journal of Mental Imagery, 21, 143-154. Hall, C. R., Mack, D., Paivio, A., & Hausenblas, H. (1998). Imagery use by athletes: Development of the sport imagery questionnaire. International Journal of Sport Psychology, 29, 73-89. Hall, E., & Erffmeyer, E. S. (1983). The effect of visuo-motor behavior rehearsal with videotaped modeling on free throw accuracy of intercollegiate female basketball players. Journal of Sport Psychology, 5,
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343-346. Hardy, L., & Callow, N. (1999). Efficacy of external and internal imagery perspectives for the enhancement of performance in tasks in which form is important. Journal of Sport and Exercise Psychology, 21, 95-112. Isaac, A., Marks, D., & Russell, D. (1986). An instrument for assessing imagery of movement: The Vividness of Movement Imagery Questionnaire (VMIQ). Journal of Mental Imagery, 10, 23-30. Jackson, P. L., Lafleur, M. F., Malouin, F., Richards, C. L., & Doyon, J. (2003). Functional cerebral reorganization following motor sequence learning through mental practice with motor imagery. Neuroimage, 20, 1171-1180. Jeannerod, M. (1994). The representing brain: Neural correlates of motor intention and imagery. Behavioural and Brain Sciences, 17, 187-245. Jeannerod, M., & Decety, J. (1995). Mental motor imagery: A window into the representational stages of action. Current Opinion in Neurobiology, 5, 727-732. Karni, A., Meyer, G., Jezzard, P., Adams, M. M., Turner, R., & Ungerleider, L. G. (1995). Functional MRI evidence for adult motor cortex plasticity during motor skill learning, Nature, 377, 155-158. Lafleur, M. F., Jackson, P. L., Malouin, F., Richards, C. L., Evans, A. C., & Doyon, J. (2002). Motor learning produces parallel dynamic functional changes during the execution and imagination of sequential foot movements. NeuroImage, 16, 142-157. Lamirand, M., & Rainey, D. (1994). Mental imagery, relaxation, and accuracy of basketball foul shooting, Perceptual and Motor Skills, 78, 1229-1230. Lang, P. J. (1979). A bio-informational theory of emotional imagery. Psychophysiology, 16, 495-512. Louis, M., Guillot, A., Maton, S., Doyon, C., & Collet, C. (2008). Effect of imagined movement speed on subsequent motor performance. Journal of Motor Behavior, 40, 117-132. Marks, D. F. (1973). Visual imagery differences in the recall of pictures. British Journal of Psychology, 64, 17-24. Miller, K. J., Schalk, G., Fetz, E., den Nijs, M., Ojemann, J., & Rao, R. (2010). Cortical activity during motor execution, motor imagery, and imagery-based online feedback. Proceedings of the National Academy of Sciences, 107, 4430-4435. Munroe-Chandler, K. J., Hall, C. R., Fishburne, G. J., & Strachan, L. (2007). Where, when and why young athletes use imagery: An examination of developmental differences. Research Quarterly for Exercise and Sport, 78, 103-116. Murphy, S. M., & Jowdy, D. P. (1992). Imagery and mental practice. In T. S. Horn (Ed.), Advances in sport psychology (pp. 221-225). Champaign, IL: Human Kinetics. Olsson, C. J., Jonsson, B., & Nyberg, L. (2008). Internal imagery training in active high jumpers. Scandinavian Journal of Psychology, 49, 133-140. Parker, J. K., & Lovell, G. (2009). Characteristics affecting the use of imagery: A youth sports academy study. Journal of Imagery Research in Sport and Physical Activity, 4, 1-15. Parker, J. K., & Lovell, G. (2011). The influence of experience upon imagery perspectives in adolescent sport performers. Journal of Imagery Research in Sport and Physical Activity, 6, Article 1. Peynircioglu, Z. F., Thompson, J. L. W., & Tanielan, T. B. (2000). Improvement strategies in free-throw shooting and grip-strength task. The Journal of General Psychology, 127, 145-156. Ploszay, A. J., Gentner, N. B., Skinner, C. H., & Wrisberg, C. A. (2006). The effects of multisensory imagery in conjunction with physical movement rehearsal on golf putting performance. Journal of Behavioral Education, 15, 247-255. Post, P. G., Wrisberg, C. A., & Mullins, S. (2010). A field test of the
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influence of pre-game imagery on basketball free throw shooting. Journal of Imagery Research in Sport and Physical Activity, 5, Article 2. Richardson, A. (1967). Mental practice: A review and discussion (Part II). Research Quarterly, 38, 263-273. Roure, R., Collet, C., Deschaumes-Molinaro, C., Dittmar, A., Rada, H., Delhomme, G., & Vernet-Maury, E. (1998). Autonomic nervous system responses correlate with mental rehearsal in volleyball training. European Journal of Applied Physiology, 78, 99-108. Savoy, C., & Beitel, P. A. (1996). Mental imagery for basketball. International Journal of Sport Psychology, 27, 454-462. Schuster, C., Kilfiker, R., Amft, O., Scheidhauer, A., Andrews, B., Butler, J., Kischka, U., & Ettlin, T. (2011). Best practice for motor imagery: A systematic literature review on motor imagery training elements in five different disciplines. BMC Medicine, 9, 75. Shea, C. H., Wright, D. L., Wulf, G., & Whitacre, C. (2000). Physical and observational practice afford unique learning opportunities. Journal of Motor Behavior, 32, 27-36. Shearer, D., Mellalieu, S., Shearer, C., & Roderique-Davies, G. (2009). The effects of a video-aided imagery intervention upon collective efficacy in an international paralympic wheelchair basketball team. Journal of Imagery Research in Sport and Physical Activity, 4, 1-25.
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Sherwood, D. E., & Lee, T. D. (2003). Schema theory: Critical review and implications for the role of cognition in a new theory of motor learning. Research Quarterly for Exercise and Sport, 74, 376-382. Smith, D., Wright, C. J., & Cantwell, C. (2008). Beating the bunker: The effect of PETTLEP imagery on golf bunker shot performance. Research Quarterly for Exercise and Sport, 3, 386-391. Sun, L., Yin, D., Zhu, Y., Fan, M., Zang, L., Wu, Y., Jia, J., Bai, Y., Zhu, B., & Hu, Y. (2013). Cortical reorganization after motor imagery training in chronic stroke patients with severe motor impairment: A longitudinal fMRI study. Neuroradiology, 55, 913-925. Taktek, K. (2004). The effects of mental imagery on the acquisition of motor skills and performance: A literature review with theoretical implications. Journal of Mental Imagery, 3, 79-114. White, A., & Hardy, L. (1995). Use of different imagery perspectives on the learning and performance of different motor skills. British Journal of Psychology, 86, 169-180. Wilson, P. H., Thomas, P. R., & Maruff, P. (2002). Motor imagery training ameliorates motor clumsiness in children. Journal of Child Neurology, 17, 491-498.
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7 The Best Route Is Not Always the Easiest One: Spatial References in Heuristics of Route Choice 1
Wen Wen1, Hideaki Kawabata2
Advanced Research Centers, Keio University, Tokyo, Japan 2 Department of Psychology, Faculty of Letters, Keio University, Tokyo, Japan
In the present study, we discovered a relationship between down-going and up-going route preferences and selection of spatial reference. The participants were asked to choose between a down-going route and an up-going route on a simplified map. When they were asked to select the better route (Experiment 1), they preferred the down-going route, although the two routes were the same shape and distance. However, when the participants were asked to select the route that seemed easier to remember and find, they favored up-going routes (Experiment 2). We suggested that the contrary route preferences were caused by different selections of spatial references. That is, the first instruction directed participants’ attention to the configurational layout of the maps (i.e., promoted the allocentric reference) and induced the down-going route preference, whereas the later instruction promoted egocentric navigating strategies and induced the up-going route preferences. Furthermore, we asked the participants to learn a down-going and an up-going route, then examined their wayfinding and spatial memory performance (Experiment 3). The participants found the goals more quickly when up-going routes were used, but remembered the locations of landmarks more accurately when down-going routes were used. Keywords: Route Choice; Spatial Reference; Allocentric Reference; Egocentric Reference; Geographic Reference; Sense of Direction
Introduction When you are traveling in a novel city, you probably need to check maps and plan a route from the nearest subway station to your hotel. Most often, there is more than one route choice. For example, there may be several stations nearby, so you need to decide which one to use and choose the best route. However, the definition of the “best route” is ambiguous. It might refer to the shortest one, the simplest one, or the one easiest to find. According to previous findings on route choice, people do not always choose the shortest route (Bailenson, Shum, & Uttal, 1998, 2000). Instead, their route-finding decisions depend on the use of general heuristics (Bailenson et al., 1998; Brunyé et al., 2012; Brunyé, Mahoney, Gardony, & Taylor, 2010; Yang & Schwaninger, 2011). For instance, people tend to select the street most in line with the target (Hochmair & Karlsson, 2005), or prefer the extreme routes over the middle ones although all the routes were the same length and required the same number of turns (Christenfeld, 1995). Furthermore, the routes with straight initial segments are preferred even though the routes may not be the shortest in distance (Bailenson et al., 1998, 2000). In addition to the studies mentioned above, Brunyé et al. (2010, 2012) recently reported a novel heuristics of southern route preference, which causes participants to preferentially choose a south-going route over a north-going route during map-based route planning. Brunyé et al. (2010) attributed this
heuristic to the misperception of increases associated with the direction, north (i.e., north is up). In line with this heuristic, participants rated a northern route as one that burned more calories and took more time to complete than a southern route. In addition, Brunyé et al. (2012) found that large-scale regional characteristics did not affect the southern route heuristic, and speculated that a north-going route may be associated with a vertically upward direction, which is more physically demanding relative to the downward direction. However, in the studies by Brunyé et al. (2010, 2012), the south-going routes appeared both south-going and down-going routes, because the north was always shown as up in all the maps used in their experiments. Therefore, it is possible that the so-called southern route preference heuristic is not actually related to geographic reference (i.e., north-south); instead, it may be due to an egocentric reference (i.e., up-down). Furthermore, in the Brunyé et al. studies (2010, 2012: p. 301), the best route was explained as “the one that was shorter and/or faster,” although there were probably individual differences in the comprehension of the “best route.” In the present study, we re-examined the heuristics of southern route preference proposed by Brunyé et al. (2010, 2012). We separated geographic and egocentric reference, examined the effect of different instructions on route preference, and tested behavioral facilitations of a down-going route and an up-going route. First, we asked people to choose the “better route” from two different origins, which were above or below the same destination, and the “better route” from the same ori-
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gin to two different destinations, which were above or below the origin, to test whether the southern route preference heuristic also refers to the south-toward (or down-toward) route (i.e., a route with a northern origin and a southern destination). Second, we added rotated compasses to the maps and changed the instruction to “choose the route easier to go,” to examine the effects of references and instructions on route preference. Third, we asked the participants to remember maps of up-going or down-going routes, and measured their wayfinding and spatial memory performance.
Experiment 1 In the Brunyé et al. studies (2010, 2012), the heuristic was called the south-going route preference, in which the southern routes went toward south at first but turned to north later; even the destinations were to either the east or the west of the origins (i.e., the start locations). Here, we first used conditions with two origins or two destinations to determine whether this heuristic also includes a preference for a south-toward route. In the two-origin condition, imagine that there were two different railway stations near a hotel (the distance between the hotel and the different stations was the same). In the two-destination condition, imagine that there were two different hotels, one to the north of the station and another to the south (the hotels were equal on all other factors). In both conditions, the participants were required to select the better route from one of the two origins or to one of the two destinations.
Method Participants Sixty-eight participants (33 female, mean age = 24.6 years, 4
left-handers) completed the route choice questionnaire. Of the participants, 43 completed paper questionnaires and 25 completed the same questionnaire via an online Google form. Materials and Procedure Two types of maps were used. One map type contained two origins and one destination (two-start maps, upper panels in Figure 1, (A1)-(A5)), and the other map type contained one origin and two destinations (two-goal map, lower panels in Figure 1, (B1)-(B5)). For each two-start map, in the up-down condition, there were two origins (i.e., start locations), presented as small circles at the top and the bottom, and one destination, presented as a star in the center. In the left-right condition, the two origins were presented at the left side and the right side. The straight line distances between the origins and the destinations were the same in all the maps. For each map, two routes started from the origins and ended at the destination. The upper and the lower route had the same shape (the routes were rotated 180˚ from each other). Black arrows were presented near the origins, showing the route directions. The routes were curved, at oblique angles, at right angles, or in a straight line (two maps for each route shape). Furthermore, the routes in half of the maps started toward the destination (the start-toward-goal condition), while the others started toward the direction opposite the destination (the start-against-goal condition) (e.g., Figure 1, A5). All the left-right maps were modified from the updown maps. In fact, to obtain the left-right maps, the up-down maps were rotated 90˚. For each two-goal map, there was an origin in the center and two destinations beside the origin. The two-goal maps were modified from the two-start maps. In fact, to obtain the two-goal maps, the positions of the origins and destinations of the two-start maps were exchanged. Sixteen
Figure 1. Examples of the maps used in Experiment 1. (A1)-(A5) are two-start maps, which contained two origins and one destination. (B1)-(B5) are two-goal maps, which contained one origin and two destinations. Origins described as “Start” are presented as white circles, and destinations described as “Goal” are presented as red-filled stars. The routes were printed in gray color with black borders. Black arrows near the starts showed the directions of the routes. Gray polygons, located randomly along the routes, served as landmarks.
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consistent with the Brunyé et al. (2010, 2012) studies in which people consistently exhibited the south-going route preference heuristic, and it does not account for the increased selections of down-going routes when the routes started in the opposite direction of the destinations in the two-goal condition. We speculate that the different route choice selection instructions promoted different spatial references and caused the contrary results. To be specific, the “choose the better route” instruction promoted an allocentric reference, in which down-going routes were preferred, whereas the “choose the route you prefer to use” instruction caused the participants to imagine they were standing at the origin and, therefore, promoted an egocentric reference, in which up-going routes were preferred. This explanation provides a good account of the results of prior studies (Brunyé et al., 2010, 2012), in which real-world maps were used and the participants were asked to select the “best route.” In this case, a geographic reference was probably promoted and southern routes were preferred. Moreover, this explanation accounts for the results of the two-goal maps. In the two-goal condition, the participants probably imagined themselves standing at the origin. Thus, the directions of the up-going routes aligned with their head directions. However, when the initial segments of the up-going routes were in the opposite direction of the egocentric head directions (in the start-against-goal condition), the preference for the up-going routes disappeared. To provide additional support for this hypothesis, we conducted the second experiment, in which the route choice instructions were changed and geographic compasses were included.
two-start maps and fourteen two-goal maps (two-goal maps containing a straight route with opposite start directions were not used) were included in the questionnaire. The two-start maps and the two-goal maps were grouped in different parts of the questionnaire. The participants started with the two-start maps and were asked to select the better route to the goal for each map. Next, for each two-goal map, they selected the route they preferred to use. Maps were printed in random order. The participants were asked to make intuitive decisions and not to change their prior choices.
Results For all up-down maps, the percentage of down-going routes selected is given in Table 1. Similarly, for all left-right maps, the percentage of right-going routes selected is also given in Table 1. The selections were compared to chance level (50%) after the application of angular transformations. For the twostart maps, the selections of the down-going routes were significantly greater than chance level for both the start-towardgoal condition and the start-against-goal condition (t(67) = 3.35, p < .01; t(67) = 3.06, p < .01, respectively). Right-going routes were selected at chance level for both start direction conditions (start-toward-goal condition: t(67) = 0.96, n.s.; start-againstgoal condition: t(67) = 1.58, n.s.). In contrast, for the two-goal maps, the selections of down-going routes were significantly less than chance level for the start-toward-goal condition (t(67) = −3.46, p < .01), whereas the selections of down-going routes in the start-against-goal condition, the selections of right-going routes in the start-toward-goal and start-against-goal conditions were all at chance level (t(67) = 1.42, n.s.; t(67) = 1.96, n.s.; t(67) = −0.16, n.s., respectively). Moreover, there were significantly more selections of down-going routes in the startagainst-goal condition than in the start-toward-goal condition (t(67) = 4.06, p < .01).
Experiment 2 In Experiment 1, a down-going route preference heuristic was observed when the participants were asked to select the “better route,” but contrary preferences appeared when the participants were asked to select “the route they prefer to use.” The instruction of selecting the better (or the best) route may promote an allocentric reference which favors a down-going route preference. If an egocentric reference is promoted (such as the case in the two-goal condition), up-going routes in which route directions align to head direction should be preferred. In Experiment 2, the route choice instruction was changed to “select the route you think is easier to remember and easier to travel.” This instruction was expected to promote an egocentric reference and induce an up-going route preference. Furthermore, we presented direction compasses together with the maps, as described in previous studies (e.g., Brunyé et al., 2010, 2012), to confirm the dominance of the egocentric reference. That is, if the participants ignored the directions shown by the compasses, the egocentric reference is considered dominant. Finally, we hypothesized that the “choose the route you prefer to use” instruction used in the two-goal condition would promote an
Discussion Experiment 1 demonstrated that the participants preferred the down-going route (to one of the two destinations) when they were asked to choose the “better one,” although a definition of the “better route” was not provided. However, they preferred an up-going route (from one of the two origins) when they were asked to choose “the one they preferred to use.” The contrary route direction preferences were quite interesting, indicating that the “better route” may not equal the one people actually considering using. A possible explanation for the results was that people probably prefer the routes on the upper side of the map, since both down-going routes in the two-start condition and up-going routes in the two-goal condition were located in the upper half of the maps. However, this explanation is not
Table 1. Mean percentages and standard deviations of down-going and right-going route selections in each condition of Experiment 1. Up-down maps Start-toward-goal Two-start Two-goal
.63 (.31)
**
.36 (.31)
**
Left-right maps Start-against-goal .61 (.29)
**
.56 (.34)
Start-toward-goal
Start-against-goal
.53 (.30)
.55 (.33)
.58 (.32)
.49 (.29)
Note: For each condition, the participants’ selections were compared to chance level. **p < .01.
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egocentric reference. However, the two-destination condition may also have influenced spatial reference. In order to exclude this possibility, we only used two-start maps and compared the results with those of Experiment 1.
Method Participants Ninety-eight participants (80 females, average age = 19.1 years, six left-handers) completed the route choice questionnaire. None of these individuals participated in Experiment 1. Materials Compasses showing north were added to the two-start maps used in Experiment 1. The compasses were illustrated as a triangle within a circle; the word “north” was printed near the acute angle of the triangle (Figure 2). The compasses indicated north as any direction (up, down, left, or right) in each map. The routes were curved or had right angles. Half of the maps contained up-down routes, and the others contained left-right routes. Half of the routes started toward the destinations, and the others started in the direction opposite the destination. A total of 32 maps were included in the questionnaire (2 map types, 4 compasses, 2 start directions, 2 shapes). The maps were printed in random order.
F(3, 291) = 4.46, p < .01, respectively). For the up-down maps, there were significantly more selections of down-going routes when the compasses pointed down (i.e., north was down) than the other conditions (Tukey’s Honestly Significant Difference (HSD) tests, ps < .05). For the left-right maps, the selections of right-going routes were greater than chance level when the compasses pointed to the right, up, and down, but were at chance level when the compasses pointed to the left (t(97) = 4.81, p < .01; t(97) = 2.98, p < .01; t(97) = 2.13, p < .05; t(97) = 0.70, n.s., respectively). We also statistically analyzed the geographic route choices (Table 3) (i.e., a south-going route refers to a down-going route when the compass pointed up, an upgoing route when the compass pointed down, a right-going route when the compass pointed left, and a left-going route when the compass pointed to the right) and found significant differences in geographic route choices (F(3, 291) = 10.82, p < .01). There were fewer selections of the south-going routes than the other route directions (Tukey’s HSD tests: ps < .01). Finally, the mean SBSOD score for all participants was 3.28 (7-point scale, SD = 1.10). The mean score was not signifi-
Procedure Prior to completing the root choice task, the participants completed the Santa Barbara Sense of Direction (SBSOD) scale (Hegarty, Richardson, Montello, Lovelace, & Subbiah, 2002). Next, for each map, they read the explanation of the map and the route choice task, and were asked to select the route that they thought was easier to remember and find. As in Experiment 1, they were instructed to make intuitive decisions and not to change their prior choices.
Results For all up-down maps, the percentage of down-going routes selected is shown in Table 2. Similarly, for all left-right maps, the percentage of right-going routes selected is also shown in Table 2. The percentage of down-going and right-going selections was compared to chance level (50%) after the application of angular transformations. For up-down maps, the selections of down-going routes were significantly less than chance level when the initial segments were toward the destinations (t(97) = −6.70, p < .01), but at chance level when the routes started against the destinations (t(97) = −1.80, n.s.). For left-right maps, right-going routes were preferred in both the start-toward-goal condition and the start-against-goal condition (t(97) = 2.73, p < .01; t(97) = 4.12, p < .01, respectively). Furthermore, the main effect of compasses was significant for both up-down and left-right maps (F(3, 291) = 7.41, p < .01;
Figure 2. Map examples showed to the participants. Compasses showing north were added to the map.
Table 2. Mean percentages and standard deviations of down-going and right-going route selections in each condition of Experiment 2. Up-down maps Start-toward-goal .33 (.23)
**
Left-right maps Start-against-goal .46 (.23)
Start-toward-goal .57 (.21)
**
Start-against-goal .59 (.21)**
Note: For each condition, the participants’ selections were compared to chance level. **p < .01.
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Table 3. Mean percentages and standard deviations of geographic route choice. South-going
North-going
East-going
West-going
.21 (.10)
.29 (.10)
.25 (.06)
.25 (.06)
cantly correlated with down-going route preference, right-going route preference, or any of the geographic route choices, showing that the route preferences were not related to sense of direction.
Discussion Contrary to the down-going route preference in Experiment 1, the participants in this experiment preferred up-going routes when selecting between two routes starting from different origins to the same destination. For Experiment 2, the route choice instruction was changed from “select the better route” to “select the route you think is easier to remember and easier to find.” As expected, the latter instruction promoted an egocentric reference and induced an up-going route preference. This hypothesis was supported by the results of the start-against-goal condition. That is, the up-going route preference disappeared when the initial segments of the routes were inconsistent with the egocentric head directions. Furthermore, the analysis of geographic route choice showed a negative priming effect of compasses. Routes misaligning to the compass were avoided; this finding indicates that this perceptual feature on maps could also influence route choices. This interpretation has important implications for map design and needs further discussion. However, another explanation of the geographic route choices results is that the participants simply did not want to go south. Unfortunately, this hypothesis is inconsistent with the findings of Brunyé and colleagues (2010, 2012) and of Experiment 1 in the present study. Finally, the observed right-going route preference in the left-right condition was probably a result of a high proportion of right-handers. In Experiments 1 and 2, we found that people favored a down-going route when an allocentric reference was dominant but preferred an up-going route when an egocentric reference was dominant. Brunyé and others (2010, 2012) suggested that the down-going direction may be associated with the vertically down direction and is perceived to be less physically demanding. Although this is possible, it does not account for the fact that spatial references changed route preference.
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& Letters Building 2 of the University of Tokyo, which has five floors, an L shape, a quadrangle, and six exits. The two routes were 83 m and 78 m in length and had five and six turns, respectively. For each route, four landmarks were specified and printed on the map as icons. The two routes did not meet or cross with each other, and were used for either an up-going route or a down-going route, by rotating the route 180˚. Photos near landmarks and goals were presented to the participants. Procedure Participants took part in the experiment individually. They first completed the SBSOD scale (Hegarty et al., 2002) outside the building, and then were told that they were going to memorize a map, find the goal without using the map, and draw a sketch-map after wayfinding. They were told not to rotate the map and to find the goal as quickly as possible. Then, they studied the first map until they reported that they had memorized the whole map. After map learning, the participants followed the experimenter to the start place, and were shown the start direction. During the wayfinding, if the participants deviated from the route for more than 5 s, they were redirected to the correct route by the experimenters. The total time, number of errors, and number of stops was recorded. After arriving at the goal, the participants returned to the place where they had received an explanation of the experiment and drew a sketchmap on a blank piece of A4-sized (210 × 297 mm) paper. After the first trial, the participants rested for about five minutes. Next, they memorized the second map, and completed the wayfinding and the map-sketching tasks. After finishing all the tasks, they gave an oral report of their navigating strategies and map-reading habits used in their daily life. The order and orientation of routes were counter-balanced between participants. The experiment lasted 40 minutes for each participant.
Results We excluded data from two participants, because one rotated the map during memorizing phase and another failed the wayfinding task. For the wayfinding task, the total time, number of errors, and number of stops were used to index task performance (Table 4). For the map-sketching task, the proportion of correct turns and the correlation of bidimensional regression
Experiment 3 It is still not clear how this heuristic of different route preferences in an allocentric and egocentric reference profits spatial behaviors. Therefore, in Experiment 3, we asked people to memorize a down-going or an up-going route. We then examined their wayfinding and spatial memory performance.
Method Participants Twenty-six individuals (12 females, mean age = 24.5 years) were recruited. None of them participated in Experiments 1 or 2 or entered the building used for wayfinding prior to the experiment. Materials We planned two routes (Figure 3) from the Faculty of Law
Figure 3. The routes used in Experiment 3. The two routes served as either a down-going route or an up-going route. Photos near the goals and icons of landmarks were printed on the maps. Photos taken near the landmarks were printed on a separate piece of paper.
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(Tobler, 1965) were used to examine the participants’ route knowledge and configurational knowledge, respectively (Table 4). In the bidimensional regression, start and end points and the four landmarks were used as “anchors.” A Fisher’s r-to-z transformation was applied to the bidimensional correlations for analysis. The differences in total time to complete the wayfinding task and the correlations of the map-sketching task were marginally significant (t(21) = 1.93, p = .07; t(21) = −1.98, p = .06, respectively). The participants found goals faster but sketched positions of landmarks less accurately when they learned an upgoing route. There were no significant differences in the other indices of task performance. Furthermore, the average SBSOD score of the participants was 4.41 (SD = 1.44) and was significantly related to only the number of stops when down-going routes were used (r = −.45, p < .05).
Discussion The results of Experiment 3 indicated that the participants acquired better egocentric route knowledge from the up-going routes, and acquired better allocentric configurational knowledge from the down-going routes. In the up-going routes condition, the orientation of the routes was aligned to the participant’s head direction. Thus, turning directions (left or right) were easy to recall during wayfinding. However, in the downgoing route condition, to decide whether to turn left or right, the participants had to mentally rotate the memorized route, which resulted in longer wayfinding times. Moreover, the negative correlation between SBSOD score and the number of stops in the down-going route condition reflected the demands of the mental rotations. On the other hand, the down-going route probably facilitated configurational knowledge by promoting an allocentric reference. In the up-going routes condition, the participants might have associated the positions of landmarks with the routes (e.g., there were stairs after turning left). However, in the down-going routes condition, route knowledge occurred at a greater cost, and the participants probably encoded positions of landmarks directly with an allocentric reference (e.g., out of environmental frames or the shape of the entire route), which resulted in more accurate configurational knowledge.
General Discussion From the results of Experiments 1 and 2, we discovered that people did not always choose the route they thought was easier to remember and easier to go for the “better route.” Although these results are counterintuitive, they reflected the relation Table 4. The total time, number of errors, and number of stops in the wayfinding task. The proportion of correct turns and the bidimensional correlation in the map-sketching task.
Wayfinding task
Map-sketching task
Down-going route
Up-going route
Total time
91 seconds
83 seconds
Errors
0.5
0.8
Stops
1.0
1.1
Correct turns
97%
99%
Correlation
.97
.93
between route choices and selections on spatial references, which was ignored by most of the prior studies on route choice. As a consequence of being asked to select the “best/better route,” an allocentric reference was promoted and down-going routes were favored, as was reported by Brunyé et al. (2010, 2012). However, as a result of being asked to select “the route you want to go much more” or “the route that seems to be easier to remember and easier to find,” an egocentric reference dominated and up-going routes were preferred. The results demonstrated that different route choice instructions may influence the dominance of spatial reference and reserve route preferences. This fact should be acknowledged in further research of route choice. Furthermore, the results of Experiment 3 provided a behavioral rationale for the abovementioned heuristics of route preference. As a result of being asked to select the best route, people paid more attention to the global spatial layout, which facilitated configurational spatial knowledge and lead to a downgoing route preference. In contrast, although the participants indicated that they would actually use the route later, they probably paid more attention to the turning directions of the routes, which were associated with egocentric route knowledge and resulted in an up-going route preference. Although the heuristics of route preference may sometimes be inefficient, they reflect a person’s navigating strategies and spatial cognitive processes. The present study started from an interest in the heuristics of south-going (down-going) route preference as reported by prior studies (Brunyé et al., 2010, 2012), and found important relations between down-going and upgoing route preferences and spatial references. In conclusion, when selecting the “best route,” people pay attention to configurational information and prefer a down-going route. In contrast, when selecting “the way easier to travel,” people turn to egocentric route information and favor an up-going route. The present study is the first to clarify the relation between route preferences and spatial references, and provides important knowledge about route choice instructions to be used in future studies.
Acknowledgements We thank Prof. Toru Ishikawa for valuable research advice. We also thank Prof. Takao Sato for supporting these experiments.
REFERENCES Bailenson, J. N., Shum, M. S., & Uttal, D. H. (1998). Road climbing: Principles governing asymmetric route choices on maps. Journal of Environmental Psychology, 18, 251-264. Bailenson, J. N., Shum, M. S., & Uttal, D. H. (2000). The initial segment strategy: A heuristic for route selection. Memory & Cognition, 28, 306-318. Brunyé, T. T., Andonova, E., Meneghetti, C., Noordzij, M. L., Pazzaglia, F., Wienemann, R., Mahoney, C. R. et al. (2012). Planning routes around the world: International evidence for southern route preferences. Journal of Environmental Psychology, 32, 297-304. Brunyé, T. T., Mahoney, C. R., Gardony, A. L., & Taylor, H. A. (2010). North is up(hill): Route planning heuristics in real-world environments. Memory & Cognition, 38, 700-712. Christenfeld, N. (1995). Choice from identical options. Psychological Science, 6, 50-55.
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Hegarty, M., Richardson, A. E., Montello, D. R., Lovelace, K., & Subbiah, I. (2002). Development of a self-report measure of environmental spatial ability. Intelligence, 30, 425-447. Hochmair, H. H., & Karlsson, V. (2005). Investigation of preference between the least-angle strategy and the initial segment strategy for route. Lecture Notes in Computer Science, 3343, 79-97.
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Tobler, W. R. (1965). Comparison of the correspondence of geographic patterns. Papers and Proceedings of the Regional Science Association, 15, 131-139. Yang, J., & Schwaninger, A. (2011). Turn right or turn left? Heuristic of adhering to the direction of destination. Applied Cognitive Psychology, 25, 703-707.
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8 Neural Substrates of Forward and Backward Associative Priming: A Functional MRI Study 1
Sarah Terrien1,2*, Fabien Gierski1,2,3, Stéphanie Caillies1, Véronique Baltazart1, Christophe Portefaix3, Laurent Pierot3, Chrystel Besche-Richard1,4 Université de Reims Champagne-Ardenne, Laboratoire Cognition, Santé, Socialisation C2S EA 6291, Reims, France 2 Service de Psychiatrie des Adultes, Hôpital Robert Debré, CHU de Reims, Reims, France 3 Pôle d’Imagerie Médicale, Hôpital Maison-Blanche, CHU de Reims, Reims, France 4 Institut Universitaire de France, Paris, France
Forward associative priming results of an association moves from the prime to the target whereas backward associative priming results of an association from the target to the prime (Koivisto, 1998). Little is known about this dissociation of process and the associated cerebral substrates. Fourteen healthy participants were included in this study. The task consisted in a lexical decision task using an fMRI-adapted semantic priming paradigm. Contrasts between forward related and forward unrelated conditions showed activation in the left temporal gyrus, left inferior prefrontal cortex, fusiform gyrus and occipital regions and cerebellum. Investigation of the different patterns of activation between forward and backward priming shows significant results: during the contrast between the forward priming effect and the backward priming effect, we observe a deactivation of BOLD response in temporal and frontal areas, which may reflect the post-lexical integration process. So, areas responsible for language and for decoding spelling seem not to be involved in the backward process. An adaptation of this research in event-related brain potentials is underway to better explore the temporality of post-lexical process. Keywords: Semantic Memory; Forward and Backward Priming; fMRI; Left Superior Temporal Gyrus; Post-Lexical Integration
Introduction Semantic priming is a well-described phenomenon in which a target word (e.g., flower) is recognized faster when it is preceded by a semantically related word (e.g., tree) than when it is preceded by an unrelated word (e.g., knife) (Meyer & Schvaneveldt, 1971; Neely, 1991). Researchers have typically used the lexical decision task to observe the priming effect. In this task, a word (the prime) is presented visually for a fraction of a second, followed after a delay by a letter-string (the target). Participants have to judge whether or not the target is a word in their native language. The main semantic priming effects are known to involve three mechanisms: automatic spreading activation (ASA), expectancy generation (EG) and semantic matching (SM) (Neely, Keefe, & Ross, 1989). The two first kinds of processes are considered to be pre-lexical processes and the third to be a post-lexical process. Several types of semantic priming have been identified in the literature, in particular forward associative priming and backward associative priming (Koriat, 1981). In forward associative priming, there is a diffusion of activation from the prime to the target, but not the other way around. In contrast, backward associative priming occurs as a result of a strong associative link moving from the target to the prime, but not the other way around (Koivisto, *
Corresponding author.
1998). Forward priming is presumably produced by pre-lexical processes, ASA at short stimulus onset asynchronies and EG at long ones (Franklin, Dien, Neely, Huber, &Waterson, 2007). In contrast, it has been shown that backward priming requires a post-lexical process occurring when an association links the target to the prime but not vice versa, and may be due to SM and not to EG or ASA (Chwilla, Hagoort, & Brown, 1998; Kahan, Neely, & Forsythe, 1999). Numerous studies have investigated the brain regions subserving semantic priming. As we would describe in more detail below, researchers first examined the overall mechanism of semantic priming compared to other cognitive processes. They then distinguished between regions involved in the different priming conditions (related vs. unrelated word pairs). Some authors have also attempted to identify the cerebral regions that support pre-lexical and post-lexical processes (Franklin et al., 2007; Kandhadai & Federmeier, 2010; O’Hare, Dien, Waterson, & Savage, 2008). Early studies were carried out on patients with brain injuries and provided inconsistent results. Some studies showed a preservation of the semantic priming effect in patients with posterior left hemisphere lesions (Blumstein, Milberg, & Shrier, 1982; Hagoort, 1997), while others found a semantic priming deficit in patients with similar brain damage (Hagoort, 1993; Henik, Dronkers, & Knight, 1993; Milberg, Blumstein, Katz,
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Gershberg, & Brown, 1995). This divergence led investigators to study this process with neuroimaging tools. Thus, several research using different neuroimaging techniques (event-related potentials (ERP) and positron emission tomography (PET)) were conducted. They mainly revealed an activation of the anterior cingulate cortex (ACC) and the left temporal anterior regions: the anterior fusiform gyrus and the hippocampal complex (Mummery, Shallice, & Price, 1999; Nobre, Allison, & McCarthy, 1994; Nobre & McCarthy, 1995). These studies relied on a contrast between a control task (decision letter) and a lexical decision task involving semantic priming (Mummery et al., 1999). Beyond the investigation of the neural substrates underlying semantic priming in general, in comparison with other cognitive tasks, authors have been also interested in the cerebral activations obtained during the related and unrelated conditions of the semantic priming task. In a functional magnetic resonance imaging (fMRI) study, Rossel, Bullmore, Williams, and David (2001) found activation of the ACC, the posterior cingulate, the right insula and the right temporal gyrus when they contrasted semantically related vs. unrelated conditions. According to these authors, the activation of temporal regions could be explained by the maintenance of ASA when the prime and the target are related, whereas the ACC’s activation could be due to its role in the inhibition of incorrect responses. Moreover, several studies using PET scanning and fMRI have shown similar results regarding the reduction of activation in the left temporal cortex (Copland et al., 2003; Mummery et al., 1999; Rossel et al., 2001) during the related condition in comparison with the unrelated condition. Using ERPs, Matsumoto, Iidaka, Haneda, Okada and Sadato (2005) showed a pattern of decreased N400 for related conditions in semantic priming. Thanks to the source localization, these authors determined that the observed N400 was probably generated by the left superior temporal gyrus and the left superior frontal gyrus. This observation is very interesting because we know that temporal areas have been found to be related to semantic memory. As mentioned above, an fMRI study (Copland et al., 2003) revealed a decrease in cerebral activation in the left inferior prefrontal cortex (LIPC) during the related condition in comparison with the unrelated condition. The LIPC is known to be involved in selecting among competing representations in semantic memory and in semantic retrieval when the required information cannot be accessed through strong pre-existing cue-target associations (Wagner, Paré-Blagoev, Clark, & Poldrack, 2001). Few studies have investigated the distinction between the neural substrates involved in forward associative priming and those involved in backward associative priming, and the results are inconclusive. For instance, an experimental study using presentation of stimuli in visual half-field by Koivisto (1998) suggests that forward priming occurs in the left hemisphere whereas backward priming seems to occur in both hemispheres or predominantly in the right one. The results of an ERP study supported this finding: Franklin et al. (2007) suggested that the observed generated left temporal N400 reflected forward processes, whereas the observed generated right parietal gyrus N400 reflected backward associated processes. However, Kandhadai and Federmeier (2010) suggested that both hemispheres were able to strategically enhance the processing of backward words. They showed that the contributions of the right and left hemispheres depended on the nature of the task (active vs. passive task). To the best of our knowledge, the only fMRI study that
45
has investigated forward and backward priming in healthy participants used the co-registered ERP/fMRI method (O’Hare et al., 2008). They showed bilateral activation of right sulcus, left frontal gyrus and cerebellum for forward priming, whereas backward priming occurred in right-hemisphere regions (median frontal gyrus, occipital area and visual cortex). However, as mentioned by the authors, this study has some methodological weaknesses. Indeed, for the asymmetrically related word pairs, authors used compound words (e.g., fruit-fly) and unidirectional related words (e.g., stork-baby). In their view, the use of compound words could create a bias because it was likely that when participants processed a backward association with compounded words (fly-fruit) they visually rearranged the prime and the target to form a compound stimulus (fruit-fly). The aim of this research was to investigate the neural substrates subserving forward and backward semantic priming among healthy participants. We decided to use an event-related fMRI paradigm with mixed related and unrelated prime-target word pairs, manipulating the forward and backward association with asymmetrically related pairs, and not with compound words, to maximize the post-lexical integration process.
Methods Participants Fourteen healthy participants (50% females; mean age = 22.5 were recruited from the department of psychology of the University of Reims Champagne-Ardenne and the University of Reims Hospital. All participants were right-handed according to the Edinburgh Inventory (Oldfield, 1971); they were native speakers of French, had normal or corrected to normal vision, and had no history of reading disabilities. They also had no past or present history of neurological or psychiatric disorders or alcohol/drug abuse or dependence, and were free of medication. All participants conformed to standard health and safety regulations regarding the use of MRI. The experimental design was submitted to the local ethics committee, which approved the study. All participants gave their written informed consent prior to the study.
Stimuli and Design Stimuli consisted of 200 pairs of words: 25 forward pairs of related words, 25 backward pairs of related words, 50 pairs of unrelated words, and 100 pseudo-words. To select the related word pairs, we first administered a free association task to a sample of 390 students at University of Reims. We chose for the backward condition only pairs of words which showed a difference of occurrence of greater than 53.06%, and with a strong relation between word A and word B (between 55.1% and 91.5%) but a weak relation between word B and word A (between 0% and 14.3%) (e.g., word A = sock and word B = shoe). For the forward condition, we picked related word pairs and pseudo-words from a previous study (Besche et al., 1997). Two lists of stimuli were drawn up according to the following rules: (1) the pseudo-words were the same in both lists; (2) each word that was part of a related pair presented in one list was presented in the corresponding unrelated condition in the other list; (3) corresponding pairs in the two lists had the same target word; (4) the unrelated primes had the same number of letters, the same first letter and the same usage frequency in the language as the word in the corresponding list (Database:
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Lexique 3, www.lexique.org). For example, in list 1, a related word pair was chaussure-lacet (shoe-lace) and in list 2 the corresponding unrelated word pair was colonel-lacet (colonellace). Stimuli were presented in a fixed random order. Each trial took place as follows: the fixation point was presented in the center of the screen for 300 ms, followed by a prime word for 200 ms, a mask for 50 ms and the target word for 3500 ms. The next fixation point appeared automatically after an interstimulus interval of 100 ms. The inter-trial interval was 3650 ms (see Figure 1). The fMRI recording was carried out over two runs (each lasting 6 minutes and 8 seconds), with a short break between them. Each run contained 100 trials. All stimuli were presented on a non-magnetic screen viewed by participants via a mirror mounted on the head-coil. Prime words were presented in white characters on a black background whereas targets were presented in pink characters on a black background. E-Prime software (Psychology Software Tools, Pittsburgh, PA) was used for the presentation of stimuli and the recording of reaction times. Responses were made on an MR-compatible response pad. The participants had to press the button with their right index finger if the target word (written in pink) was a real word and with their right middle finger if the target word was a pseudo-word. Only correct answers were considered.
Image Acquisition and Procedure Images were acquired using a 3-Tesla whole-body MRI scanner (Achieva, Philips Medical Systems, Best, The Netherlands) with an 8-channel head coil. Head motions were minimized with a forehead strap and a comfortable padding around the participant’s head. For each participant, a T1-weighted anatomical image oriented parallel to the Brain AC-PC Line was first acquired using a fast field echo sequence (T1-FFE, TR = 252.758 ms; TE = 2.30 ms; flip angle = 80˚; 32 axial slices; slice thickness = 4.50 mm; no gap; FOV = 240 × 144 × 240 mm; matrix = 268 × 214; and acquisition voxel size = 0.43 × 0.43 × 4.5 mm3). Functional data were acquired from an ascending slice 2D-T2*-weighted EPI sequence sensitive to blood-oxygen-level-dependent (BOLD) contrast. This sequence was acquired in the same axial plane as the T1-weighted structural images and had the following parameters: 2D-T2*FFE-EPI; TR = 2000 ms; TE = 33 ms; flip angle = 90˚; 32 axial slices; slice thickness = 4.50 mm; no gap; matrix = 80 × 80; FOV = 240 × 240 mm3; acquisition voxel size = 3 × 3 × 4.5 mm3. The functional volumes were collected during two functional sessions of 184 volumes). Finally, a high resolution
CAT $$$$
+ (fixation point) 300 ms
DOG (prime) 200 ms
Figure 1. Trial procedure.
(mask) 50 ms
(target) 3000 ms
Time
T1-weighted anatomical image was acquired using a 3D turbo field echo sequence (3D-T1-TFE, TR = 8 ms; TE = 3.73 ms; flip angle = 8˚; 160 axial slices; slice thickness = 1 mm; FOV = 240 × 240 mm; matrix = 240 × 240; and acquisition voxel size = 1 × 1 × 1 mm3).
fMRI Analyses The fMRI data were analyzed using Statistical Parametric Mapping (SPM8, Wellcome Department of Cognitive Neurology, Institute of Neurology, London, UK; www.fil.ion.ucl. ac.uk/spm/software/spm8). MRIcro software (www.micro.com) was used for image conversion. Five initial brain volumes of the functional run were discarded from the analyses to eliminate non-equilibrium effects of magnetization. Functional images were spatially realigned to the first volume, slice time corrected, and normalized to the standard space of the Montreal Neurological Institute (MNI) brain. Images with excessive head movements (>2 mm or > 2˚) were excluded from analyses. Spatial smoothing was done with an isotropic three-dimensional Gaussian filter with a full width at half maximum of 8 mm. A high-pass filter was implemented using a cut-off period of 128 seconds to remove low-frequency drift from the time series. For each participant, first-level contrast images were estimated for the following contrasts: forward related vs. forward unrelated, forward unrelated vs. forward related, backward related vs. backward unrelated and backward unrelated vs. backward related. The six movement parameters estimated during the realignment procedure were entered as regressors of non-interest into the model to control for the variance caused by micro-displacements of the head. Then, in order to examine our hypothesis, we used a second-level paired t-test with an extent threshold of 10 voxels and a statistical threshold of P < .001, uncorrected, to explore differences between forward and backward priming activations. We made investigated the following contrasts: forward priming (forward related vs. forward unrelated) vs. backward priming (backward related vs. backward unrelated). The voxel coordinates of activations are reported in the MNI space in Table 1. Labeling was based on the AAL brain atlas (Tzourio-Mazoyer et al., 2002) using WFU PickAtlas (Maldjian, Laurienti, & Burdette, 2004; Maldjian, Laurienti, Kraft, & Burdette, 2003).
Results Behavioral Data Participants’ mean reaction times are presented in Table 1. Two two-way ANOVAs with condition (unrelated/related) and type of relation (forward/backward) as factors were conducted with Statistica 7.1 on reaction times for correct answers for both participants (F1) and items (F2). The rate of correct answers was 98.96 (SD: 0.97). As expected, the analyses revealed a significant condition effect (related vs. unrelated; F1 (1,13) = Table 1. Mean reaction times (SD)(in milliseconds) for lexical decision. Forward
Backward
Related
766 (91.91)
818 (96.80)
Unrelated
832 (124.75)
890 (135.71)
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18.54; p < .001; F2 (1,98) = 23.27; p < .001), a significant effect of type of relation (backward vs. forward; F1 (1,13) = 21.41; p < .001; F2 (1,13) = 11.19; p < .001), and no significant interaction [F1 (1,13) < 1; F2 (1,98) < 1).
fMRI Data The contrast between the forward unrelated condition and the forward related condition revealed significant activations (see Table 2). We observed bilateral activations of the inferior orbital frontal gyrus, the cingulum, and the medial and superior occipital gyrus. In the right hemisphere, we observed active tions of the fusiform gyrus, the cuneus, the cerebellum, the parahippocampalgyrus, the insula, the putamen, the medial occipitotemporalgyrus, and the lingual gyrus. In the left hemisphere we observed an activation of the superior temporal gyrus. The forward related > forward unrelated contrast revealed no significant activation. The contrast between the backward unrelated condition and the backward related condition revealed small activated clusters,
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with the largest having 26 voxels in the right cerebellum. The other two clusters were located in the left cerebellum (10 voxels) and the left medial occipital gyrus (14 voxels). The backward related > backward unrelated contrast revealed no significant activation (see Table 3). The contrast between the forward priming effect and backward priming effect revealed five significant clusters of activations. The largest cluster of activation was located in the left superior temporal gyrus (53 voxels), specifically in Wernicke’s area (see Figure 2(a)). The other clusters were located in the right hemisphere in the temporal sub-gyrus, the medial frontal gyrus and precentralgyrus, the frontal sub-gyrus and the cingulate gyrus, the fronto-parietal gyrus, and the insula and putamen. The opposite subtraction revealed no significant difference. We performed a plot estimation to dissociate the activation and deactivation under forward and backward priming. This analysis in each cluster revealed increased activation in the forward priming condition and deactivation in the backward priming condition (see Figure 2(b) and Table 4).
Table 2. Results of fMRI forward priming effect. Coordinates (MNI)
t-value
Number of voxels
Anatomical regions X
Y
Z
Fusiform gyrus (R)
42
−50
−6
5.89
63
Frontal sub-gyrus-Cingulate gyrus (R)
22
−24
32
5.66
58
Cingulum (R)
20
14
36
4.96
53
Superior temporal gyrus (L)
−50
−6
−6
4.59
40
Superior and middle occipital gyrus-Cuneus (R)
28
−66
28
4.48
40
Inferior orbital frontal gyrus (R)
38
34
−8
4.37
27
Medial occipitotemporalgyrus-Cerebellum-Parahippocampalgyrus-Cuneus (R)
26
−52
4
4.34
209
Insula – Putamen (R)
34
−8
2
4.33
20
Superior occipital gyrus (L)
−26
−88
36
4.13
45
Cingulum (L)
−20
−48
32
4.07
35
Inferior orbital frontal gyrus (L)
−24
32
−12
3.99
12
Cerebellum (R)
10
−46
−18
3.97
12
Medial occipitotemporalgyrus-Cuneus-Lingual gyrus (R)
12
−74
8
3.92
54
Medial occipital gyrus (L)
−40
−82
2
3.92
19
Superior occipital gyrus (R)
22
−82
2
3.89
12
Table 3. Results of fMRI backward priming effect. Coordinates (MNI)
t-value
Number of voxels
Anatomical regions X
Y
Z
Inferior occipital gyrus – Middle temporal gyrus (R)
48
−80
–2
4.41
14
Cerebellum (R)
34
−54
−26
4.18
26
Cerebellum (L)
−30
−54
−26
3.61
10
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Contrast estimate [-50, -14,-2]
1.5 1 0.5 0 -0.5 -1 Forward
Backward
(a)
(b)
Figure 2. Brain activation during forward and backward priming. (a) Activation to the effect of Forward > Backwardconditions displayed on a 1mm isotropic version of the MNI152 (Montreal Neurological Institute) standard brain (threshold: p < .001 uncorrected). (b) Activation in the cluster is illustrated graphically with extracted estimate of BOLD signal change during priming. Table 4. Results of fMRI difference in priming effect. Coordinates (MNI)
t-value
Number of voxels
Anatomical regions X
Y
Z
Superior temporal gyrus (L)
−50
−14
−2
5.39
53
Temporal Sub-gyrus (R)
42
−50
−4
5.34
23
Medial frontal gyrus-Precentralgyrus (R)
6
−18
52
4.83
47
Frontal sub-gyrus-Cingulate gyrus (R)
22
−24
34
4.77
48
Fronto-parietal gyrus (R)
24
−32
50
4.28
24
Putamen-Insula (R)
34
−8
2
4.15
22
Discussion In this research, we studied forward semantic integration and backward semantic integration with an original semantic priming paradigm that had not previously been used in an fMRI study. A similar paradigm was used in an ERP study (Franklin et al., 2007) and in a co-registered ERP/fMRI study (O’Hare et al., 2008). The interesting feature of our study was that it used unilaterally linked words for the backward related pairs to maximize the post-lexical integration process in this condition. Behavioral analysis showed a significant priming effect in both forward and backward conditions, with no significant interaction. Franklin et al. (2007) did not mention any difference between backward and forward priming. These behavioral results suggest there is no difference in spreading activation between pre- and post-lexical processes. However, the functional results showed different patterns of activation in the forward and backward conditions.
Forward Priming The activation contrast between the forward unrelated and forward related conditions highlighted several cerebral areas
but we can consolidate some of them. Some of the brain regions activated were not predicted but were understandable given their role in certain cognitive functions. According to Pulvermüller (2012), different brain regions not necessarily directly involved in language interact in the treatment of the meaning of words in the human mind. First of all, we saw activation of the occipital regions: bilateral superior gyrus, medial occipital gyrus and cuneus. Activation of the superior gyrus and medial occipital gyrus bilaterally had been found in another semantic priming study (Rossel et al., 2003). It may be explained by the fact that during presentation of a target word that is unrelated to the prime, participants may need more time for lexical decision-making reflecting a more complex cognitive process than in the related condition. It is possible that this lexico-semantic processing requires more involvement of visual areas to recognize orthographic patterns. And the cuneus is a brain region of the striatal cortex, which projects visual information to the extrastriatal cortex and is implicated in pattern recognition and visual attention. In our study, we found activation in two brain regions that had been identified as being mainly involved in semantic priming: the ACC and the LIPC, located in the medial orbital frontal gyrus (Copland et al., 2003; Matsumoto et al., 2005). Reduced
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activation of the right ACC in the related condition reveals a high level of perceptual abstraction during the presentation of unrelated words because these cerebral regions play a role in the representation of perceptual artifacts and living creatures (Gainotti, 2006). This reduction in activation is consistent with other studies (Copland et al., 2003; Matsumoto et al., 2005; Mummery et al., 1999; Rossel et al., 2001) and can be explained by the ACC’s role in the inhibition of incorrect answers in decision-making (Rossel et al., 2001). Indeed, in the forward unrelated condition, the presentation of the target leads to incorrect EG, which must be inhibited by the participant. The activation in the LIPC during the unrelated condition reflects its involvement in semantic processing: its role is to select and retrieve the correct representation in semantic memory when the right information is not accessible through an existing association (Copland et al., 2003). If the prime and the target are related, it might appear that the subject does not need to select the correct answer or create a new association in memory. However, in the unrelated condition, the association does not exist, so subjects need to search for associations in semantic memory, which calls upon the LIPC. The activation of the posterior cingulate cortex in the unrelated condition can be explained by its role in the visuospatial processing of stimuli, similarly to the implication of the occipital regions. The fusiform gyrus is normally known for its involvement in face recognition, but we also know that it is necessary for the recognition of complex shapes (Simon, Koutstaal, Pince, Wagner, &Schacter, 2003). Reduced activation in this region during related pair processing shows again that word recognition is facilitated when the prime and the target are connected. Indeed, in the unrelated condition, participants must make an effort to understand and integrate the word presented, whereas in the related condition it is the process of semantic priming that allows recognition of the word, without going through a word decoding phase. This decrease of activation in Wernicke’s area when identifying the target as a word in the related condition may be explained by the fact that in this condition the participant does not have to implement processing involving understanding or semantic memory because the semantic priming effect facilitates the answer. The activation of the lingual gyrus in the unrelated condition prompts a similar conclusion: subjects mobilize the cerebral zones responsible for word recognition. Activation of the right cerebellum in the unrelated condition may be explained by the plausible implication of the posterolateral region of this cerebral structure in associative relations (Gebhart, Petersen, & Thach, 2002). Moreover, this region seems to be involved in the generation of correct predictions concerning the relation between two stimuli in multiple processes (Bellebaum & Daum, 2011; Timmann et al., 2010). A transcranial magnetic stimulation study showed that stimulation of the cerebellum improves lexical associative priming (Argyropoulos, 2011). So it is possible that this region is more solicited in a condition where no semantic relation exists between two stimuli and the participant fails to find a semantic matching association. As Sabb, Bilder, Chou, and Bookheimer (2007) observed in an fMRI study, the insula is activated during indirect priming, reflecting the role of this structure in working memory and attention. Another interesting study highlights this brain region’s involvement in a search for semantic alternatives (Ketteler, Kastrau, Vohn, & Huber, 2008), which may be illustrated here in the failed semantic matching between the prime
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and the target in the unrelated condition. The ventral occipitotemporal gyrus, and more specifically the extrastriatal cortex, is involved in visual word recognition and a lesion there causes repetition in the reading process (Behrmann, Nelson, & Sekuler, 1998; Philipose et al., 2007; Starrfelt, Habekost, & Leff, 2009); this might explain the activation of this region in our study. Sass, Krach, Sachs, and Kircher (2009) also found activation of the right putamen in this experimental condition. Daselaar et al. (2001) demonstrated the role of the medial temporal lobe in semantic retrieval thanks to activation of the right parahippocampal region, which might explain the activation of this region in the “unrelated” condition, in which participants had to recognize a word without help from semantic priming. Several clusters of activation identified in our study are brain areas that the Rossel et al. (2001) study identified as responsible for decision-making without lexical priming effects, such as the lingual gyrus, the fusiform gyrus, and Wernicke’s area.
Backward Priming The literature about the locus of activation of backward priming is neither abundant nor unanimous. An ERP study (Franklin et al., 2007) conducted with the divided visual field presentation (Koivisto et al., 1998) and an fMRI study (O’Hare et al., 2008) agreed that activation was localized in the right hemisphere during post-lexical processing. On the other hand, Kandhadai and Federmeier (2010) suggested that hemispheric lateralization was due not to the type of lexical processing (forward vs. backward) but to the nature of the task (passive vs. active). In our study, we found three clusters of activation, two of which were located in the right hemisphere. The activation of the right inferior occipital gyrus and the middle temporal gyrus in the same cluster reflects the activation of the associative visual cortex, which allows for pattern recognition. Activation in the right occipital area was also noted by Franklin et al. (2007). The involvement of these occipital and temporal regions might be explained by the process of orthographic word recognition, but this suggestion is speculative. Bilateral cerebellar activations are found in many functional imaging studies and lesion case studies report cerebellar involvement in language (Gordon, 1996; Leiner, Leiner, & Dow, 1993; Marien, Engelborghs, & De Deyn, 2001; Schmahmann & Pandya, 1997). It is not clear whether this activation is specific to backward priming. That is why we choose to contrast forward priming activations and backward priming activations to see the real difference in activation between these two priming conditions.
Forward Priming > Backward Priming Five clusters of activations appeared when we contrasted forward priming and backward priming. These regions should represent areas responsible for pre-lexical priming. The activations were essentially located in temporal and frontal regions. The activation in the left superior temporal gyrus (Wernicke’s area) shows that pre-lexical processing uses that classical language area. Other cerebral regions involved are known to subserve word recognition, such as the middle cingulate gyrus, which is responsible for the deletion of irrelevant information and decision-making, and the medial frontal and precentralgyri and particularly the posterior cingulate cortex, which performs evaluative functions. Right insula activation has been found in the locus of activation responsible for the priming process in
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Rossel et al.’s (2001) fMRI research, while Sass et al. (2009) find activation in the putamen. The activation in the right frontal sub-gyrus can be explained by its connection with the insula, which is also activated in this contrast. Moreover, this structure is the only part of the frontal lobe with a link to the insula (Catani et al., 2012), so this finding may reflect the spreading of activation between these two structures during the lexical decision task. It should be noted that the central sub-gyrus is a structure that straddles several lobes and can be considered as an extension of the somato-sensory primary cortex. So, the activation in the right temporal sub-gyrus is certainly linked to that in the frontal sub-gyrus and insula. Activation of the premotor cortex does not appear to be specifically related to pre-lexical semantic priming but most likely relates to the participant’s motor response. The most interesting result of this study is that all clusters in which we find activation for the forward > backward priming contrast manifested activation in the forward condition and deactivation in the backward condition. This means that there is a real difference in the processes involved in pre- and postlexical semantic priming. Indeed, areas responsible for language and for decoding spelling (fusiform gyrus) seem to be not involved in the backward process. The reduction in BOLD response in the temporal and frontal regions when the related condition is compared to the unrelated condition reflects a decrease in the neuronal activity necessary to recognize words. Indeed, lexical decisions are easier and faster in the related condition because the presentation of the prime decreases the amount of activation required to recognize the related target word. This process involved is ASA (Stowe et al., 1999). Copland et al. (2003) speculated that this decrease in neuronal activity was the consequence of better post-lexical integration. In their view, the temporal resolution of fMRI cannot validate this hypothesis. However, in our study we manipulated the verbal material to make a difference between pre- and post-lexical processes, and the observations of Copland et al. seemed to be consistent with our results. The finding in our study of the deactivation of the BOLD response in the temporal and frontal areas in the backward condition is consistent with speculation by Copland et al. that post-lexical processing is necessary in the backward priming condition. In summary, contrasts between experimental conditions show activation only during the subtraction of the related condition from the unrelated condition. No cerebral region is specific to semantic priming but most are involved in language processing (left temporal gyrus), decision-making (LIPC), pattern recognition (fusiform gyrus and occipital regions), and generation of correct predictions regarding the relation between two stimuli (cerebellum). Indeed, these cerebral areas are responsible for different cognitive processes that may be called upon during lexical decision-making when the prime and the target are not related (Copland et al., 2003; Mummery et al., 1999; Rossel et al., 2001). In this condition, the participant has to make an effort to understand and integrate the presented word, while in the related condition the presentation of the prime facilitates the recognition of the target word. Thus, the recognition process is easier and does not require a complex cognitive process. Another interesting finding of this research is the deactivation of the BOLD response in temporal and frontal areas, which may reflect post-lexical integration. A limitation on our study is that prime-target pairs for the forward condition are not asymmetrical; consequently, we in-
Psychology Handbook
tend to carry out a new experiment with only asymmetrical pairs to make the backward and forward condition material more uniform. We plan to adapt this experiment to event-related brain potentials to better explore the temporality of backward and forward processes.
REFERENCES Argyropoulos, G. (2011). Cerebellar theta-burst stimulation selectively enhances lexical associative priming. Cerebellum, 10, 540-550. Behrmann, M., Nelson, J. J., & Sekuler, E. B. (1998). Visual complexity in letter-by-letter reading: “Pure” alexia is not pure. Neuropsychologia, 36, 1115-1132. Bellebaum, C., & Daum, I. (2011). Mechanisms of cerebellar involvement in associative learning. Cortex, 47, 128-136. Besche, C., Passerieux, C., Segui, J., Sarfati, Y., Laurent, J. P., & Hardy-Baylé, M. C. (1997). Syntactic and semantic processing in schizophrenic patients evaluated by lexical-decision tasks. Neuropsychology, 4, 498-505. Blumstein, S. E., Milberg, W., & Shrier, R. (1982). Semantic processing in aphasia: Evidence from an auditory lexical decision task. Brain and Language, 17, 301-315. Catani, M., Dell’Acqua, F., Vergani, F., Malik, F., Hodge, H., Roy, P., et al. (2012). Short frontal lobe connections of the human brain. Cortex, 48, 273-291. Chwilla, D. J., Hagoort, P., & Brown, C. M. (1998). The mechanism underlying backward priming in a lexical decision task: Spreading activation versus semantic matching. The Quarterly Journal of Experimental Psychology A: Human Experimental Psychology, 51A, 531-560. Copland, D. A., de Zubicaray, G. I., McMahon, K., Wilson, S. J., Eastburn, M., & Chenery, H. J. (2003). Brain activity during automatic semantic priming revealed by event-related functional magnetic resonance imaging. NeuroImage, 20, 302-310. Daselaar, S., Rombouts, S., Veltman, D., Raaijmakers, J., Lazeron, R., & Jonker, C. (2001). Parahippocampal activation during successful recognition of words: A self-paced event-related fMRI study. NeuroImage, 13, 1113-1120. Franklin, M. S., Dien, J., Neely, H. N., Huber, E., & Waterson, L. D. (2007). Semantic priming modulates the N400, N300, and N400RP. Clinical Neurophysiology, 118, 1053-1068. Gainotti, G. (2006). Anatomical functional and cognitive determinants of semantic memory disorders. Neuroscience and Biobehavioral Reviews, 30, 577-594. Gebhart, A. L., Petersen, S. E., & Thach, W. T. (2002). Role of the posterolateral cerebellum in language. In S. M. Highstein, & W. Thach (Eds.), The cerebellum: Recent developments in cerebellar research (pp. 318-333). New York: New York Academy of Sciences. Gordon, N. (1996). Speech, language, and the cerebellum. European Journal of Disorders of Communication, 31, 359-367. Hagoort, P. (1993). Impairments of lexical-semantic processing in aphasia: Evidence from the processing of lexical ambiguities. Brain and Language, 45, 189-232. Hagoort, P. (1997). Semantic priming in Broca’s aphasics at a short SOA: No support for an automatic access deficit. Brain and Language, 56, 287-300. Henik, A., Dronkers, N. F., & Knight, R. T. (1993). Differential effects of semantic and identity priming in patients with left and right hemisphere lesions. Journal of Cognition and Neuroscience, 5, 45-55.
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Kahan, T. A., Neely, J. H., & Forsythe, W. J. (1999). Dissociated backward priming effects in lexical decision and pronunciation tasks. Psychonomic Bulletin and Review, 6, 105-110. Kandhadai, P., & Federmeier, K. D. (2010). Automatic and controlled aspects of lexical associative processing in the two cerebral hemispheres. Psychophysiology, 47, 774-785. Ketteler, D., Kastrau, F., Vohn, R., & Huber, W. (2008). The subcortical role of language processing. High level linguistic features such as ambiguity-resolution and the human brain: An fMRI study. NeuroImage, 39, 2002-2009. Koivisto, M. (1998). Backward priming and postlexical processing in the right hemisphere. Laterality, 3, 21-40. Koriat, A. (1981). Semantic facilitation in lexical decision as a function of prime-target association. Memory and Cognition, 9, 587-598. Leiner, H. C., Leiner, A. L., & Dow, R. S. (1993). Cognitive and language functions of the human cerebellum. Trends in Neurosciences, 16, 444-447. Maldjian, J. A., Laurienti, P. J., & Burdette, J. H. (2004). Precentralgyrus discrepancy in electronic versions of the Talairach atlas. NeuroImage, 21, 450-455. Maldjian, J. A., Laurienti, P. J., Kraft, R. A., & Burdette, J. H. (2003). An automated method for neuroanatomic and cytoarchitectonic atlasbased interrogation of fMRI data sets. NeuroImage, 19, 1233-1239. Marien, P., Engelborghs, S., & De Deyn, P. (2001). Cerebellar neuroncognition: A new avenue. ActaNeurologicaBelgica, 101, 96-109. Matsumoto, A., Iidaka, T., Haneda, K., Okada, T., & Sadato, N. (2005). Linking semantic priming effect in functional MRI and event-related potentials. NeuroImage, 24, 624-634. Meyer, D. E., & Schvaneveldt, R. W. (1971). Facilitation in recognizing pairs of words: Evidence of a dependence between retrieval operations. Journal of Experimental Psychology, 90, 227-234. Milberg, W., Blumstein, S. E., Katz, D., Gershberg, F., & Brown, T. (1995). Semantic facilitation in aphasia: Effects of time and expectancy. Journal of Cognition and Neuroscience, 7, 33-50. Mummery, C. J., Shallice, T., & Price, C. J. (1999). Dual-process model in semantic priming: A functional imaging perspective. NeuroImage, 9, 516-525. Neely, J. H. (1991). Semantic priming effects in visual word recognition: A selective review of current findings and theories. In D. Besner, & G. W. Humphreys (Eds.), Basic processes in reading: Visual word recognition (pp. 264-336). Hillsdale, NJ: Lawrence Erlbaum Associates, Inc. Neely, J. H., Keefe, D. E., & Ross, K. L. (1989). Semantic priming in the lexical decision task: Roles of prospective prime-generated expectancies and retrospective semantic matching. Journal of Experimental Psychology: Learning, Memory, and Cognition, 15, 10031019. Nobre, A. C., Allison, T., & McCarthy, G. J. (1994).Word recognition in the human inferior temporal lobe. Nature, 372, 260-273.
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Nobre, A. C., & McCarthy, G. J. (1995). Language-related field potentials in the anterior- medial temporal lobe: II. Effects of word type and semantic priming. Journal of Neuroscience, 15, 1090-2008. O’Hare, A. J., Dien, J., Waterson, L. D., & Savage, C. R. (2008). Activation of the posterior cingulate by semantic priming: A co-Registered ERP/fMRI study. Brain Research, 1189, 97-114. Oldfield, R. C. (1971). The assessment and analysis of handedness: The Edinburgh inventory. Neuropsychologia, 9, 97-114. Philipose, L. E., Gottesman, R. F., Newhart, M., Kleinman, J. T., Herskovits, E. H., Pawlak, M. A., et al. (2007). Neural regions essential for reading and spelling of words and pseudowords. Annals of Neurology, 62, 481-492. Pulvermüller, F. (2012). Meaning and the brain: The neurosemantics of referential, interactive, and combinatorial knowledge. Journal of Neurolinguistics, 25, 423-459. Rossel, S. L., Bullmore, E. T., Williams, S. C. R., & David, A. S. (2001). Brain activation during automatic and controlled processing of semantic relations: A priming experiment using lexical-decision. Neuropsychologia, 39, 1167-1176. Sabb, F. W., Bilder, R. M., Chou, M., & Bookheimer, S. Y. (2007). Working memory effects on semantic processing: Priming differences in pars orbitalis. NeuroImage, 37, 311-322. Sass, K., Krach, S., Sachs, O., & Kircher, T. (2009). Lion-tiger-stripes: Neural correlates of indirect semantic priming across processing modalities. NeuroImage, 45, 224-236. Schmahmann, J. D., & Pandya, D. N. (1997). The cerebrocerebellar system. International Review of Neurobiology, 41, 31-60. Simon, J. S., Koutstaal, W., Pince, S., Wagner, A. D., & Schacter, D. L. (2003). Neural mechanisms of visual object priming: Evidence for perceptual and semantic distinctions in fusiform cortex. NeuroImage, 19, 613-626. Starrfelt, R., Habekost, T., & Leff, A. (2009). Too little, too late: Reduced visual span and speed characterize pure alexia. Cerebral Cortex, 19, 2880-2890. Stowe, L. A., Paans, A. M., Wijers, A. A., Zwarts, F., Mulder, G., & Vaalburg, W. (1999). Sentence comprehension and word repetition: A positron emission tomography investigation. Psychophysiology, 36, 786-801. Timmann, D., Drepper, J., Frings, M., Maschke, M., Richter, S., Gerwig, M., et al. (2010). The human cerebellum contributes to motor, emotional and cognitive associative learning: A review. Cortex, 46, 845-857. Tzourio-Mazoyer, N. N., Landeau, B. B., Papathanassiou, D. D., Crivello, F. F., Etard, O. O., Delcroix, N. N., et al. (2002). Automated anatomical labeling of activations in SPM using a macroscopic anatomical parcellation of the MNI MRI single-subject brain. NeuroImage, 15, 273. Wagner, A. D., Paré-Blagoev, E. J., Clark, J., & Poldrack, R. A. (2001). Recovering meaning: Left prefrontal cortex guides controlled semantic retrieval. Neuron, 2, 329-338.
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9 Socio-Emotional Status, Education, and Time-Discounting in Japanese Non-Smoking Population: A Multi-Generational Study Shoko Yamane1, Taiki Takahashi2, Akiko Kamesaka3, Yoshiro Tsutsui4, Fumio Ohtake5 2
1 Faculty of Economics, Kinki University, Osaka, Japan Department of Behavioral Science, Center for Experimental Research in Social Sciences, Hokkaido University, Hokkaido, Japan 3 School of Business Administration, Aoyama Gakuin University, Tokyo, Japan 4 Graduate School of Economics, Osaka University, Osaka, Japan 5 Institute of Social and Economic Research, Osaka University, Osaka, Japan
Recent studies in behavioral economics and neuroeconomics have revealed that emotion affects impulsivity in intertemporal choice. We examined the roles of socio-emotional status (i.e., perceived stress, depression, quality of sleep, loneliness) in temporal discounting behavior by Japanese non-smokers in a generation-specific manner (20 - 70 s) with a relatively large sample size (N = 3450). We observed that 1) both men and women are the most impulsive in their 60 s; 2) education has a negative impact on impulsivity in men aged 40 - 49 and women aged 50 - 59; 3) perceived stress has a negative impact on impulsivity in men aged 60 - 69; and 4) sleeplessness has negative and positive impacts on impulsivity in men aged 40 - 49 and women aged 30 - 39, respectively. Biological and social factors underlying observed findings are discussed. Keywords: Time Discounting; Impulsivity; Stress; Depression; Emotion; Behavioral Economics
Introduction Because temporal discounting behavior (intertemporal choice; preference for smaller sooner rewards over larger later ones) influences one’s decisions, economists and neuroeconomists have shown tremendous interest in investigations into temporal discounting (Frederick, Loewenstein, & O’Donoghue, 2002; Takahashi, 2009). Recently, roles of affect in temporal discounting behavior have been drawing much attention in behavioral economics and neuroeconomics (Ifcher & Zarghamee, 2011; Löckenhoff, O’Donoghue, & Dunning, 2011; McClure, Laibson, Loewenstein, & Cohen, 2004). Specifically, Ifcher and Zarghamee (2011) demonstrated that mild positive affect significantly reduced impulsivity in intertemporal choice. Löckenhoff et al. (2011) reported that non-emotional intertemporal choice is reduced by age; while emotional intertemporal choice is insensitive to age. However, these studies examined only positive and/or disruptive (i.e., “visceral”; Loewenstein, 1996) emotions’ effect on intertemporal choice.
Emotion and Intertemporal Choice In the rapidly evolving field of neuroeconomics (Ernst, 2012; Loewenstein, Rick, & Cohen, 2008; Phillips, Kim, & Lee, 2012; Takahashi, 2009), effects of stress and depression on intertermporal choice have been examined (Takahashi, 2004; Takahashi et al., 2008a; Takahashi, Shinada, Inukai, Tanida, Takahashi, Mifune, Takagish, Horita, Hashimoto, Yokota, Kameda, & Yamagishi, 2010), in relation to altered functioning of the stress system (i.e., Hypothalamic-pituitary-adrenal (HPA) axis and sympatho-adrenal medullar (SAM) system) and catecholamine/monoamine (dopaminergic and serotonergic) systems.
Takahashi and colleagues have previously observed that depressed patients are impulsive in the near future (Takahashi et al., 2008), and low cortisol (a human stress steroid hormone) levels were associated with impulsive intertemporal choice by men (Takahashi, 2004), salivary alpha-amylase (a non-invasive biomarker of SAM activation) is negatively related to impulsivity in both men and women (Takahashi et al., 2010). Also, a reduction in serotonergic activities increases impulsivity in intertemporal choice (Schweighofer, Bertin, Shishida, Okamoto, Tanaka, Yamawaki, & Doya, 2008). These findings indicate that negative affect, as well as positive affect, influences temporal discounting behavior. However, to date, no study examined the roles of negative affect (especially, social emotions) in intertemporal choice in a large sample. Concerning social emotions, a recent neuroendocrinological study observed that loneliness increased impulsivity via biological pathways distinct from the signaling pathways in which testosterone affects impulsivity (Fujisawa, Nishitani, Ishii, & Shinohara, 2011). Also, recent studies in health economics asked effect of loneliness on health and cognitive functioning in relation to retirement from labor markets (Coe & Zamarro, 2011; Bonsang, Adam, & Perelman, 2012). Therefore, it may have implications for both labor and health economics to investigate the role of loneliness in impulsivity in intertemporal choice.
Age and Intertemporal Choice In addition to the roles of affect in intertemporal choice, the effect of age on intertemporal choice has been studied (Green, Fry, & Myerson, 1994; Read & Read, 2004; Loeckenhoff, 2011; Steinberg, Graham, O’Brien, Woolard, Cauffman, & Banish,
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Socio-Emotional Status, Education, and Time-Discounting in Japanese Non-Smoking Population: A Multi-Generational Study
2009). Green et al., (1994) reported that temporal discounting was highest for children and lowest for older adults; in contrast, Read and Read (2004) observed that older people discount more than younger people and that middle aged people discount less than either group. Apparently, more studies with a large sample size regarding the relationship between age and temporal discounting are needed.
Education and Intertemporal Choice Education may lower endogenous time-discount rate, because economists Becker and Mulligan (1997) argue that education can be understood as an investment in patience. Education can be understood as a tool that helps people to perceive future pleasures as less remote. In neuroeconomics, Berns, Laibson, and Loewenstein (2007) have emphasized the role of anticipation of future events in making choices whose consequences play out over time. Also, Peters and Büchel (2010) demonstrated that episodic future thinking reduces impulsivity in intertemporal choice, via cognitive function-related brain regions. Kirby, Winston, and Santiesteban (2005) reported that high grades in the college student are associated with patience in intertemporal choice (lowered time-discount rate). Because education systems differ across countries and generations, it is important to examine the relationship between education and temporal discounting in Japan with multiple-generations. Some studies in labor economics have examined the roles of sex in economic decision (Fehr-Duda, De Gennaro, & Schubert, 2006; Kimmo & Brent, 2010) because there are large differences not only in the relative compensation, but also in the presence of women in the highest paid jobs (e.g., Azmat, Güell, & Manning, 2004; Arulampalam, Booth, & Bryan, 2007). Because the movement of women into the Japanese society has changed in several decades, it may be interesting to see the relationship between intertemporal choice and sex over generations.
Sleep and Intertemporal Choice In both behavioral economics and neuroeconomics, effect of sleep deprivation on economic decision-making has been attracting attention, because effect of sleep deprivation on impulsivity is important in considering workplace safety (Acheson, Richards, & de Wit, 2007; Reynolds & Schiffbauer, 2004a; Venkatraman, Huettel, Chuah, Payne, & Chee, 2011). Reynolds and Schiffbauer (2004b) reported that sleep deprivation increased impulsivity in intertemporal choice. Menz, Büchel, and Peter (2012) demonstrated that sleep deprivation altered neural processing underlying decision under risk. It is therefore important to examine the effect of sleeplessness on intertemporal choice in large samples.
come inequality over generations, pension problems). In the investigations into the relationships between Socio-emotional status, education, and time-discounting, it is important to exclude the habitual smokers, because chronic nicotine intake is associated with an increase in impulsivity in intertemporal choice for gain in Japanese people (Ohmura, Takahashi, & Kitamura, 2005). Overall, the present study examined the relationships of various types of socio-demographic variables to impulsivity in intertemporal choice in non-smokers. This study is the first to examine this in a large sample. It is expected that relationships between the variables and impulsivity in intertemporal choice may vary across generations.
Methods Data Our data were obtained from “Survey of Living Preferences and Satisfaction” conducted by the 21st Century COE program of Osaka University in February 2011. This survey consists of 100 questions about detailed data on individual attributes. 5386 Japanese men and women between the ages of 20 and 65 were chosen by two-stage sampling and surveyed by the visit-replacement method.
Assessment of Time-Discount Rate The key variable, time discounting, is obtained by following procedure. The respondents were told to choose between two options, “A” and “B”. The respondent receives JPY 10,000 (around USD 120) today when he chooses option “A”, while he receives a different amount in seven days when he chooses option “B”1. This question consists of nine choices. For example in sixth choice, the respondents compare JPY 10,000 today to JPY 10,383 (around USD 125) in seven days. In this case, choosing option “B” instead of option “A” is the same as receiving 200% of the annual interest rate. The questionnaire is presented in Table 1, where the amount received under option “A” is specified as JPY 10,000 and the imputed interest rate for option “B” changes from −10% to 5000%. Table 1. Questionnaire to elicit time-discount rate. Suppose you have two mutually-exclusive options to receive some money. You may choose Option “A”, to receive 10,000 JPY in two days; or Option “B”, to receive a different amount in nine days. Compare the amounts and delay until its receipt in Option “A” with Option “B” and indicate which option you would prefer for each pair of all nine choice pairs. Option A (Receipt in Today)
Intertemporal Choice and Field Behavior With respect to the relationships between impulsivity in intertemporal choice and field behavior, a recent behavioral economic study (Chabris, Laibson, Morris, Schuldt, & Taubinsky, 2008) demonstrated that time-discount rate measured in the laboratory could predict various types of field behaviors (e.g., exercise, BMI, smoking). Hence, it can be said that assessment of time-discount rates in multi-generational Japanese population may be important for a better understanding of Japanese economic situations (e.g., gender gap in the labor market, in-
1
Option B Interest rate (Receipt in 7 days) (Annual)
Circle A or B
JPY 10,000
JPY 9980
−10%
A
B
JPY 10,000 JPY 10,000
JPY 10,000 JPY 10,029
0% 10%
A A
B B
JPY 10,000 JPY 10,000
JPY 10,076 JPY 10,191
40% 100%
A A
B B
JPY 10,000
JPY 10,383
200%
A
B
JPY 10,000
JPY 10,575
300%
A
B
JPY 10,000
JPY 11,917
1000%
A
B
JPY 10,000
JPY 195,689
5000%
A
B
The exchange rate was about $1 = ¥83 at February 2011.
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Table 2. Number of subjects by generation. Male 64 152 269 325 363 162 1335
Female 113 287 495 499 525 196 2115
Total 177 439 764 824 888 358 3450
log gross time discount rate
1
Generations 20 - 29 30 - 39 40 - 49 50 - 59 60 - 69 70 - 79 Total
0
Assessment of Education
.1 .2 .3 .4 .5 .6 .7 .8 .9
The authors expected that the respondents would choose option “A” at low interest rates, but as the imputed interest rate rises, the authors expected they would ultimately switch to option “B” at a certain critical high rate. The individual respondents’ discount rates can be inferred by estimating the interest rate at which respondents are indifferent between the delayed receipt of option “B” and the more immediate receipt of option “A”. The present study employed the procedures of measurement and analysis of time-discount rate similar to the authors’ previous study (Ikeda, Kang, & Ohtake, 2010; Kimball, Sahm, & Shapiro, 2008). The authors estimated the gross discount rate for each respondent according to a lognormal distribution function. This estimation enables us to obtain the interest rates between which he switched his choice from option “A” to “B”. for each respondent, including those who stuck to option “A” or “B”. It is to be noted that the authors utilized logged gross time-discount rate as a dependent variable, following our previous study.
Assessment of Drinking The authors obtain the drinking habit of the respondents using answers to the question “Do you drink alcoholic beverages?”. It was measured by six point ordinal scale, such as 1) if “Don’t drink at all” (N = 1287), 2) if “Hardly drink” (N = 1240), 3) if “Drink sometimes” (N = 1385), 4) if “A can of beer or its equivalent a day, everyday” (N = 828), 5) if “Three cans of beer or its equivalent a day, everyday” (N = 550), and 6) if “Five cans of beer or its equivalent a day, everyday” (N = 79).
Results Time-Discount Rate across Generations The samples sizes for different age groups (“generations”) are presented in Table 2. Time-discount rate (logged gross time-discount rate) over generations of men and women are presented in Figures 1(a) and (b), respectively. Correlations between time-discount rate and other variables are presented in Tables 3(a)-(l), by generations. Though not tested statistically,
40
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70
generation
1
(a)
log gross time discount rate
The socio-emotional status are obtained, with Likert scales, by the degree of agreement for the following sentences; “I’ve been feeling stressed lately”, “I’ve been feeling depressed lately”, “I’ve been feeling lonely lately”, and “I haven’t been sleeping well lately”. Each response was on five point scale from 1 (I totally disagree to it) to 5 (I totally agree to it). That is, the high score means that he perceives stress more.
30
.1 .2 .3 .4 .5 .6 .7 .8 .9
Assessment of Socio-Emotional Status and Sleeplessness
20
0
The authors assessed the respondents’ education level by four categories. The variable of education takes 1) if the respondent graduated primary or middle school (N = 539); 2) if graduated high school or two-year college (including those who left college without a diploma; N = 3417); 3) if graduated fouryear college (including those who left graduate school without master degree; N = 1225); and 4) if graduated higher than master’s course (N = 102).
20
30
40
50
generation
(b)
Figure 1. (a) Time-discount rate of men; (b) Time-discount rate of women.
the readers can see that men and women had highest time-discount rate in their sixties (Figures 1(a) and (b)). Furthermore, men generally had higher time-discount rate than women within all generations.
Education and Time-Discount Rate First, the authors examine the relationship between timediscount rate and education. It was observed significant negative correlations between education level and time-discounting of men aged 40 - 49 (Table 3(c)) and women aged 50 - 59 (Table 3(j)). Although the correlations between education level and time-discount rate were not always significant, the direction of the effect of education level on time-discounting were mostly negative, consistent with previous studies indicating that more educated people are more patient in intertemporal choice (Kirby et al., 2005). It is to be noted that this effect of education level on time-discount rate is not because more educated people smoke less. The present subjects were all non-smokers.
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55
Socio-Emotional Status, Education, and Time-Discounting in Japanese Non-Smoking Population: A Multi-Generational Study
Table 3. (a) Men aged 20 - 29 (N = 64); (b) Men aged 30 - 39 (N = 152); (c) Men aged 40 - 49 (N = 269); (d) Men aged 50 - 59 (N = 325); (e) Men aged 60 69 (N = 363); (f) Men aged 70 - 79 (N = 162); (g) Women aged 20 - 29 (N = 113); (h) Women aged 30 - 39 (N = 287); (i) Women aged 40 - 49 (N = 495); (j) Women aged 50 - 59 (N = 499); (k) Women aged 60 - 69 (N = 525); (l) Women aged 70 - 79 (N = 196). (a) Time discounting
Drinking
Education
Stress
Depression
Sleeplessness
Loneliness
Time discounting Drinking
−.037
1
Education
−.054
.100
1
Stress
−.047
.079
.039
1
Depress
.062
−.038
−.052***
.545
1
Sleepless
.074
−.105
−.062***
.301***
.348
1
Loneliness
−.119
−.073
.075***
.451***
.678
.241
1
Stress
Depression
Sleeplessness
Loneliness
1
(b) Time discounting
Drinking
Education
Time discounting Drinking
−.122
1
Education
−.153
−.024
1
Stress
−.005
.076
−.077
1
Depress
.041
.035
−.024***
.645
1
Sleepless
−.071
−.028*
−.137***
.345***
.496
1
Loneliness
.035
−.015
−.036***
.358***
.571***
.445
1
Stress
Depression
Sleeplessness
Loneliness
1
(c) Time discounting
Drinking
Education
Time discounting Drinking
.015
1
Education
−.207***
.151
1
Stress
.007
.052
−.021
1
Depress
.044
−.055
−.006***
.635
1
Sleepless
−.014***
−.19
−.065***
.337***
.461
1
Loneliness
−.009
−.128
−.030***
.413***
.535***
.432
1
Stress
Depression
Sleeplessness
Loneliness
1
(d) Time discounting
Drinking
Education
Time discounting Drinking
.011
1
Education
−.069
.021
1
Stress
−.087
−.021
−.064
1
Depress
−.035
.013
−.081***
.703
1
Sleepless
.026
−.020
−.118***
.437***
.582
1
Loneliness
−.024
−.004
−.067***
.439***
.625***
.567
1
Stress
Depression
Sleeplessness
Loneliness
1
(e) Time discounting
Drinking
Education
Time discounting Drinking
.005
1
Education
.014
.006
1
Stress
−.096*
−.092
−.026
1
Depress
−.019
−.072
−.027***
.684
1
Sleepless
.011
.026
.005***
.334***
.450
1
Loneliness
.045
−.040
−.017***
.385***
.564***
.477
1
1
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56
Psychology Handbook
(f) Time discounting
Drinking
Education
Stress
Depression
Sleeplessness
Loneliness
Time discounting Drinking
−.134
1
Education
−.023
−.079
1
Stress
−.052
−.099
.031
1
Depress
.032
−.164
−.086***
.648
1
Sleepless
.060
−.160
−.115***
.391***
.460
1
Loneliness
.063
−.084*
−.126***
.549***
.669***
.421
1
Stress
Depression
Sleeplessness
Loneliness
1
(g) Time discounting
Drinking
Time discounting Drinking
−.118
1
Education
−.106
.003
Education
1
1
Stress
−.127
.014
.085
1
Depress
−.114
.117
.117***
.665
1
Sleepless
−.015
.054
−.044***
.520***
.551
1
Loneliness
.017
.067*
.147***
.380***
.535***
.286
1
Stress
Depression
Sleeplessness
Loneliness
(h) Time discounting
Drinking
Education
Time discounting Drinking
.005
1
Education
−.058
−.015
1
Stress
.027
−.05
.009
1
Depress
.044
−.07
−.091***
.687
1
Sleepless
.076*
−.099
−.076***
.417***
.561
1
Loneliness
.030
−.013
−.057***
.414***
.586***
.483
1
Stress
Depression
Sleeplessness
Loneliness
1
(i) Time discounting
Drinking
Time discounting Drinking
.001
1
Education
−.054
.034
Education
1
1
***
Stress
.037
.035
−.113
1
Depress
.019
.040***
−.123***
.692
1
Sleepless
−.034
.017
−.099***
.342***
.470
−.008
*
***
***
Loneliness
.042
−.077
.368
.531
***
1 .496
1
Sleeplessness
Loneliness
(j) Time discounting Time discounting Drinking Education Stress
Drinking
Education
Stress
Depression
1 −.046 −.064
***
−.072
1 .128
1
.016
−.032 *
***
1
Depress
−.030
−.015
.740
1
Sleepless
.028
.034***
−.156***
.335***
.462
1
Loneliness
−.055
−.034
−.026***
.425***
.514***
.491
−.080
1
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57
Socio-Emotional Status, Education, and Time-Discounting in Japanese Non-Smoking Population: A Multi-Generational Study
(k) Time discounting
Drinking
Education
Time discounting Drinking
−.011
1
Education
−.076
.056
1
Stress
Depression
Loneliness
1
Stress
.029
.015
1
Depress
.062
.035
−.022***
.679
1
Sleepless
.074
−.015
−.064***
.398***
.531
***
***
Loneliness
Sleeplessness
.069
.030
−.017
.433
.607
1
***
.527
1
Sleeplessness
Loneliness
(l) Time discounting
Drinking
Education
Time discounting Drinking
.194
1
Education
.076
.104
1
Stress
.049
−.029
.041
Depression
1
***
Depress
.004
−.015
−.021
Sleepless
.025
.052
−.016***
Loneliness
Stress
.084
.100
.051
***
Socio-Emotional Status and Time-Discount Rate Next, the authors performed correlation analysis between socio-emotional status (i.e., depression, stress, loneliness) and time-discounting. It was observed that stress was negatively related to time-discount rate of men aged 60 - 69 (Table 3(e)), indicating that relatively old men with high perceived stress are less impulsive in intertemporal choice. Other factors of socioemotional status (i.e., depression, loneliness) were not significantly related to time-discount rate for all generations.
Sleeplessness and Time-Discount Rate The authors then analyzed the relationship between sleeplessness and time-discount rate, to examine the role of the quality of sleep in impulsivity in intertemporal choice. It was found that sleeplessness had opposite effects on time-discount rate between men and women; i.e., sleeplessness was negatively and positively associated with time-discount rate of men aged 40 49 (Table 3(c)) and women aged 30 - 39 (Table 3(h)), respectively.
Drinking and Time-Discount Rate Because time-discount rate is related to the intake of addictive drugs (Bickel & Marsch, 2001) in drug-dependent subjects, the authors examined the relationship between alcohol intake and time-discounting in the present non-alcoholic population. The authors observed no significant relationship between drinking and time-discount rate for gain. This indicates that alcohol intake by non-alcoholic subjects does not significantly relate to impulsivity in intertemporal choice for gain, consistent with our previous study with Japanese university students, reporting that alcohol intake was only related to procrastination (i.e., temporal discounting of loss), but not impulsivity (i.e., temporal discounting of gain) in non-alcoholic students (Takahashi, Ohmura, Oono, & Radford, 2009).
1 .630
1
.312***
.431
.349
***
.534
1
***
.479
1
Discussion To our knowledge, this is the first study to demonstrate that 1) both men and women have the highest time-discount rate in their 60 s; 2) education has a negative impact on time-discount rate of men aged 40 - 49 and women aged 50 - 59; 3) perceived stress has a negative impact on time-discount rate of men aged 60 - 69; and 4) sleeplessness has negative and positive impacts on time-discount rate of men aged 40 - 49 and women aged 30 39, respectively, in a multi-generational Japanese population. Also, it was observed that men were generally more impulsive in intertemporal choice than women, consistent with a previous study with American subjects (Kirby & Markovic, 1996). Furthermore, alcohol intake did not influence intertemporal choice for gain by the present Japanese subjects, consistent with our previous study with non-alcoholic Japanese university students (Takahashi et al., 2009) which demonstrated that alcohol use is related to temporal discounting of loss, but unrelated to temporal discounting of gain. It is also to be underscored that our present Japanese sample did not include habitual smokers, which can exclude our previously-reported dose-dependent effect of nicotine intake on intertemporal choice by Japanese subjects (Ohmura et al., 2005). These findings have some implications for behavioral economics and neuroeconomics, as well as evolutionary biology and economics, which are addressed below. Some behavioral economic and/or psychological studies suggests that adult human time-discount rates decline monotonically over the life course and are much lower by age seventy than in young adulthood (e.g., Green, Myerson, & Ostaszewski, 1999). A recent developmental psychological study also reported that children’s time-discount rate decreases according to their age (Steinberg et al., 2009). Evolutionary psychologists Daly and Wilson (2005) questioned the evolutionary biological foundations of the age-dependence of time-discount rate. An evolutionary economist Rogers (1994) has argued that the
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58
age-dependence of human time and risk preference is optimally determined by intergenerational resource transfers and the effects of personal reputation on the fitness prospects of family members. Our present finding that humans are most impulsive in their 60 s irrespective of sex should be taken into account in these evolutionary economic and biological studies. As stated earlier, it makes an economic sense that education is related to a reduction in time-discount rate (Becker & Mulligan, 1997). The presently-observed negative relationships between education and time-discount rate of men in 40 s and women in 50 s are consistent with the economic theory. The reason why a strong negative effect of education on time-discount rate did not exist in other generations should further be examined in future behavioral economic studies in relation to changes in Japanese educational systems. There was a negative correlation between perceived stress and time-discount rate of men in their 60 s, but not of women in the same age range. This is consistent with our previous neuroeconomic studies which demonstrated that a cortisol (a stress steroid hormone) level had a negative impact on time-discount rate of men (Takahashi, 2004) but not in women (Takahashi et al., 2010). In our previous study (Takahashi et al., 2010), however, another biological marker of stress (i.e., salivary alphaamylase) was negatively related to time-discount rate, irrespective of subject’s sex. It is therefore possible that the presently-assessed “perceived stress” is more strongly related to chronic activation of HPA system, rather than SAM system. This issue should be examined in future studies on the relationship between negative affect and economic decision-making. On the other hand, loneliness and depression did not dramatically affect time-discount rate in the present non-clinical subjects. Our previous study (Takahashi et al., 2008a) reported that clinically depressed subjects had higher time-discount rate in the near future. It is therefore important to ask the distinction between non-clinical and clinical states of being depressed among healthy and clinical subjects. Consistent with previous laboratory experimental studies (Acheson et al., 2007; Reynolds & Schiffbauer, 2004b), sleeplessness tended to enhance women’s time-discount rate in their 30 s. In contrast, sleeplessness was negatively related to men’s time-discount rate in their 40 s. A recent neurobiological study demonstrated that sleep deprivation has more detrimental effect on cognitive performance in female rats, in comparison to male rats (Hajali, Sheibani, Esmaeili-Mahani, & Shabani, 2012). Therefore, it may be conceivable that there are neurobiological sex differences in the relationships between sleep deprivation and impulsivity in intertemporal choice. Another possibility is that sleeplessness is related to differences in socioeconomic status in men aged 40 - 49. These possibilities should more extensively be studied in future economic research. In line with evolutionary biological theory (Daly & Wilson, 2005) and an experimental study (Kirby & Markovic, 1996), the present study revealed that men were generally more impulsive than women in intertemporal choice. This gender difference is not due to a difference in smoking status between men and women, because our present subjects were non-smokers. Our previous neuroeconomic study demonstrated that testosterone (a male steroid hormone) is nonlinearly related to time-discount rate (Takahashi et al., 2006). A more recent study by labor economists also reported a nonlinear relationship between testosterone and risk-aversion in women (Sapienza, Zingales, & Maestripieri, 2009). Taken together, studies in neu-
Psychology Handbook
roeconomics should examine the roles of sex steroid hormones, in addition to stress steroid hormones, in determining a gender difference in economic decision-making across generations. Apart from the main objectives of the present study, it is striking that education markedly reduces negative affect such as depression and loneliness in most generations (though there are some exceptions). Future studies in economics of education should pursuit this effect of education on emotion, in order to further establish the relationships between education and happiness. Concerning the relationship between age and temporal discounting, the roles of anticipatory time-perception and responsivity of brain reward systems (e.g., the striatum) have recently been attracting much attention (Löckenhoff, 2011; Löckenhoff et al., 2011). Our previous studies indicate that anticipatory time-perception may be related to impulsivity in temporal discounting behavior (Takahashi, 2005; Takahashi et al., 2008). It is therefore important to examine the role of age-dependency of time-perception in intertemporal choice, in future behavioral economic studies. Moreover, it is known that there are some “anomalies” in intertemporal choice (e.g., hyperbolic discounting, sign effect, subadditive discounting, delay-speedup asymmetry, and interval effect) (Frederick, Shane, Loewenstein, & O’Donoghue, 2002; Kinari, Ohtake, & Tsutsui, 2009; Scholten & Read, 2010; Takahashi, 2009). Future studies in behavioral economics should examine whether these anomalies in intertemporal choice are related to socio-emotional status, age, and education. It is now discussed that several limitations exist in the present study. First, the present study only examined Japanese population. Drinking and smoking habit differ across societies and cultures, future studies should examine other populations. Second, biological markers of stress and depression (e.g., cortisol and serotonin) were not examined in the present study. Future studies should examine the roles of neurobiological markers in the relationships between emotion, demographics, and impulsivity in intertemporal choice, to help us to develop neuroeconomic understandings of human intertemporal choice.
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Socio-Emotional Status, Education, and Time-Discounting in Japanese Non-Smoking Population: A Multi-Generational Study
field behavior. Journal of Risk and Uncertainty, 37, 237-269. Coe, N. B., & Zamarro, G., (2011). Retirement effects on health in Europe. Journal of Health Economics, 30, 77-86. Daly, M., & Wilson, M. (2005). Carpe diem: Adaptation and devaluing the future. The Quarterly Review of Biology, 80, 55-61. Ernst, M. (2012). The usefulness of neuroeconomics for the study of depression across adolescence into adulthood. Biological Psychiatry, 72, 84-86. Fehr-Duda, H., De Gennaro, M., & Schubert, R. (2006). Gender, financial risk, and probability weights. Theory and Decision, 60, 283-313. Frederick, S., Loewenstein, G., & O’Donoghue, T. (2002). Time discounting and time preference: A critical review. Journal of Economic Literature, 40, 351-401. Fujisawa, T. X., Nishitani, S., Ishii, S., & Shinohara, K. (2011). Differential modulation of impulsive behavior by loneliness and testosterone in adolescent females. Neuro Endocrinology Letters, 32, 836840. Green, L., Fry, A. F., & Myerson, J. (1994). Discounting of delayed rewards: A life-span comparison. Psychological Science, 5, 33-36. Green, L., Myerson, J., & Ostaszewski, P. (1999). Discounting of delayed rewards across the life span: Age differences in individual discounting functions. Behavioural Processes, 46, 89-96. Hajali, V., Sheibani, V., Esmaeili-Mahani, S., & Shabani, M. (2012). Female rats are more susceptible to the deleterious effects of paradoxical sleep deprivation on cognitive performance. Behavioural Brain Research, 228, 311-318. Ifcher, J., & Zarghamee, H. (2011). Happiness and time preference: The effect of positive affect in a random-assignment experiment. American Economic Review, 101, 3109-3129. Ikeda, S., Kang, M. I., & Ohtake, F. (2010). Hyperbolic discounting, the sign effect, and the body mass index. Journal of Health Economics, 29, 268-284. Kimball, M. S., Sahm, C. R., & Shapiro, M. D. (2008). Imputing risk tolerance from survey responses. Journal of the American Statistical Association, 103, 1028-1038. Kimmo, K., & Brent, S. (2010). Emotional reactions to losing explain gender differences in entering a risky lottery. Judgment and Decision Making, 5, 159-163. Kinari, Y., Ohtake, F., & Tsutsui, Y. (2009). Time discounting: Declining impatience and interval effect. Journal of Risk and Uncertainty, 39, 87-112. Kirby, K. N., & Marakovic, N. N. (1996). Delay-discounting probabilistic rewards: Rates decrease as amounts increase. Psychonomic Bulletin & Review, 3, 100-104. Kirby, C., Winston, G., & Santiesteban, M. (2005). Impatience and grades: Delay-discount rates correlate negatively with college GPA. Learning and Individual Differences, 15, 213-222. Löckenhoff, C. E. (2011). Age, time, and decision making: from processing speed to global time horizons. Annals of the New York Academy of Sciences, 1235, 44-56. Löckenhoff, C. E., O’Donoghue, T., & Dunning, D. (2011). Age differences in temporal discounting: The role of dispositional affect and anticipated emotions. Psychology and Aging, 26, 274-284. Loewenstein, G. (1996). Out of control: Visceral influences on behavior. Organizational Behavior and Human Decision Processes, 65, 272-292. Loewenstein, G., Rick, S., & Cohen, J. D. (2008). Neuroeconomics. Annual Review of Psychology, 59, 647-672. McClure, S. M., Laibson, D. I., Loewenstein, G., & Cohen, J. D. (2004). Separate neural systems value immediate and delayed monetary re-
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wards. Science, 306, 503-507. Menz, M. M., Buchel, C., & Peters, J. (2012). Sleep deprivation is associated with attenuated parametric valuation and control signals in the midbrain during value-based decision making. The Journal of Neuroscience, 32, 6937-6946. Ohmura, Y., Takahashi, T., & Kitamura, N. (2005). Discounting delayed and probabilistic monetary gains and losses by smokers of cigarette. Psychopharmacology, 182, 508-515. Peters, J., & Büchel, C. (2010). Episodic future thinking reduces reward delay discounting through an enhancement of prefrontal-mediotemporal interactions. Neuron, 66, 138-148. Phillips, P. E., Kim, J. J., & Lee, D. (2012). Neuroeconomics. Frontiers in Behavioral Neuroscience, 6 . Read, D., & Read, N. L. (2004). Time discounting over the lifespan. Organizational Behavior and Human Decision Processes, 94, 22-32. Reynolds, B., & Schiffbauer, R. M. (2004a). Impulsive choice and workplace safety: A new area of inquiry for research in occupational settings. The Behavior Analyst, 27, 239-246. Reynolds, B., & Schiffbauer, R. (2004b). Measuring state changes in human delay discounting: An experiential discounting task. Behavioural Processes, 67, 343-356. Rogers, A. R. (1994). Evolution of time preference by natural selection. American Economic Review, 84, 460-481. Sapienza, P., Zingales, L., & Maestripieri, D. (2009). Gender differences in financial risk aversion and career choices are affected by testosterone. Proceedings of the National Academy of Sciences, 106, 15268-15273. Scholten, M., & Read, D. (2010). The psychology of intertemporal tradeoffs. Psychological Review, 117, 925-944. Schweighofer, N., Bertin, M., Shishida, K., Okamoto, Y., Tanaka, S. C., Yamawaki, S., & Doya, K. (2008). Low-serotonin levels increase delayed reward discounting in humans. The Journal of Neuroscience, 28, 4528-4532. Steinberg, L., Graham, S., O’Brien, L., Woolard, J., Cauffman, E., & Banish, M. (2009). Age differences in future orientation and delay discounting. Child Development, 80, 28-44. Takahashi, T. (2004). Cortisol levels and time-discounting of monetary gain in humans. Neuroreport, 15, 2145-2147. Takahashi, T. (2005). Loss of self-control in intertemporal choice may be attributable to logarithmic time-perception. Medical Hypotheses, 65, 691-693. Takahashi, T. (2009). Theoretical frameworks for neuroeconomics of intertemporal choice. Journal of Neuroscience, Psychology, and Economics, 2, 75-90. Takahashi, T., Ohmura, Y., Oono, H., & Radford, M. (2009). Alcohol use and discounting of delayed and probabilistic gain and loss. Neuroendocrinology Letters, 30, 749-752. Takahashi, T., Oono, H., Inoue, T., Boku, S., Kako, Y., Kitaichi, Y., Kusumi, I., Masui, T., Nakagawa, S., Suzuki, K., Tanaka, T., Koyama, T., & Radford, M. H. (2008a). Depressive patients are more impulsive and inconsistent in intertemporal choice behavior for monetary gain and loss than healthy subjects—An analysis based on Tsallis’ statistics. Neuroendocrinology Letters, 29, 351-358. Takahashi, T., Oono, H., & Radford, M. H. (2008b). Psychophysics of time perception and intertemporal choice models. Physica A, 387, 2066-2074. Takahashi, T., Sakaguchi, K., Oki, M., Homma, S., & Hasegawa, T. (2006). Testosterone levels and discounting delayed monetary gains and losses in male humans. Neuroendocrinology Letters, 27, 439444. Takahashi, T., Shinada, M., Inukai, K., Tanida, S., Takahashi, C., Mifune, N., Takagishi, H., Horita, Y., Hashimoto, H., Yokota, K., Kameda, T., & Yamagishi, T. (2010). Stress hormones predict hyper-
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bolic time-discount rates six months later in adults. Neuroendocrinology Letters, 31, 616-621. Venkatraman, V., Huettel, S. A., Chuah, L. Y., Payne, J. W., & Chee,
Psychology Handbook
M. W. (2011). Sleep deprivation biases the neural mechanisms underlying economic preferences. The Journal of Neuroscience, 31, 3712-3718.
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10 Do Positive School Experiences and Preference for American Culture Moderate the Association between School-Based Ethnic Discrimination and Mental Health for Filipino American Adolescents? 1
Tzu-Fen Chang1*, Eun-Jin Han2, Esther E. Onaga1, M. Brent Donnellan3 Department of Human Development and Family Studies, Michigan State University, East Lansing, USA 2 Department of Social Welfare, Seoul Women’s University, Seoul, South Korea 3 Department of Psychology, Michigan State University, East Lansing, USA
This study examines short-term and longitudinal associations between school-based discrimination and mental health, (i.e., self-esteem and depression) and the moderating roles of “preference for American culture” and positive school experiences, for 684 Filipino American adolescents drawn from the Children of Immigrants Longitudinal Study (CILS). Our findings suggest that school-based discrimination predicted increased levels of depression and lower levels of self-esteem in short-term but not in long-term. The shortterm negative associations between discrimination and mental health were not moderated by levels of preference for American culture, and positive school experiences decrease the negative association between discrimination and self-esteem. Implications from this study are discussed. Keywords: Filipino American Adolescents; Discrimination; Mental Health; Cultural Preference; School Experiences
Introduction Filipino American adolescents are underrepresented in the mental health literature (David & Okazaki, 2006; Nadal, 2009), even though Filipino Americans are the third-largest Asian American ethnic group in the US, totaling 2.56 million individuals (US Census, 2010). Despite the large number of Filipino Americans residing in the US, they are frequently described as the “invisible minorities” (Cimmarusti, 1996). Filipino Americans experience higher rates of perceived ethnic discrimination than other major Asian American ethnic groups (Gee, Spencer, Chen, Yip, & Takeuchi, 2007) and are under represented in mental health research. Gee and colleagues (2009) link mental health outcomes with perceived discrimination experiences. However, there has been little investigation on the short-term and long-term mental health consequences of these negative experiences on Filipino Americans. In addition, little is known about acculturation or school experience roles as moderators of perceived discrimination on the short-term and longterm mental health of this group. This paper addresses these research gaps through data drawn from the Children of Immigrants Longitudinal Study (CILS; Portes & Rumbaut, 19912006). Prior research using the CILS data examined mental health by examining two key cognitive and affective dimensions of *
Corresponding author.
psychosocial adaptation—self-esteem and depression. Rumbaut (1997) found that among all different nationalities examined in Wave I (1992) of the CILS, only the Filipinos (and Vietnamese) showed statistically significant lower self-esteem scores. They also showed higher depression scores, especially among the female students. The CILS dataset offers the opportunity to examine longitudinal associations between perceived discrimination and mental health. We targeted school-based experiences because ethnic discrimination is prevalent among Asian American children in this setting (Gee et al., 2009). The study investigates the moderating effects of “preference for American culture” (one of the major indicators of acculturation) and school experiences on both short-term and long-term associations between discriminatory experiences and mental health. Investigating whether these factors moderate mental health outcomes (both short-term and long-term) would render valuable, practical interventions with this population.
Literature Review Filipino Americans Filipino Americans are distinctive from other Asian American groups because “they are the only Asian American group that experienced direct American colonization” (David & Okazaki, 2006: p. 5). With this history of colonization, first and se-
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cond generation Filipino Americans have a deep connection with American culture and possess English skills (Nadal, 2009), which leads to an underlying assumption that Filipino Americans can more easily adapt to and acculturate into the American society than other Asian Americans of similar generational groups. On the contrary, scholars have noted that the assumption based on their distinctive history is likely to mask true adjustment difficulties (Gee et al., 2009; Rumbaut, 1996; Wolf, 1997). For example, in a large-scale immigrant survey (Rumbaut, 1996), two-thirds of the Filipino adolescent respondents reported perceiving ethnic discrimination. The 2007 California Health Interview Survey also showed that almost half of Filipinos experienced less respect due to their race or accent in their speech in the past year and 50% of the discrimination within their lifetime occurred in educational settings (as cited in Gee et al., 2009).
Ethnic Discrimination and Mental Health in Filipino American Adolescents Exposure to ethnic discrimination can produce multiple detrimental effects on ethnic minority adolescents’ mental health, such as depression, low self-esteem, low self-efficacy, and anxiety (Gee et al., 2009). Few studies have examined the Filipino adolescent population in this area. Rumbaut (1996) found that Filipino adolescents who experienced ethnic discrimination were more susceptible to depressive symptoms. In an in-depth quailtative study, Wolf (1997) suggests that experiences of ethnic discrimination and inequality account for why some Filipino American adolescents suffer from psychological maladjustment (e.g., anxiety and depression) that further leads to increased suicidal ideation. Prior research did not pay much attention to the long-term associations between ethnic discrimination and mental health among Filipino adolescents, with the exception of Ying and Han’s (2006) study in which they found that current perception of school-based ethnic discrimination, and not past school-based experiences of discrimination, predicted levels of depression. Some features distinguish our study from Ying and Han’s study. First, we examined the associations of ethnic discrimination not only with depression but also with self-esteem in shortand long-term outcomes. Second, while Ying and Han’s (2006) study examined school-based discrimination on middle adolescence (Mage = 14.12 years), we examined this phenomenon for late adolescence (Mage = 17.13 years). Third, our study examined the role of potential moderators, i.e., preference for American culture (one of the major indicators of acculturation) and school experiences, for associations of discrimination with depression and self-esteem.
Acculturation as a Moderator Empirical findings have been mixed regarding whether hostculture orientation serves as a buffer or an exacerbator in moderating the negative associations between discrimination and mental health of ethnic minority adolescents. One line of research suggests that higher levels of orientation toward the host culture alleviate the negative associations between discrimination and mental health, e.g., less depression among Somali male adolescent refugees (Ellis et al., 2010) and higher self-esteem among American Indian female adolescents (Galliher, Jones, &
Psychology Handbook
Dahl, 2010). This line of research can be interpreted with the lens of social identity theory (Turner, Brown, & Tajfel, 1979), in which holding a positive view toward a particular social group can contribute to strong identification with the group and further benefit psychological or externalized functioning. Accordingly, individuals with ahigh orientation toward the host culture might be less susceptible to the harm of ethnic discrimination given that they can easily seek social resources/supports of the host society to counteract these discriminatory encounters. Another line of research based on cognitive dissonance theory (Festinger, 1957) resulted in opposite findings. This theory posits that two discordant cognitions can expose individuals to psychological maladjustment. Based on this theory, adolescents who are highly oriented toward the host culture but also feel discriminated are likely to produce two competing cognitions: They are insiders due to high acculturation versus they are foreigners due to discrimination. The two dissonant beliefs can aggravate adolescents’ psychological maladjustment as shown by findings of Latino and Chinese American adolescents studies (Brenner & Kim, 2009; Umanã-Taylor & Updegraff, 2007). To our understanding, no research thus far has focused on acculturation as a moderator for Filipino American adolescents. Doing so would therefore be worthy to enhance our understanding on whether high orientation toward the host culture plays as a protector or an exacerbator in moderating associations between discrimination and mental health for Filipino population. This looks at one indicator of acculturation—preference for American culture measured in this dataset.
School Experiences as a Moderator The integrative model on developmental competencies of minority children highlights children’s experiences in a microsystem, such as in school (Garcia et al., 1996). Our focus is then on whether the school environment conveys friendly messages and experiences for minority children, positively influencing their psychosocial and behavioral development. The adolescents’ perceptions of having positive school experiences (e.g., school safety, a good learning environment, and positive peer/teacher relations) benefit Asian American adolescents’ mental health, e.g., less depression, less social stress and anxiety, and higher self-esteem (Lei, 2003; Way & Robison, 2003). An analysis of the data drawn from the CILS also reveals that youths attending schools they perceived as unsafe displayed significantly lower self-esteem and higher depressive symptoms compared to those attending schools they perceived as safe (Rumbaut, 2005). Other research shows that these positive perceptions of the school environment might mitigate Asian American children’s perceptions of negative encounters of discrimination and racism due to their minority status (Lee, 2003). However, no research has yet examined whether positive school experiences can mitigate the negative associations between ethnic discrimination and mental health in Filipino Americans. This study is directed to narrow this research gap by examining the moderating effect of school experiences, i.e., students’ perceptions of school safety and learning environment.
Hypotheses Several hypotheses are tested in this paper. First, schoolbased discrimination, both past (at Wave I) and current (at
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Do Positive School Experiences and Preference for American Culture Moderate the Association between School-Based Ethnic Discrimination and Mental Health for Filipino American Adolescents?
Wave II), would significantly predict increased levels of depression and lower levels of self-esteem in Filipino American adolescents. Several studies on ethnic minority children have shown that exposure to discrimination can predict poor mental health, e.g., more depression and low self-esteem among Chinese Americans (Juang & Cookston, 2009) and African Americans (Brody et al., 2006) in both short-term and long-term. Previous findings on ethnic minority children have been mixed with respect to the moderating effects of preference for American culture (e.g., Benner & Kim, 2009; Ellis et al., 2010; Galliher et al., 2010; Umanã-Taylor & Updegraff, 2007). Thus we do not postulate whether levels of preference act as a buffer or as an exacerbator for either short-term or long-term associations of discrimination with levels of depression and self-esteem. With respect to the moderating effects of school experiences, due to the protective roles played by positive school environments, we hypothesized that positive school experiences would buffer the negative associations of discrimination with depression and self-esteem. Specifically, positive school experiences would (a) decrease the positive associations of both past and current discrimination with levels of depression; and (b) decrease the negative associations of both past and current discrimination with levels of self-esteem.
Method Participants The Children of Immigrants Longitudinal Study (CILS; Portes & Rumbaut, 1991-2006) data examined adjustment processes of first and second generation immigrants with origins from Asia and Latin America in three Waves. In the Wave I, adolescents in 8th and 9th grades from all public and private schools in San Diego and Miami were recruited. Recruitment criteria included adolescents born in the United States who had at least one parent born abroad and those who were foreign-born and have resided in the United States for at least five years. The total sample consisted of 5262 adolescents at Wave I and 4288 adolescents (81.5% of the original sample) at the Wave II. Wave III involved a sample that reached early adulthood, with an average age of 24 years of age, but this study examined only data collected at Waves I and II. At Wave I, 819 Filipino American adolescents participated in the CILS, and 724 of the original adolescents participated in the follow-up study at Wave II. The majority of respondents (98.7%) were drawn from San Diego at Wave I. This study analyzed only those participating in the follow-up study and those reporting depression, self-esteem, and school-based discrimination experiences at both Waves, yielding the final sample of 676 adolescents. Of the sample, the proportion of males (50.1%) and females (49.9%) were almost equal. At Wave I, their mean age was 14.13 years (SD = .78) and their mean grade level was 8.54 (SD = .50). Over half of the participants (57.3%) were born in the United States, 38.4% were born in Philippines, while the rest (4.3%) were born in other countries (e.g., in Europe or Asia). Those born in Philippines or in other countries were collapsed into the category of first generation, while those born in the United States were second generation. The average age of migration for the first-generation participants was 6.70 years (SD = 4.67). With respect to socioeconomic status (SES), 3.2% were wealthy, 45.4% were upper-middle class, 39.5% were lower-middle class, 10.6% were working-class, .3% were poor,
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and the remaining (1%) were missing. SES was reported by adolescents at Wave I. For parental education, 33.7% of fathers and 26.9% of mothers received a high school degree or below, while 56.6% of fathers and 63.8% of mothers were universityeducated or beyond. The remaining parents (9.7% of fathers and 9.3% of mothers) did not report their educational level.
Measures Depression. Depression was measured by four items from Center for Epidemiological Studies-Depression Scales (CES-D; Radloff, 1977) for Wave I and Wave II. These items included: How often have you felt this way during the past week? “I felt sad”, “I could not get going”, “I didn’t feel like eating; my appetite was poor”, and “I felt depressed”. Responses were scored on a 4-point scale on which: 0 = rarely; 1 = some of the time; 2 = occasionally; 3 = most of the time. The four items were summed and averaged to yield the mean level of depression. The alpha reliability of this scale was .74 at Wave I and .76 at Wave II. The reliability and validity of the CESD-4 have been found to be sufficient in comparison with the full 20-item CESD (Melchior, Huba, Brown, & Reback, 1993). Self-Esteem. In both Waves, levels of self-esteem were measured by Rosenberg’s Self-Esteem scale (1979) with ten items. Examples of items were as follows: “I am a person of worth”, “I do things as well as other people”, and “I do not have much to be proud of”. Responses were scored on a 4-point scale on which: 0 = disagrees a lot; 1 = disagrees a little; 2 = agrees a little; 3 = agrees a lot. Five items were worded negatively and five items were worded positively. We reverse-weighted the negatively phrased items, and summed and averaged all the items to yield the mean level of self-esteem. The alpha reliability of this scale in the present study was .81 at Wave I and .84 at Wave II. School-Based Discrimination. School-based discrimination included three kinds of discrimination in school settings: teacher discrimination, peer discrimination, and counselor discrimination. In both waves, adolescents answered the question: “Have you ever felt discriminated against by teachers?” Similarly, adolescents separately responded to the questions related to “whether you have ever felt discriminated against by peers” and “whether you have ever felt discriminated against by counselors.” Each response was coded as dichotomous variables (0 = No and 1 = Yes) and then summed. School-based ethnic discrimination score was based on the study conducted by Ying and Han (2006). Preference for American Culture. Orientation toward the host society was assessed by levels of preference for doing things the American way as reported at Wave II. Adolescents only answered one question: “How often do you prefer American ways of doing things?” This item was scored on a 4-point scale on which: 0 = never, 1 = sometimes, 2 = most of the time, and 3 = all the time. One study using the CILS data identified this item as the indicator of levels of acculturation (Ying & Han, 2007). In this study, we focus on this indicator of acculturation. School Experiences. At Wave II, school experiences measured participants’ perceptions of school safety and the learning environment. The results of the factor analysis indicated the two-dimensional structure of the perceived school experiences scale. The first extracted factor was correlated with items assessing school discipline, grading fairness, and teachers’ attitudes. The second extracted factor was highly correlated with
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three items: “Don’t feel safe in school” (r = .52, p < .001), “Students disruptions prevent learning” (r = .53, p < .001), and “Many gangs in school” (r = .55, p < .001). This study focuses on the second factor. Responses were scored on a 4-point scale on which: 0 = disagrees a lot; 1 = disagrees a little; 2 = agrees a little; 3 = agrees a lot. The scores of all items were reversely coded for further analyses and convenience of interpretation. All the items were summed and averaged to yield the mean level of school experiences. Higher scores represent more positive school experiences. The alpha reliability of this scale in the present study was .54.
Results Descriptive statistics are presented in Table 1. Participants reported low levels of depression and school-based discrimination at Waves I and II, as indicated by scores below midpoint of item range. Participants reported high levels of self-esteem at both waves and high levels of preference for American culture, as indicated by scores beyond midpoint of item range. Their school experiences were moderately positive given that the mean was close to the midpoint of item range.
Analyses Before testing the study hypotheses, we explored the relations between demographic variables and the study variables. Compared to the male adolescents, the female adolescents reported higher levels of depression at Wave I and Wave II (ts(674) = 6.21 and 5.49, ps < .001 and .001, respectively), lower levels of self-esteem at Wave I and Wave II (ts(674) = 3.62 and 2.15, ps < .001 and = .034, respectively), and more positive school experiences at Wave II (t(674) = 2.44, p = .014). Compared to the first-generation adolescents, the second-generation adolescents reported higher levels of preference for American culture at Wave II (t(674) = 2.68, p = .008). Grade point average (GPA) was significantly and positively correlated with levels of self-esteem at Wave I and Wave II (rs(674) = .25 and .16, ps < .001 and .001, respectively) and school experiences at Wave II (r(674) = .14, p < .001). Based on prior research (Umanã-Taylor & Updegraff, 2007) and initial analyses, Table 1. Descriptive statistics of the major variables. Range Variable
M
SD
Potential
Actual
Depression WI
.67
.63
0-3
.0 - 3.0
Depression WII
.72
.65
0-3
.0 - 3.0
Self-esteem WI
2.26
.49
0-3
.40 - 3.0
Self-esteem WII
2.42
.51
0-3
.80 - 3.0
School-based discrimination WI
.57
.77
0-3
.0 - 3.0
School-based discrimination WII
.70
.87
0-3
.0 - 3.0
Preference for American culture at WII
2.14
.89
0-3
.0 - 3.0
School experiences WII
1.67
.68
0-3
.0 - 3.0
regression analyses controlled for covariates including gender, generational status, GPA, age, and SES. SES is the unit-weighted standardized scale as created by Portes and Rumbaut (19912006). We used single dummy codes for gender (1 = female) and generational status (1 = first generation). In addition, when examining the discrimination-adjustment link, prior research controlled for the past levels of adjustment (Benner & Kim, 2009; Brody et al., 2006). Thus, to test associations between past or current discriminatory experiences and depression and self-esteem, respective levels at Wave I were controlled. Four separate hierarchical multiple regression analyses examined the associations of past and current school-based discrimination with depression and self-esteem. Four regression models were implemented for each regression analysis. In Model 1, we entered the previously-mentioned controlled variables. Model 2 tested associations of past or current school-based discrimination with mental health at Wave II, given that covariates were statically controlled. To test associations of past discriminatory experiences with depression and self-esteem, school-based discrimination at Wave I was entered. To test associations of current discriminatory experiences with depression and selfesteem, school-based discrimination at Wave II was entered. In Model 3, preference for American culture and school experiences were entered as a block. Model 4 tested moderating effects of preference for American culture and school experiences on links between discrimination and mental health. To test associations of past discriminatory experiences withdepression and self-esteem, two interactions were entered as a block: school-based discrimination at Wave I by preference for American culture and school-based discrimination at Wave I by school experiences. To test associations of current discriminatory experiences with depression and self-esteem, two interactions were entered as a block: school-based discrimination at Wave II by preference for American culture and school-based discrimination at Wave II by school experiences. Based on Cohen and colleagues’ recommendations (2003), school-based discrimination Waves I and II, preference for American culture at Wave II, and school experiences at Wave II were centered on their means to decrease multicollinearity. ΔR2 and Fchange were computed between the main-effect model (Model 3) and the moderator model (Model 4). For the interaction model (i.e., Model 4), ΔR2 and its level of significance provided information on what percentage of additional variance interaction effects accounted for depression and self-esteem at Wave II. When ΔR2 of any model was not significant, the following model was not conducted.
Test of Associations between Past School-Based Discrimination and Mental Health Association between School-Based Discriminatory Experiences at Wave I and Depression at Wave II. Results are shown in Table 2. In Model 1, levels of depression at Wave II was positively and significantly predicted by levels of depression at Wave I (β = .30, p < .001), gender (being female) (β = .17, p < .001), and SES (β = .10, p = .009), but was negatively and significantly predicted by GPA (β = −.10, p = .008). Contrary to our hypothesis, school-based discrimination with covariates controlled did not significantly predict depression at Wave II (see Model 2). The long-term association between school-based discrimination and depression was not significant. Because ΔR2
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Do Positive School Experiences and Preference for American Culture Moderate the Association between School-Based Ethnic Discrimination and Mental Health for Filipino American Adolescents?
Table 2. Hierarchical multiple regression testing the associations of school-based discrimination at Wave I with depression at Wave II and self-esteem at Wave II. Model 1 Variable
Model 2
B (SE)
β
B (SE)
β
.31***(.04)
.30
Outcome variable: Depression at Wave II Depression at Wave I
.31***(.04)
.30
***
***
Gender (1 = female)
.22 (.05)
.17
.22 (.05)
.17
Age
−.02(.03)
−.03
−.02(.03)
−.03
SES
.13**(.05)
.10
.13**(.05)
.10
Generational status (1 = first generation)
.06(.05)
.05
.06(.05)
.05
GPA
**
−.10
**
−.08 (.03)
−.10
−.02(.03)
−.02
−.08 (.03)
School-based discrimination at Wave I Intercept
.65
F
19.71
R2
.15
.67 ***
16.92*** .15
Fchange
.35
∆R2
.00 Outcome variable: Self-esteem at Wave II
Self-esteem at Wave I
.39***(.04)
.38
.39***(.04)
.38
Gender (1 = female)
−.06(.04)
−.06
−.06(.04)
−.06
Age
.00(.02)
.00
.00(.02)
.00
SES
−.05(.04)
−.05
−.05(.04)
−.05
Generational status (1 = first generation)
.05(.04)
.05
.05(.04)
.05
GPA
.06*(.02)
.09
.06*(.02)
.09
−.01(.02)
−.01
School-based discrimination at Wave I Intercept
1.49***
1.50***
F
23.45***
20.08***
R2
.17
.17
Fchange 2
∆R *
**
Note: p < .05. p < .01.
.07 .00
***
p < .001 (two-tailed tests).
of Model 2 was not significant, we did not conduct the following regressions to test moderating effects of preference for American culture and school experiences. Association between school-based discriminatory experiences at Wave I and self-esteem at Wave II. Results are shown in Table 2. In Model 1, levels of self-esteem at Wave I (β = .38, p < .001) and GPA (β = .09, p = .015) positively and significantly predicted levels of self-esteem at Wave II. Contrary to our hypothesis, school-based discrimination at Wave I with controlled covariates did not significantly predict self-esteem at Wave II (see Model 2). The long-term association between school-based discrimination and self-esteem was not signifi-
cant. Because ΔR2 of Model 2 was not significant, we did not conduct the following regressions to test moderating effects of preference for American culture and school experiences.
Associations between Current School-Based Discrimination and Mental Health and Moderating Effects Association between Current School-Based Discriminatory Experiences at Wave II and Depression at Wave II. Results are shown in Table 3. Model 1 results were the same as those shown in Model 1 to test the association between past school-
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based discrimination and depression at Wave II. In Model 2, school-based discrimination at Wave II (β = .16, p < .001) with controlled covariates positively and significantly predicted depression at Wave II (see Table 3). This finding was consistent
with our hypothesis that the short-term, school-based discrimination significantly predicted higher levels of depression. Model 3 shows that levels of depression at Wave II were negatively and significantly predicted by school experiences at
Table 3. Hierarchical multiple regression testing the associations of school-based discrimination at Wave II with depression at Wave II and self-esteem at Wave II. Model 1 variable
B (SE)
Model 2 β
B (SE)
Model 3 β
B (SE)
Model 4 β
B (SE)
β
Outcome variable: Depression at Wave II ***
Depression at Wave I
.31 (.04)
.30
.30***(.04)
.29
.27***(.04)
.27
.28***(.04)
.27
Gender (1 = female)
.22***(.05)
.17
.23***(.05)
.18
.25***(.05)
.19
.25***(.05)
.19
Age
−.02(.03)
−.03
−.02(.03)
−.02
−.02(.03)
−.03
−.02(.03)
−.02
**
**
**
**
SES
.13 (.05)
.10
.14 (.05)
.10
.13 (.05)
.10
.13 (.05)
.10
Generational status (1 = Foreign-Born)
.06(.05)
.05
.06(.05)
.04
.05(.05)
.04
.04(.05)
.03
GPA
**
−.10
**
−.11
*
−.09
**
−.10
−.08 (.03)
−.09 (.03) ***
SD at Wave II
.12 (.03)
.16
−.07 (.03) ***
−.08 (.03) ***
.11 (.03)
.12
.11 (.03)
.14
PAC
.03(.04)
.03
.04(.04)
.04
SE
***
−.16
***
−.15 (.03)
−.16
.06(.04)
.05
−.01(.04)
−.01
−.15 (.03)
SD at Wave II× PAC SD at Wave II× SE Intercept
.65
.50
.78
.73
F
19.71***
20.29***
18.47***
15.27***
R2
.15
.18
.20
.20
20.36
Fchange 2
∆R
***
10.16
.03
***
.91
.02
.00
Outcome variable: Self-Esteem at Wave II Self-esteem at Wave I
***
.39 (.04)
.38
.39***(.04)
.39
.38***(.04)
.37
.38***(.04)
+
.37
*
*
Gender (1 = female)
−.06(.04)
−.06
−.06 (.04)
−.06
−.08 (.04)
−.07
−.08 (.04)
−.08
Age
.00(.02)
.00
−.01(.02)
−.01
.00(.02)
.00
.00(.02)
.00
SES
−.05(.04)
−.05
−.06(.04)
−.05
−.05(.04)
−.05
−.06(.04)
−.05
Generational status (1 = Foreign-Born)
.05(.04)
.05
.05(.04)
.05
.06(.04)
.06
.06(.04)
.06
GPA
*
.06 (.02)
.09
*
.06 (.02) ***
SD at Wave II
−.08 (.02)
PAC
*
.10
.05 (.02)
.08
.06 (.02)
.09
−.14
***
−.07 (.02)
−.12
***
−.07 (.02)
−.11
−.03(.03)
−.03
−.02(.03)
−.02
***
SE
*
.12 (.03)
SD at Wave II× PAC
.17
*
.12 (.03)
.16
.02(.03)
.02
*
SD at Wave II× SE
.07 (.03)
Intercept
1.49***
1.58***
1.40***
1.41***
F
23.45***
22.98***
20.97***
17.82***
R2
.17
.19
.22
.23
Fchange ∆R2
16.87 .02
***
11.40 .03
***
.08
3.07* .01
Note: SD = School-based Discrimination; PAC = Preference for American Culture; SE = School Experiences. +p < .10. *p < .05. **p < .01. ***p < .001 (two-tailed tests).
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Do Positive School Experiences and Preference for American Culture Moderate the Association between School-Based Ethnic Discrimination and Mental Health for Filipino American Adolescents?
Discussion Supportive of the initial hypotheses, this study found negative associations between school-based ethnic discrimination and the mental health of Filipino American adolescents in the short-term. This finding corresponds to the positive correlation between current school-based discrimination and levels of depression for Filipino American adolescents found by Ying and Han (2006), albeit that their target was middle adolescents. This is also consistent with scholars’ caution that Filipino Americans’ special US colonized circumstances can mask Filipino American adolescents’ adjustment challenges of racism and discrimination (Rumbaut, 1996). The evidence of the short-term link not withstanding, the findings do not suggest the long-term toll from discriminatory experiences upon the mental health of Filipino American adolescents. Findings on other ethnic minority adolescents show similar results. For instance, in a study on Chinese Americans (Benner & Kim, 2009), past experiences of long-term discrimi-
1.7
Negative School Experiences
1.65 Self-esteem (Wave II)
Wave II (β = −.16, p < .001), but not by preference for American culture at Wave II. This result suggests that current positive school experiences were related to less depression. In Model 4, the school-based discrimination at Wave II by preference for American culture interaction effect and the school-based discrimination at Wave II by school experiences interaction effect were not significant. These findings reveal that levels of preference for American culture and school experiences did not moderate short-term association between discrimination and depression. Association between Current School-Based Discriminatory Experiences at Wave II and Self-Esteem at Wave II. Results are shown in Table 3. The results of Model 1 were the same as those shown in Model 1 in the analyses testing the association between past school-based discrimination and self-esteem at Wave II. In Model 2, school-based discrimination at Wave II (β = −.14, p< .001) negatively and significantly predicted levels of self-esteem at Wave II. This finding was consistent with our hypothesis that the short-term school-based discrimination significantly predicted lower levels of self-esteem. Model 3 shows that levels of self-esteem at Wave II were positively and significantly predicted by school experiences at Wave II (β = .17, p < .001), but not by preference for American culture at Wave II. This result suggests that current positive school experiences were related to increased self-esteem. In Model 4, the school-based discrimination at Wave II by preference for American culture interaction effect was not significant and the school-based discrimination at Wave II by school experiences interaction effect was significant (β = .08, p = .013). ΔR2 and Fchange were significant between Model 3 and Model 4 (ΔR2 = .01; Fchange (2, 677) = 3.07, p = .042). This finding indicates that the moderating effect of school experiences accounted for an additional 1.0% of the variance of self-esteem at Wave II (i.e., the change between Model 3 and Model 4). A further post-hoc analysis revealed that self-esteem at Wave II was negatively related with school-based discrimination at Wave II for children with negative school experiences (1 SD below the mean; b = −.19, p < .001), but not for those with positive school experiences (1 SD above the mean; b = −.03, p = .492) (Figure 1). For Filipino American adolescents, positive school experiences buffered the short-term negative association between discrimination and self-esteem.
1.6 1.55
Positive School Experiences
1.5 1.45 1.4 1.35 1.3
School-based Discrimination (Wave II)
1.25 -0.17
0.7
1.57
Figure 1. Interaction effect between school-based discrimination at wave ii and school experiences at Wave II and self-esteem at Wave II as the outcome variable; Note. B = unstandardized regression coefficient; −.17 = mean-1SD; .70 = mean; 1.57 = mean + 1SD. ***p < .001.
nation (reported in middle adolescence) predicted poor school engagement and academic performance but did not lead to increased levels of depression (reported in late adolescence). Another study on male American Indian adolescents suggests that past experiences of discrimination predicted decreased selfesteem (reported two years later) only in a marginal significance level, but are strongly linked with their substance use (Galliher et al., 2010). Taken together, the findings of this study and other literature suggest that the longitudinal harm of ethnic discrimination is less significant to psychological adjustment, but might exact more severe consequences on externalized outcomes (e.g., school performance and engagement or substance use). However, caution is in order when drawing implications of these findings. Although this study showed that past experiences of discrimination do not appear to associate with detrimental effects on long-term mental health of late adolescents, these experiences might emerge as a threatening factor for Filipino Americans’ mental health in adulthood. Further research should focus on longitudinal studies tracing associations between past discriminatory experiences and mental health as individuals become younger or older adults. This study extended the study of Ying and Han (2006) by examining moderating effects of both preference for American culture and school experiences for associations of school-based discrimination with depression and self-esteem for Filipino American adolescents. Our study shows preference for American culture did not moderate the associations between current experiences of school-based discrimination with depression and self-esteem. This finding suggests that school-based discrimination may bring similar levels of negative effects on mental health among Filipino American adolescents with both high and low preference for American culture. This might be explained by their colonial history. Although Filipinos are geographically defined as Asians, they have a unique culture, i.e., being more heavily impacted by Spanish and American colonization than the cultures of other Asian groups (David & Okazaki, 2006). Due to direct American colonization, first and second generation Filipino Americans bears a colonial mentality whereby their native culture can be denigrated and American culture accorded a superior status (David & Okazaki, 2006).
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The colonial mentality is prevalent among Filipino Americans and internalized into their cognition (David & Okazaki, 2006). For example, Filipino Americans commonly hold self-image of “being Americanized”. Accordingly, we surmised that Filipino American adolescents might subconsciously or consciously view themselves as being Americanized as important, regardless of their tendencies of acculturation, such as preference for American culture. The cognition of being Americanized conveys a very discordant message against their discriminatory encounters, such as feeling alienated from American peers. The cognitive dissonance theory posits that two discordant cognitions can expose individuals to psychological maladjustment (Festinger, 1957). Based on this theory, the degrees of negative associations between discriminatory experiences and mental health are plausibly similar for Filipino American adolescents, regardless of whether they hold high or low preference for American culture. Contrary to the research findings of the moderating effect of acculturation on Latino and Chinese Americans (Benner & Kim, 2009; Umanã-Taylor & Updegraff, 2007), our study suggests that acculturation exacerbates the negative association between discrimination and mental health. Moreover, our finding was contradictory to the assumption drawn from social identity theory (Turner et al., 1979) and findings on Somali male adolescent refugees (Ellis et al., 2010) and American Indian female adolescents (Galliher et al., 2010), which suggest that acculturation buffers the negative association between discrimination and mental health. We argue that these mixed findings on the moderating role of acculturation (including indicators such as preference for American culture, language usage, and participation of activities) might stem from three different values about acculturation across different ethnic groups. First, some groups may view high acculturation as an access to gain social supports of the host culture against discriminatory experiences. Second, some groups may view acculturation as a proof of being assimilated into the host culture; thus, discrimination and acculturation should be treated as two incompatible cognitions. Third, the colonial mentality such as high self-image of being Americanized is strongly rooted in Filipino Americans’ cognition whereby acculturation plays a less important role in moderating the effect of discrimination. Alternatively, the mixed findings may be due to inconsistent measures of acculturation: Umanã-Taylor and Updegraff (2007) and Ellis et al. (2010) assessed behavioral domain, Galliher et al. (2010) and our study assessed cultural preference, and Benner and Kim (2009) assessed both domains and values. Using a consistent measure of acculturation should be conducted in the future. This study extended previous studies on the protective and buffering role played by positive school experiences for the association between ethnic discrimination and self-esteem. Positive school experiences, i.e., a safe and positive learning environment, were found to alleviate the negative association between school-based discrimination and self-esteem in the shortterm. Research on Asian American adolescents or college students has shown that a positive school environment, including school safety and positive peer/teacher relations, mitigates perceptions of discrimination (Lee, 2003), and protects adolescents from negative associations between discrimination and mental health the negative effects of discrimination on mental health, e.g., depression (in Taiwanese immigrants, Tsai, 2006; in African Americans, Brody et al., 2006). In line with these findings, our study suggests that school safety and a positive learning environment might mitigate the short-term negative association
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of school-based discriminatory encounters for Filipino American adolescents’ mental health. Taken together, the findings from our study and other literature suggest that the overall quality of safe and positive school environment may influence ethnic minority children’s perception of negative encounters that occurred in school and thus protect the ethnic minority children’s mental health. One unexpected finding is that adolescents’ SES was negatively associated with depression given that other covariates were controlled. This finding is inconsistent with the long established association between low SES and increased risk of depression (e.g., a meta-analysis by Lorant and colleagues, 2003). However, this can be explained by the diminishing returns hypothesis (Farmer & Ferraro, 2005). This hypothesis posits that compared to Whites, ethnic minorities gain less economic or social-status returns accompanied by high SES. These diminishing returns increase high SES ethnic minorities’ awareness of the social and economic inequalities and in turn are detrimental to their mental health. Thus, among ethnic minorities, high SES compared to low SES individuals tend to experience increased risk of depression. Our finding supports this hypothesis.
Limitations and Implications Despite providing new insights on the mental health of Filipino American adolescents, this study has some limitations. First, the present study’s failure to detect significant long-term associations between ethnic discrimination and mental health might be linked to the nature of the CILS data, i.e., a lapse of three years between Waves I and II, diminishing the strength of the association. Future studies with shortened time points (e.g., one or two years) and assessing more time points would more clearly describe the longitudinal effects of discrimination. Second, measurement limitation rests on the construct of adolescents’ acculturation orientation. In the CILS data, adolescents’ acculturation orientation was only assessed by one item measuring preference for American culture. Previous research has revealed that the nature of acculturation is multi-dimensional and multi-faceted (Berry, 2003). The use of only one item cannot reflect the overall picture of acculturation of Filipino American adolescents. This limitation might also explain the failure to capture the moderating effect of acculturation. Future studies should assess Filipino adolescents’ acculturation with scales based on a multi-dimensional framework. Third, we surmised that the failure to detect the moderating effect of preference for American culture is explained by the prevalence of a colonial mentality in the Filipino population, regardless of their levels of acculturation. However, this study could not examine the relation between colonial mentality and acculturation given that the CILS data did not provide any items or scales assessing colonial mentality. In fact, only one study to date attempted to quantify and measure the colonial mentality of Filipino American adolescents (Bergano & Bergano-Kinney, 1997). Yet, their measure has been questioned with low face validity due to the limited numbers of items (David & Okazaki, 2006). Future research to develop more valid measures of colonial mentality will clarify its relationship to acculturation. Doing so would better describe the link between colonial mentality and the overall psychological adjustment of the Filipino American adolescents. Fourth, one statistical issue rests on the extent of statistical
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Do Positive School Experiences and Preference for American Culture Moderate the Association between School-Based Ethnic Discrimination and Mental Health for Filipino American Adolescents?
power for detecting interaction effects. One interaction effect was found, i.e., school-based discrimination at Wave II by school experiences at Wave II, but this study had a low power to detect this interaction (∆R2 was .01). As Cohen et al. (2003) noted, interactions are not easy to be observed in social science research and often explain a small portion of variance over and above first-order effects (i.e., ΔR2 from .01 to .05). Although ∆R2 of this study fell into this range, the interpretation of this significant interaction effect should be interpreted with caution due to the low power. These limitations notwithstanding, the present study provides useful information on how adults in school settings such as educators and clinicians can assist Filipino American adolescents to overcome the harm of discriminatory experiences. Our research suggests that both highly and lowly acculturated adolescents might be susceptible to negative effects of current school-based ethnic discrimination in the short-term. Educators’ and clinicians’ support of school and psychological adjustment with all Filipino American adolescents, regardless of their levels of acculturation, becomes critical. Another implication is that school administrators and teachers play important roles to provide positive school experiences, i.e., a safe and good learning environment for students. Evidence from our study that strong levels of school safety and good learning environment appear to be protective factors against school-based ethnic discrimination suggests that school administrators and teachers have significant roles to support Filipino American adolescents. For example, they can consistently monitor their school for unsafe situations among students (e.g., conflicts between racial/ethnic groups and gang activities) as well as foster a positive learning environment. Facilitating a safe school environment and robust learning experiences can help decrease potential harm of school-based discrimination and further enhance Filipino American adolescents’ mental health.
REFERENCES Benner, A. D., & Kim S. Y. (2009). Experiences of discrimination among Chinese American adolescents and the consequences for socioemotional and academic development. Developmental Psychology, 45, 1682-1694. Bergano, A. L., & Bergano-Kinney, B. L. (1997). Images, roles, and expectations of Filipino Americans by Filipino Americans. In M. P. P. Root (Ed.), Filipino Americans: Transformation and identity (pp. 198-207). Thousand Oaks, CA: Sage. Berry, J. W. (2003). Conceptual approaches to acculturation. In K. Chun, P. Balls-Organista, & G. Martin (Eds.), Acculturation: Advances in theory, measurement, and applied research (pp. 17-37). Washington DC: American Psychological Association Press. Brody, G. H., Chen, Y.-F., Murry, V. M., Ge, X., Simons, R. L., Gibbons, F. X., & Cutrona, C. E. (2006). Perceived discrimination and the adjustment of African American youths: A five-year longitudinal analysis with contextual moderation effects. Child Development, 77, 1170-1189. Cimmarusti, R. A. (1996). Exploring aspects of Filipino-American families. Journal of Marital and Family Therapy, 22, 205-217. Cohen, J., Cohen, P., West, S. G., & Aiken, L. S. (2003). Applied multiple regression/correlation analysis for the behavioral sciences (3rd ed.). Mahwah, NJ: Lawrence Erlbaum. Cordova, F. (1983). Filipinos: Forgotten Asian Americans. Dubuque, IA: Kendall/Hunt. David, E. J. R., & Okazaki, S. (2006). Colonial mentality: A review and
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recommendation for Filipino American psychology. Cultural Diversity & Ethnic Minority Psychology, 12, 1-16. Ellis, B. H., MacDonald, H. Z., Klunk-Gillis, J., Lincoln, A., Strunin, L., & Cabral, H. J. (2010). Discrimination and mental health among Somali refugee adolescents: The role of acculturation and gender. The American Journal of Orthopsychiatry, 80, 564-575. Espiritu, Y. L., & Wolf, D. L. (2001). The paradox of assimilation: Children of Filipinoimmigrants in San Diego. In R. G. Rumbaut, & A. Portes (Eds.), Ethnicities: Children of immigrants in America. Berkeley, CA: University of California Press. Farmer, M., & Ferraro, K. (2005). Are racial disparities in health conditional on socioeconomic status? Social Science& Medicine, 60, 191204. Festinger, L. (1957). A theory of cognitive dissonance. Stanford, CA: Stanford University Press. Galliher, R. V., Jones, M. D., & Dahl, A. (2010). Concurrent and longitudinal effects of ethnic identity and experiences of discrimination on psychosocial adjustment of Navajo adolescents. Developmental Psychology, 47, 509-526. García Coll, C., Lamberty, G., Jenkins, R., McAdoo, H. P., Crnic, K. Wasik, B. H., & Garcia, H. V. (1996). An integrative model for the study of developmental competencies in minority children. Child Development, 67, 1891-1914. Gee, G. C., Ro, A., Shariff-Marco. S., & Chae, D. (2009). Racial discrimination and health among Asian Americans: Evidence, assessment, and directions for future research. Epidemiologic Review, 31, 130151. Juang, L. P., & Cookston, J. T. (2009). Acculturation, discrimination, and depressive symptoms among Chinese American adolescents: A longitudinal study. The Journal of Primary Prevention, 30, 475-496. Lee, R. M. (2003). Do ethnic identity and other-group orientation protect against discrimination for Asian Americans? Journal of Counseling Psychology, 50, 133-141. Lei, J. L. (2003). (Un)Necessary toughness?: Those “Loud Black Girls” and those “Quiet Asian Boys”. Anthropology and Education Quarterly, 34, 158-181. Lorant, V., Deliege, D., Eaton, W., Robert, A., Philippot, P., & Ansseau, M. (2003). Socioeconomic inequalities in depression: A meta-analysis. American Journal of Epidemiology, 157, 98-112. Melchior, L. A., Huba, G. J., Brown, V. B., & Reback, C. J. (1993). A short depression index for women. Educational and Psychological Measurement, 53, 1117-1125. Nadal, K. L. (2009). Filipino American psychology: A handbook of theory, research, and clinical practice. Bloomington, IN: Authorhouse. Portes, A., & Rumbaut, R. G. (2008). Children of Immigrants Longitudinal Study (CILS), 1991-2006 [Computer file]. ICPSR20520-v1. Bibliographic Citation: Ann Arbor, MI: Inter-University Consortium for Political and Social Research [distributor], 2008-01-07. Radloff, L. (1977). The CES-D scale: A self report depressions scale for research in the general population. Applied Psychological Measurement, 1, 385-401. Rosenberg, M. (1979). Components of Rosenberg’s self-esteem scale. Conceiving the self. New York: Basic Books. Rumbaut, R. G. (1996). The crucible within: Ethnic identity, self-esteem, and segmented assimilation among children of immigrants. In A. Portes (Ed.), The new second generation (pp. 119-170). New York: Russell Sage. Rumbaut, R. G. (1997). Achievement and ambition among children of immigrants in Southern California. Working Paper No. 215. Annandale-on-Hudson, NY: The Jerome Levy Economics Institute of Bard College. Rumbaut, R. G. (2005). Turning points in the transition to adulthood: Determinants of educational attainment, incarceration, and early child-
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bearing among children of immigrants. Ethnic and Racial Studies, 28, 1041-1086. Tsai, J. H. (2006). Xenophobia, ethnic community, and immigrant youths’ friendship network formation. Adolescence, 41, 285-298. Turner, J. C., Brown, R. J., & Tajfel, H. (1979). Social comparison and group interest in in-group favouritism. European Journal of Social Psychology, 9, 187-204. Umanã-Taylor, A., & Updegraff, K. A. (2007). Latino adolescents’ mental health: Exploring the interrelations among discrimination, ethnic identity, cultural orientation, self-esteem, and depressive symptoms. Journal of Adolescence, 30, 549-567. US Census Bureau (2010). Profile of general population and housing characteristics: 2010 demographic profile data. http://factfinder2.census.gov/faces/tableservices/jsf/pages/productvie w.xhtml?pid=DEC_10_DP_DPDP1 Way, N., & Robinson, M. G. (2003). A longitudinal study of the effects
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of family, friends, and school experiences on the psychological adjustment of ethnic minority, low-SES adolescents. Journal of Adolescent Research, 18, 324-346. Wolf, D. L. (1997). Family secrets: Transnational struggles among children of Filipino immigrants. Sociological Perspectives, 40, 457-482. Ying, Y.-W., & Han, M. (2006). The effect of intergenerational conflict and school-based racial discrimination and depression and academic achievement in Filipino American adolescents. Journal of Immigrant and Refugee Studies, 4, 19-35. Ying, Y.-W., & Han, M. (2007). The longitudinal effect of intergenerational gap in acculturation on conflict and mental health in Southeast Asian American adolescents. The American Journal of Orthopsychiatry, 77, 61-66.
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11 Competitive Orientations and Men’s Acceptance of Cosmetic Surgery Bill Thornton1, Richard M. Ryckman2, Joel A. Gold2 1
Department of Psychology, University of Southern Maine, Portland, USA 2 Department of Psychology, University of Maine, Orono, USA
As with women, men are experiencing increased pressure to achieve media-conveyed societal ideals for appearance and their consideration of cosmetic surgery as a means to enhance their appearance for competitive advantage in social and career realms has been increasing. This study considered individual differences in competitive orientations and the acceptance of cosmetic surgery among men. Hypercompetitiveness (psychologically unhealthy) was predictive of acceptance of cosmetic surgery even after age, self-esteem, body mass index, and body dysmorphia were taken into account. Personal development competitiveness (psychologically healthy) was negatively associated with body dysmorphia and was not predictive of acceptance of cosmetic surgery among men. These results for men, along with previous research among women (Thornton et al., 2013), indicate that a hypercompetitive orientation contributes to the consideration of cosmetic surgery independent of body image concerns for both men and women. Keywords: Appearance; Attractiveness; Body Image; Competitiveness; Hypercompetitiveness; Cosmetic Surgery
Introduction Physical appearance is well-documented as being an important characteristic for both women and men and has implications for both intrapersonal well-being and interpersonal interactions (Hatfield & Sprecher, 1986; Jackson, 1992; Langlois et al., 2000). Historically, women are presumed to compete intrasexually on the basis of their appearance (Buss, 1989; Darwin, 1871; Fisher & Cox, 2011). As such, it is a woman’s appearance, not her accomplishments, that has been her most valued asset for social and economic survival within a culture (Brownmiller, 1984; Rothblum, 1994; Wolf, 1991). From an early age women are exposed to the sociocultural expectations with regard to their appearance. These norms are pervasively conveyed in the media and frequently depict unattainable standards for appearance on which a woman’s worth is based (American Psychological Association, 2007). In addition, there is often the not so subtle implication that women must strive to be more competitive through efforts that enhance their attractiveness (Bessenoff, 2006; Derenne & Beresin, 2006). Not only are these “appearance standards” used to evaluate others, but also they may be internalized and women begin to self-objectify and critically evaluate themselves on the basis of these same standards (Franzoi, 1995; Fredrickson & Roberts, 1997). It is these external and internal pressures that are believed to have resulted in heightened feelings of inadequacy and anxiety among women with regard to their physical appearance and body-image and contributes to the prevalence of body dysmor-
phia and disordered eating among women (Derenne & Beresin, 2006; Veale, 2004). Appearance concerns also underlie women’s acceptance of cosmetic surgery as a means to boost their self-esteem and enhance their social and career potential (Callaghan, Lopez, Wong, Northcross, & Anderson, 2011; Calogero, Pina, Park, & Rahemtulla, 2010; Henderson-King & Brooks, 2009). In contrast to the emphasis placed on women’s appearance, a man’s interpersonal and social attractiveness has traditionally relied more on his apparent skills, abilities, and accomplishments rather than physical appearance (Jackson, 1992; Sherrow, 2001). Intrasexual competition among men is based on a display of resource acquisitions (Buss, 1989) and derogation of other men’s abilities and achievements (Buss & Dedden, 1990). However, while objectifying women has had a long history, there has been noted an increasingly obvious trend for objectifying men on the basis of their appearance (Faludi, 1999; Moradi & Huang, 2008; Pope, Phillips, & Olivardia, 2000; Sherrow, 2001). Indeed, just as the media has conveyed the cultural standards of appearance for women, men have been increasingly defined by their looks, particularly a youthful appearance and a lean, muscular body (Faludi, 1999; Moradi & Huang, 2008; Sherrow, 2001). As with women, men (and boys) may come to internalize these standards and engage in self-objectification (Moradi & Huang, 2008). Although not to the same degree as women, men are increasingly experiencing appearance and body image concerns (Thompson & Cafri, 2007; Thompson, Schaefer, &
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Menzel, 2012) with implications for diminished self-esteem, depression, body dysmorphia, disordered eating, and the unhealthy use of steroids and supplements in order to achieve a lean muscularity (Agliata & Tantleff-Dunn, 2004; Cash, 2000; Davis, Karvinen, & McCreary, 2005; Moradi & Huang, 2008; Muth & Cash, 1997; Pope, Gruber, Choi, Olivardi, & Phillips, 1997). Men’s appearance concerns also have implications for considering cosmetic surgery to improve appearance and enhance their social and career potential. The American Society of Plastic Surgeons (ASPS, 2012) reported that, of the 20.2 million procedures performed in the United States, 72% were cosmetic surgeries or minimally invasive procedures undertaken to improve one’s appearance, enhance self-esteem, and increase social and career opportunities. Although men are in the minority with regard to undergoing these procedures (9%), the number of procedures among men has increased 22% since 2000. Among the top procedures are those for facial rejuvenation (e.g., facelift, eyelids, botox, skin peel) and achieving a leaner body (e.g., liposuction and breast reduction).
Competitive Orientation and Acceptance of Cosmetic Surgery Horney (1937) had distinguished between two different types of competitiveness. For instance, hypercompetitiveness was considered a psychologically unhealthy competitive orientation based in neurosis. In contrast, a psychologically healthy competitive orientation, subsequently referred to as personal development competitiveness, reflects less concern with task outcome (i.e., win or lose), but more on the self-discovery, selfimprovement, and personal growth and development that can be gained through competition. Hypercompetitive Orientation. As originally described by Horney (1937), hypercompetitiveness is an indiscriminate need to compete and win at all costs as a neurotic means to maintain and enhance an otherwise fragile self-esteem. Based in childhood experiences, this need stems from having authoritarian parents who are abusive and demeaning, and who strongly emphasize personal success in an achievement-oriented society. Thus, by manipulating, controlling, derogating, or otherwise overcoming others, the hypercompetitive individual is able to deal with feelings of inadequacy. Research has noted that hypercompetitiveness is indeed a neurotic predisposition and associated with low self-esteem, high anxiety, narcissism, the need to control and dominate others, deceitful and unscrupulous behavior, and willingness to strategically manipulate impressions for self-aggrandizement (e.g., Dru, 2003; Ross, Rausch, & Canada, 2003; Ryckman, Hammer, Kaczor, & Gold, 1990; Ryckman, Libby, van den Borne, Gold, & Lindner, 1997; Ryckman, Thornton, & Butler, 1994; Ryckman, Thornton, Gold, & Burckle, 2002; Thornton, Lovley, Ryckman, & Gold, 2009; Watson, Morris, & Miller, 1998). Personal Development Competitive Orientation. In contrast, a personal development competitive orientation is an alternative psychologically healthy perspective. This is characterized by competition with others, not against others; less interest on extrinsic outcomes (i.e., win/lose), but more intrinsic interest in the task itself and the self-evaluation and personal growth gained through competition. Horney (1937) posited that positive childhood experiences with warm, supportive parents would enable healthy interpersonal relationships and the participation in
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competitive pursuits with a sense of mutual respect and trust of others. Research has noted that this competitive orientation is related to different psychological and social health indicators, including high self-esteem, achievement and affiliation, empathic, altruistic, and forgiving, but not associated with neuroticism, dominance, and aggressiveness (e.g., Collier, Ryckman, Thornton, & Gold, 2010; Ryckman & Hamel, 1992; Ryckman, Hammer, Kaczor, & Gold, 1996; Ryckman, Libby, van den Borne, Gold, & Lindner, 1997). Among women, these two competitive orientations have been shown to relate differentially to disordered eating (Burkle, Ryckman, Gold, Thornton, & Audesse, 1999) as well as body dysmorphia and the acceptance and consideration of cosmetic surgery (Thornton, Ryckman, & Gold, 2013). In particular, Thornton et al. reported hypercompetitiveness to be positively related to both body dysmorphia and acceptance of cosmetic surgery, but hypercompetitiveness proved to be a stronger predictor of cosmetic surgery than body dysmorphia. In contrast, personal development competitiveness was negatively related, although not significantly so, to both body dysmorphia and consideration of cosmetic surgery. As such, hypercompetitive women may have a greater need to achieve unrealistic standards of appearance in a neurotic striving to overcome feelings of inferiority and gain advantage over female rivals in physical attractiveness; thus, the greater acceptance of cosmetic surgery as a means to enhance one’s appearance for such purpose. As with women, males today may feel increasingly pressured to achieve media-conveyed societal ideals for appearance and are showing an increased consideration of cosmetic surgery as a means to enhance their appearance, and perhaps their competitiveness in personal, social, and career realms. The present research was conducted to examine the relationship hypercompetitiveness and personal development competitiveness have with body dysmorphia and the acceptance of cosmetic surgery among men.
Method Participants and Procedure Participants consisted of a nonclinical sample of 131 Caucasian male undergraduates at a public university in the northeastern United States. Their mean age was 24.27 (SD = 6.49); ages ranged from 18 to 47. In exchange for extra credit in their psychology course, the students completed a set of questionnaires for the stated purpose of obtaining baseline data for comparison purposes in subsequent research. In addition to assessments of competitive orientations, body-image, and attitudes toward cosmetic surgery (described below), students provided height and weight with which to compute a body mass index (BMI; mean BMI was 25.08, and ranged from 17 to 31).
Assessment Instruments Hypercompetitive Attitude (HCA). The 26-item HCA scale is a reliable and valid assessment of individual differences in hypercompetitive attitudes (Ryckman et al., 1990). Sample items are “Winning in competition makes me feel more powerful as a person,” and “If you don’t get the better of others, they will surely get the better of you.” Participants respond to items on a 5-point Likert scale ranging from strongly disagree (1) to strongly agree (5). Scores can range from 26 to 130, with higher scores indicating a stronger hypercompetitive orientation. The
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internal consistency of this scale in the present study was adequate (α = 0.80). Personal Development Competitive Attitude (PDCA). The 15-item PDCA scale is a reliable and valid assessment of a psychologically healthy competitive orientation concerned more with personal growth and development than individual attainment (Ryckman et al., 1996). Sample items are “I value competition because it helps me to be the best that I can be,” and “I enjoy competition because it brings me and my competitors closer together as human beings.” Individual items are responded to on a 5-point scale, strongly disagree (1) to strongly agree (5). Scores can range from 15 to 75, with higher scores indicative of a greater personal development competitive attitude. The internal consistency of this scale in the present study was adequate (α = 0.85). Situational Inventory of Body-Image Dysphoria (SIBID). The 20-item SIBID is a reliable and valid assessment of individual differences with regard to people experiencing negative feelings about their bodies (Cash, 2002). Sample items are “I have negative emotional experiences when I look in the mirror,” and “I have negative emotional experiences when I am trying on new clothes at the store.” Items are responded to using a 5-point scale ranging from never (0) to almost always (4). Scores can range from 20 to 80, with higher scores reflecting greater body-image dysphoria. This scale had adequate internal consistency in the present study (α = 0.97). Acceptance of Cosmetic Surgery (ACS). The 15-item ACS scale is a reliable and valid assessment of individuals’ attitudes regarding acceptance of, and propensity for, cosmetic surgery (D. Henderson-King & E. Henderson-King, 2005). Sample items are “I would consider having cosmetic surgery as a way to change my appearance so that I would feel better about myself,” and “If I was offered cosmetic surgery for free, I would consider changing a part of my appearance that I do not like.” Items are responded to on a 5-point scale ranging from not at all (1) to very much (5). Scores can range from 15 to 75, with higher scores indicating greater acceptance of, and interest in having, cosmetic surgery. The internal consistency of the scale in the present study was adequate (α = 0.95). Social Self-Esteem. The Texas Social Behavior Inventory (TSBI; Helmreich & Stapp, 1974) is a reliable and valid 16-item assessment of an individual’s self-esteem reflecting one’s perceived level of social comfort and competence. Sample items are “I feel secure in social situations,” and “I enjoy social gatherings with other people.” Item responses used a 5-point scale ranging from not at all (1) to very much (5) characteristic of me. Scores could range from 16 to 80 with higher scores indicative of greater social self-esteem. Internal consistency of this measure in the present study was adequate (α = 0.75).
Results Correlational Analyses Pearson correlation coefficients were computed among the different variables and are presented in Table 1. Men’s age correlated positively with BMI (r = 0.23, p < 0.01). While older men had higher BMIs, their age was not related to situational body dysmorphia (r = 0.06). As might be expected, BMI and body dysmorphia were positively related, but not significantly so (r = 0.15). And, while older males generally had higher social self-esteem (r = 0.27, p < 0.01), they also were more favorably disposed toward cosmetic surgery (r = 0.33, p < 0.001), the latter
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Table 1. Intercorrelations among study variables.
Age BMI
Age
BMI
TSBI
SIBID
ACS
HCA
-
0.23b
0.27b
0.06
0.33c
0.07
0.06
-
0.02
0.15
0.06
0.22a
−0.16
-
−0.32c
−0.20a
0.05
0.47c
-
0.42b
0.13
−0.30c
-
0.28b
0.17
-
0.28b
TSBI SIBID ACS HCA
PDCA
Note: n = 131. ap < 0.05; bp < 0.01; cp < 0.001.
consistent perhaps with a youth-oriented cultural atmosphere. Acceptance of cosmetic surgery was also significantly related to body dysmorphia (r = 0.42, p < 0.001), but not BMI (r = 0.06). A similar pattern had been observed previously among women (Thornton et al., 2013). Interestingly, both hypercompetitiveness and personal development competitiveness were positively correlated with cosmetic surgery acceptance (rs = 0.28, p < 0.01 and 0.17, p < 0.05, respectively). The positive relationship between personal development, an otherwise healthy competitive orientation, and acceptance of cosmetic surgery was unexpected. This is in contrast to a negative relationship reported for women (Thornton et al., 2013) and may be due to a positive relationship between hypercompetitiveness and personal development competitiveness among men in the present study (r = 0.28, p < 0.01).
Regression Analysis To consider further the two competitive orientations and acceptance of cosmetic surgery, a hierarchical regression analysis was conducted with attitudes toward cosmetic surgery as the criterion. These results are summarized in Table 2. Men’s age, BMI, and social self-esteem were entered as an initial block to control statistically for individual differences on these variables (R2 = 0.12); F(3,127) = 5.83, p < 0.001. This was then followed by a stepwise consideration of body dysmorphia, hypercompetitiveness, and personal development competitiveness. Body dysmorphia was identified as the next best significant contributor to the prediction equation (R2 = 0.34, p < 0.001), F(4,126) = p < 0.001. Hypercompetitiveness was able to contribute further to the regression (R2 = 0.38), F(5,125) = 15.49, p < 0.001. Personal development competitiveness was excluded from entry as it did not contribute significantly to the regression.
Discussion Both correlational and regression analyses in the present study demonstrate that the two competitive orientations differ in their relationship to body dysmorphia and attitudes toward cosmetic surgery for men. While hypercompetitiveness was not related to body dysmorphia, it did relate positively with attitudes toward cosmetic surgery. In contrast, personal development competitiveness was negatively related to body dysmorphia, but was not significantly related to cosmetic surgery. Moreover, hypercompetiveness was found to be a significant predictor of acceptance of cosmetic surgery while personal development competitiveness failed to be of predictive utility in this regard, an outcome that is comparable to previous reports on women (Thornton et al., 2013). Dissatisfaction with one’s physical appearance is typically associated with favorable attitudes toward cosmetic surgery
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Table 2. Regression analysis for acceptance of cosmetic surgery. Variable
β
R2
t
ΔR2 b
Step 1
0.12
Age
0.30
3.35b
BMI
−0.01
−0.07
TSBI
0.12
1.37
Age
0.23
2.99
a
BMI
−0.07
−0.94
TSBI
0.30
3.74b
SIBID
0.53
6.52b
Age
0.25
b
3.09
BMI
−0.11
−1.51
TSBI
0.28
3.61b
SIBID
0.48
6.31b
HCA
0.51
2.84a
Step 2
Step 3
0.34b
0.22
0.38b
0.04
Note: Variable excluded at Step 3: PDCA, β = 0.15, t < 1.8, ns. ap < 0.01; bp < 0.001.
(Calogero et al., 2010; Slevec & Tiggemann, 2010). Interestingly, Menzel et al. (2011) have reported body dissatisfaction to be a stronger determinant of attitudes toward cosmetic surgery among men rather than women. The present findings with men are consistent with this notion in that body dysmorphia entered the regression prior to hypercompetitiveness, whereas in previous research with women (Thornton et al., 2013), body dysmorphia entered the regression following the inclusion of hypercompetitiveness. The increased emphasis on males’ appearance and the pressure on males to achieve some cultural ideal has been attributed, in part, to the increasing equality between men and women in the workplace (Pope et al., 2000). Women have become more able to compete directly with men for power and resources rather than having to “attract a mate” using their appearance. Traditionally, men could rely on skills, abilities, and a display of status and resources to be competitive in the interpersonal marketplace, however, manhood is becoming increasingly defined by youthful appearance and fitness and conveyed through glamorous depictions that objectify and dehumanize, the same issues that were demeaning for women (Faludi, 1999). Nevertheless, self-promotion based on their physical attractiveness, body image, and fitness remains a prime strategy among women, and is a common strategy among men as well, in intrasexual competition for the attention of prospective mates (Fisher & Cox, 2011). It would appear that a hypercompetitive orientation may very well contribute further to consideration of enhanced appearance through cosmetic surgery for both women and men independent of body image concerns. In their consideration of social and psychological factors that may contribute to favorable attitudes and behavior toward cosmetic surgery, Menzel et al. (2011) noted the need to identify such characteristics so that clinicians and surgeons might take them into account when determining the suitability of those seeking to undergo such procedures. While surgical and minimally invasive procedures may be of psychological and social benefit to those with subclinical (mild-moderate) appearance
concerns (Margraf, Meyer, & Lavallee, 2013), such treatments do not reduce the appearance concerns of those with body dysmorphic disorder, and may actually intensify their concerns (Crerand, Franklin, & Sarwer, 2006; Crerand, Menard, & Phillips, 2010). Following cosmetic treatments, those with body dysmorphic disorder frequently develop or shift their preoccupation to other appearance concerns (Tignol, Biraben-Gotzamanis, Martin-Guehl, & Grabot, 2007; Veale, 2000) and repetitively undergo cosmetic treatments to correct their perceived appearance defects (Crerand et al., 2010). Body dysmorphic disorder may be an obvious contraindication to cosmetic surgery. Considering the maladaptive nature of hypercompetitiveness, it also may be a personality trait of concern in this regard. With a neurotic need to compete and win at all costs in order to cope neurotically with feelings of inadequacy and feel good about themselves, the appearance domain may be one more arena in which hypercompetitive individuals must strive to best others. With the additional pressure of intrasexual competition among both men and women, a hypercompetitive orientation may contribute further to consideration of cosmetic surgery in order to be more competitive and ultimately “win” in their social and career endeavors. And, like those with body dysmorphic disorder, hypercompetitive individuals may never be satisfied with the results and seek additional treatments in a constant effort to maintain or enhance their competitive advantage through appearance.
REFERENCES Agliata, D., & Tantleff-Dunn, S. (2004). The impact of media exposure on males’ body image. Journal of Social and Clinical Psychology, 23, 7-22. American Psychological Association (2007). Report of the APA task force on the sexualization of girls. Washington, DC: Author. American Society of Plastic Surgeons (2012). Plastic surgery statistics report. http://www.plasticsurgery.org/news-and-resources/2012-plastic-surg ery-statistics.html Bessenoff, G. R. (2006). Can the media affect us? Social comparison, self-discrepancy, and the thin ideal. Psychology of Women Quarterly, 30, 2369-2251. Brownmiller, S. (1984). Femininity. New York: Simon & Schuster. Burckle, M. A., Ryckman, R. M., Gold, J. A., Thornton, B., & Audesse, R. J. (1999). Forms of competitive attitude and achievement orientation in relation to disordered eating. Sex Roles, 40, 853-870. Buss, D. M. (1989). Sex differences in human mate preferences: Evolutionary hypotheses tested in 37 cultures. Behavioral and Brain Sciences, 12, 1-49. Buss, D. M., & Dedden, L. (1990). Derogation of competitors. Journal of Social and Personal Relationships, 7, 395-422. Callaghan, G. M., Lopez, A., Wong, L., Northcross, J., & Anderson, K. R. (2011). Predicting consideration of cosmetic surgery in a college population: A continuum of body image disturbance and the importance of coping strategies. Body Image, 8, 267-274. Calogero, R. M., Pina, A., Park, L., & Rahemtulla, Z. (2010). The role of sexual objectification in college women’s cosmetic surgery attitudes. Sex Roles, 63, 32-41. Cash, T. F. (2000). Manuals for the appearance schemas inventory, body image ideals questionnaire, multidimensional body-self relations questionnaire, and situational inventory of body-image dysphoria. http://www.body-images.com Cash, T. (2002). The situational inventory of body-image dysphoria:
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Psychometric evidence and development of a short form. International Journal of Eating Disorders, 32, 362-366. Collier, S. A., Ryckman, R. M., Thornton, B., & Gold, J. A. (2010). Competitive personality attitudes and forgiveness of others. Journal of Psychology, 144, 535-543. Crerand, C. E., Franklin, M. E., & Sarwer, D. B. (2006). Body dysmorphic disorder and cosmetic surgery. Plastic and Reconstructive Surgery, 118, 1167-1180. Crerarnd, C. E., Menard, W., & Phillips, K. A. (2010). Surgical and minimally invasive cosmetic procedures among persons with body dysmorphic disorder. Annals of Plastic Surgery, 65, 11-16. Darwin, C. (1871). The descent of man and selection in relation to sex. London: John Murray. Davis, C., Karvinen, K., & McCreary, D. R. (2005). Personality correlates of a drive for muscularity in young men. Personality and Individual Differences, 39, 349-359. Derenne, J. L., & Beresin, E. V. (2006). Body image, media, and eating disorders. Academic Psychiatry, 30, 257-261. Dru, V. (2003). Relationships between an ego orientation scale and a hypercompetitive scale: Their correlates with dogmatism and authoritarianism factors. Personality and Individual Differences, 35, 1509-1524. Faludi, S. (1999). Stiffed: The betrayal of the American man. New York: Harper Collins. Fisher, M., & Cox, A. (2011). Four strategies used during intrasexual competition for mates. Personal Relationships, 18, 20-38. Franzoi, S. (1995). The body-as-object versus the body-as-process: Gender differences and gender considerations. Sex Roles, 33, 417437. Fredrickson, B. L., & Roberts, T. (1997). Objectification theory: Toward understanding women’s lived experiences and mental health risks. Psychology of Women Quarterly, 21, 173-206. Hatfield, E., & Sprecher, S. (1986). Mirror, mirror...The importance of looks in everyday life. Albany, NY: SUNY Press. Helmreich, R., & Stapp, J. (1974). Short forms of the Texas Social Behavior Inventory (TSBI), an objective measure of self-esteem. Bulletin of the Psychonomic Society, 4, 473-475. Henderson-King, D., & Henderson-King, E. (2005). Acceptance of cosmetic surgery: Scale development and validation. Body Image, 2, 137-149. Henderson-King, D., & Brooks, K. D. (2009). Materialism, sociocultural appearance messages, and parental attitudes predict college women’s attitudes about cosmetic surgery. Psychology of Women’s Quarterly, 33, 133-142. Horney, K. (1937). The neurotic personality of our time. New York: Norton. Jackson, L. A. (1992). Physical appearance and gender: Sociobiological and sociocultural perspectives. Albany, NY: SUNY Press. Langlois, J. H., Kalakanis, L., Rubenstein, A. J., Larson, A., Hallam, M., & Smoot, M. (2000). Maxims or myths of beauty? A meta-analytic and theoretical review. Psychological Bulletin, 126, 390-423. Margraf, J., Meyer, A. H., & Lavallee, K. L. (2013). Well-being from the knife? Psychological effects of aesthetic surgery. Clinical Psychological Science, 1, 239-252. Menzel, J. E., Sperry, S. L., Small, B., Thompson, J. K., Sarwer, D. B., & Cash, T. F. (2011). Internalization of appearance ideals and cosmetic surgery attitudes: A test of the tripartite influence model of body image. Sex Roles, 65, 469-477.
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Moradi, B., & Huang, Y. (2008). Objectification theory and psychology of women: A decade of advances and future directions. Psychology of Women Quarterly, 32, 377-398. Muth, J. L., & Cash, T. F. (1997). Body-image attitudes: What difference does gender make? Journal of Applied Social Psychology, 27, 1438-1452. Pope, H. G., Gruber, A. J., Choi, P., Olivardia, R., & Phillips, K. A. (1997). Muscle dysmorphia: An unrecognized form of body dysmorphia disorder. Psychosomatics, 38, 548-557. Pope, H. G., Phillips, K. A., & Olivardia, R. (2000). The Adonis complex: The secret crisis of male body obsession. New York: The Free Press. Ross, S. R., Rausch, M. K., & Canada, K. E. (2003). Competition and cooperation in the five-factor model: Individual differences in achievement orientation. Journal of Psychology, 137, 323-337. Rothblum, E. D. (1994). ‘I’ll die for the revolution but don’t ask me not to diet’: Feminism and the continuing stigmatization of obesity. In P. Fallon, M. A. Katzman, & S. C. Wooley (Eds.), Feminist perspectives on eating disorders (pp. 53-76). New York: Guilford Press. Ryckman, R. M., & Hamel, J. (1992). Female adolescents’ motives related to involvement in organized team sports. International Journal of Sport Psychology, 23, 147-160. Ryckman, R. M., Hammer, M., Kaczor, L. M., & Gold, J. A. (1990). Construction of a hypercompetitive attitude scale. Journal of Personality Assessment, 55, 620-629. Ryckman, R. M., Hammer, M., Kaczor, L. M., & Gold, J. A. (1996). Construction of a personal development competitive attitude scale. Journal of Personality Assessment, 66, 374-386. Ryckman, R. M., Libby, C. R., van den Borne, B., Gold, J. A., & Lindner, M. A. (1997). Values of hypercompetitive and personal development competitive individuals. Journal of Personality Assessment, 69, 271-283. Ryckman, R. M., Thornton, B., Gold, J. A., & Burckle, M. A. (2002). Romantic relationships of hypercompetive individuals. Journal of Social and Clinical Psychology, 21, 517-530. Ryckman, R. M., Thornton, B., & Butler, J. C. (1994). Personality correlates of the Hypercompetitive Attitude Scale: Validity tests of Horney’s theory of neurosis. Journal of Personality Assessment, 62, 84-94. Sherrow, V. (2001). For appearance’ sake: The historical encyclopedia of good looks, beauty, and grooming. Westport, CT: Oryx Press. Slevec, S., & Tiggemann, M. (2010). Attitudes toward cosmetic surgery in middle aged women: Body image, aging anxiety, and the media. Psychology of Women Quarterly, 34, 65-74. Thompson, J. K., & Cafri, G. (2007). The muscular ideal. Washington, DC: American Psychological Association. Thompson, J. K., Schaefer, L., & Menzel, J. (2012). Internalization of the thin and muscular ideal. In T. F. Cash (Ed.), Encyclopedia of Body Image and Human Appearance (pp. 499-504). Waltham, MA: Academic Press. Thornton, B., Lovley, A., Ryckman, R. M., & Gold, J. A. (2009). Playing dumb and knowing it all: Competitive orientation and impression management strategies. Individual Differences Research, 7, 265-271. Thornton, B., Ryckman, R. M., & Gold, J. A. (2013). Competitive orienttations and women’s acceptance of cosmetic surgery. Psychology: Individual Development, 4, 67-72. Tignol, J., Biraben-Gotzamanis, L., Martin-Guehl, C., Grabot, D., & Aouizerate, B. (2007). Body dysmorphic disorder and cosmetic surgery: Evolution of 24 subjects with a minimal defect in appearance 5 years after their request for cosmetic surgery. European Psychiatry, 22, 520-524. Veale, D. (2000). Outcome of cosmetic surgery and ‘DIY’ surgery in patients with body dysmorphic disorder. The Psychiatrist, 24, 218-221.
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petitiveness. Imagination, Cognition, and Personality, 17, 249-259. Veale, D. (2004). Advances in a cognitive behavioral model of body dysmorphic disorder. Body Image, 1, 113-125.
Wolf, N. (1991). The beauty myth: How images of beauty are used against women. New York: William Morrow and Company.
Watson, P. J., Morris, R. J., & Miller, L. (1998). Narcissism and the self as continuum: Correlations with assertiveeness and Hypercom-
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12 Neuropsychological Profile of Anti-NMDA Receptor Encephalitis Laura Marcos-Arribas1, Justino Jiménez Almonacid2, Alberto Marcos Dolado2* 1
Social and Human Sciences Faculty, Comillas Pontifical University, Madrid, Spain 2 Neurology Department, Hospital Clínico San Carlos, Madrid, Spain
Anti-N-methyl-d-aspartate (NMDA) receptor encephalitis is a life-threatening disorder that often occurs as a paraneoplastic encephalitis and usually begins with neuropsychological or psychiatric symptoms. We report a case of NMDA receptor encephalitis due to an ovarian teratoma, which began with severe and progressive amnesia and behavioral changes, reversed after surgical treatment and plasmapheresis. Using a battery of cognitive tests, its neuropsychological profile before treatment showed a complete alteration of the short and long term memory of both verbal and visual fixation, with clear improvement with cues and with intrusions, and saving other cognitive domains, such as working, episodic and semantic memory, executive, visuospatial, praxical thinking and language functions. These deficits reverted to normalcy with treatment. So, we can conclude that anti-NMDA receptor encephalitis is a rare entity that can be potentially serious depending on early management and diagnosis. We must suspect this entity in children or young people presenting with behavioural disturbances and crisis, with a cognitive pattern of complete alteration in short and long term memory improving with cues, and respecting other cognitive domains. Keywords: Anti-NMDA Receptor Encephalitis; Ovarian Teratoma; Amnestic Syndrome; Priming; Neuropsychology
Introduction Anti-N-methyl-d-aspartate (NMDA) receptor encephalitis is a life-threatening disorder that often occurs as a paraneoplastic neuropsychiatric encephalitis (Rosenfeld, 2011). It predominantly affects young women with a strong association with ovarian teratomas but can be recognized also in women without tumors, in men and in children (Dalmau, 2008; Prüss, 2010; Dalmau, 2011). Its frequency and prevalence is unknown because of the rarity of its appearance. Due to the role that NMDA receptor plays in learning this entity normally begins with memory deficits, but also with psychiatric symptoms and seizures. The presence of type NMDA autoantibodies in serum or cerebrospinal fluid is specific for this novel disorder and has changed not only the diagnosis of the entity but also the concept of inmunomediated cerebral disorders (Suzuki, 2013; Rosenfeld & Titulaer, 2012). The removal of the ovarian teratoma and the early immunological treatment improves the prognosis decreasing the risk of recurrence, but the early diagnosis only depends on prompt suspicion and the rapid recognition of its clinical manifestations (Iizita, 2010; Johnson, 2010; Alexopoulos, 2011; Young 2013). And although the initial and predominant presentation of this disease is the neuropsychological clinic, little information about the cognitive deficits is available (Finke, 2012). Therefore, we report a case of a NMDA receptor encephalitis due to an ovarian teratoma who debuted with severe and pro*
Corresponding author.
gressive amnesia and behavioral changes, describing her attentional, mnesic, executive, linguistic and praxis profiles before and after successful treatment.
Case Report A 24-year-old woman was taken to the emergency room by her colleagues for consistent behavior disorders, repeating recurring questions and difficulties completing routine daily job duties. She had no personal or family history of medical or neurological diseases. She had been working in a management company for six months, and was highly educated. She was not taking any medications or recreational drugs, but consumed alcohol occasionally. Although the clinical picture was exacerbated in the day of admission, similar difficulties had been progressively presented all along the previous month, with lack of flexibility, mental rigidity, emotional lability and irritability. She does not complain of headache or fever. The general exam was normal but hyperperspiration. The neurological examination in the emergency room showed a normal consciousness level with good collaboration but suspicious behavior. The language was normal in comprehension, repetition, naming and fluency. There was no negligence. A short memory deficit was evident, with inability to recognize the examiner after five minutes, repeated questions about her situation, normal event and semantic memory with lacunar retrograde amnesia regarding recent weeks. Visual field,
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eye fundus, pupils, cranial nerves exam, motor, sensory and coordination systems, reflexes and gait were normal. No meningeal signs were present. From a behavioral point of view during examination the patient worked at any time in carrying out the tests. She has a great interest on what her condition was, showing a good sense of humor, sometimes joking. Despite this, the patient was nervous throughout the whole process, worrying constantly about the reason for the evaluation, and how she would recover from what was going on. Sometimes she showed frustration or irritability when not performing either an exercise or when we did not explain her exactly what we are testing. Because of her fixing inability she sometimes feels disoriented and with repeated blocked moments. She also had episodic psychomotor agitation and anxiety, referred to taste “glue” sensations. The patient had partial knowledge of the problem and stated “I was living like the movie Memento”. She needed to write down everything that she could not remember from what had been explained, visits, etc. With a suspected syndromic diagnosis of subacute anterograde amnesia due to limbic or autoimmune encephalitis we began treatment with an antiepileptic drug and performed a cranial tomography scan, blood and cerebrospinal fluid analysis, all reported as normal. The patient was admitted to study and a magnetic resonance imaging and breast exploration showed no abnormalities. During admission, the patient had fluctuating behavior disorders such as psychomotor agitation, mild desinhibition, bad mood and some delusions. She also presents no response to external stimuli episodes, lasting seconds. And EEG was normal but for diffuses low waves. The gynecological ultrasound exam detected a tumor in the left ovary, suggestive of teratoma. Surgery was scheduled. Then we performed the following neuropsychological battery: Information and orientation subtest of the Weschler Memory Scale III (WMS-III). Logical Memory I and II of the WMS-III. Semantic memory. Episodic memory. Couple of words I and II of the WMS-III. Symbols subtest of the WAIS-III. Word List of the WMS-III. Letter-Number sequencing of the WMS-III. Digit span, both in forward and reverse order. Rey-Osterrieth Complex Figure (Figures 1 and 2). Visual Photo-test (Carnero, 2004). Boston Naming Test (30 items). Memory Imparment Screen (MIS) (Buschke, 1999). Overlaping figure test of Poppelreuter. Ideomotor praxias. Ideative praxias. Bimanual and unimanual sequencing task. Graphic programming (Figures 3 and 4). Abstract thinking. Semantic errors inhibition. FAS. Bimanual Luria maneuver. The patient underwent surgery within 7 days since admission and the diagnosis of mature ovarian teratoma was confirmed by pathology studies. Nine alternate days sessions of plasmapheresis were then started. The presence of antibodies directed against the NMDA receptor was confirmed in cefalospinal fluid.
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Figure 1. Rey-Osterrieth Complex Figure copy.
Figure 2. Rey-Osterrieth Complex Figure immediate recall.
Figure 3. Alternating programming.
Figure 4. Graphic loops.
After one month we repeated the neuropsychological battery. The previous and final results were shown in Table 1, and Figures 5-7. As we see, the patient regained almost normal mental state in four weeks, and gradually all behavioral disorders
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Figure 5. Rey-Osterrieth Complex Figure copy after treatment.
Figure 6. Rey-Osterrieth Complex Figure immediate recall after treatment.
Figure 7. Rey-Osterrieth Complex Figure delayed recall after treatment.
and seizures disappeared. After 4 months of follow-up she remains asymptomatic having recovered their normal complex functionality.
Discussion In a patient with abrupt onset of short term memory loss, behavioural changes and temporal lobe seizures we classically must discard limbic encephalitis (Zuliani, 2012). In the last few
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years the encephalitis associated with NMDA receptor antibodies has been characterised as distinct forms from the limbic encephalitis, above all because of the higher proportion of patients are children or young women initially admitted to emergency hospitals for acute anxiety, behavioural change or psychosis (Rosenfeld & Dalmau, 2012). Anti-NMDA receptor encephalitis belongs to the group known as paraneoplastic neurological syndromes, which are a rare and heterogeneous group of diseases that can affect any area of the nervous system having in common their association with cancer (often hidden in the time of clinical onset) and a likely autoimmune pathogenesis (Rosenfeld, 2011). Specifically, the anti-NMDA antibodies associated with different types of extra-limbic encephalitis and limbic structures has recently partnered with a neurological syndrome characterized by disturbances of consciousness, involuntary movements and seizures (Dalmau, 2008; Lebon, 2012; Waas, 2012). It is considered as a paraneoplastic syndrome associated primarily with ovarian tumors in young women, but can occur in the absence of neoplasia. In most cases, we can detect also severe alterations of consciousness, dysautonomia, complex involuntary movements, hyperthermia and respiratory failure requiring treatment in intensive care units. In our case, we directly search for an underlying tumor due to clinical debut and having ruled other entities out with additional studies. We do not wait for confirmation with autoimmune antibody assays, as this usually comes belatedly, so that does not change the initial management. Usually, tumor resection leads to complete recovery of clinical with few long-term neurological sequels (Tanyi, 2012; Boeck, 2013; Dabner, 2012; Pham, 2011; Titulaer, 2013). It so occurred in our patient, with complete recovery of initial deficits in about a month of evolution. But not rarely, this entity can have a poor neurological recovery with permanent deficits (Armangue, 2012; Peery, 2013). The clinical onset of this entity is similar in signs and symptoms to other diseases, so only high clinical suspicion lead to an early diagnosis. Given the large impact on the prognosis of early institution of treatment, it is a priority to know their neuropsychological profile to suspect the entity among compatible cases. At admission our patient showed severe impairment of short-term memory and memory setting, presenting a retrograde gap about the facts of the last two months. She also showed a mild impairment in working memory and attention, without alterations in semantic and episodic memories, executive, visuospatial, praxical, thinking and language functions. To be more specific, testing the Information and Orientation part of the WMS-III, the patient was oriented in person, but not in time or space. We can explain this altered alopsiquic consciousness by the absence of mnemonic fixation. In Logical Memory task of WMS-III she obtained very low scores, with a learning curve with negative value, indicating not only that there was no learning but there were also information lost between B1 to B2 stories. Furthermore, the total score in Logical Memory II have decreased until zero since the first presentation, representing a null retention. However, the total score on Recognition of Logical Memory was high for both A and B stories, indicating a good facilitated cued recall. In the Rey Complex Figure the patient reported difficulties to hold and handle the pencil but clear apraxia was not evident. The copy was made in 24 minutes, for her high perfectionism and obsessive behavior, without visuospatial or praxical deficits.
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Table 1. Neuropsychological battery scores before and after treatment. Before Treatment
After Treatment
9/13
11/13
Logical Memory I
Story A: 10/25 Story B1: 9/25 Story B2: 8/25 Total (A+B1): 19/50 Total (A+B1+B2): 27/75 Learning curve (B2-B1): −1
Story A: 21/25 Story B1: 13/25 Story B2: 19/25 Total (A+B1): 34/50 Total (A+B1+B2): 53/75 Learning curve (B2-B1): 6
Logical Memory II
Story A: 0/25 Story B1: 0/25 Total (A+B): 0/50
Story A: 20/25 Story B1: 17/25 Total (A+B): 35/50
Recognition
Story A: 10/15 Story B: 10/15
Story A: 13/15 Story B: 14/15
Retention Percentage
Information and Orientation (WMS III)
Logical Memory (WMS III)
0%
87.5%
Semantic Memory
14/15
14/15
Episodic Memory
10/10
10/10
Couple of Words I
List A: 0/8 List B: 0/8 List C: 2/8 List D: 1/8 Learning slope (List D-A): 1
List A: 5/8 List B: 7/8 List C: 8/8 List D: 8/8 Learning slope (List D-A): 3
Couple of Words II
Total score: 0/8
Total score: 8/8
Recognition
16/24
24/24
Retention Percentage
0%
100%
Symbols (WAIS III)
Hits: 43 Mistakes: 1 Immediate Recall: 0/9
Hits: 45 Mistakes: 5 Immediate Recall: 9/9
Word List (WMS III)
List A: First trial: 7/12 Second trial: 5/12 Third trial: 5/12 Fourth trial: 6/12 Intrusions: 1 Total score: 23/48 List B: 4/12 Intrusions: 2 List A Recall: 0/12 First contrast (List A first trial-List B): 3 Learning curve (List A fourth trial-List A first trial): −1 Second contrast (List A fourth trial-List A recall): 5
List A: First trial: 6/12 Second trial: 10/12 Third trial: 10/12 Fourth trial: 12/12 Intrusions: 1 Total score: 38/48 List B: 7/12 Intrusions: 0 List A Recall: 10/12 First contrast (List A first trial-List B): −1 Learning curve (List A fourth trial-List A first trial): 6 Second contrast (List A fourth trial-List A recall): 2
Letter-Number (WMS III)
9/27
11/27
Digit Span
Forward order: 9/16 Reverse order: 7/14 Total: 16/30
Forward order: 10/16 Reverse order: 8/14 Total: 18/30
Rey-Osterrieth Complex Figure
Copy: 36/36 (24 minutes) Immediate recall: 3/36 (1 minute) Delayed recall: 0/36
Copy: 36/36 (26 minutes) Immediate recall: 28/36 (4 minute) Delayed recall: 29/36 (5 minute)
Visual Photo-test
36
47
Boston Naming Test (30)
28
30
MIS of Buschke
0/8
8/8
Poppelreuter
15/15
15/15
Ideomotor Praxias
Right arm 6/6 Left arm 6/6 Bimanual 3/3
Right arm 6/6 Left arm 6/6 Bimanual 3/3
Ideative Praxias
Right arm 3/3 Left arm 3/3 Bimanual 2/2
Right arm 3/3 Left arm 3/3 Bimanual 2/2
Sequencing Task
Right arm 1/1 Left arm 1/1 Bimanual 1/1
Right arm 1/1 Left arm 1/1 Bimanual 1/1
Couple of Words (WMS III)
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Continued Graphic Programming
6/6
6/6
Abstract Thinking
12/12
12/12
Semantic Errors Inhibition
4/5
5/5
FAS
F: 20 A: 21 S: 20
F: 21 A: 25 S: 23
Bimanual Luria Maneuver
Right arm 1/1 Left arm 1/1
Right arm 1/1 Left arm 1/1
She did all copy taking reference measurements with the pencil using the paper as a rod, jumping from one line to another although the form was not completed and repeating some steps. In the Immediate Recall test, which took exactly one minute, she obtained an extremely low score, indicating a huge failure of retention. In the Delayed Recall test she did not only forgot the figure but also did not remembered having been copying or watching it, showing total anterograde amnesia. In the first completion of Couples of Words of WMS-III she obtained a very low learning slope. The patient was unable to respond almost a single right word and invented words with similar semantic categories. The word pairs recalling was null, showing angry because of it, improving a lot the recognition later. The same happened with the delayed recall, obtaining a 0% of retention percentage. The performance of copy part of the Symbols test in WAIS-III was appropriate, but she showed an inadequate capacity to retain any symbol. In the Word List test from the WMS-III, the patient showed a very low grade of retention being the last words the most repeated, with some intrusions. The delayed recall was again very poor since she could not remember any word. With the successive repetitions she obtained a negative learning curve, meaning anterograde amnesia. In the Letter-Number test in WMS-III the patient’s score was very low for her inability to remember the slogan, showing that short memory is also altered. The working memory was adequate, with normal score in the Digit Span, direct and reverse, like her executive function. The semantic and episodic memories were assessed with two sets of structured questions on general knowledge and past events. Both were normal. To evaluate the visual memory we performed a Spanish validate test, the Photo-Test of Carnero et al. (Carnero, 2004). This test shows six objects for patient to name, performing it after an interference task, evoking male names for a half-minute, and woman names for a half-minute more. Then the patient is asked for the pictures. We can provide cues if not remembered by the patient. The patient obtained a normal score on gender name fluency, but a null visual delayed recall, with good recovery after cues. We can conclude something similar about the MIS, with null delayed memory, although in this case she did not improve with cues. We cannot observe any difficulties in language evocation in Boston Naming Test or fluency in FAS, visuospatial perception on Poppelreuter, apraxic or disexecutive disturbance on bimanual and unimanual sequencing task and Luria, graphic programming, semantic errors inhibition and abstract thinking. With the evolution we show a clear improvement of the cognitive and behavioral picture of the patient within almost the normal score range on the neuropsychological battery. As sig-
nificant data outside the normal in this second cognitive assessment, we found the results of Symbols and Letter-Number tests. We can probably explain this because the patient was somewhat inattentive and trying to finish fast the examination. In addition, throughout the interview was evident great improvement in the recognition with cues, above all in Logical Memory, Couple of Words and Photo Test. Given that in this type of encephalitis the main involvement are the hippocampal and limbic systems, one would expect an absence of gain with tracks, as in all the hippocampal memory models. But, this is not our patient’s case, and suggests to us a beneficial effect of priming, which cannot be explained by other means or cognitive resources. Therefore, we can characterize the neuropsychological profile of the NMDA receptor encephalitis as a complete alteration of the short and long memory of both verbal and visual fixation, with clear improvement with cues for priming effect and with intrusions, and saving other cognitive domains, as working and semantic memories, executive, visuospatial, praxical, thinking and language functions.
Conclusion Anti-NMDA receptor encephalitis is a rare entity that can be potentially very serious, depending the complete reversal of the deficits and good prognosis on the early treatment. Since this disease usually debuts with cognitive and behavioural symptoms, a neuropsychological characterization is essential to help the early diagnosis. We must suspect this entity in children or young people presenting with behavioural disturbances and crisis, with a complete alteration of the short and long memory improving with cues, and respecting other cognitive domains.
Acknowledgements The authors thank M. J. García Barrero for reviewing the manuscript.
REFERENCES Alexopoulos, H., Kosmidis, M. L., Dalmau, J., & Dalakas, M. C. (2011) Paraneoplastic anti-NMDAR encephalitis: Long term follow-up reveals persistent serum antibodies. Journal of Neurology, 258, 15681570. Armangue, T., Petit-Pedrol, M., Dalmau, J. (2012). Autoimmune encephalitis in children. Journal Child Neurology, volume 11, pages 1460-9. Boeck, A.L., Logemann, F., Krauß, T., Hussein, K., Bültmann, E., Trebst, C., & Stangel, M. (2013). Ovarectomy despite negative imaging in anti-NMDA receptor encephalitis: Effective even late. Case Reports in Neurological Medicine, 2013, Article ID: 843192. Buschke, H., Kuslansky, G., Katz, M., Stewart, W. F., Sliwinski, M. J., Eckholdt, H. M., & Lipton, R. B. (1999). Screening for dementia
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withthe memory impairment screen. Neurology, 2, 231-238. Carnero, C., & Montoro, M. T. (2004). El Test de las Fotos. Revista de Neurología, 9, 801-806. Dalmau, J., Gleichman, A. J., Hughes, E. G., et al. (2008) AntiNMDA-receptor encephalitis: Case series and analysis of the effects of antibodies. The Lancet Neurology, 7, 1091-1098. Dabner, M., McCluggage, W. G., Bundell, C., Carr, A., Leung, Y., Sharma, R., & Stewart, C. J. (2012). Ovarian teratoma associated with anti-N-methyl D-aspartate receptor encephalitis: A report of 5 cases documenting prominent intratumoral lymphoid infiltrates. International Journal of Gynecological Pathology, 31, 429-437. Dabner, M., McCluggage, W. G., Bundell, C., Carr, A., Leung, Y., Sharma, R., & Stewart, C. J. (2012). Ovarian teratoma associated with anti-N-methyl D-aspartate receptor encephalitis: A report of 5 cases documenting prominent intratumoral lymphoid infiltrates. International Journal of Gynecological Pathology, 31, 429-437. Finke, C., Kopp, U. A., Prüss, H., Dalmau, J., Wandinger, K. P., & Ploner, C. J. (2012). Cognitive deficits following anti-NMDA receptor encephalitis. Journal of Neurology, Neurosurgery & Psychiatry, 83, 195-198. Iizuka, T., Yoshii, S., Kan, S., et al. (2010). Reversible brain atrophy in anti-NMDA receptor encephalitis: A long-term observational study. Journal of Neurology, 257, 1686-1691. Johnson, N., Henry, C., Fessler, A. J., & Dalmau, J. (2010). AntiNMDA receptor encephalitis causing prolonged nonconvulsive status epilepticus. Neurology, 75, 1480-1482. Lebon, S., Mayor-Dubois, C., Popea, I., Poloni, C., Selvadoray, N., Gumy, A., & Roulet-Perez, E. (2012). Anti-N-methyl-D-aspartate (NMDA) receptor encephalitis mimicking a primary psychiatric disorder in an adolescent. Journal of Child Neurology, 27, 1607-1610. Peery, H. E., Day, G. S., Doja, A., Xia, C., Fritzler, M. J., & Foster, W. G. (2013). Anti-NMDA receptor encephalitis in children: The disorder, its diagnosis, and treatment. Handbook of Clinical Neurology, 112, 1229-1233.
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of anti-NMDA receptor encephalitis. Journal of Clinical Apheresis, 26, 320-325. Prüss, H., Dalmau, J., Harms, L., Höltje, M., Ahnert-Hilger, G., Borowski, K., Stoecker, W., & Wandinger, K. P. (2010). Retrospective analysis of NMDA receptor antibodies in encephalitis of unknown origin. Neurology, 75, 1735-1739. Rosenfeld, M. R., Dalmau, J. (2011). Anti-NMDA-receptor encephalitis and other synaptic autoimmune disorders. Current Treatment Options in Neurology, 13, 324-332. Rosenfeld, M. R., & Dalmau, J. O. (2012). Paraneoplastic disorders of the CNS and autoimmune synaptic encephalitis. Continuum (Minneaplis, Minn), 2, 366-383. Rosenfeld, M. R., Titulaer, M. J., & Dalmau, J. (2012). Paraneoplastic syndromes and autoimmune encephalitis: Five new things. Neurology Clinical Practice, 2, 215-223. Suzuki, S., Seki, M., & Suzuki, N. (2013). Recent concept of limbic encephalitis: Progress in anti-NMDA receptor encephalitis. Japanese Journal of Clinical Immunology, 36, 86-94. Tanyi, J. L., Marsh, E. B., Dalmau, J., & Chu, C. S. (2012). Reversible paraneoplastic encephalitis in three patients with ovarian neoplasms. Acta Obstetricia et Gynecologica Scandinavica, 91, 630-634. Titulaer, M. J., McCracken, L., Gabilondo, I., et al. (2013). Treatment and prognostic factors for long-term outcome in patients with antiNMDA receptor encephalitis: An observational cohort study. The Lancet Neurology, 12, 157-165. Young, P. J., Baker, S., Cavazzoni, E., Erickson, S. J., Krishnan, A., Kruger, P. S., Rashid, A. H., & Wibrow, B. A. (2013). A case series of critically ill patients with anti N-methyl-D-aspartate receptor encephalitis. Critical Care and Resuscitation, 1, 8-14. Waas, J. A., & Storm, A. H. (2012). Anti-NMDA-receptor encephalitis: A neuropsychiatric illness requiring further study. Tijdschrift voor Psychiatrie, 54, 279-283. Zuliani, F., Graus, F., Giometto, B., et al. (2012). Central nervous system neuronal surface antibody associated syndromes: Review and guidelines for recognition. Journal of Neurology, Neurosurgery & Psychiatry, 83, 638-645.
Pham, H. P., Daniel-Johnson, J. A., Stotler, B. A., Stephens, H., & Schwartz, J. (2011). Therapeutic plasma exchange for the treatment
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13 The Effects of Family Structure on the Development of Bilinguality Lily Halsted Queens University of Charlotte, Charlotte, USA
This study examines the role of family structure in the development of different levels of bilinguality. Students from five different public and private universities responded to an extensive survey on various aspects of bilinguality. Participants were divided into three groups: monolinguals, non-fluent bilinguals and fluent bilinguals. In line with the initial hypothesis, higher levels of bilinguality correlated with having more bilingual family members. Also further evidence was found for the importance of the mother, father and sisters in becoming bilingual. Additionally, the presence of bilingual step-parents and grandparents on acquisition and maintenance of a second language was examined and fund to be much less influential than the role of the parents. Finally, the influence of socio-economic status (SES) on development of bilinguality was measured with no clear effect being found. The unique contribution of this study is that it attempts to connect the influence of specific family members to different levels of bilinguality. Keywords: Bilingualism; Heritage Languages; Monolinguals; Language Use Surveys
Introduction It is estimated that over 70% of the world’s population speak more than one language (Trask, 1999). Trask asserts that being able to speak two or more languages has most likely been the norm across societies for thousands of years. A key question is how large majorities of people—then and now—have been able to acquire and maintain more than a single language. One possible explanation is the influence of family members and the home linguistic environment on the individual. In recent years there have been a number of studies that have examined the effect of family dynamics on the presence and advancement of bilinguality in children (Harding & Riley, 1986; Gregory & Williams, 2000; Kenner, 2000; Obied, 2009; Dale, Harlaar, Haworth, & Plomin, 2010). In the United States immigrants create the most common bilingual environments in families. We know that immigrant children often choose not to interact with one another in their parents’ (heritage) language but instead adopt the dominant language of that society (Miller, 1983). This choice can ultimately lead to the inhibition of the parents’ language in the younger generation (Levy, McVeigh, Marful, & Anderson, 2007). This may be why the rate of bilinguality is estimated to be only 20% in the United States (Shin & Kominski, 2010) as opposed to 70% for the rest of the world. There have been many studies that have documented some of the benefits of bilinguality in such areas as executive control (Bialystok, 1986, 1988, 1999; Bialystok & Craik, 2010), achievements in physics and mathematics (Farrell, 2011), success in acquisition of foreign languages as adults (Eisenstein, 1980; Thomas, 1988; Keshavarz & Astaneh, 2004) and a decreased reduction in attentional processes as a result of natural aging for bilinguals (Bialystok, Craik, Klein, & Viswanathan, 2004; Bia-
lystok, Craik, & Ryan, 2006). At the same time, there seem to be some disadvantages to being bilingual including lower scores recorded in vocabulary tests in both languages (Oller & Eilers, 2002) and a reduction of access to the first language after a period of immersion in the second language (Linck, Kroll & Sunderman, 2009). As the lifelong advantages of being bilingual would seem to outweigh the disadvantages it is important to determine how one becomes and remains bilingual or even multilingual. In general, the path of bilingual child rearing seems to be influenced by family structure. Within the immediate family, the role of mothers in the encouragement and promotion of bilingualism in children has been emphasized in the past (Baker, 2000). The argument is that mothers, especially stay at home mothers, spend more time with their children. If the mothers speak a different language, they have more opportunities to promote bilinguality in their children. Of course this will only occur if the mother chooses to use her native language with her children. Some mothers prefer to promote the dominate language of their culture with their children to make sure the child assimilates better into society. The role of the father in the linguistic development of children, on the other hand, is more reflective of the affiliative nature of his relationship with his smaller children. Fathers’ language use often relates to the same context as their children, in contrast to the mother’s language which tends to be more practical and disciplinary in nature (Baker, 2000). However, when the mother is the speaker of the minority language in the family the children seem to have a higher chance of adoption of that language compared to when the father is the minority speaker. This effect exists, perhaps, because even in our mod-
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ern societies mothers spend more time with their children (Clyne, 1982; Kamada, 1995). Furthermore, some studies show that the possibility of bilingual development increases when both parents speak the minority language at home or when they both speak the minority language but only one also speaks the dominant language (Yamamoto, 2001). Clearly, this is a fairly stringent requirement for the adoption of a minority language. In addition, some of the newer studies place greater emphasis on the importance of schooling in the promotion and maintenance of bilinguality (Shin, 2005). In terms of the possible influence of siblings in the bilingual development of the child, some studies indicate that first-born children are more likely to become bilinguals in comparison to later born children (Manaster, Rhodes, Marcus, & Chen, 1998). It also seems that older children are more likely to become bilingual and encourage and promote bilinguality and biliteracy in their younger siblings (Baker, 1995; Gregory & Williams, 2000, Obied, 2009). As for a particular dynamic among siblings, there is some evidence that in general sisters are better at encouraging the advancement of the minority language in their siblings and can be good language teachers to their younger brothers (Azimita & Hesser, 1993; Rashid & Gregory, 1997). Most studies that focus on family dynamics and second language development tend to examine the evidence within one culture or one linguistic environment (Obied, 2009, Portuguese; Yamamoto, 2001, Japanese; Shin, 2005, Korean; Rashid & Gregory, 1997, Sylheti; Farrell, 2011, Maltese; Bialystok, Craik, Klein, & Viswanathan, 2004, Tamil; Linck, Kroll, & Sunderman, 2009, Spanish). We know that different cultural attitudes, as well as pride and the degree of determination to preserve one’s heritage and language, can influence how much of an effort parents and the family as a whole make to preserve their native language (Baker, 1995). Now, as has been true many other times during the course of human history, all languages are not viewed as equal. Based on the large number of people who wish to adopt or communicate in a particular language, some languages, such as Latin, were considered prestige languages. Currently, in many areas of the world English is considered a prestige language. This is in contrast to heritage languages which are spoken by fewer individuals in the community and are typically not taught in schools. Over time, these heritage languages tend to lose ground to prestige languages and are increasingly forgotten by later generations of immigrant families (Lambert & Taylor, 1990; Shum, 2001). In an effort to control for possible differences in culture, ethnicity and language as they relate to family structure, the subjects in the present study were recruited from five different colleges and universities in two different states. By casting a wide net it was possible to include participants who spoke a diverse range of heritage languages and came from families with origins in many different countries outside of the United States. Socioeconomic status (SES) has also been considered as another factor that can affect bilinguality in children (Morton & Harper, 2007). To see if SES had any role, the subjects for the current study were recruited from a variety of academic institutions (private and state universities, and a community college) with very different tuition and family income levels. Overall, the advantages of being bilingual outweigh the disadvantages. Clearly, many societies in the world are aware of this fact and adhere to it, while in the United States we continue to lag behind the rest of the world in the development and maintenance
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of bilinguality in our children and adolescents. In the present study it was hypothesized that with bilingual participants, and especially fluent bilinguals, there would be a strong influence of immediate family members (parents and siblings) on the advancement of the subjects’ second language fluency. This will not be the case in monolinguals and will play a less significant role with less fluent bilinguals. It was expected that grandparents would not have as much influence as parents or siblings as they tend to be less available during a person’s childhood when most language development takes place. In general, it was expected that bilingual and fluent bilingual subjects have more family members in their household who speak a minority language. It was also expected that step-parents would play a similar role as grandparents in a child’s second language development. School was expected to have a lesser influence than family on second language acquisition.
Method Subjects The subjects for this study consisted of 122 college students, 93 of these students (76%) were females and 29 (24%) were males. This ratio reflects the larger number of female psychology students at the participating institutions. The subjects for this study included students from four public and private universities as well as a community college. Four of these institutions were located in North Carolina and one in Tennessee. Participants ranged in age from 18 to 52 years old. The mean was 22.4 years (SD = 5.71) and median was 21 years. Out of 122 subjects, 49 reported themselves to be bilingual. The remaining 73 subjects spoke only one language: (monolingual). All subjects were English speakers, with the second language spoken by the bilingual subjects included Spanish, French, Polish, Farsi and German. Most of the subjects were enrolled in various psychology classes and participated in this study in exchange for extra credit. The socio-economic background of subjects was diverse. A high proportion of the private university students came from higher income families, while the students from the public universities were more representative of the middle class. Students attending the community college had a lower average family income compared to the other two groups. Specific characteristics of the subjects are reported in Table 1.
Procedures and Measures A 100-item, multi-scale online survey on bilinguality was designed for this study and made available to participating students. In addition to basic demographic information, the survey measured the level of competence of the participants in a second language (reading, writing and speaking). It also measured the subject’s level of interest and engagement in their second language, as well as the amount of time spent in reading or conversation in that language. The 48 questions that dealt specifically with the levels, depth and the frequency of bilingual behaviors in the subjects are listed in the appendix. In this survey we also tried to determine the sources and causes of bilinguality as it is influenced by family structure. Toward the end of the survey there were several questions asking about second language abilities for each member of a par-
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family income under $100,000.
Table 1. Characteristics of the participant groups. Characteristic
Monolinguals
Number of participants
Non-fluent Fluent bilinguals bilinguals
73
25
24
Mean age (years)
22.8
20.9
22.9
Mean age of second language acquisition (years)
n/a
10.5
3.3
% born in US (or in English-speaking countries)
100%
88%
50%
% with mother born outside USa
1%
20%
83%
% with father born outside USa
4%
12%
87%
n/a
28%
75%
1%
4%
21%
% learning second language before age 5 % attending foreign language classes (after school/weekends)
85
Note: aIn non-English speaking countries.
ticipant’s immediate (mother, father, step parents or siblings) and extended (grandparents) family. There were also questions about each parent’s place (country) of birth, level of education, linguistic competence and how often they speak a second language at home.
Results Monolingual versus Bilingual The first analysis for this study was to determine the level of bilingual capabilities of the respondents. In the present study subjects were considered to be bilingual if they 1) said they spoke a second language, 2) claimed to still speak the language, and 3) could speak the language at least “pretty well.” These questions were followed by more in-depth question about their linguistic abilities. Nearly half (45%) of the respondents answered “yes” to the two questions “Do you speak any languages other than English? and “Do you still speak this ‘second’ language?” After excludeing six subjects who responded “not very well” to a later question on language fluency (“How well can you speak your second language?”), there were a total of 49 respondents (40%) considered to be bilingual for this study. An additional 73 respondents were classified as monolinguals. Among the bilingual subjects, 24 reported being fluent in their second language while the other 25 felt they could speak their second language either “pretty well” or “very well.”
Demographic Characteristics There were no significant associations between bilinguality and gender (χ2(1) = 0.28, ns), age (F(1,119) = 0.72, ns), year in school (χ2(3) = 4.85, ns), or family income (χ2(1) = 0.02, ns). Similarly, among bilinguals there were no significant associations between language fluency and gender (χ2(1) = 0.725, ns), age (F(1,48) = 2.56, ns) or year in school (χ2(3) = 4.64, ns). However, within the sample of bilinguals there was a significant association with family income (χ2(1) = 5.03, p < 0.03), with fluent bilinguals more likely to come from homes with a
Presence of Bilingual Family Members Monolinguals versus Bilinguals Table 2 presents the percentages of monolingual and bilingual respondents with specific family members who spoke a second language. All survey respondents were asked the question “Growing up, were there other family members who lived in your home who regularly spoke a language other than English” and if so, “what is their relationship to you?” Among monolinguals it was rare to find any other family members who spoke a second language. The highest percentages were for mother (6%), father (6%) and grandmother (6%). In this group only 4% reported having both a mother and a father who spoke a second language. In contrast, 61% of the bilingual group reported one or more family members who spoke another language. The highest percentages with this group were for mother (49%) and father (47%). For 42% of bilinguals, both parents spoke a second language. Counting up the total number of family members who spoke a second language, the mean for bilinguals (2.41, SE = 0.38) was significantly greater than the mean for monolinguals (0.23, SE = 0.08), F(1,120) = 43.94, p < 0.001. Table 3 presents the zero-order correlations of presence/absence of each type of bilingual family member with whether a subject was monolingual or bilingual. The correlations were significant for every family member with the exception of step-mother. A stepwise linear regression was then performed to determine more precisely which specific bilingual family members had the strongest association with the subjects’ bilinguality. The strongest predictors of bilingualism were having a bilingual mother (β = 0.32, SE = 0.13, p < 0.01) followed by having a bilingual sister (β = 0.26, SE = 0.16, p < 0.05). The overall model fit was R2 = 0.29. Fluent versus Non-Fluent Bilinguals As shown in Table 1, half of the fluent bilinguals in this Table 2. Percent of family members who spoke a language other than English: monolinguals and bilinguals. Family
Monolingual
Bilingual
Member
(N = 73)
(N = 49)
Mother
6%
49%
Father
6%
47%
Step-mother
1%
6%
Step-father
1%
8%
Grandmother
4%
29%
Grandfather
4%
37%
Sister
4%
35%
Brother
0%
31%
Any member
11%
61%
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Psychology Handbook
100%
Table 3. Correlation of presence of bilingual family member with subjects’ bilinguality and level of fluency. Bilinguality
Member
(N = 122)
Percentage
Family
Fluency (N = 49)
r
p
Mother
0.51
Father
a
80% 60% 40%
a
r
p
0.001
0.67
0.001
0.49
0.001
0.72
0.001
Step-mother
0.13
0.080
0.26
0.036
Step-father
0.17
0.003
0.16
0.136
Grandmother
0.40
0.001
0.35
0.007
Grandfather
0.35
0.001
0.37
0.004
Sister
0.49
0.001
0.57
0.001
Brother
0.46
0.001
0.50
0.001
20% 0% M o the r
F a the r
S is te r
B ro the r
Gra ndm o the r Gra ndfa the r
Bilingual Family Me mbe r Monolingual
Non-Fluent Bilingual
Fluent Bilingual
Figure 1. Fluency level related to presence of bilingual family members. Table 4. Percent of family members who spoke a language other than English: non-fluent bilinguals and fluent bilinguals. Family
Non-fluent bilingual
Fluent bilingual
Member
(N = 25)
(N = 24)
Mother
16%
83%
Father
12%
83%
Step-mother
0%
13%
Step-father
4%
13%
Grandmother
20%
54%
Grandfather
12%
46%
Sister
8%
63%
Brother
8%
54%
Any member
32%
91%
a
Note: One-tailed.
study were born outside of the United States in non-English speaking countries. In contrast, only 12% of the non-fluent bilinguals were born outside the US. Furthermore, fully 75% of the fluent bilinguals started learning their heritage language before the age of five, compared to only 28% of the non-fluent bilinguals. In addition, within the bilingual group, a large majority of the fluent speakers had family members who spoke another language at home. Table 4 (and Figure 1) shows that the highest percentages were for mother (83%), father (83%) and sister (63%). In this group of fluent bilinguals, 79% reported having both a mother and father who spoke a second language. For the bilinguals who were less fluent in the second language, only about one in six had another family member who spoke another language: mother (16%), father (12%), and grandmother (20%). Only 8% of the non-fluent bilinguals had both a mother and father who spoke a second language. Counting up the total number of family members who spoke a second language, the mean for fluent bilinguals (4.08, SD = 0.51) was significantly greater than the mean for non-fluent bilinguals (0.80, SD = 0.33), F(1,120) = 43.94, p < 0.0001. As presented in Table 3, even within the two groups of bilinguals, presence/absence of each type of bilingual family member was still correlated significantly with whether a subject was a fluent or non-fluent bilingual speaker. Within the two groups of bilingual respondents, a stepwise linear regression found that the presence of a bilingual father was the best predictor of overall second language fluency (β = 0.72, SE = 0.10, p < .0001). The overall model fit was R2 = 0.51.
Where Was the Second Language Learned? Another question asked only of the bilinguals was “where did you learn to speak this second language?” Table 5 (and Figure 2) presents the percentage response for specific sources of language learning for the two levels of bilinguality. For non-fluent bilinguals the primary source of language learning was “at school” (80%). In contrast, for the fluent bilinguals, parents edged out school by 79% to 67%. Table 5 also presents the zero-order correlations for each source of learning with degree of bilinguality. Learning from parents, grandparents and
Table 5. Source of language learning and level of bilingual fluency: percentages and correlations. Non-fluent bilingual
Fluent bilingual
Fluency
(N = 25)
(N = 25)
(N = 49)
%
%
r
pa
Parents
26%
79%
0.44
0.002
Grandparents
20%
58%
0.39
0.006
Other family
20%
58%
0.39
0.006
School
80%
67%
−0.15
0.304
Traveling
32%
21%
−0.13
0.373
Language classes
16%
13%
−0.05
0.733
Language source
Note: aTwo-tailed.
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The Effects of Family Structure on the Development of Bilinguality
100%
Percentage
80% 60%
Non-Fluent
40%
Fluent
20%
ss es
La
ng ua g
ec
la
lin g
oo l
Tt ra ve
Sc h
ily am
en ts
th er f O
nd pa r
G
ra
Pa r
en ts
0%
Source of Language Le arning
Figure 2. Source of second language learning for fluent and non-fluent bilinguals.
other family members were the strongest correlates with becoming fluent in a second language. A stepwise linear regression found that the best predictor of second language fluency was whether or not subjects had learned the language from their parents (β = 0.44, SE = 0.13, p < 0.005). The overall model fit was R2 = 0.19.
Discussion This study aimed to examine the concept of bilinguality on a deeper level. It considered not only whether or not participants were bilingual, but among the bilinguals it sought out possible explanations for different levels of second language mastery. Currently there is no unified definition in the literature for bilinguality. Older studies set very stringent criteria and required full mastery of both languages (Bloomfield, 1933). More modern studies, however, tend to be more lax with some even considering people bilingual who have only receptive abilities in their second language and very little productive abilities (Diebold, 1964). There are very few studies that examine socioeconomic factors as they relate to bilinguality. For example, Morton and Harper (2007) attributed a better performance on the Simon task to children having a higher socioeconomic status (SES). Although the subjects for the current study were chosen purposefully from higher education institutions that collectively draw students from across the SES spectrum, the only SESrelated effect was that fluent bilinguals tended to come from households that earn less than $100,000 per year. This is quite a high break point and does not indicate any clear socioeconomic effect. There were significant results found for the influence of family members on the development of bilinguality. Close to half the bilinguals in this study came from homes where both their parents were also bilingual as opposed to only 6% of the monolinguals. This effect was even stronger when we compared the two fluent and non-fluent bilingual groups. Fluent bilinguals were much more likely to have bilingual parents as opposed to either non-fluent bilinguals or monolinguals. These results confirmed the main hypothesis for this study and are consistent with previous findings (Yamamoto, 2001; De Houwer, 2007). It is important to note that even within the bilingual group degree of second language fluency was strongly related to the home environment. It is clear that when one or both parents speak a
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second language the child has a greater chance of being exposed to the second language, especially if parents communicate with each other and other family members in their native language. Accordingly, it seems sensible that more exposure results in higher levels of fluency. This study found that having more family members speak a different language is associated with a higher degree of bilinguality in the child. Having a bilingual mother was the best predictor of being bilingual, which is consistent with the strong role most mothers play early in a child’s life during the most active period for language acquisition. This result is consistent with earlier research that found a strong influence of bilingual mothers (Baker, 2000; Kamada, 1995). The next most important person in the family who can foster and nurture bilinguality was found to be the sister. This result is again in line with previous findings in this area (Rashid & Gregory, 1997). Sisters seem to not only be good teachers of a second language but they may be more willing to communicate in the heritage language with their siblings. Bilingual grandparents, on the other hand, while promoting bilinguality, weren’t as influential as parents or siblings. The most important member of the family for distinguishing non-fluent bilinguals from fluent bilinguals was the father. In part, this is likely due to the addition of another bilingual member to the family (beyond the mother), but it is also likely to be due to the particular role most fathers play in the family. Overall, having a bilingual mother increases the chances of a child becoming bilingual in the first place, having a bilingual sister further helps other family members to become bilingual, but ultimately it is the presence of a bilingual father that is likely to lead to the highest levels of second language proficiency. In our modern society with increasingly larger number of blended families there is a need to examine the role of stepparents in nurturing bilinguality in their children. The current literature in this area has for the most part neglected this increasingly common family type. In this study we did not find a strong effect for the role of step-parents in second language acquisition. This may be because in the survey there were no questions to measure how long the subject may have lived with any step-parent. If the step-parent has not been in the household for long enough or early enough in the life of the child then their linguistic influence would be expected to be quite limited. On the other hand, if a bilingual step-parent has been in the family for many years and still has not been able to influence the child’s language then there must be a specific dynamic involved that diminishes the influence of step-parents compared to birth parents. This is a question that should be addressed by future research. Lastly, this study examined the influence of second language schooling for the two groups of bilingual respondents. Schooling was found to play a more important role in the language acquisition of non-fluent bilinguals compared to the fluent group. For the fluent group the most important factor was found to be other family members, particularly parents. Finally, as bilinguality is a complex topic it can never be attributed to one single factor, in the present study, familial influence. It is understood that community support or other factors not directly addressed in this study could also have an impact on bilinguality.
Conclusion In this study we took a closer look at bilinguality, not as a
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monolithic characteristic of a person, but as a capability in individuals that is mastered to different degrees. Across the spectrum, from monolingual to non-fluent bilingual to fluent bilingual, it is clear that the influence of family is a strong force in the acquisition, maintenance and ultimate mastery of another language. This study contributes to our current understanding of the development of bilinguality; in particular, the role that family influence plays in promoting and preserving bilinguality among American children.
Acknowledgements The researcher would like to thank Dr. Marc Halsted for his valuable advice and suggestions with the survey and final draft of the study. Also thanks to Kristine Miller and Jocelyne Morillo for their assistance in collecting data for this study.
REFERENCES Azmita, M., & Hesser, J. (1993). Why children are important agents of cognitive development: A comparison of siblings and peers. Child Development, 64, 430-444. Baker, C. (1995). A parents’ and teachers’ guide to bilingualism. London: Arnold. Baker, C. (2000). A parent and teacher’s guide to bilingualism (2nd ed.) (parent and teacher’s guide series No. 1). Clevedon: Multilingual Matters. Bialystok, E. (1986). Children’s concept of the word. Journal of Psycholinguistic Research, 15, 13-32. Bialystok, E. (1988). Levels of bilingualism and levels of linguistic awareness. Developmental Psychology, 24, 560-567. Bialystok, E. (1999). Cognitive complexity and attentional control in the bilingual mind. Child Development, 70, 636-644. Bialystok, E., & Craik, F. I. M. (2010). Cognitive and linguistic processing in the bilingual mind. Psychological Science, 19, 19-23. Bialystok, E., Craik, F. I. M., & Ryan J. (2006). Executive control in a modified antisaccade task: Effects of aging and bilingualism. Journal of Experimental Psychology: Learning, Memory, and Cognition, 32, 1341-1354. Bialystok, E., Craik, F. I. M., Klein, R., & Viswanathan, M. (2004). Bilingualism, aging, and cognitive control: Evidence from the Simon Task. Psychology and Aging, 19, 290-303. Bloomfield, L. (1933). Language. New York: Holt. Clyne, M. (1982). Multilingual Australia. Melbourne: River Seine. Dale, P., Harlaar, N., Haworth, C., & Plomin, R. (2010). Two by two: A twin study of second language acquisition. Psychological Science, 21, 635-640. De Houwer, A. (2007). Parental language input patterns and children’s bilingual use. Applied Psycholinguistics, 28, 411-424. Diebold, A. R. (1964). Incipient bilingualism. In D. Hymes (Ed.), Language in culture and society. NY: Harper and Row. Eisenstein, M. (1980). Childhood bilingualism and adult language learning aptitude. International Review of Applied Psychology, 29, 159-172.
Farrell, M. (2011). Bilingual competence and students’ achievements in physics and mathematics. International Journal of Bilingual Education and Bilingualism, 14, 335-345. Gregory, E., & Williams, A. (2000). City literacies, learning to read across generations and cultures. London: Routledge. Harding, E., & Riley P. (1986). The bilingual family: A handbook for parents. Cambridge: Cambridge University Press. Kamada, L. (1995). Report on bilingual family case studies in Japan: Significant factors affecting bilinguality. Bunkei Ronso, 30, 3. Kenner, C. (2000). Home pages: Literacy links for bilingual children. Stoke-on-Trent: Trentham Books. Keshavarz, M., & Astaneh, H. (2004). The impact of bilinguality on the learning of English vocabulary as a foreign language. Bilingual Education and Bilingualism, 7, 295-302. Lambert, W. E., & Taylor, D. M. (1990). Coping with cultural and racial diversity in urban America. New York: Praeger Publishers. Levy, B. J., McVeigh, N. D., Marful, A., & Anderson, M. C. (2007). Inhibiting your native language: The role of retrieval-induced forgetting during second-language acquisition. Psychological Science, 18, 29-34. Linck, J., Kroll, J., & Sunderman, G. (2009). Losing access to the native language while immersed in a second language. Psychological Science, 20, 1507-1515. Manaster, G., Rhodes, C., Marcus, M., & Chen, J. (1998). The role of birth order in the acculturation of Japanese Americans. Psychologia, 41, 155-170. Miller, J. (1983). Many voices: Bilingualism, culture and education. London and New York: Routledge. Morton, J. B., & Harper, S. N. (2007). What did Simon say? Revisiting the bilingual advantage. Developmental Science, 10, 719-726. Obied, V. (2009). How do siblings shape the language environment in bilingual families? International Journal of Bilingual Education and Bilingualism, 12, 705-720. Oller, D. K., & Eilers, R. E. (2002). Language and literacy in bilingual children. Clevedon, UK: Multilingual Matters. Rashid, N., & Gregory, E. (1997). Learning to read, reading to learn: The importance of siblings in the language development of young bilingual children. In E. Gregory (Ed.), One child, many worlds: Early learning in multicultural communities (p. 112). London: David Fulton. Shin, H. B., & Kominski, R. A. (2010). Language use in the United States: 2007, American community survey reports, ACS-12. US Census Bureau, Washington DC. Shin, S. (2005). Developing in two languages: Korean children in America. Clevedon, UK: Multilingual Matters. Shum, L. (2001). The effect of environmental factors on bilingualism among Chinese and Korean Americans. Applied Linguistics, 1, 1. Thomas, J. (1988). The role played by metalinguistic awareness in second and third language learning. Journal of Multilingual and Multicultural Development, 9, 235-247. Trask, R. L. (1999). Key concepts in language and linguistics. New York: Routledge. Yamamoto, M. (2001). Language use in interlingual families: A Japanese-English sociolinguistic study. Clevedon, UK: Multilingual Matters.
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Appendix Bilingual Study Questionnaire (Selected Items) 1. Do you speak any languages other than English? 2. What is the other (second) language? 3. Did you learn to speak your “second” language BEFORE you learned to speak English? 4. How old were you when you started to learn the “second” (non-English) language? 5. Do you still speak this “second” language? 6. Approximately how many years have you spoken this second language? 7. Do you speak a third language? If so, what is that language? 8. Where did you learn to speak this second language? Check all that apply. From parents From grandparents From other family members From friends In school While traveling In language classes outside of school Other 9. Growing up, who else in your family spoke this second language? Check all that apply. Mother Father Grandparents Brothers/sisters Cousins Aunts/uncles No one else Other 10. In what situations do you currently use your second language? Check all that apply. At school At work At home With parents With friends With grandparents With brothers/sisters With college roommates When traveling in another country At language school/class Other 11. Currently, how much of the time do you use your second language? 12. How much do you like speaking in your second language? 13. How well can you speak your second language? 14. Are you able to READ in your second language? 15. Are you able to WRITE in your second language? 16. How much do you like WRITING in your second language?
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17. Do you ever read books or magazines in your second language for pleasure? 18. How much do you like READING in your second language? 19. Do you ever watch TV shows or listen to radio programs in your second language? 20. Do you like the TV programs or radio programs broadcast in your second language? 21. Do you ever listen to music in your second language? 22. Do you like music sung in your second language? 23. Do you feel proud to be able to speak a second language? 24. Why or why not? 25. How comfortable are you speaking your second language in public? 26. Why or why not? 27. Has anyone ever made fun of you speaking your second language? 28. Did your parents encourage/require you to learn your second language? 29. Did your parents require you to go to second language classes? 30. Do you plan to continue to learn/improve/maintain your second language skills? 31. Why or why not? 32. Do you ever feel embarrassed to speak your second language in public? 33. Why or why not? 34. Growing up, did you attend any foreign language classes AFTER SCHOOL OR ON WEEKENDS? 35. How many years did you attend these language classes? 36. How old were you when you stopped attending these classes? 37. Why did you stop attending your second language school/ classes? 38. How many hours of homework did you have in your second language each week? 39. Did you ever have difficulties with the amount of second language homework? 40. What grades did you usually get in your foreign language school/classes? 41. Have you ever visited a non-English speaking country? 42. Please list the non-English speaking country or countries you have visited. 43. Which non-English speaking country have you spent the most time visiting/living in? 44. How many times have you visited this country? 45. Approximately how old were you when you first visited this country? 46. Approximately how old were you when you last visited? 47. Typically, how long did the visits to this country last? 48. Did you speak in the native language of this country while you visited?
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14 The Role of Parental Involvement in Classroom Life in Greek Primary and Secondary Education Yota Xanthacou, Thomas Babalis, Nektarios A. Stavrou University of Athens, Athens, Greece
Research findings indicated the importance of parental role in the educational process of children providing support for the strong connection between parental role and educational process. The purpose of the present study was to examine the role of parental involvement in classroom life in Greek Primary and Secondary education. A sample of one hundred and fifty five (155) students (69 boys, 86 girls) ranging in age from eleven to fifteen years volunteered to participate in this study. For the purpose of the study, students completed the Classroom Life Measure, which took place during their lessons. The results showed that the pressure from their parents to the study the lessons contributed to the increase of the state-anxiety felt by children, but simultaneously to increase of the negative self-esteem. The parents of primary school students are engaged in a higher degree with the homework, but also seek their children’s participation in school activities. Keywords: Parental Involvement; Classroom Life; Anxiety; Self-Esteem
Introduction International bibliography and research point out the importance of parental role in the educational process of children, and the parental desire to contribute to the improvement of those conditions, which could help their children achieve higher levels of performance and success. A variety of research findings (Babalis & Katsaouni, 2011) demonstrate the importance of the characteristics of effective schools concerning the development of a healthy climate of communication and collaboration between school and family and prove that parental involvement— related to the learning procedure—not only contributes to the acquisition of knowledge, but also to social and sentimental progress. Simultaneously, various benefits arise for everyone involved, as well as teachers and parents (Berner, 2004; Christenson & Sheridan, 2001; Epstein, 1995, 2001; Epstein, Coates et al., 1997; Epstein, Sanders et al., 2002; Hoover-Dempsey et al., 1997; Patrikakou, Weissber et al., 2005). However, some important factors were not investigated at the aforementioned studies, such as psychological traits of children, for example state-anxiety, which is taken into account in the present study in relation with parental involvement. Moreover, it is true that the school which welcomes parents is a school open to society and its changes. During the last decade, in many countries, the educational policy has involved pupils’ parents in the educational organization, seeing them as important co-operators. For that, many special programs are applied trying to actively enrol parents in school events. International organizations, universities, political entities responsible for education, research centres, scientific associations, social organizations etc. are seriously occupied with this subject. In 1996 UNESCO (Delor) pointed out the need of co-operation among family, school and society. The European Union took into account this dimension and tried to reduce school dropouts and the increase of the contribution to life-long learning. For
more than 20 years at Harvard University functions the research program called “Harvard Family Research Project”, which is addressed to teachers, parents, society members and to all responsible for the engraving of educational policy, providing information to reinforce and coordinate their action and facilitate the cooperation among school, family and society. In US universities specific research institutes have been established, such as the Institute of Responsive Education at Boston University and the Centre on Families, Communities, Schools and Children Learning at Johns Hopkins University. In 1991 the International Network of Scholars of Home-School Relations was founded with more than 200 members from 30 countries and in 1995 European Research Network about Parents in Education followed.
The Role of Parental Involvement in the Relationship between the School and the Students’ Family The role of parental involvement is better understood when the parents and teachers understand one another’s expectations, simultaneously keeping communication which will allow both sides to acknowledge the progress and the child’s behaviour at home and at school; the way students perform on homework, their interests, talents, school attitudes and social interactions as well (Albright & Weissberg, 2010). All these compose the axes on which our study focuses, which are supplemented with the following factors: teacher and student academic and personal support, extrinsic motivation, self-esteem and state-trait anxiety. The combination of the concrete psychometric tools adds novelty to our research. The models which refer to the relationship between school and family, have dominated since 1980, showing the importance which is rendered to the interaction among people and groups involved in the educational procedure. The beginning happened with Bronfenbrenner’s (1979) bio-ecosystemic model supporting that a person, during his life, par-
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ticipates in many different systems connected to one another with an interactive and interdependent relationship. Epstein’s (1995) model of overlapping spheres of influence portray the three spheres, family, school and society, which through their influences pupils are evolved and learn as well. Then, Ryan and Adam (1995) emphasize on the whole of the individual characteristics of a family’s members and mutual function related to the child and his/her development and their proximity of influence on the child’s behaviour and effects. Recently, Hoover-Dempsey’s and Sandler’s model (2005) of parental involvement targeted understanding the reasons why parents ought to be involved in their children’s education. Christenson and Sheridan (2001) believe that an effective communication is the foundation of family’s involvement in education. Parents involved in children’s activities—both at home and at school—understand the benefit that derives: 1) Improvement of their relationships with their children. 2) Children’s progress. 3) Better capacity to support children doing their homework. 4) Better estimation of teacher’s effectiveness. Parents received feedback through the satisfaction coming from the new relation with the school, especially when teachers encourage and reinforce their participation. A prerequisite for fertile communication among parents, teachers and school headmasters is that their relationship must be based on mutual trust (Haynes et al., 1996), which is the indispensable ingredient for the success of effective communication and development of a healthy relationship between school and family (Christenson & Sheridan, 2001). Thereby, children feel satisfied in their life, an indicator of general positive self-esteem, as a result of the mutual understanding between the important “others” who are engaged in their daily routine. The “self-esteem” criterion, which has not been so far fairly examined relative to parental involvement, is highlighted in the present research including both the positive and the negative aspect of it. School should be the first to take initiatives related to school’s communication between family and society (Milonakou-Keke, 2006). In practice as she points out, the cooperation between school and family reinforces the collaborative atmosphere and drives parents, pupils and teachers to a better understanding of the targets of the school. Epstein (2001) declares that if parents are well-informed, if they know what exactly is happening at school, if they are encouraging and if, in general, they are involved in the life of their child, pupils have more positive attitudes toward education, higher ambitions and a better presentation. Here are some aspects of parental involvement: Parents are informed and give necessary information to school staff. They are involved in educational activity at home, supervising the child in order to complete his/her homework. Participate in school decisions and administration. Have frequent communication with the teacher and are informed not only about their child’s performance, but also the educational dimension of their parental role. Localize the needs of children in order to be capable to helping them. Have great expectations related to the child’s performance. Offer help to school, such as volunteering, etc. Factors that usually influence parental involvement are related to the demographical characteristics of parents, such as sex, social and economic status, educational status, profession, nationality, etc. Its manifestation depends on the attitudes and
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expectations of parents that, according to research, are connected to the increased motives of their children for school success. Thus, school, with its rules, its demands and the characteristics of the headmaster’s/teachers’ personality can welcome or impede parental involvement. According to a series of research findings (Christenson & Sheridan, 2001; Epstein, 2001; Georgiou, 2001) the more usual types of parental involvement are: supervision of school behavior, control of out-of-school behavior, help with homework, communication with the school. Undoubtedly, control of out-ofschool behavior and frequent communication with school are the most effective activities. In Greece the parents’ participation in school happenings has been institutionalized with the obligatory establishment in every school unit of a parent guardian association consisting of all the parents of the students. Nevertheless, the law seems to mostly cover the formal and legal dimension of the parents’ involvement in the school unit and shows less interest in an essential pedagogic relationship between the family and the school. As well as this, research related to the communication and cooperation between family and school is very limited. There is now the necessity for researching the role of parental involvement in the school to result in valuable conclusions concerning the real image of the Greek educational system. The purpose of the present study was to examine the relationship between classroom life, students’ self-esteem, anxiety and parental involvement in Primary and Secondary education students. More specifically, the present study aimed at examining the differences based on gender and education level in students’ classroom life as well as the level at the type of parental involvement.
Methodology Participants A sample of one hundred and fifty five (155) students (69 boys, 44.5%; 86 girls, 55.5%) volunteered to participate in this study. They represented four grades of Primary and Secondary Education (41 students of 5th Grade Primary Education, 59 students of 6th Grade Primary Education, 26 students of 1st Grade Secondary Education and 21 students of 2nd Grade Secondary Education). The students ranged in age from eleven (11) to fifteen (15) years (Μ = 12.42, SD = 1.30).
Instrumentation Classroom Life Measure First, the students completed the Classroom Life Measure (Johnson D. W., & Johnson R., 1983; Johnson, D. W., Johnson, R. T., Buckman, & Richards, 1985). The original instrument of Classroom Life Measure is a 90-item self-report scale measureing students’ feeling in the educational environment and especially in their classroom. The 90 items constitute 17 factors, out of which six factors were examined in the present study. Specifically, the followings factors were measured in the present study: 1) teacher academic support (4 items) (Cronbach a = .65); 2) teacher personal support (4 items) (Cronbach a = .67); 3) student academic support (4 items) (Cronbach a = .69); 4) student personal support (5 items) (Cronbach a = .77); 5) extrinsic motivation—social support (5 items) (Cronbach a = .67) and 6) academic self-esteem (5 items) (Cronbach a = .68). The value of each factor is the sum of the items of the factor divided by
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the number of items of each factor. The answers were given in 5-point type scale ranging from 1 to 5, where high values indicate high levels of each dimension. State-Trait Anxiety Inventory The State-Trait Anxiety Inventory for Children (STAI-C; Spielberger, Gorsuch, Lushene, 1970) which was constructed by Spielberger, Edwards, Lushene, Montuori and Platzek (1973) and was adopted to the Greek population by Psychountaki (1995) and Psychountaki, Zervas, Karteroliotis and Spielberger (2003), has been developed in order to measure the state-trait anxiety of children in susceptibility conditions (Cronbach a = .87). Self-Esteem Scale The Self-Esteem Scale (Rosenberg, 1965) has been developed in order to evaluate the personal estimation of the student. The instrument is being administered with the instruction to complete it according to “how one usually feels in his/her life”. The instrument consists of ten (10) questions, which are summarized in a single factor that refers to general self-esteem (Cronbach a = .81). Also, it is possible to result in two value factors, which are positive self-esteem (Cronbach a = .90) and negative self-esteem (Cronbach a = .91). Parental Involvement Scale The Parental Involvement Scale (Georgiou, 2000) has been developed in order to examine the degree of participation, interest and involvement of parents in the educational process and the overall education of their children. The Parental Involvement Scale consists of five (5) factors, which evaluate five different dimensions-factors of parental involvement, namely: 1) homework (Cronbach a = .84); 2) pressure (Cronbach a = .70); 3) participation in school activities (Cronbach a = .67); 4) child’s personality development (Cronbach a = .65) and 5) control (Cronbach a = .68). The value of each factor—dimension is the sum of the items of the factor divided by the number of items of each factor and is ranging from 0 to 4, where high values indicate high levels of each dimension. Procedure of the Instrumentation Completion-Data Collection The instrumentation completion was done during the lessons of the students in the context of two administrations. Specifically, for the purposes of the study, students completed the Classroom Life Measure, which took place during the lessons of the students in the classroom they were studying. The administration and completion of the scale was done in the presence of the researcher, who gave all the necessary clarifications, thus contributing to a better understanding of the items. The duration of Life Scale Measuring Classroom completion was about forty (40) minutes. In the second administration students completed the State-Trait Anxiety Inventory and the Self-Esteem Scale. The duration of the questionnaires completion was about twenty (20) minutes and was done again in the presence of the researcher to resolve any queries on the part of students and provide all the necessary explanations and instructions. Regarding the instrumentations which were completed by the parents of the students, the Parental Involvement Scale was sent to parents of students through a sealed envelope. Surveyed parents were distributed, through their children, a file contain-
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ing: 1) a letter explaining to parents the purpose and importance of research, as well as the necessary explanations concerning the confidentiality and anonymity of responses; 2) the measureing instrument and 3) a responsive file. At the same time, parents were informed that they should return the completed questionnaires within ten (10) days. Statistical Analysis of the Research Data The method of multiple analysis of variance; MANOVA was used to investigate the purposes of the study. Specifically, differences in factors of Parental Involvement Scale between the two genders (boys, girls), students of primary and secondary Education were examined, as well as between students with low and high overall and school self-esteem. The Pearson r coefficient was used to examine the relationships between the examined variables (Cohen, 1988). The statistical package that we used in the present study is SPSS Ver. 19.0.
Results Correlations between the Examined Variables in the Total Number of the Students in the Sample Tables 1-3 present the correlations between the examined variables of the research. Specifically, the correlations between the factors of the following instrumentation were examined: 1) Classroom Life Scale; 2) State-Trait Anxiety Inventory; 3) Self-Esteem Scale and 4) Parental Involvement Scale. Correlational analysis. Significant intercorrelations were found among the Parental Involvement Scale subscales (Table 1). The factors of Parental Involvement Scale indicated low to medium value intercorrelations, ranging from .09 to .47. In particular, the highest correlations occurred between the control factor and the factors homework, pressure and personality development of the child. Also, moderate positive correlations were found between the factor homework with the factors pressure and participation in school activities, and between the factors participation in school activities and personality development, indicating that parents’ characteristics and behavior interact in order to form their behavior. Table 2 presents the results of the intercorrelations between the factors of Parental Involvement Scale and Classroom Life Measure Subscales. The results showed the existence of significant correlations between the factors of both instrumentations. Specifically, academic self-esteem was positively correlated with school activities (r = .32, p < .001) and negatively to pressure (r = −.21, p < .01), while the factor extrinsic motivation—social support showed a positive correlation with the factor pressure (r = .20, p < .01). The aforementioned results indicate that there is a correlation between the pressure that parents exert to their child and the way the students experience the classroom life. Table 3 presents the results of the correlations between the factors of Parental Involvement Scale, State-Trait Anxiety Inventory and Self-Esteem Scale in the whole sample. Positive correlations were found between extrinsic motivation-social support factors and pressure, as well as between the factors participation in school activities and school self-esteem. On the other hand, a negative correlation was found between pressure and school self-esteem. The results indicate that the level of pressure that parents exert to their children is related to an in-
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Table 1. Intercorrelations among parental involvement scale subscales. Homework
Pressure
School activities
Personality development
Control
1.00
.30***
.34***
.25**
.47***
*
.47***
***
.20**
Homework Pressure
1.00
.09
School activities
.19
1.00
.32
Personality development
.42***
1.00
Control *
**
Note: p < .05; p < .01;
1.00 ***
p < .001.
Table 2. Intercorrelations among parental involvement scale and classroom life measure subscales. Teacher support
Students support
.03
.00
Extrinsic motivation—social support .10
Academic self-esteem
Homework Pressure
−.13
−.12
.20**
−.21** .32***
.14
School activities
.00
.03
.00
Personality development
−.01
.00
−.19*
.12
Control
−.07
.00
.14
−.11
Note: *p < .05; **p < .01; ***p < .001.
Table 3. Correlations among factors of parental involvement scale, state-trait anxiety inventory and self-esteem scale in the whole sample. State-trait anxiety
Positive self-esteem
Negative self-esteem
Homework
−.10
.02
−.05
General self-esteem .07
Pressure
.36***
−.15
.23**
−.36*** −.01
School activities
−.07
−.14
−.14
Personality development
−.01
−.04
−.03
−.01
Control
.13
−.03
.15
−.16*
Note: *p < .05; **p < .01; ***p < .001.
crease in child’s anxiety and negative self-esteem, whereas in the other hand elevated pressure by the parents decrease child’s general self-esteem.
Table 4. Mean (Μ), standard deviations (SD) of boys and girls in the factors of the parental involvement scale. Boys
Girls
M (SD)
M (SD)
Homework
2.17 (1.02)
2.15 (1.12)
Differences in Factors of Parental Involvement Scale The Tables 4-7 present the differences in factors of Parental Involvement Scale (homework, pressure, participation in school activities, personality development, control). Specifically, differences according to the gender (boys, girls), the education level (Primary education, Secondary education), students’ general self-esteem (low, high) and students’ academic self-esteem (low, high) were examined. Table 4 presents the differences between the students of Primary and Secondary education in the Parental Involvement Scale factors. The results of multiple analysis of variance did not support the existence of statistically significant differences between boys and girls (Wilks’ Λ = .958, F(1,153) = 1.295, ns, 2p = .042), indicating that there is no difference between boys and girls in the involvement of their parents; involvement. Table 5 presents the differences between the students of primary school and high school in the factors of Parental Involvement Scale. The results of multiple analysis of variance showed the existence of statistically significant differences between students of primary school and high school (Wilks’ Λ = .919, F(1,153) = 2.611, p < .05, 2p = .081). The follow-up analy- ses showed the existence of statistically significant differences in the factors: 1) homework (F(1,153) = 7.752, p < .01,
Pressure
2.68 (1.01)
2.60 (.91)
School activities
2.66 (.82)
2.73 (.092)
Personality development
2.51 (.88)
2.80 (.70)
Control
2.29 (1.08)
2.36 (1.05)
Table 5. Mean (Μ), standard deviations (SD) in parental involvement scale subscales between primary and secondary education students. Primary education students
Secondary education students
M (SD)
M (SD)
Homework
2.33 (1.01)
1.84 (1.11)
Pressure
2.57 (.99)
2.71 (.91)
School activities
2.81 (.86)
2.50 (.87)
Personality development
2.72 (.76)
2.57 (.86)
Control
2.37 (1.00)
2.26 (1.16)
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2p = .048) (Mdifference = .49) and 2) participation in school activities (F(1,153) = 4.638, p < .05, 2p = .029) (Mdifference = .31). The results revealed that parents behavior differentiates based on whether their children are in Primary or Secondary education. Table 6 presents the differences between students with low and high self-esteem in the factors of Parental Involvement Scale. Multiple analysis of variance results showed the existence of statistically significant differences between students of low and high general self-esteem (Wilks’ Λ = .856, F(1,153) = 4.816, p < .001, 2p = .144). The follow-up analyses showed the existence of statistically significant differences in the factors: 1) pressure (F(1,153) = 15.790, p < .001, 2p = .097) (Mdifference = .60) and 2) control (F(1,153) = 5.920, p < .05, 2p = .039) (Mdifference = .42). The results showed that the higher the level of pressure and control by the parents in their children behavior the lower the level of boys’ and girls’ self-esteem. Table 7 presents the differences between students with low and high academic self-esteem in the factors of Parental Involvement Scale. The results of the multiple analysis of variance showed the existence of statistically significant differences between students of low and high academic self-esteem (Wilks’ Λ = .856, F(1,153) = 4.945, p < .001, 2p = .144). The follow-up analyses showed the existence of statistically significant differences in the factors: 1) pressure (F(1,153) = 5.139, p < .05, 2p = .025) (Mdifference = .35) and 2) control (F(1,153) = 5.920, p < .05, 2p = .039) (Mdifference = .19). As in the previous result, the low level of students academic self-esteem is related to a higher level of pressure and control by the parents in their children behavior.
Discussion and Conclusion The results of the intercorrelations between the factors of Table 6. Mean (Μ), standard deviations (SD) in Parental Involvement Scale subscales between students of low and high general self-esteem. Low general self-esteem
High general self-esteem
M (SD)
M (SD)
Homework
2.16 (1.07)
2.14 (1.07)
Pressure
2.94 (.84)
2.34 (.98)
School activities
2.71 (.76)
2.73 (.93)
Personality development
2.60 (.84)
2.73 (.79)
Control
2.55 (1.06)
2.13 (1.05)
Table 7. Mean (Μ), standard deviations (SD) in parental involvement scale subscales between students of low and high academic self-esteem. Low academic self-esteem
High academic self-esteem
M (SD)
M (SD)
Homework
2.05 (1.11)
2.24 (1.04)
Pressure
2.80 (.92)
2.45 (.96)
School activities
2.42 (.88)
2.92 (.82)
Personality development
2.56 (.84)
2.75 (.77)
Control
2.42 (1.06)
2.23 (1.06)
Parental Involvement Scale showed the existence of statistically significant correlations. Specifically, parents who get involved to a significant extent with the homework of their child, put at the same time a continuous control over the educational process of their child, but also to some extent this control takes the form of pressure from the parent to their child—student. At the same time, it appears that parents who get involved at home preparing the lessons for their children, participate alongside in school activities more frequently, but also believe that the systematic involvement with their children’s learning contributes to the development of the personality of their child. According to many research results (Fan, 2001; Kim, 2002), the effects of parental involvement are long-termed and positively related to childrens’ good adjustment indices. Also, according to the results of the correlations of the Parental Involvement Scale factors it seems that parents “associate” or “confuse” the control towards their children with the pressure. The fact should become understandable in the behavior of the parents, because their interest in their children’s progress may often evolve into a form of pressure, which the parents do not want, and which may have a negative effect on the progress and the overall development of the child—student. The results are consistent with earlier research (Georgiou, 2000b) indicating that Cyprus parents who put pressure on their children made them question their ability to succeed in school. Finally, commenting on the intercorrelations between the dimensions of the Parental Involvement Scale parents who are engaged in frequent and intense control to their children about their progress, believe at the same time that this contributes to the development of their child’s personality. Thereafter the correlations between the perceived classroom climate, as it was assessed by the selected factors of the Classroom Life Measure, with the factors of the Parental Involvement and Causal Performance Scales were examined. The results of the correlations showed that the pressure on the part of parents contributed to students seeking a higher degree of extrinsic motivation, and also the social support from the school environment by students, possibly in an attempt to compensate for the negative climate experienced from the study and preparation of lessons at school. Also, the negative correlation between pressure and school self-esteem of the students reveals that the more intense the pressure of parents is towards their children to study, the lower the self-esteem the students have about their ability to respond successfully to the requirements of the school, or in other words it reduces the sense of personal competence. On the other hand, it seems that the student’s participation in school activities helps to increase school self-esteem, as a result of the stronger and closer interaction with the other students of the school. As Babalis (2005) indicates the experience that a child gains at school and at home and the interaction with parents and teachers has a direct consequence in its self-concept and general behaviour. Finally it seems that the more developed the personality of the child is, according to the views of the parents, the lower is the effort to find extrinsic motivation and social support on the part of the student. This result is particularly important, and shows the crucial role of parents in personality development of their children, a factor which may contribute to a greater sense of autonomy and personal growth of the child, who will not have the necessity of environmental incentives to achieve the objectives they have set in the educational process.
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The Role of Parental Involvement in Classroom Life in Greek Primary and Secondary Education
The examination of the correlations between the dimensions of Parental Involvement Scale with the factors of State-Trait Anxiety Scale and the positive, negative and general self-esteem showed the existence of statistically significant correlations. Specifically, the results showed that the pressure from their parents to the study the lessons contributed to the increase of the state-anxiety felt by children, but simultaneously to the increase of the negative self-esteem and the restriction of the student’s general self-esteem, a fact which shows that the child’s feeling of pressure from their parents to prepare and study the lessons contributes to the emergence of negative emotions, but also to the creation of a negative self-esteem on the child’s ability to successfully meet the demands of the school. The same effect, although to a lesser extent, has the feeling of parent’s control to their child, which seems to reduce the feeling of general esteem the student has towards them and their general abilities. The Causal Performance Scale with the State-Trait Anxiety Scale and the Self-Esteem Scale did not show significant correlations, except for the fact that the high intelligence of the child was combined with lower negative self-esteem on his part. The same effect, although to a lesser extent, has the feeling of parent’s control to their child, which seems to reduce the feeling of general esteem the student has towards them and their general abilities. The Causal Performance Scale with the State-Trait Anxiety Scale and the Self-Esteem Scale did not show significant correlations, except for the fact that the high intelligence of the child was combined with lower negative self-esteem. The possibility of positive correlation between parental involvement and school success, positive self-esteem, personal development, high expectations and decreased stateanxiety is expected to improve the effectiveness and efficiency of the Greek Educational System and will conduce to its qualitative upgrading. This research will also contribute to the understanding and interpretation of the problems and dysfunctions that the Greek Education faces in relation to childrens’ learning and interpersonal relationships, that will help to their successfully coping and enhancement of the teachers’ and parents’ work. The results of the present research indicate that the organization of common meetings and seminars, programs of inclusive education, where both teachers and parents will be able to attend at the same time, is a major step towards a meaningful contact and exchange of views between them. Moreover, the willingness that the parents show to get systematically involved in their childrens’ learning and development, could lead to the groundbreaking proposal of an individual “Parents’ Curriculum”, which will direct and facilitate parents’ work at home. Thus, parental involvement and communication between parents and teachers will upgrade the cognitive, social and emotional environment of the children in Greek school.
REFERENCES Albright, M. I., & Weissberg, R. P. (2010). School-family partnerships to promote social and emotional learning. In S. L. Christenson, & A. L. Reschly (Eds.), Handbook of school-family partnerships for promoting student competence(pp. 246-265). New York: Routledge. Babalis, Th. (2005). The socialization of child in the classroom. Helping with their school adjustment (in Greek language). Athens: El-
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linika Grammata. Babalis Th., & Katsaouni K. (2011). Family-school relations. Parents’ role. Matters of Educational Planning, 4, 148-166. Berger, E., (2004). Parents as partners in education. Families and schools working together (6th ed.). Upper Saddle River, NJ: Pearson Merrill Prentice Hall. Bronfenbrenner, U. (1979). The ecology of human development: Experiments by nature and design. Cambridge, MA: Harvard University Press. Christenson, S., & Sheridan, S. (2001). Schools and families—Creating essential connections for learning. New York: The Guilford Press. Epstein, J. (1995). School, family, community partnerships: Caring for the children we share. Phi Delta Kappan, 92, 701-712. Epstein, J. (2001). School, family, and community partnerships: Preparing educators and improving schools. Boulder, CO: Westview Press. Epstein, J., Coates, L. et al. (1997). School, family and community partnerships. San Francisco, CA: Corwin Press. Epstein, J., Sanders, M. et al. (2002). School, family, and community partnerships—Your handbook for action (2nd ed.). Thousand Oaks, CA: Corwin Press, INC. Fan, X. (2001). Parental involvement and student’s academic achievement: A growth modeling analysis. Journal of Educational Research, 80, 330-337. Georgiou, S. (2000a). School-family relationship and child’s development (in Greek language). Athens: Ellinika Grammata. Georgiou, S. (2000b). The causal effect of the performance from parents, parental involvement and child’s performance (in Greek language). Psychology, 7, 191-206. Hoover-Dempsey, K., & Sandler, H. (1997). Why do parents become involved in their children’s education? Review of Educational Research, 67, 3-42. Hoover-Dempsey, K., Walker, J. et al. (2005). Why do parents become involved? Research findings and implications. Elementary School Journal, 106, 105-130. Johnson, D. W., & Johnson, R. (1983). Social interdependence and perceived academic and personal support in the classroom. Journal of Social Psychology, 120, 77-82. Johnson, D. W., Johnson, R. T., Buckman, L. A., & Richards, P. S. (1985). The effect of prolonged implementation of cooperative learning on social support within the classroom. Journal of Psychology, 119, 405-411. Kim, E. (2002). The relationship between parental involvement and children’s educational achievement in the Korean immigrant family. Journal of Comparative Family Studies, 33, 529-543. Milonakou-Keke, H. (2006). Modern theoritical approaches to communication among school, family and community (in Greek language). Athens: Atrapos. Patrikakou, E., Weissber, R. et al. (2005). School, family partnerships for children’s success. The series on social emotional learning. New York: Teachers College Press. Rosenberg, M. (1965). Society and the adolescent self-image. Princeton, NJ: Princeton University Press. Ryan, B., & Adams, G. (1995). The family-school relationships model. In B. Ryan, G. Adams et al. (Eds.), The family school connection (pp. 3-28). Thousand Oaks, CA: Sage Publications. Spielberger, C. D., Gorsuch, R. L., & Lushene, R. E. (1970). Manual for the state-trait anxiety inventory. Palo Alto, CA: Consulting Psychologists Press. Spielberger, C. D., Edwards, C. D., Lushene, R. E., Montuori, J., & Platzek, D. (1973). The state-trait anxiety inventory for children (preliminary manual). Palo Alto, CA: Consulting Psychologists Press.
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15 A Novelty-Induced Change in Episodic (NICE) Context Account of Primacy Effects in Free Recall Eddy J. Davelaar Department of Psychological Sciences, Birkbeck, University of London, London, UK
Formal cognitive models of episodic memory assume that during encoding list items become associated with a changing context representation. However, this representation is recency-biased and thus can not account for primacy effects under conditions that prevent rehearsal. In this paper, it is hypothesized that one source underlying primacy effects is the detection of novelty. In three experiments, it is shown how novelty at the perceptual and semantic level can explain the full serial position function of first recall probabilities, including primacy effects. It is proposed that an item becomes distinctive due to increase in the change within a distributed episodic context representation, induced by novelty detection. The theory makes three assumptions. First, items become associated with a distributed context representation. Second, the context representation changes with item presentation. Third, the rate of contextual change is related to the perceptual and conceptual difference computed between the presented item and the previous item (or items in the buffer). This theory captures primacy effects in first recall probabilities without recourse to a rehearsal process and provides a mechanistic account of distinctiveness. Keywords: Distinctiveness; Novelty-Detection; Episodic Context; Distributed Context; Contextual Change
Introduction One of the most robust results in cognitive psychology is the U-shaped serial position curve obtained in the immediate free recall task (Murdock, 1962). In the free recall task, participants are presented with a sequence of words and are instructed to recall as many words as possible in any order. Words presented at the beginning or end of the sequence are remembered better than words presented in the middle of the sequence. These phenomena are referred to as primacy and recency effects, respectively. There exists a number of theories that can account for these results and have advanced our understanding of the mechanisms of human memory. Primacy effects in list memory have been explained in a variety of ways. Many dual-store and dual-trace models assume that the first item enters an empty short-term memory (STM) buffer from which it is displaced after the buffer is filled to capacity, leading to that item residing in STM longer than subsequent items. As episodic trace strength is a function of the duration that items reside in the buffer, the episodic trace for the first item will be stronger than subsequent items (Atkinson & Shiffrin, 1968; Davelaar et al., 2005; Raaijmakers & Shiffrin, 1980). Other encoding models explain primacy effects in terms of more opportunity for rehearsing the first items (Murdock & Metcalfe, 1984; Tan & Ward, 2001; Ward, 2002). There are two types of rehearsal explanations. In one, increased rehearsal opportunities for the first few items lead to increased opportunities for encoding and hence to a stronger trace. This rehearsal-enhanced encoding is assumed in early work on re-
hearsal (Atkinson & Shiffrin, 1968; Rundus, 1971; Rundus & Atkinson, 1971; Brodie & Murdock, 1977). In the second type of rehearsal explanation, increased rehearsal opportunities for the first few items lead to increased probabilities that the items are still in the rehearsal cue at the end of the list presentation. This rehearsal-enhanced accessibility of the items is assumed in the more recent work on rehearsal (Tan & Ward, 2001) in which no short-term buffer is presumed. This denial of a shortterm buffer requires that such models liken the rehearsal process that occurs during list presentation to mini-retrievals (Ward, 2002; see also Laming, 2006). Retrieval-based explanations of primacy effects appeal to the notion of the first items being more distinctive (Murdock, 1960; Neath, 1993). This notion has proven useful to account for the finding that after retrieval of end-of-list items, participants continue retrieving begin-of-list items, as if the first item contains a tag that is accessible at retrieval (Davelaar et al., 2005; Murdock & Metcalfe, 1984). Although the explanations in terms of buffer-enhanced encoding, rehearsal-enhanced encoding, rehearsal-enhanced accessibility, and distinctiveness all capture the basic pattern, they are not mutually exclusive. When procedures are in place that minimizes the use of rehearsal, primacy is still found. For example, Richardson and Baddeley (1976) found primacy effects in immediate free recall under articulatory suppression. Primacy effects in immediate free recall are also found in an incidental task (Baddeley & Hitch, 1977) and when participants are required to make a semantic judgment for each word (Howard & Kahana, 1999). In a procedure called the continuous-distractor paradigm, each item
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is preceded and followed by an interval of distractor activity. Even though this procedure abolishes the opportunity to rehearse, the items during the distractor activity and equates the duration that each item resides in the buffer, primacy effects are still found (e.g., Bjork & Whitten, 1974; Neath, 1993; Thapar & Greene, 1993). These results suggest that not all primacy gradients found in serial position functions are a consequence of a rehearsal mechanism or a buffer. However, this is not to say that all primacy gradients are due to distinctiveness-based retrieval mechanisms. Evidence supporting the view that primacy effects may have an origin during encoding comes from neuroscientific investigations. Electrophysiological studies have revealed that enhanced gamma band activity is correlated with enhanced memory performance for earlier list positions (Sederberg et al., 2006). In the neuroscientific literature these results have been discussed with reference to the computation of novelty (Debener, Herrman, Kranczioch, Gembris, & Engel, 2003): the higher the novelty of an item, the larger the neural response. The neural response for the first item would then be the result of a larger difference between the first item and the fixation stimulus (that is typically presented before the first item) than between the second and the first item. Importantly, it has been shown that increased activation in the same brain areas that compute novelty also predicts recall performance (Kirchoff et al., 2000). Whereas the neuroscientific evidence points to the medial-temporal cortex as the site for novelty signals that are related to increased memory, neurocomputational models of memory have implicated the medial-temporal cortex as a contextual system (e.g., Howard et al., 2005; Norman & O’Reilly, 2003). This triple conjunction of novelty, contextual change and enhanced memory in the same brain area raises the question whether a novelty signal is directly related to contextual change, which in turn is related to increased memory performance. In what follows next, I will put forward the hypothesis that novelty is one source for change in episodic context and that contextual change leads to enhanced memory for the first item after the change. The hypothesis is critically different from its nearest neighbors. That is, the novelty signal itself does not lead to an enhanced memory trace or causes an increase in dimensional distinctiveness at retrieval. Instead, the contextual change at encoding leads to the first item after a change to be relatively less different from the context during retrieval than expected based on temporal distance alone. As above, the proposed hypothesis is compatible with the other explanations of primacy effects and the question which view is superior is not taken up here. Together, the behavioral data on primacy effects supports the existence of a mechanism that favors the first item in a list and the neuroscientific data points towards a novelty-signal that is computed on-line. To directly test the idea that novelty contributes to primacy effects, a series of experiments was conducted addressing the following questions. First, can primacy effects be enhanced by making the first item in a list more novel? Second, can novelty during list presentation create a midlist primacy effect? To preview, the data confirms the role of novelty in generating primacy effects. In the next section, a formalization of the novelty-induced primacy effect is presented in what will be called the novelty-induced change in episodic context model or NICE context model for short. This is then followed by three experiments and a general discussion.
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Distinctiveness through Novelty-Driven Change in Episodic Context Within the memory literature, the term distinctiveness has been used as an explanation for such well-known empirical findings as the primacy effect in serial position functions (Murdock, 1960; Neath, 1993) and the isolation effect (Brown, Neath, & Chater, 2007). However, some researchers have argued that “Distinctiveness itself cannot be used as an explanation for effects of distinctiveness” (Hunt & Lamb, 2001: p. 1359). Instead perceived novelty leads items to become encoded in episodic contexts that have just undergone a relatively large change and are therefore seen at retrieval as being more distinctive. In other words, distinctiveness is not a process, but an end-product. The model presented here adds a further nuance in that local distinctiveness and encoding-retrieval match are tightly connected. In this paper, a novelty-based mechanism is proposed that produces primacy effects. The model is a changing-context model in which contextual change is driven by novelty. The model is named the Novelty-Induced Change in Episodic (NICE) context model and has three critical assumptions, two of which were employed successfully in previous changing-context models (i.e., Glenberg et al., 1983; Howard & Kahana, 1999; Mensink & Raaijmakers, 1988). First, context is a distributed representation of active and inactive elements. Second, the context representation changes slowly over time by making active elements inactive (with probability ) and inactive elements active (with probability ). Third, the probability of activation is a positive function of the novelty of a stimulus. In short, the model is a Markov system with novelty-dependent transition probabilities. Each of these assumptions will be addressed in turn.
Distributed Context In following several investigators (e.g., Burgess & Hitch, 1999; Dennis & Humphreys, 2001; Glenberg et al., 1983; Howard & Kahana, 2002; Mensink & Raaijmakers, 1988; Norman & O’Reilly, 2003) context is a distributed representation of active and inactive elements. The anatomical location of this context representation may be debated, but in some computational models the entorhinal cortex in the medial-temporal lobe is assumed to be the location (Howard et al., 2005; Norman & O’Reilly, 2003). It is known that patients with damage to the medial-temporal lobe suffer from long-term memory loss (Scoville & Milner, 1957; Baddeley & Warrington, 1970), being unable to recall items that were presented early in the list. Assuming that the elements correspond to (groups of) neurons in the medial-temporal lobe allows an investigation whether the model is able to address the finding that activation in the medial-temporal lobe reflects not only the amount of novelty detected, but also is predictive of subsequent memory.
Contextual Change During presentation of a stimulus, active contextual elements may be de-activated, while currently inactive elements may be activated. This process is probabilistic with being the probability that an active element becomes inactive and with being the probability that an inactive element becomes active. In following Mensink and Raaijmakers (1988; see also Estes, 1955; Murdock, 1972), the total number of active elements A(t)
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at time t is given by:
At A0 e
(α β) t
N
β α+β
1 e
α+β t
which asymptotes at N/( + ) (the maximum number of active elements). A(0) is the number of active elements at time = 0.
Novelty-Dependency In the models of Mensink and Raaijmakers (1988) and Howard and Kahana (2002), the transition probabilities were assumed to remain constant. However, this assumption makes the system’s dynamics independent of the nature of the items. This counters the evidence reviewed above showing systematic variations in brain activation based on the type of material and more specifically the novelty of an item. Here, it is assumed that and are variable (see also Murdock, 1972) and are positively correlated with the novelty of an item. Novelty, , is measured as the total number of attended features in a (distributed) stimulus representation that become activated. Stimulus representations contain semantic features of the to-be-remembered word and the features of the background picture on which the word is presented, but only those that are attended to by the participant. The probabilities and for a given could then be formulated as = F(0, ) and = G(0,). Here, 0 and 0 are the minimal probabilities that are present when a stimulus is immediately repeated. The functional form of equations F() and G() are not known, but suffice is to say that > 0 for several of the data sets looked at. Future work could address the precise equations in detail. These equations show that the distance between the values of and becomes smaller with increase in novelty and implies that the asymptotic level of the total number of active elements, N/( + ), would then become larger (with N/2 as its maximum). This is important, as it suggests that with these three assumptions in place, the number of active elements that will be encoded with the stimulus is larger for a novel than for a similar stimulus. In other words, similar stimuli are encoded in similar contexts. Novel stimuli are encoded in dissimilar contexts (increased contextual change) with more contextual elements.
resentation will differ more strongly from the context representation associated with its predecessor. This would lead to a higher likelihood of retrieving novel stimuli.
Model Simulation Figure 1 shows a demonstration of the NICE context model. Vectors of 100,000 binary elements were used in the simulation with values = 0.8 and = 0.01. A list of 10 items is simulated in which no novelty signal is provided at the beginning of the list, novelty is provided at the beginning, and where a novelty signal is also provided during presentation of the item in position 6. Novelty is implemented as a momentary increase in = 0.08. The striking observation is that the NICE context model is able to produce a primacy effect due to change in episodic context as well as showing an enhancement in memory performance for the novel item in position 6. In other words, the model gave rise to primacy via a process of novelty-induced contextual change. To understand the reason why the model produces this striking pattern, the dissimilarity among the context vectors that were encoded with the ten items and the context vector prior to the first item (labeled “B”) and after the last item (labeled “R”) are plotted in a multidimensional scaling (MDS) solution in Figure 2. The model was rerun 1,000 times for each of the three lists and subjected to MDS analyses, forcing the retrieval vector, R, in the upper right quadrant. In the simulation without novelty for the first item, the MDS solution forms a horseshoe in two dimensions with B and R at either side. The MDS solution using three dimensions were not significantly worse, but revealed that along the third dimension the B and R are far removed. When the presentation of the first item coincides with increased novelty, the horseshoe pattern changes such that the vector for the first item moves away from the B vector and gets closer to the R vector. In other words, the first item becomes locally more distinctive from the start of the list and more similar to the retrieval context. When the item in the sixth position coincides with increased novelty, the same happens in that the sixth vector gets closer to the R vector. Moreover, two solutions exist with different orientations for the sequence involving the first five items, which implies that the
Memory Encoding and Retrieval During encoding, active stimulus features and active contextual elements become associated. This matrix of connections represents the episodic memory of the events and is used in the retrieval of those events. Memory performance is assumed to be dependent on the similarity between the context at encoding and the context at test (Tulving, 1983; see Nairne, 2002 for a challenge). This is equivalent to the number of elements that are active at the time of test and were associated with a particular stimulus. The details of a retrieval process are less important than the actual consequence that novelty-driven contextual change has on the retrieval probability (for detailed models see Howard & Kahana, 2002; Mensink & Raaijmakers, 1988). However, several general aspects of this contextual retrieval are relevant. First, the similarity and therefore the probability of retrieval decreases with increasing distance between the encoded context and the test context, leading to a recency effect (see Howard & Kahana, 2002). Second, due to the transition probabilities being novelty-dependent, a novel stimulus will be associated with more contextual elements and the context rep-
Figure 1. Simulated serial position functions showing lack of primacy effects without novelty and primacy effects when novelty is present.
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Figure 2. Multidimensional scaling solutions for the three simulations. The solutions are arranged to have the retrieval context vector, R, in the upper-left quadrant. Each panel includes the context vectors for all ten items and the context vector prior to the first item, B. The lower panels show MDS solutions (without B) of the simulation with novelty in positions 1 and 6. The left and right panels present 840 and 160 solutions, respectively.
novelty during presentation of the sixth item created two sublists. This is further strengthened by the fact that the distance between context vectors 5 and 6 is larger in both solutions compared to the unitary lists. This provides the computational argument that the enhanced memory for the first item after a change is contextually similar to a primacy effect.
Experimental Study In applying the model to data, the question arises what type of data is suitable. The model only addresses contextual change and therefore can only be tested with data on first recall probabilities. To date no published report addressed first recall probabilities in relation to novelty-induced change. Three free recall experiments were conducted to provide such data. In Experiment 1, the relative novelty of the very first item is manipulated to test the assertion that novelty-induced change in episodic context contributes to primacy effects in the absence of rehearsal. In Experiment 2, the background context is manipulated while participants memorized words. In Experiment 3, a critical item is embedded in a list of category exemplars from a different semantic category.
Experiment 1 In Experiment 1, participants were presented with a modified delayed free recall task in order to explore the mechanisms underpinning the primacy effect. The novelty of the first item was manipulated by preceding it with a variable number of nonword items consisting of random consonants. In addition, we looked at whether rehearsal interacts with novelty. If the primacy effect due to novelty interacts with that induced by rehearsal then it is assumed that both are manifestations of a single process. Thus lack of an interaction can be interpreted as a validation of a separate process that contributes to primacy effects. The rationale for the particular manipulation of novelty is as
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follows. The calculation of novelty implies that a current item is different from the items that preceded it. This difference might be at several levels, such as perceptual (different colors) and conceptual (different semantics). As we used unrelated word in the experiment, each word is equally different conceptually and perceptually from its predecessor, except the very first item. This item is preceded by the fixation prompt that tells the participant that the presentation of the list will begin. Thus, the very first item coincides with additional perceptual change. To equate the differences at the perceptual level, letters are used instead of a fixation cross, such as a plus sign. In addition, it is expected that the computation of novelty is larger after a series of similar items. Thus, in the sequence “+ A B”, the word “B” is less novel than in the sequence “+ A A A A B”. As we are interested in the resulting primacy effect that is due to encoding processes and not due to dynamics unfolding during the retrieval phase, we looked at the first recall of a trial. This is the purest measure of primacy effect, uncontaminated with retrieval-related strategies. We expected that there will be more primacy than recency when there are more nonwords preceding the very first item.
Materials and Methods Participants Forty-eight participants (22 females) took part in this experiment. Half were allocated to the no-rehearsal condition and the other half to the rehearsal condition. Design The experiment conformed to a 5 × 10 × 2 mixed factorial design crossing the between-subjects factor rehearsal (“no rehearsal” group, n = 24, “rehearsal” group, n = 24) with two within-factors: nonwords (number of nonwords 0 - 4) and word serial position. Materials A total of 230 common words and 45 nonwords were used as stimuli. The words were selected such that none had any negative connotations (which could lead to enhanced novelty) and all had a word frequency count between 100 - 1000 in a million. Words within each list did not have any semantic or phonological relation. Letter repetition on the same letter-position was avoided. Nonwords consisted of strings of 3 to 5 consonants, matching the range of word lengths. Example nonwords include: kpnsk, mjn, klbn. Each of the 23 lists consisted of ten words and 0 to 4 nonword items, creating five conditions with 4 lists in each condition (and 3 practice lists). Procedure Participants were tested individually and received instructions on the computer screen and verbally by the experimenter. All stimuli were presented on the computer screen. Participants in the rehearsal condition received instructions to rehearse the words from the list during list presentation. After instructions about the delayed free recall task, participants practiced two 10-word lists, one without nonwords (nonword - 0 condition) and one with three nonwords (nonword - 3 condition). The sequence of ten words and variable number of nonwords was presented at a rate of one item per second in the middle of the screen, each item masking the previous one. After the words were presented, a prompt appeared indicating the start of the
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distractor task. The distractor task consisted of nine mathematical problems, such as “7 − 3 = 3” and participants indicated the accuracy of the equation by pressing the K- or S-key on the keyboard when it was correct or incorrect, respectively. The maximum duration for each mathematical problem was 2.5 s and participants were advised to respond within 2 seconds to each of the problems as accurately as possible. Following this distractor activity, three question marks appeared, prompting the participant to start recalling as many words from the list as possible in any order. Although only the very first response was of interest, all answers were record by the experimenter to encourage the participant to memorize all the words during list presentation. After the two practice trials, 21 trials were presented of which the first one was a “warming up list” with two nonwords and was thus excluded from the analyses. The test lasted approximately 25 minutes.
Results and Discussion Figure 3 presents the serial position curves of the first recall probabilities for the no-rehearsal and the rehearsal group. From the figure it is clear that the distractor task abolished the recency effect in the no-rehearsal group. However, a recency effect is present in the rehearsal group, which is due the fact that participants are able to rehearse items during a difficult distractor task if requested to do so. As the first recall probabilities are normalized (the values sum to one), the rehearsal group necessarily have lower levels of primacy. As our focus is on the primacy effect, we used the PR-index
(Davelaar et al., 2005) to get a relative estimate of the primacy/ recency gradient. The PR-index is larger than 0.5 when there is more recency than primacy and smaller than 0.5 when there is more primacy than recency. Therefore, the PR-index summarizes the entire the serial position curve in a single value. This value varies as a function of the number of nonwords presented as shown in Figure 4. The data in Figure 4 were subjected to a 2 (rehearsal group) × 5 (number of nonwords) mixed ANOVA. There was a main effect of number of nonwords [F(4, 184) = 2.573, MSe = .017, p < .05], showing more primacy with increasing number of nonwords in both groups. The main effect of group and the interaction between group and number of nonwords were not significant (p > .12). Participants in both groups showed tendency to recall more primacy words from lists preceded by the maximum four nonword items. This finding supports the hypothesis that the primacy effect is enhanced when the very first item coincides with a larger level of novelty. In addition, instead of enhanced primacy effects in the rehearsal group, the group shows recency effects. This finding shows that the rehearsal process retrieves only the more recent items. Typically, the immediate free recall task is used in which the most recent items can be retrieved from short-term memory and thus rehearsal can not contribute to the performance. However, in the delayed free recall task, all items have been displaced from short-term memory. Any rehearsal process that can unfold will not take the very first item, but instead the most recent item, as expected from a recency-based account of retrieval (Tan & Ward, 2000; Ward, 2002). Finally, the lack of an interaction between novelty and rehearsal confirms that the two are operating on different parts of the list.
Experiment 2 Experiment 1 confirmed the view that novelty of the very first item contributes to the primacy effect in free recall. This novelty was induced by presenting a number of items that differ from the very first item and were similar to each other. In principle, it should be possible to have a primacy effect present in a single list of items in which the first half of the list differs from the second half of the list. In our conception, the presentation of the very first item of the second half will coincide with a high level of novelty and should thus be better remembered. In Ex-
Figure 3. Serial position curves for both groups as a function of the number of nonwords seen prior to the very first item.
Figure 4. The primacy/recency index computed over the first recall probabilities. The smaller the index, the more primacy there is in the serial position curve.
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periment 2, we varied the background on which words are presented. The rationale for this choice was that the background is unrelated and irrelevant to the task, but forms part of the episodic context in which the word is encoded. When the same context is presented during retrieval, memory for items encoded in that context should be better. This allows investigating whether the match in context at encoding and retrieval interacts with the effect of novelty. If this is the true, novelty and episodic context are related.
Materials and Methods Participants Forty-one participants (35 females) took part in this experiment. Design The current experiment conformed to a 5 × 10 within-subject design crossing the factors background (5 levels) and word serial position. Materials A total of 150 common words were used as stimuli. The words were selected such that none had any negative connotations and all had a word frequency count between 100 - 1000 in a million. Words within each list did not have any semantic or phonological relation. Letter repetition on the same letter-position was avoided. Each of the 15 lists consisted of ten words. Background pictures were landscapes of forests, beaches, cities, and mountain ranges. Procedure Participants were tested individually and received instructions on the computer screen and verbally by the experimenter. Each word was presented for one second on the computer screen on top of a picture that filled the entire screen. Participants were told to ignore the background picture and focus on the words to be remembered. After the final word, participants recalled as many words as possible in any order. There was no time limit imposed for recall. The background picture varied according to 5 conditions. Condition 1 (AA/A): the background picture was the same for all 10 words and was also present during the retrieval. Condition 2 (AA/B): the background picture was the same for all 10 words, but a different picture was presented during retrieval. Condition 3 (AB/A): words 1-5 were presented on top of a different picture than words 6-10 and during the retrieval the picture that was presented during the first half was re-presented. Condition 4 (AB/B): same as condition 3, but during retrieval the picture that was presented during the second half was re-presented. Condition 5 (AB/C): same as condition 3, but during retrieval the picture was a totally different one. The lists were counterbalanced across participants so that the different lists were presented in each of the different context-conditions. There were 3 lists per condition and no picture was presented in more than one trial.
Results and Discussion Figure 5 shows the first recall probabilities as a function of
Figure 5. Top panel: Serial position curves for the conditions in Experiment 2. The first five items were presented with the same background picture, denoted by “A”. The second five items were presented with the same background picture, but could be either the same or different than the first list half. During retrieval, a picture stayed on the screen which was either the same or different than the picture presented during encoding. Compare with the simulation results in Figure 1. Bottom panel: the raw scores for all experimental conditions.
context condition. A deviation score was calculated between conditions 2 - 5 and condition 1 (not shown), which serves as a baseline condition, for the words in positions 1 and 6. A 4 (condition) × 2 (list-half) ANOVA conducted on the deviation scores revealed a marginal effect of condition [F(3, 120) = 2.50, MSe = 0.026, p = .063] and a significant contrast effect on the interaction [F(1, 40) = 6.38, MSe = 0.022, p < .05]. This was further unpacked using t-tests. Comparing conditions AA/B and AB/C revealed a significant effect of a contextual change despite the lack of an encoding-retrieval match [t(40) = 2.23, p < .05]. When the retrieval context matched either list-half, the list position matching the context was enhanced (position 1 in AB/A and position 6 in AB/B), although this did not reach significance. The AB/B [t(40) = 3.11, p < .01] and AB/C [t(40) = 2.23, p < .05] conditions showed enhanced recall for position 6. Thus, both change in episodic context during list presentation and contextual encoding-retrieval match contribute to first recall. Finally, comparing the AB/B and AB/C conditions revealed no statistical difference, suggesting that the change-induced en-
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hancement and the encoding-retrieval match are not independent. Experiment 2 reveals that changing an irrelevant background picture is sufficient to produce enhanced recall performance for the first item after the change. In analogy, this constitutes a mini-primacy effect. As shown in the simulations in Figures 1 and 2. This is consistent with the view that novelty as induced by change in episodic context contributes to primacy effects. The data in Experiment 2 is too sparse to run correlational analyses relating the size of the primacy effect with the size of the novelty effect. This is taken up in Experiment 3.
Experiment 3 Experiments 1 and 2 provide the first evidence of primacy effects being driven by novelty. However, in Experiment 1, the novelty was induced at the item level, whereas in Experiment 2 this was induced at the level of episodic context. It is therefore possible that the mini-primacy effect was driven by the change in context and not necessarily by item-level novelty. The third and final experiment employs a delayed free recall task of semantically related items in which one item in the middle of the list is semantically unrelated to the rest. The novelty for that item is then based on item-level analysis. This unrelated item, the isolate, is positioned either at the beginning or in the middle of the list. If item-level novelty (and not just context-level novelty) contributes to primacy effects, then normal primacy effects should correlate with the increased memory for the isolate when presented in the middle list position.
Materials and Methods Participants Seventeen participants (11 females) took part in this experiment. Design The current experiment conformed to a 2 × 12 within-subject design crossing the factors isolate position (position 1 or position 6) and word serial position. Materials A total of 240 common words were used as stimuli. The words were selected such that none had any negative connotations and all had a word frequency count between 100 - 1000 in a million. Words within each list were semantically related by virtue of being exemplars for a single category. Each of the 20 lists consisted of twelve words. A word that was unrelated to the words in the list was presented either on position 1 (b-list) or position 6 (m-list). There were 10 lists per condition and the location of the isolate was counterbalanced across participants. Procedure Participants were tested individually and received instructtions on the computer screen and verbally by the experimenter. Each word was presented for one second on the computer screen. After the final word, a prompt appeared indicating the start of the distractor task. The distractor task consisted of nine mathematical problems, such as “7 – 3 = 3” and participants indicated the accuracy of the equation by pressing the K- or S-key on the keyboard when it was correct or incorrect, respectively. The maximum duration for each mathematical problem
was 2.5 s and participants were advised to respond within 2 seconds to each of the problems as accurately as possible. Following this distractor activity, three question marks appeared, prompting the participant to start recalling as many words from the list as possible in any order. There was no time limit imposed for recall.
Results and Discussion Figure 6 presents the first recall serial position curves. As can be seen, the isolate is reported more often that the words in the same position, but related to the other words in the list. This constitutes the basic isolation effect also known as the Von Restorff effect. Our focus is on whether the size of the isolation effect on position 6 (m-list minus b-list) correlates with the normal primacy effect (position 1 in the m-list) and with the additional benefit when the isolate is in position 1 (b-list minus m-list). To provide a baseline, the correlational analyses were repeated for all other serial positions (2 - 5, 7 - 12). The correlation between the recall difference in position 6 correlated significantly with the primacy effect [r(17) = −.63, p < .01] and with the addition to the primacy effect [r(17) = .91, p < .001]. The only other position that showed significance was the final list position with the normal primacy effect [r(17) = −.51, p < .05]. This pattern makes sense given that for the recall, the end-of-list context is used as a memory cue and is directly responsible for the first recalls. The last item is encoded in an episodic context that is similar to the end-of-list context. However, the final list item does not coincide with enhanced novelty and therefore it does not correlate with the novelty-induced enhancement on the primacy effect or even with the novel item itself. The results support the view that item-level novelty drives better first recall performance of the items and that normal primacy effects is partly driven and is enhanced by item-level novelty. As an aside, the lack of correlations between the primacy effects and item number 7 suggests that the semantic novelty of item 7 is not as great as item number 6. This suggests that novelty is calculated against all items in short-term memory, which is consistent with the results of Experiment 1 where the primacy gradient is gradually enhanced when placing more nonwords in short-term memory. However, Experiment 2 clearly showed a close connection between novelty-induced memory enhancement and change in episodic context. The overall pattern of results can be accommodated in the NICE
Figure 6. Serial position curves of the data in Experiment 3. The isolate was presented either in position 1 or in position 6.
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context model to which we now turn.
General Discussion The three experiments provide evidence for the view that item-level novelty and context-level novelty enhance memory performance and contribute to primacy effects in free recall. As expected (Glenberg et al., 1983; Howard & Kahana, 1999; Murdock, 1972), the NICE context model produces recency effects. However, the important difference is that the probabilities of activating and de-activating contextual elements are made conditional on the novelty value between the previously and the newly presented items. As the first item is different from the information preceding it, its presentation coincides with an enhanced level of novelty, which in turn speeds up the change in episodic context. This additional change makes that first item more locally distinctive and more accessible during retrieval. Although the begin- and end-points have been used in several models in memory retrieval (Brown, Preece, & Hulme, 2000; Burgess & Hitch, 1999; Davelaar et al., 2005; Henson, 1998; Metcalfe & Murdock, 1981; Neath, 1993; Shiffrin & Cook, 1977), none of these models provide a mechanistic explanation for the higher distinctiveness of the beginning and end of a list. The NICE context model provides such an explanation. One of the assumptions is that novelty is measured as the difference in representation between the current and the previous item (plus background). This is consistent with single-store models that do not postulate a limited-capacity buffer. When a buffer is postulated, however, the novelty-signal could be computed from the current item and the buffer items. Such a change to the model does not invalidate the central thesis of this paper (i.e., Novelty can Induce Change in Episodic context) and may even provide a novel way to address the need for a limited-capacity buffer in understanding free recall performance. In addition, it is assumed that stimulus representations contain semantic features of the to-be-remembered word and the features of the background picture on which the word is presented. Although this captures the data with a minimum set of assumptions, this operationalization of stimulus representations comes from the view that the background environment is also input and differs from the internal context representation. Despite the regular usage of context in computational models of memory, no clear understanding has been reached about what context is (and is not) (see for a recent review, Klein, Shiffrin & Criss, 2007). Regarding novelty detection, it has been proposed that detection of novelty is related to increase in the release of acetylcholine, a neurotransmitter that originates from the basal forebrain and modulates several brain areas, including structures in the medial-temporal lobe. The mechanism by which the brain detects novelty is yet unclear, but there are several ways in which a novelty signal can be obtained in a neurocomputational model. For example, in ART models (Grossberg, 2012) an interplay between bottom-up input and top-down feedback leads to a novelty-signal when the top-down feedback does not resonate with the bottom-up input. In those models, the resulting novelty-signal is used to allow a new higher-level representation to become activated and get associated with the novel bottom-up input. A non-interactive (bottom-up and top-down) architecture is also possible when using units that adapt over time. This
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adaptation (aka habituation, neural fatigue, synaptic depression) leads to the total activation to be an indicator of perceived stimulus novelty (Davelaar et al., 2011). The NICE context model provides a solution to the question of how a context model can retrieve the first item of a preceding list. Jang and Huber (2008) replicated the so-called listbefore-last experiments by Shiffrin (1970), showing that participants are able to skip the just encoded list and retrieve items from the preceding list. This provides a major challenge to all context models that are recency-biased. One solution is to assume that a hierarchy of contextual elements exists, such that different levels have faster or slower transition probabilities (cf. Davelaar & Usher, 2002; Glenberg et al., 1983). The modeler can then choose those elements that fluctuate in the same rhythm as the presentation of the trials. Another approach is to assume that each first item is more distinctive than the other items and thus can provide an anchor point during retrieval. The NICE context model produces memory traces for the first items of all lists that are locally distinctive. Thus retrieving the first item of the preceding list is easier than retrieving the middle item of the preceding lists, despite that the middle items are temporally more recent. It also naturally accounts for the observation that after retrieving items from the end of the list, the next item to be retrieved is most likely to be the very first list item (Laming, 1999).
Concluding Remarks The current approach is not meant as an alternative to existing models, but instead introduces a mechanism by which other context models can capture primacy effects. For example, in TCM (Howard & Kahana, 2002), where contextual change is item-dependent, a similarity structure between the retrieved contexts of list items could be introduced. As the retrieved context vector of the first item differs more from that of the fixation stimulus than that of the second item, the change in the ongoing context will be larger for the first than the second item. It remains to be seen whether this modification to TCM would produce the desired results. Nevertheless, the basic concept will be the same, i.e., a source of contextual change is the novelty of an item at perceptual and conceptual levels.
Author Note Preliminary versions of this work were presented at the 3rd Context and Episodic Memory Symposium in 2005 and the 1st Computational Cognitive Neuroscience Meeting in 2005. The author would like to thank Marta Sibilska for running Experiment 1.
REFERENCES Atkinson, R. C., & Shiffrin, R. M. (1968). Human memory: A proposed system and its control processes. In K. W. Spence, & J. T. Spence (Eds.), The psychology of learning and motivation: Advances in research and theory (Vol. 2, pp. 89-195). New York: Academic Press. Baddeley, A. D., & Hitch, G. J. (1977). Recency re-examined. In S. Dornic (Ed.), Attention and performance (Vol. 6). Hillsdale, NJ: Lawrence Erlbaum Associates Inc. Baddeley, A. D., & Warrington, E. K. (1970). Amnesia and the distinction between long- and short-term memory. Journal of Verbal Learning and Verbal Behavior, 9, 176-189.
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Bjork, R. A., & Whitten, W. B. (1974). Recency-sensitive retrieval processes in long-term free recall. Cognitive Psychology, 6, 173-189. Brodie, D. A., & Murdock, B. B. (1977). Effects of presentation time on nominal and functional serial position curves of free recall. Journal of Verbal Learning and Verbal Behavior, 16, 185-200. Brown, G. D. A., Neath, I., & Chater, N. (2007). A temporal ratio model of memory. Psychological Review, 114, 539-576. Brown, G. D. A., Preece, T., & Hulme, C. (2000). Oscillator-based memory for serial order. Psychological Review, 107, 127-181. Burgess, N., & Hitch, G. J. (1999). Memory for serial order: A network model of the phonological loop and its timing. Psychological Review, 106, 551-581. Craik, F. I. M., & Watkins, M. J. (1973). The role of rehearsal in short term memory. Journal of Verbal Learning and Verbal Behavior, 12, 599-607. Davelaar, E. J., & Usher, M. (2002). An activation-based theory of immediate item memory. In J. A. Bullinaria, & W. Lowe (Eds.), Connectionist models of cognition and perception: Proceedings of the seventh neural computation and psychology workshop. Singapore City: World Scientific. Davelaar, E. J., Goshen-Gottstein, Y., Ashkenazi, A., Haarmann, H. J., & Usher, M. (2005). The demise of short-term memory revisited: Empirical and computational investigations of recency effects. Psychological Review, 112, 3-42. Davelaar, E. J., Tian, X., Weidemann, C. T., & Huber, D. E. (2011). A habituation account of change detection in same/different judgments. Cognitive, Affective, & Behavioral Neuroscience, 11, 608-626. Debener, S., Herrman, C. S., Kranczioch, C., Gembris, D., & Engel, A. K. (2003). Top-down attentional processing enhances auditory evoked gamma band activity. Neuroreport, 14, 683-686. Estes, W. K. (1955). Statistical theory of distributional phenomena in learning. Psychological Review, 62, 369-377. Glenberg, A. M., Bradley, M. M., Kraus, T. A., & Renzaglia, G. J. (1983). Studies of long-term recency effect: Support for a contextually guided retrieval hypothesis. Journal of Experimental Psychology: Learning, Memory, and Cognition, 9, 231-255. Grossberg, S. (2012). Adaptive resonance theory: How a brain learns to consciously attend, learn, and recognize a changing world. Neural Networks, 37, 1-47. Henson, R. H. A. (1998). Short-term memory for serial order: The startend model. Cognitive Psychology, 36, 73-137. Howard, M. W., & Kahana, M. J. (1999). Contextual variability and serial position effects in free recall. Journal of Experimental Psychology: Learning, Memory and Cognition, 25, 923-941. Howard, M. W., & Kahana, M. J. (2002). A distributed representation of temporal context. Journal of Mathematical Psychology, 46, 269299. Howard, M. W., Fotedar, M. S., Datey, A. V., & Hasselmo, M. E. (2005). The temporal context model in spatial navigation and relational learning: Toward a common explanation of medial temporal lobe function across domains. Psychological Review, 112, 75-116. Hunt, R. R., & Lamb, C. A. (2001). What causes the isolation effect? Journal of Experimental Psychology: Learning, Memory, & Cognition, 27, 1359-1366. Jang, Y., & Huber, D. E. (2008). Context retrieval and context change in free recall: Recalling from long-term memory drives list isolation. Journal of Experimental Psychology: Learning Memory and Cognition, 34, 112-127. Kirchoff, B. A., Wagner, A. D., Maril, A., & Stern, C. E. (2000). Pre-
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frontal-temporal circuitry for episodic encoding and subsequent memory. Journal of Neuroscience, 20, 6173-6180. Klein, K. A., Shiffrin, R. M., & Criss, A. H. (2007). Putting context in context. In J. S. Nairne (Ed.), The foundations of remembering: Essays in honor of Henry L. Roediger III. New York: Psychology Press. Laming, D. (1999). Testing the idea of distinct storage mechanisms in memory. International Journal of Psychology, 34, 419-426. Laming, D. (2006). Predicting free recall. Journal of Experimental Psychology: Learning, Memory, and Cognition, 32, 1146-1163. Mensink, G.-J., & Raaijmakers, J. G. W. (1988). A model of interfereence and forgetting. Psychological Review, 95, 434-455. Metcalfe, J., & Murdock, B. B. (1981). An encoding and retrieval model of single trial free recall. Journal of Verbal Learning and Verbal Behavior, 20, 161-189. Murdock, B. B. (1960). The distinctiveness of stimuli. Psychological Review, 67, 16-31. Murdock, B. B. (1962). The serial position effect of free recall. Journal of Verbal Learning and Verbal Behavior, 64, 482-488. Murdock, B. B. (1972). Short-term memory. In G. H. Bower & J. T. Spence (Eds.), The psychology of learning and motivation (Vol. 5). New York: Academic Press. Nairne, J. S. (2002). The myth of the encoding-retrieval match. Memory, 10, 389-395. Neath, I. (1993). Distinctiveness and serial position effects in recognition. Memory & Cognition, 21, 689-698. Norman, K. A. & O’Reilly, R. C. (2003). Modeling hippocampal and neocortical contributions to recognition memory: A complementary learning systems Approach. Psychological Review, 110, 611-646. Raaijmakers, J. G. W., & Shiffrin, R. M. (1980). SAM: A theory of probabilistic search of associative memory. In G. Bower (Ed.), The psychology of learning and motivation (Vol. 14). New York: Academic Press. Richardson, J. T. E., & Baddeley, A. D. (1975). The effect of articulatory suppression in free recall. Journal of Verbal Learning and Verbal Behavior, 14, 623-629. Rundus, D. (1971). An analysis of rehearsal processes in free recall. Journal of Experimental Psychology, 89, 63-77. Rundus, D., & Atkinson, R. C. (1970). Rehearsal procedures in free recall: A procedure for direct observation. Journal of Verbal Learning and Verbal Behavior, 9, 99-105. Scoville, W. B., & Milner, B. (1957). Loss of recent memory after bilateral hippocampal lesions. Journal of Neurology, Neurosurgery, and Psychiatry, 20, 11-21. Sederberg, P. B., Gauthier, L. V., Terushkin, V., Miller, J. F., Barnathan, J. A., & Kahana, M. J. (2006). Oscillatory correlates of the primacy effect in episodic memory. NeuroImage, 32, 1422-1431. Shiffrin, R. (1970). Forgetting: Trace erosion or retrieval failure? Science, 168, 1601-1603. Shiffrin, R. M., & Cook, J. R. (1978). Short-term forgetting of item and order information. Journal of Verbal Learning and Verbal Behavior, 17, 189-218. Tan, L., & Ward, G. (2000). A recency-based account of primacy effects in free recall. Journal of Experimental Psychology: Learning, Memory, and Cognition, 26, 1589-1625. Tulving, E. (1983). Elements of episodic memory. New York: Oxford University Press. Ward, G. (2002). A recency-based account of the list length effect in free recall. Memory & Cognition, 30, 885-892.
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16 Does System 1 Process both Local and Nonlocal Information in Intuitive Judgment and Decision Making? Available Evidence and a Research Agenda Proposal Patrizio Tressoldi Dipartimento di Psicologia Generale, Università di Padova, Padova, Italy
This paper argues that System 1, (the mental processing system mainly involved in the processing of unconscious information) in contrast to System 2, (mainly involved in the processing of conscious information), processes not only local information conveyed by sensory organs, but also nonlocal ones, that is, those beyond the detection range of sensory organs. The striking similarities observed between the characteristics of local and nonlocal information processing by System 1, offer the possibility of using most of the experimental protocols used to investigate local information for the nonlocal information. Available evidence is presented and a research agenda is outlined that could raise fascinating questions and answer about the functioning of the human mind. Keywords: System 1; System 2; Unconscious Information Processing; Nonlocal Information
Introduction Dual-Process Model of Information Processing: System 1 and System 2 Although some authors have traced the dual-process theory of information processing to William James, a consensus has been achieved on the theoretical and empirical definition of two distinct ways of perceiving and thinking that characterize the functioning of human mental activity, System 1 and System 2 as defined by Epstein (1994, 2008); Stanovich (1999); Kahneman, (2003, 2011); Kahneman & Frederick (2002); Evans & Stanovich (2013). These information processing systems can be summarised as the extremes of a continuum with System 1 as a fast, automatic, emotional, stereotypic, large capacity, sub- and unconscious way of processing at one end, and System 2 as a slow, effortful, capacity limited, controlled and conscious way of processing information at the other. There is some evidence that System 1’s unconscious cognitive activity influences consumer preferences (Friese, Wänke, & Plessner, 2006), interpersonal processes (Fitzsimons & Bargh, 2003), emotional reactions (Tamietto et al., 2009) and the pursuit of specific goals (Custers & Aarts, 2010). A useful and clearly expressed comparison of the main characteristics of System 1 and System 2 within four different clusters, is offered by Evans (2008)1, see Table 1. At present, the theoretical and empirical investigation is largely devoted to the exploration of the conditions that trigger the activation of one system or the other, (e.g. Greifeneder, Bless, & Pham, 2011; Bolte & Goschke, 2005; Evans & Stanovich, 1
A similar comparison has been done by Epstein (2008).
2013), defining which problems can be solved more efficiently by using one system or the other, (e.g. Usher et al., 2011), and determining if and how these two systems can interact to exploit their characteristics for increasing information processing efficiency (e.g. Evans, 2008; Kruglanski & Gigerenzer, 2011). What information do these two systems use? The general consensus is that all the information is received only by the sensory organs. As strange as it may seem, there is a research line more than 80 years old, which investigates whether the human mind can process information received by bypassing the sensory organs (see Tressoldi, 2011, for a review) although it has only recently been theoretically and empirically examined within a dual-system framework. Even if it pursued under different names and theoretical approaches, we can define this as the study of System1 nonlocal information processing. In the following sections we define the characteristics of this information processing system. We then outline the empirical findings obtained so far and conclude with a proposal for a research agenda to pursue investigation of the interactions in the processing systems of both local and nonlocal information.
Could System 1 Process Nonlocal Information2? Suppose our brain and consequently our mind could receive information related to objects, people, emotions, natural envi2
The meaning of “nonlocal” is used here only as presented in the text and not as physical or biological quantum-like properties. An interpretation of mental nonlocal functions as possible physical or biological quantum-like properties is presented in Tressoldi & Khrennikov (2012).
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Table 1. Clusters of attributes associated with dual systems of thinking following Evans (2008). System 1
System 2 Cluster 1—Consciousness
Unconscious (preconscious)
Conscious
Implicit
Explicit
Automatic
Controlled
Low effort
High effort
Rapid
Slow
High capacity
Low capacity
Default process
Inhibitory
Holistic, perceptual
Analytic, reflective
Cluster 2—Evolution Evolutionarily old
Evolutionarily recent
Evolutionary rationality
Individual rationality
Shared with animals
Uniquely human
Nonverbal
Linked to language
Modular cognition
Fluid intelligence
Cluster 3—Functional characteristics Associative
Rule based
Domain specific
Domain general
Contextualized
Abstract
Pragmatic
Logical
Parallel Stereotypical
Sequential Egalitarian
Cluster 4—Individual differences Universal
Heritable
Independent of general intelligence
Linked to general intelligence
Independent of working memory
Limited by working memory capacity
ronment, etc., from beyond the constraints of our sensory organs by acting like an information detector. In simple terms, this would involve expressing nonlocal perception characteristics in different ways from the perception of information transmitted by our sensory organs which are limited by their biological detection range. We will call this System 1 nonlocal information processing (S1_nip) postulating that its activity precedes System 1 local processing (S1_lip) and obviously System 2 activity. The hypothesis of a mind or consciousness without space and perhaps time constraints is not new and we can trace its roots back to certain philosophical theories, such as idealism, panpsychism, neutral or mental monism and more recently nonphysical realism (Staune, 2013) and the dual-aspect monism
(Antmaspacher, 2012). For example, Idealism is the family of views which assert that reality, or reality as we know it, is fundamentally mental, mentally constructed, or otherwise immaterial (e.g. Bolender, 2001). Panpsychism states that mind is a fundamental feature of the world which exists throughout the universe. Unsurprisingly, each of the key terms, “mind”, “fundamental” and “throughout the universe” is subject to a variety of interpretations by panpsychists, leading to a range of possible philosophical positions (Pihlström, 2008). Mental Monism holds that all is mind and that the ultimate constituents of the world are individual momentary experiences which in themselves are neither mental nor physical, but of which, differently arranged, both minds and material things are composed. In other words, the concept of nature itself is a construct of mind that can only be known through hypotheses tested by reference to experience (Velmans, 2012). Non-physical realism refers to the assumption that reality cannot be explained exclusively by observable causes in spacetime and consciousness and matter stem from a unique substance that would “ante-date the scission between the subject and the objet” (Staune, 2013) a theoretical approach similar to the dual-aspect monism (Antmaspacher, 2012) elaborated after a detailed reconstruction of the Pauli-Jung conjecture which yields a psychophysically neutral, unitary reality beyond the distinction of the mental and the material. In psychology, the term and characteristics of nonlocal mind or consciousness were first proposed by Dossey (1989) and more recently by Clarke (1995) and Carpenter (2004, 2012) in his First Sight Model. This paper is the first systematic proposal to introduce this model of processing within the dual-model framework. Which nonlocal information can be received by S1_nip? In theory it should be all the information available in the universe regardless of distance and perhaps time constraints. But how can a living mind survive this massive flow of information? One possibility, supported by evidence (see Section 2), is that this information has a very low signal-to-noise ratio and in the normal condition of the mind functioning in a waking status of consciousness, System 2 and S1_lip functioning will almost completely mask nonlocal information signals. A good analogy is our daily immersion in the ocean of information transmitted by electromagnetic waves that we are unaware of until we decide to perceive them by tuning our detectors, radio, smartphones, etc. to amplify their signal strength to a level compatible with our sensory organs’ detection characteristics. If this assumption is correct, we should observe better detection of nonlocal information reducing or bypassing the activity of S1_lip and System 2 processing of local information. How is it possible to reduce or bypass S1_lip and System 2 activity? One possibility is to reduce or eliminate completely the flow of information sent by the sensory organs and the information processing of S1_lip and System 2. For example, to reduce the flow of information sent by the sensory organs, participants in experiments have been immersed in a ganzfeld environment (see a description of a typical protocol in the Appendix). Another alternative to bypassing S1_lip and System 2 activity is to record the neuro- or psychophysiological signals correlated with nonlocal information (see description in the Appendix). With these two experimental protocols, the supposedly non-local information may be detected consciously because any other
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mental activity of S1_lip and System 2 is maximally reduced in a ganzfeld environment, whereas with the second protocol it is possible to detect directly the purported nonlocal information at an unconscious level when it impinges on the central or peripheral nervous system.
Evidence3 It is relevant at this point to ask what the differences are in S1_nip detection accuracy for nonlocal information with different degrees of S1_lip and Sensory 2 involvement. In Table 2, we list the best evidence available from meta-analyses in decreasing order of effect size (ES) values expressed as Cohen’s d standardised difference. Except for the “anticipatory physiological signals” where ES is the difference between the two stimulus categories, in all of the other experimental conditions, ES is the difference with respect to the expected chance. From the data presented in Table 2, it is clear that the detection of information of S1_nip decreases almost linearly, passing from a condition where S1_lip and System 2 are bypassed, i.e. in dream status or when recording neuro- and psychophysiological signals, to a condition where S1_lip and System 2 activity is reduced, i.e. in a ganzfeld environment or in an altered state of consciousness, to conditions in which nonlocal information is almost completely lost, i.e. in normal status of consciousness when S1_lip and System 2 are both active, independently if free or forced-choice procedures are used. In summary, the more System 2 and S1_lip are activated, the more nonlocal information is destroyed (suppressed) in analogy with a situation where we try to understand what a friend is telling us in a disco. If we compare the efficiency of S1_lip in some experimental conditions, we can see how much stronger is its detection accuracy with respect to S1_nip (see Table 3). Similarly to what has been observed for S1_nip, we can see
Experimental condition
Source
N. Studies
Weighted random effect ES (95% CI)
Semantic categorization priming
Van den Bussche et al. (2009)
23
.80 (.60 - 1.00)
Lexical and naming priming
Van den Bussche et al. (2009)
32
.47 (.36 - .58)
Problem solving Incubation effect
Sio & Ormerod (2009)
117
.29 (.20 - .38)
Unconscious thought theory
Strick et al. (2011)
92
.22 (.14 - .30)
that the S1_lip efficiency decreases when passing from conditions where System 2 is bypassed, i.e. priming, to conditions where System 2 is temporarily inhibited (Van den Bussche et al., 2009) or made busy during System 1 processing, i.e., problem-solving incubation and unconscious complex problem-solving tasks (i.e. Sio & Ormerod, 2009; Strick et al., 2011). The comparison of ESs presented in Tables 2 and 3, clearly shows the superior efficiency of S1_lip where the information is sent to the sensory organs in any case, with respect to S1_nip. The smallest efficiency values of S1_lip are close to the largest values of S1_nip, supporting the hypothesis that the nonlocal information signal-to-noise ratio is weak and hence its detection can easily be suppressed by S1_lip or System 2 processing activity, even if we cannot exclude the possibility that it still has a weak influence both of them.
System 1 Local and Nonlocal Information Processing Comparison
Free response in Ganzfeld
Tressoldi (2011)
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.13 (.09 - .17)
At this point it is possible to compare the characteristics of S1_nip and S1_lip using the same template used to compare S1_lip with System 2 (see Table 4). The characteristics in bold are those assumed to be specific only to S1_nip. Those with a question mark, need to be tested. A striking similarity emerges with regard to the characteristics of the two information processing systems. A few basic differences obviously exist in terms of their origin, receptive capacity, constraints imposed by sensory organs for S1_lip, unbounded for S1_nip and different interference vulnerability, partly consequent on the different signal-to-noise ratios that are higher for S1_lip.
Free-response in ASC*
Storm et al. (2010)
16
.11 (.03 - .19)
A Research Agenda
Implicit behavioral anticipation effects in NSC**
Tressoldi et al. (submitted)
82
.09 (.06 - .12)
Forced-choice in NSC
Tressoldi (2011)
72
.01(.006 - .015)
Free-response in NSC
Storm et al. (2010)
14
−.03 (−.06 - .002)
Table 2. Experimental evidence obtained from meta-analyses of S1_nip detection accuracy in decreasing order of ES values. Experimental condition
Source
N. Studies
Weighted random effect ES (95% CI)
Dream
Sherwood and Roe (2003)
22
.24 (.20 - .28)
26
.21 (.13 - .29)
Anticipatory Mossbridge et al. physiological signals (2012)
Note: *ASC = altered states of consciousness, like hypnosis, deep meditation; ** NSC = normal state of consciousness. 3
Table 3. Some Experimental evidence obtained from meta-analyses of S1_lip detection accuracy in decreasing order of ES values.
We are aware that the interpretation of this evidence (as support to the reality of nonlocal perception) is hotly debated, but there is not sufficient space in this paper to discuss all alternative explanations.
The analysis of the characteristics of S1_lip and S1_nip, suggests that, apart from the basic difference in the source of information, they should function in a very similar way even if the effects on behaviour and System 2 are stronger for S1_lip and interference of System 2 is stronger for S1_nip than S1_lip. It follows that most of the experimental protocols that are used to study S1_lip can be used to study S1_nip. For example, all the protocols used to study the priming effects with S1_lip can easily be adapted to study these effects, presenting both subliminal and completely masked priming information. For example, Figure 1 shows a classical example of semantic priming where the priming, the picture of a hammer in this case, is presented subliminally. If we present the picture of the hammer
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Table 4. Similarities and differences between S1_nip and S1_lip. S1_nip
S1_lip Cluster 1—Consciousness
Unconscious (preconscious)
Unconscious (preconscious)
Implicit
Implicit
Automatic
Automatic
Low effort
Low effort
Rapid
Rapid
High capacity
High capacity
Default process
Default process
Holistic, perceptual
Holistic, perceptual
Cluster 2—Evolution Evolutionarily innate
Evolutionarily old
Evolutionary rationality
Evolutionary rationality
Shared with animals
Shared with animals
Nonverbal
Nonverbal
Modular cognition
Modular cognition
Cluster 3—Functional characteristics Associative
Associative
Domain specific
Domain specific
Contextualized??
Contextualized
Pragmatic
Pragmatic
Parallel
Parallel
Stereotypical??
Stereotypical
Cluster 4—Individual differences Universal
Universal
Independent of general intelligence
Independent of general intelligence
Independent of working memory
Independent of working memory
Cluster 5—Interaction with System 2 Affect System 2
Affect System 2
Affected by System 2
Affected by System 2
Cluster 6—Sensorial characteristics Unbounded by sensory organs detection characteristics
Bounded by sensory organs detection characteristics
Interference from information out of sensory detection
No influence by information out of sensory detection
Very low signal/noise ratio
Signal/noise ratio depends from the duration and the strength of sensory organs stimulation
Figure 1. Classical example of a procedure to investigate unconscious semantic priming.
completely covered, we can investigate whether naming can be primed by the nonlocal perception. If our premises are valid, we should observe similar priming effects in both conditions even if they are weaker (i.e. lower effect sizes) associated with the presentation of nonlocal information. One example on how to combine subliminal and nonlocal information, is offered by Carpenter, Simmonds-Moore and Moore (2012) that studied the Mere Exposure Effect, that is the tendency for persons to experience a greater liking or attraction for things as a function of having been exposed to them previously. These authors used both subliminal and nonlocal information by simply masking them completely during their presentation in a way that no sensory information is available. Other functioning similarities are expected. For example it could be tested if semantic and perceptual object features presented out of the range of the detection of sensory organs, differentially modulates the sensitivity of unconscious processing pathways, producing similar effects of attentional induction such as those studied by Martens, Ansorge, & Kiefer (2011). The core of this research agenda should be the study of the relationships between these three information processing systems. Thus some of the main questions that need to be asked are: What are the adaptive advantages of having both an S1_lip and an S1_nip? Can an S1_lip and an S1_nip be used cooperatively to enhance their specific properties? What are the neuro- and psychophysiological correlates of an S1_lip and an S1_nip? How can we exploit the information processing of S1_nip, for example by detecting and amplifying the signal strength of its neuro- and psychophysiological correlates, to assist System 2 information processing? Are some so-called “anomalous” or “exceptional” perceptual and cognitive experiences a sign of enhanced S1_nip (e.g. Fach et al., 2013)? What is the role of implicit goals pursuit (Custers & Aarts, 2010) and basic needs (see Epstein, 2008) in the facilitation or inhibition of S1_nip detection accuracy? Which individual differences facilitate the use of S1_lip and S1_nip information in avoiding the interference of System 2 (e.g. the role of Zen meditation, Strick et al., 2012)?
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Many more questions are obviously possible, but their resolution depends on how many scientists are interested in exploring this frontier of the human mind.
Acknowledgements English was independently revised by the Proof Reading Service and the Professional Editing Services
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judgments are based on common principles. Psychological Review, 118, 97. Kahneman, D. (2011). Thinking, fast and slow. New York: Farrar, Straus and Giroux. Kahneman, D., & Frederick, S. (2002). Representativeness revisited: Attribute substitution in intuitive judgement. In T. Gilovich, D. Griffin, & D Kahneman (Eds.), Heuristics and biases: The psychology of intuitive judgment (pp. 49-81). Cambridge, UK: Cambridge University Press. Martens, U., Ansorge, U., & Kiefer, M. (2011). Controlling the unconscious attentional task sets modulate subliminal semantic and visuomotor processes differentially. Psychological Science, 22, 282291. Mossbridge, J., Tressoldi, P., & Utts, J. (2012). Predictive physiological anticipation preceding seemingly unpredictable stimuli: A meta-analysis. Frontiers in Psychology, 3, 390. Pihlström, S. (2008). Panpsychism—A neglected jamesian alternative? Journal of Philosophical Research, 32, 319-347. Sherwood, S. J., & Roe, C. A. (2003). A review of dream ESP studies conducted since the maimonides dream ESP program. Journal of Consciousness Studies, 10, 85-109. Sio, U. N., & Ormerod, T. C. (2009). Does incubation enhance problem solving? A meta-analytic review. Psychological Bulletin, 135, 94120. Stanovich, K. E. (1999). Who is rational? Studies of individual differences in reasoning. Mahwah, NJ: Elrbaum. Staune, J. (2013). Towards non-physical realism. In A. Suarez, & P. Adams (Eds.), Is science compatible with free will? (pp. 209-224). New York: Springer. Storm, L., Tressoldi, P. E., & Di Risio, L. (2010). Meta-analyses of free-response studies 1992-2008, assessing the noise reduction model in parapsychology. Psychological Bulletin, 136, 491-494. Storm, L., Tressoldi, P. E., & Di Risio, L. (2012). Meta-analysis of ESP studies, 1987-2010: Assessing the success of the forced-choice design in parapsychology. Journal of Parapsychology, 72, 243-273. Strick, M., Dijksterhuis, A., Bos, M. W., Sjoerdsma, A., van Baaren, R. B., & Nordgren, L. F. (2011). A meta-analysis on unconscious thought effects. Social Cognition, 29, 738-762. Strick, M., van Noorden, T. H., Ritskes, R. R., de Ruiter, J. R., & Dijksterhuis, A. (2012). Zen meditation and access to information in the unconscious. Consciousness and Cognition, 21, 1476-1481. Tamietto, M. et al. (2009). Unseen facial and bodily expressions trigger fast emotional reactions. PNAS, 106, 17661-17666. Tressoldi, P. E. (2011). Extraordinary claims require extraordinary evidence: The case of non-local perception, a classical and Bayesian review of evidences. Frontiers in Psychology, 2, 117. Tressoldi, P., & Khrennikov, A. (2012). Remote state preparation of mental information: A theoretical model and a summary of experimental evidence. Neuro Quantology, 10, 394-402. Tressoldi, P. E., Rabeyron, T., Duggan, M., & Bem, D. (submitted). Feeling the future: A meta-analysis of experiments on the anomalous anticipation of random future events. Usher, M., Russo, Z., Weyers, M., Brauner, R., & Zakay, D. (2011). The impact of the mode of thought in complex decisions: Intuitive decisions are better. Frontiers in Psychology, 2, 37. Van den Bussche, E., den Noortgate, W., & Reynvoet, B. (2009). Mechanisms of masked priming: A meta-analysis. Psychological Bulletin, 135, 452-477. Velmans, M. (2012). Introduction to monist alternatives to physicalism. Journal of Consciousness Studies, 19, 9-10.
Kruglanski, A. W., & Gigerenzer, G. (2011). Intuitive and deliberate
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Appendix Synthetic Description of a Typical Experimental Protocol for the Study of S1_Nip Perception in a Ganzfeld Environment In a typical ganzfeld experiment, the “receiver” is left in a room relaxing in a comfortable chair with halved ping-pong balls over the eyes, and with a red light shining on them. The receiver is asked to keep his/her eyes open, and to wear headphones through which white or pink noise is played. The receiver is exposed to this state of mild sensory homogenization for about a half hour. During this time a target usually a photograph or a short videoclip randomly drawn from a set of four possible targets (each as different from one another as possible) is projected on a screen located in a distant room isolated from the “receiver’s” room without any possibility to receive sensory information (a common variant is the use of a “sender” who observes the chosen target). During the ganzfeld stimulation period, the receiver verbally describes any impressions that come to mind. These “mentations” are recorded by the experimenter (who is also blind to the target) via an audio recording or by taking notes, or both. After the ganzfeld period ends, the receiver is taken out of the ganzfeld state and is presented with four photos or video clips, one of which was the target along with three decoys. The receiver is asked to choose which target best resembles the image sent by the distant sender. The evaluation of a trial is based on (a) selection of one image by the receiver, based on his/her assessment of the similarity between his/her subjective impressions and the various target possibilities, possibly enhanced by listening to his/her mentation recorded during the session, or (b) an independent judge’s assessment of similarity between the various targets and the participant’s mentation recorded during the session. The results are then collected in the form of “hit rates” over many trials, (i.e., the proportion of trials in which the target was correctly identified). Because four possible targets are typically used in these studies, the chance hit rate is normally 25%. After many repeated trials, hit rates that significantly exceed chance expectation are taken as evidence for nonlocal information transfer. Most of these experiments are now fully automated, eliminating the possibility of data recording errors.
Because participants perform at chance on these tasks, guessing tasks generally create a random distribution of events producing separable physiological responses that reflect brief states of positive arousal (following feedback indicating a correct guess) and negative and/or lower arousal (following feedback indicating an incorrect guess). Regardless of the paradigm, physiological measures [skin conductance, heart rate, blood volume, respiration, electroencephalographic (EEG) activity, pupil dilation, blink rate, and/or blood oxygenation level dependent (BOLD) responses] are recorded throughout the session, and stimulus times are usually marked in the physiological trace itself. These continuous data are later portioned according to a pre-determined “anticipatory period” designated for analysis (generally 0.5 - 10 s preceding stimulus presentation, depending on the temporal sensitivity of the physiological measure and the intertrial interval). The portioned data are marked according to the type of stimuli they precede (arousing or neutral stimuli for the arousing vs. neutral paradigm, feedback indicating correct or incorrect guesses for the guessing paradigm). Pre-stimulus data are then compared across stimulus types. It has been known for some time that arousing and neutral stimuli produce somewhat different post-stimulus physiological responses in humans. However, what is remarkable is that many of the studies examined here make the claim that, for instance, the same physiological measure that yields a differential post-stimulus response to two stimulus classes also yields a differential pre-stimulus response to those same stimulus classes, prior even to the random selection of the stimulus type by the computer. Authors of these studies often refer to the effect as presentiment (sensing an event before it occurs) or unexplained anticipatory activity; we favor the latter terminalogy as it describes the phenomenon without implying that the effect truly reflects a reversal of the usual forward causality.
Synthetic Description of a Typical Experimental Protocol for the Study of S1_Nip Perception Recording Neuro and/or Psychophysiological Correlates Two paradigms are used: 1) randomly ordered presentations of arousing vs. neutral stimuli, or 2) guessing tasks for which the stimulus is the feedback about the participant’s guess (correct vs. incorrect). In arousing vs. neutral stimulus paradigms, participants are shown, for example, a randomly intermixed series of violent and emotionally neutral photographs on each trial, and there is no a priori way to predict which type of stimulus will be viewed in the upcoming trial. In guessing tasks, on each trial participants are asked to predict randomly selected future stimuli (such as which of four cards will appear on the screen) and once they have made their prediction, they then view the target stimulus, which becomes feedback for the participant.
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17 Perceptions of Diversity: Global versus Local Perceptions* Gizelle L. Gilbert1, Candace Myers2, M. Diane Clark2#, Shelley Williams2, Angela McCaskill2 1
Phoenix Day School for the Deaf, Phoenix, USA 2 Gallaudet University, Washington DC, USA
The current study investigated climate and diversity issues and how they contributed to students’ attitudes and experiences at a private university for the deaf. A 40-item survey was administered to assess the global perspectives regarding diversity. This scale was reduced to a 16-item scale with four subscales using exploratory factor analysis, labeled Multicultural: Diversity is Enriching, Abstract Liberalism, Cultural Racism, and Color-Blind Racism. In addition, focus groups were conducted to investigate the local perspectives of diversity of those who hold minority status within the overall cultural milieu. Keywords: Diversity; Multicultural; Abstract Liberalism; Cultural Racism; Color-Blind Racism
Perceptions of Diversity among Deaf and Hard of Hearing University Students: Global versus Local Perceptions With the election and then re-election of a Black man as President of the United States, some people of color and many Whites state that the US is in a “post-racial” era (Bonilla-Silva & Dietrich, 2011). In contrast to these statements, Bonilla-Silva and Dietrich argue that there is a new racism, which they term color-blind racism. The tenets of color-blind racism include: abstract liberalism, cultural racism, and the minimization of racism. This focus on abstract liberalism uses a “blame the victim” rationale for those who find themselves without equal opportunities; here a free market ideology is the basis for the “haves” and the “have-nots.” This view allows those who hold these beliefs to be unconcerned about inequality in the welfare system (Monnat, 2010), health care (Rosenblatt, 2009), and even extends to beliefs about immigration (Shattell & Villalba, 2008). Bonilla-Silva and Dietrich (2011) point out that racism in today’s society is implicit and institutionalized. Therefore, color-blind racism is based on the dominance of Whites in the society and not on individual prejudice. This systematic racism allows the dominant group, i.e., Whites, to explain, rationalize, and defend their “free market” interests. To better understand this new racism, one must be aware of the “location” that groups of people hold in the system; it is not an individual’s location within the system, but rather the location of the group as a whole that leads to these effects of color-blind racism. For example, many Latinos believe that they have equal opportuni*
Authors’ note: This work was partially supported by the Office of Diversity and Inclusion and the Gallaudet Research Institute through a small grant. We would like to thank all of the participants who took part in this project. # Corresponding author.
ties for success here in the US (McClain et al., 2006). This belief by Latinos in their equality has led several researchers (Bonilla-Silva, 2004; Twine & Gallagher, 2008) to claim that many Latinos identify as Whites and for McClain et al. to claim that many Latinos “adopt anti-Black beliefs.” Given these beliefs that differ by location, it becomes important to investigate both individual and institutional perceptions of diversity. In past years, a liberal arts university for deaf and hard of hearing students administered climate surveys to gain an understanding of how students viewed the campus climate. Using the Student Cultural Attitudes and Climate Survey (SCACS), this project proposed two studies to both follow up the SCACS results and to better understand overall institutional perceptions of campus diversity as well as to conduct focus groups to investigate the impact of being a member in a local minority group. Therefore, a survey was designed based on the SCACS as well as past research to evaluate global and local perspectives of diversity. This survey was followed up by focus groups that were conducted to evaluate local perspectives of diversity, using homogeneous groups from selected locations. It is important to understand both of these perspectives as those holding a color-blind perspective have been found to show more implicit prejudice than those holding a multicultural perspective that views diversity as enriching (Richeson & Nussbaum, 2003). Results from the earlier SCACS were reported as either “conducive to student success” or “barriers to student success.” Climate attributes that were viewed as conducive to student success included a belief that the university promoted a respect for diversity, that the university has done a good job in providing activities that promoted cultural understanding, and that attending diversity programs helped to build the community. In contrast, one of the climate attributes reported as a barrier to student success included the belief by students of color that the academic expectations placed on them by faculty and staff was
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based on their race or ethnicity. Students of color also reported that they had to represent their racial or ethnic group in class discussions, felt that they did not belong to the university community, and a large number of African American and Latino students reported that they felt uncomfortable going to see a faculty member of a different race or ethnic group. The SCACS report found that the climate affected both the creation of knowledge as well as individual members of the academic community. In conjunction with results from this report, the Perceptions of Diversity survey was developed and sent out. This survey was designed to determine students’ perspectives on the extent to which the university’s environment was welcoming, inclusive, and supportive. Students shared their attitudes regarding the campus climate based on race and diversity.
Study 1: The Perceptions of Diversity Survey The Perceptions of Diversity survey included 5 demographic categories (gender, academic classification, year entered the university, hearing status, and race/ethnicity) and 40 survey items. Nineteen survey items were drawn from McTighe Musil et al. (1999) and the remaining 21 items were developed by the project investigators based on current literature, the earlier SCACS findings and current diversity trends at the university (see Appendix A for complete survey). The 40 survey items were presented in Likert format: Strongly Disagree, Disagree, Neutral, Agree, and Strongly Agree. Of the 40 survey items, 20 percent of the items were reverse-worded. These reverseworded items were based on current research that suggested that these statements are not true, i.e., “Everyone has the same opportunities.”
Method Participants. A sample of 132 (8%) of the 1611 registered students responded to the Perceptions of Diversity survey. Forty-five men and 87 women completed the survey. Within these gender demographics were 16 freshmen, 26 sophomores, 30 juniors, 34 seniors, 15 graduate students, 3 special students, and 4 students who selected “Other” (e.g. English Language Institute, International, Post-baccalaureate and Continuing Education students). Four students did not specify their academic classification. Students reported their hearing status and 76.5% identified themselves as Deaf, 12.9% identified as hard of hearing, 9.1% identified as hearing, and 1.5% declined to specify their hearing status. Race and ethnicity were reported by all but 3% of our participants: 44.7% were Whites; 19.7% were African American/Black; 13.6% were Hispanic/Latino; 7.6% were Asian/Pacific Islander; 5.3% were International; 5.3% were Multiracial; and .8% selected ‘Other.’ Procedures. The Perceptions of Diversity studies were advertised in the campus daily announcements sent out on email, as well as through announcements by officers during student organization meetings, and through flyers posted in public areas on campus, as well as in dormitories. Participation was open to all current students. The researchers set up a booth in the Student Academic Center for two hours every day for one month. Students stopped by, signed an informed consent and completed the survey. Survey items and response choices were provided in American Sign Language (ASL) at the student’s request. Upon returning the completed survey, each student re-
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ceived a payment voucher and the researchers used a snow-ball recruiting technique where they asked those who already participated to encourage others to participate. Data Analysis. The five Likert scale categories were collapsed into three categories for this analysis: disagree, neutral, and agree. Exploratory factor analysis (EFA) with a varimax rotation was conducted to reduce the data and identify latent constructs in the Perceptions of Diversity scale. Using the scree plot, it was determined that the elbow occurred at four factors. Subsequent analysis was based on items loading significantly on these four factors. To create subscales that would have utility in determining prevalent attitudes of future respondents, only items that loaded grader than .5 on each of the top four factors were retained, resulting in highly distinct subscales. Using this criterion, 16 of the original 40 items were retained.
Results Given that 24 items were eliminated as either redundant or not contributing to the most significant underlying latent attitudinal factors, a second EFA was run to assess whether the relative orthogonality of the factors would be maintained with the reduced item set. As expected, the strength of the four-factor structure was increased after deleting items that did not contribute, with 55.1% of the total item variance being explained by the reduced set of items. Items were examined to determine appropriate subscale labels for the factors. These are as follows: Multicultural: Diversity is Enriching, Abstract Liberalism, Cultural Racism, and Color-Blind Racism. The overall structural model showing these four factors and the loadings of their associated items is presented in Figure 1. Finally, we developed simple subscale computational rules for users of the Perceptions of Diversity instrument that entailed adding together the Likert ratings for all the items within each of the subscales and dividing by the number of items in the subscale. For this scale, we included the original 5-point Likert ratings and this yielded a set of four scores between 1 and 5 (the same as the Likert ratings themselves) that represented the average rating of respondents for items within each subscale. Subscale scores below three demonstrate a level of disagreement with the statements within the scale. Subscale scores above three indicate a level of agreement with the statements within the scale. Scores close to three indicate the lack of an opinion one way or another. The subscales include the following items from the original SCACS survey, which also can be seen in Figure 1. The Multicultural: Diversity is Enrichingsubscale included items 24, 25, 26, 27, 28, 29 and 30. Abstract Liberalism included items 5, 12, 18, and 27. The Cultural Racism subscale included items 7 and 39. Finally, the Color-blind Racism subscale included items 4, 31, and 33. To obtain subscale scores, one adds up the Likert scores for each item and divides by the number of items in each subscale. To create the new Perceptions of Diversity scale, use the items found in the four subscales and add the appropriate Likert scores for each item. A follow-up post-hoc analysis was performed on the newly developed subscales, comparing white students to students of color. Table 1 presents the means and standard deviations for the Perceptions of Diversity subscales for white students versus students of color. There were no significant differences on any of the factors, suggesting that overall, or global, perceptions do
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24. I prefer to interact with students of the same race/ethnicity because I feel that students of different races/ethnicities do not understand my culture. 25. Instruction is modified to suit students’ language and learning styles.
26. Faculty sees all students as capable regardless of race/ethnicity. Factor 1 Multicultural: Diversity is Enriching.
27. My sense of ethnic identity is strengthened by my sense of self and my community. 28. I do not understand why people of color eat together at the cafeteria or are often seen sitting and walking together around campus. 29. It is important that my professors use examples that are relevant to different race/ethnic groups. 30. My opinions are valued by others.
5. Gallaudet University promotes diversity
Factor 2 Abstract Liberalism
12. Minorities get unnecessary special privileges ahead of more qualified people. 18. Diversity is a non-issue—we all have equal access to resources. 27. My sense of ethnic identity is strengthened by my sense of self and my community.
10. I feel pressured to use ASL, even though it is not my primary language. Factor 3 Cultural Racism
39. My race gives me special privileges.
4. Everyone ha s the same opportunities.
Factor 4 Color-Blind Ra cism
31. Fa culty use race/ethnic examples where appropriate. 33. I feel that when I participa te in class, I have the support of my classmates and fa culty.
Figure 1. Path diagram for the perceptions of diversity scale.
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not differ by race on campus. Table 2 presents the correlation matrix of the derived scores. The unit scaling proposed for easily computing interpretable subscale scores, undermines the orthogonality by using the unweighted item ratings directly in the computation of the scores and it is clear that the scaling strategy results in co-linearity among the derived scores. However, the pattern of correlations among the subscale scores is interesting in that the three subscales that are more global (Multicultural: Diversity is Enriching, Abstract Liberalism, and Color-Blind Racism) are all highly intercorrelated while the one local subscale called Cultural Racism, focusing on pressure to use ASL and that my race gives me privileges, is uncorrelated (see Table 2).
Discussion The reduced Perceptions of Diversity scale includes three global subscales and one local subscale focusing on race and the use of sign language. Interestingly, all three of the global subscales were highly correlated. Therefore, the Multicultural: Diversity is Enriching subscale and the Color-Blind Racism subscale appear not to tap different values in this sample. Future research with different local groups may find that these subscales do highlight different latent attitudes. The current sample seems to find the local group of ASL users versus those whose first language is not ASL as the main local group. If a deaf sample is not the dominant local group in Table 1. Subscale means and standard deviations for white participants as well as participants of color. Subscales
Participant Race/Ethnicity
N
Mean
Standard Deviation
t test
Multicultural
White
56
2.28
.36
t = −1.31 p = .194
People of Color
66
2.37
.38
White
56
2.16
.36
People of Color
67
2.26
.43
White
58
1.78
.59
People of Color
68
1.87
.60
White
59
2.23
.50
People of Color
68
2.28
.60
Abstract Liberalism
Cultural Racism
Color-Blind Racism
t = −1.43 p = .163
t = −.85 p = .40
t = −.48 p = .63
Table 2. Correlations among the perceptions of diversity subscales.
C-B MC AL *
MC
AL
CR
*
.50
*
.01
.47
*
.04
.43
.07
Correlation is significant at the .01 level, 2-tailed; MC = Multicultural; ALAbstract Liberalism; CR = Cultural Racism; C-B = Color-Blind Racism.
future studies, the Cultural Racism subscale may include additional items relating to race, ethnicity, sexual orientation, and gender. Items related more specially to these local groups should be included if the Perceptions of Diversity scale is used in a different sample. In terms of a comparison of the earlier SCACS survey to the current Perceptions of Diversity scale, the climate at the university appears to have changed, such that when given a general survey, the campus community reports feeling respected, comfortable, and valued. This result suggests that efforts to “warmup” the climate have been successful, at least at the global level. When only this type of general survey is used, one could conclude that diversity has become “a non-issue.” It is still important to check the perceptions of those in local groups before coming to this conclusion. Study 2 used a qualitative method to investigate local groups on campus to provide a second pointof-view.
Study 2: Local Focus Groups For the focus groups, a comprehensive list of 12 questions was developed from the SCACS findings. The content of these questions were identified in the SCACS report as findings that required further exploration; meaning the results left more questions than answers. All questions were asked in each of the five focus groups. See Appendix B for the complete list of questions.
Method Five focus groups from selected locations were organized: African American/Black, Asian/Pacific Islander, Hispanic/ Latino, native ASL signers, and new signers. Each focus group consisted of 3 to 5 students and a facilitator. The facilitators were faculty, staff, and students who previously completed Diversity Dialogue training. The focus groups were videotaped for transcription purposes. At the end of transcription, data was destroyed. Participants. A total of 20 undergraduate, graduate and special students participated in the focus groups: 4 African American/Black, 5 Asian/Pacific Islander, 4 Hispanic/Latino, 4 native ASL signers, and 3 new signers (all from European American backgrounds). Seventeen of the 20 participants were female and 3 were male. Procedures. Students were instructed in the advertisements to contact the first author to set up a date and time to participate in a focus group. When students contacted the first author, they were given a link to a Doodle poll where they selected their availability. The first author then contacted facilitators to confirm their availability and students whose availability matched the confirmed date and time were contacted to participate. For consistency within the focus groups, selected facilitators were assigned to groups that matched their location, i.e. the Asian/ Pacific Islander group was facilitated by an individual of Asian/ Pacific Island descent and the native ASL signer group was facilitated by an individual who was also a native ASL signer. When students showed up to participate in the focus groups, they signed an informed consent form and a video release form. Ground rules were explained. An interpreter was provided for the new signer group to provide sign support for students and the facilitator as needed. The video camera was left in standalone mode for the duration of the focus groups. Participation
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took one hour and students were compensated $20 for their time.
Results Transcript confirmation processes were conducted through a sign-to-English process. No identifying information was included in the transcriptions. The research team identified themes and discussed the identification and coding of the themes. Once 100% inter-rater reliability was reached, a method of constant comparisons was used to find themes for each local group response. Frequencies were calculated for each group of each theme that was identified. Transcription Coding. Responses were reviewed and coded according to a central theme. Most frequently occurring responses (those that occurred in 40% of the transcriptions) were coded. Responses such as “I can see who’s moving up the ladder at (name of university) based on their last name, their deaf school…”, “It’s easy to become ‘buddies’ with administrators whose families know each other or through family friends”, and “The teacher favors those from Deaf families” were coded as favoritism. Responses such as “… if someone of a different race wants to succeed, they have to adjust to White culture. They have to dress the way that Whites do and practice like Whites” were coded as cross-cultural issues indicating that one feels that they must conform to society’s standards to be accepted. A total of 22 themes emerged from the focus groups. A complete list of themes can be found in Table 3. Table 3. Focus group themes. 1) The university represents diversity 2) Oppression 3) Racism and discrimination 4) Cross-cultural issues 5) White privilege 6) Deaf privilege 7) Rejection 8) Communication barriers 9) Lack of exposure to different cultures 10) Separation 11) Bias 12) Tokenism 13) Favoritism 14) Cliques 15) Race and ethnicity course should/should not be required 16) Teachers don’t have time to answer students’ questions 17) No mixed interactions 18) Coursework is/is not challenging 19) Students don’t feel welcomed/belonging 20) The university and its professors have low expectations/standards of students 21) Lack of mentors/role models 22) Lack of diversity in faculty and staff
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The first step towards understanding diversity is to define it. Each focus group opened with asking students to explain their definition of diversity. Students presented concrete and abstract definitions of diversity. Many definitions were similar across groups. Everyone agreed that diversity is different across cultures, races, ethnicities, skin color, deaf, hard of hearing, and hearing, as well as in different backgrounds such as education, values, family heritage, and talents. Disabilities and sexual orientations were also included in some definitions. Some unique definitions of diversity were presented. An Asian/Pacific Islander participant said, “To me, it means like one bowl of vegetables in a salad. It has tomatoes, lettuce, different things mixed. To me, it’s similar to mixing different people in one community.” Another student in the same group said, “Educational differences too. Value differences, family heritage—same and different. That’s called diversity too.” A participant in the native ASL group said, “Diversity could be a localized skill in what people are good at. For example, some people are good at welding, technology, or playing sports. That is my definition of diversity.” After defining diversity, students were asked whether they thought that the university reflected those definitions of diversity. African American/Black (75%) and Hispanic/Latino (100%) students did not think that the university represented diversity. Reasons for this perception included the presence of cliques and separation on campus. Students saw cliques within those of the same race, hearing status, student organizations, and educational background (i.e. those who attended a deaf school versus those who were mainstreamed). These students do not “break away” from cliques. In the Hispanic/Latino group, one student answered “In my opinion, not really. When I picture diversity at (name of university), I thought it would be like 40% Black, 40% different [races]. When I came here, I felt like there wasn’t a lot of diversity.” Another student agreed saying that she “didn’t see anyone interacting and breaking away from cliques.” From students’ responses, it is clear that there is rejection happening as well as cross-cultural issues. Some students thought that the university represented diversity because there were Deaf, hard of hearing, and hearing students on one campus. Often this view of diversity becomes dominant on campus. The issue of linguistic privilege emerged as a theme for 60% of Asian/Pacific Islanders and 100% of native ASL signers. African American/Black and Hispanic/Latino respondents did not mention linguistic privilege. New signers felt pressured to be able to sign as well as those who had been signing all/most of their lives. One new signer described an incident in which she was voicing with another student and a Deaf student said to her, “I am Deaf, you must sign now.” The new signer said, “New signers can’t communicate too fast… We were left out of the conversation.” Communication barriers were more of an issue for the new signers than any other group. New signers reported positive and negative experiences learning sign language. Negative experiences included being left out of class discussions and feeling pressured to sign like native signers. Positive experiences were finding that most people at the university helped them understand sign language; there was support from “most” students for new signers. Some students reported that they enjoyed being at the university. They felt more comfortable. The Deaf world is a “wonderful experience.” One student said it was a dream of hers since she was little to learn sign language. She wanted a richer experience. Another student saw problems when she first
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arrived at (name of university), but as she adjusted, the university started to feel like home. In the Hispanic/Latino focus group, students felt that tokenism was an issue. It was reported by 75% of Hispanic/Latino participants that students of color were being used as tokens on the basis of making an organization look diverse and exploitation of student athletes from underrepresented groups by the athletic department. This group of students implied that organizations care more about looking diverse than they do about their minority members. Analysis of transcriptions revealed a favoritism theme. Sixty percent of Asian/Pacific Islanders and 75% of Hispanic/Latino participants reported that they thought that there was favoritism at the university. One student in the Asian/Pacific Islander group said, “I ask a question, the teacher looks at her book and moves on to another chapter. But I am not the only one that happens to. It happens to other students too, but the students it happens to are students of color. Those students who are U.S. citizens or American, the teacher cares about them and answers their questions.” An Asian/Pacific Islander also stated an incident where a White student was promoted ahead of her, which she attributed to the student being in the same fraternity as their boss. The student said, “We both started working in the computer lab at the same time, but the other student is higher up and is the boss’ personal assistant. I felt ashamed.” In the current study, students agreed that there is separation on campus, but they did not necessarily see these separations by race and ethnicity. Rather, they were centered on sharing similar interests such as sports, student organizations, and having attended a Deaf school. Twenty-five percent of African American/Black respondents, and 75% of Hispanic/Latino and native ASL respondents reported cliques. Respondents in the Asian/ Pacific Islander group blamed student organizations for the separation on campus. One Asian/Pacific Island respondent said, “I know diversity means we have organizations but I think that is one of the reasons for separation. Like BDSU (Black Deaf Student Union), APA (Asian/Pacific-Islander Association), ELISO (English Language Institute Student Organization) could cause people to think that these are Asian groups or Black groups. They have to because (name of university) has diverse organizations, but it could be one of the reasons for making people separated.” A suggestion to reduce the issue of separation and cliques was to make all student organizations one diversity organization. The top officers of each organization (Presidents and Vice Presidents) would lead the larger diversity group. “That way, all student organizations will support each other’s events. The structure should be similar to ELISO (English Language Institute Student Organization).” A Hispanic/Latino participant said that friendships were mostly between those who interacted through sports, reflecting this type of common bond as a basis for friendships. While Asian/Pacific Islanders perceive student organizations as barriers to diverse interactions, the Hispanic/Latino group had a different perspective. They reported that international students from Europe or those with a lighter complexion fit in more with Whites, whereas “darker skinned international students… struggle more to fit in with different groups.” According to one student, groups are “really based on skin color.” Asian/Pacific Islanders said that students tend to gather with those of the same race, e.g. Whites with Whites, Blacks with Blacks, while Asian and international students “mix with each other.” Sports and other special interests also influenced social
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circles. The issues of mixed interactions where they pertain to interracial and interethnic friendships and interacting with individuals of different groups was raised in the SCACS report. We followed up on this perception in the 2012 focus groups. Fifty percent, (n = 2) of African American/Blacks, 20% of Asian/Pacific Islanders, 75% of Hispanic/Latinos, and 100% of native ASL respondents agreed that there are mixed interactions on campus. One Hispanic/Latino student said of these mixed interactions, “I do see some friendships based on having the same interests such as sports, academics, work, and similar major.” Another student in this group stated, “Yes, I feel I interact, but I feel that [I interact] more with people in my FCS major who are White and Latino.” These comments indicate that while students may see these interactions as mixed, they are based on interests, and not race. Within these mixed interactions, students do not always feel comfortable around their same-race peers. A Hispanic/Latino student said, “I feel more comfortable interacting with different groups at (name of university) compared to Hispanics”, which shows that these students pursue such interactions. In contrast, the remaining 50% in the African American/Black group felt that there was not much racial diversity in regards to group interactions. Students socialize “inside” their race. While these students hold their own beliefs and perceptions, they remain open to interacting with different people on campus. The majority (100%) of Hispanic/Latino respondents reported a lack of mentors and role models at the university. Students felt that the absence of Hispanic/Latino mentors played a major role in the lack of retention of Hispanic/Latino students. These mentors should exemplify how the students should function as community members. How can they know how to succeed when they “do not see Latino staff, faculty, and administrator role models in the community?” Students know that the mentors are there; but they are not visible at the university. One student asked, “What have they been doing all this time?”
Discussion As can be seen in these qualitative comments, diversity remains an issue on campus. Local groups have specific problems in terms of feeling valued and/or respected. Latino students did not see role models, noting that the faculty and staff at the university do not include people from their background. Students reported issues related to favoritism and tokenism, and noted that like groups often find comfort within their own members. International students from Africa noted that they did not “fit in” as well as international students from Europe and those with lighter skin. These responses seem to reflect Color-blind Racism, with implicit racist attitudes being overlooked by groups with more privilege but impacting those who have historically been targets of overt racism. New signers noted an issue related to linguistic privilege. This issue was also seen in the Cultural Racism subscale discussed earlier. This university is a bilingual environment, with ASL and written English given equal standing. Those students who are late learners of ASL or use simultaneous communication (signing and voicing at the same time) noted that they were often the targets of heated comments that focused on their use of oral language. Using spoken English was reported as “taboo” and could make one the target of bullying. Linguistic privilege has been the target of many programs established through the
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Office of Diversity as well as the chief academic officers of the campus. It appears that this issue is more of a “hot button” than more traditional diversity issues such as sexism or racism.
General Discussion Overall, the current studies support past research, where students stay within their comfort zones because those are where they feel they can truly be themselves. However, Pratt (1990; as cited in McTighe Musil et al., 1999) emphasized the need for students to leave the “comfort zone” and enter a “contact zone” where they can get to know each other. Our findings showed that students were moving beyond their comfort zones into the contact zone at the institutional level. From both studies, students clearly recognize the importance of diversity. At the more localized level, there are still perceptions of separation and staying within one’s comfort zone reported in the focus groups. Mixed interactions often did not occur. But there was the mention of cliques, who often based on attending a deaf school. This focus on favoritism and linguistic privilege was also detected in the EFA in the Cultural Racism subscale. Interestingly, some definitions of diversity focused only on hearing status, i.e., there was diversity because deaf, hard of hearing, and hearing students were on campus. Importantly, most native ASL users are white; most native signers come from a European background and are often of Jewish descent, as they are the group who carry this specific genetic trait. In their study of perceptions of deaf ethnic minority students, Parasnis and Fischer (2005) quoted a participant who said that being around people like themselves was related to being in their comfort zone. Within a group of people who are similar, one does not feel judged and they feel free to be themselves. Additionally, Tatum (2003) explained that Black students tend to sit together because there is less pressure. In the current study, we found similar results in that students in the focus groups said that groupings were linked to having things in common. In the current study, students in the Hispanic/Latino focus group, implied that they felt more comfortable having another student of the same race there. Students also said that whatever they said would be supported when they had someone else of the same race/ethnicity in their class. It was important for students to see themselves not only in the student body, but also in the faculty and staff at the university. They placed value on ethnic role models. Past research (Parasnis, Samar, & Fischer, 2005) supported the view that having ethnic minority role models was more important than having a deaf role model. They found that White, Hispanic, and Asian deaf students at the National Technical Institute for the Deaf (NTID) felt that having role models who are deaf and of an ethnic minority was equally important while African American deaf students reported that they needed ethnic minority role models more than deaf role models. This finding seemed to be true of our Hispanic/Latino focus group participants. In the current study, we found that White and African American/Black students thought that diversity was not an issue and there was equal access for all. In contrast, Parasnis and Fischer (2005) cited research maintaining that social status and access to information was not equal for everyone. It was also found that more White students than International students believed that everyone had the same opportunities. Both findings support a color-blind perspective by Whites. The afore-
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mentioned statement is not only true within the university but for society as a whole. Some students honestly answered that they only knew of their own privileges in regard to having the same opportunities. Parasnis and Fischer (2005) pointed out that it was vital to the retention and success of ethnic minority students that institutions confront diversity in curricular and co-curricular activities. Programs that teach students about multicultural backgrounds as well as ongoing dialogues about race and diversity should be provided. From our transcriptions, we could see how important it was for students to see themselves not only in the curriculum, but also in the faculty. A university should be a reflection of its student body. New signers found it hard to follow class discussions. The abovementioned situations by new signers can be reflective of White privilege in which White individuals feel entitled to certain privileges based on their race. In this focus group, all members were White, a sampling strategy to attempt to address the confounding of Whiteness with being a native signer. Therefore, in this situation linguistic privilege can be attributed to native signers feel entitled because of visual language access. Native signers have constant access to communication whereas new signers who have just entered a signing environment are faced with the task of adapting to a new culture and language. Although linguistic privilege has yet to be defined in the literature, this discussion poses the following question: Is linguistic privilege for native signers similar to the privileges found in other dominant groups? Are native signers a dominant group at this university? Is there a mechanism that will make new signers more a part of this group? These questions warrant further exploration. Transcriptions from the new signers group indicated communication barriers that could be attributed to being in the early stages of language acquisition. New signers are still learning to communicate and are not near the level of proficiency as their more experienced peers. They may be able to catch on to what is being said around them, provided that the signer is signing at a steady pace. Thus, it seems that more understanding needs to happen as well as support from faculty, staff, and fellow students. The perspectives of new signers and native ASL signers towards the campus climate were an arena that has not been visited in the past. These two groups were not based solely on hearing status. When designing this study, we suspected that new signers would have different perspectives of the campus from native ASL signers. In the new signer focus group, our findings were not similar to the other groups. This group had more specific issues. Clearly, this group struggled with two things during their discussion: one was their feelings of oppression; the other was communication—putting their thoughts into words due to their level of signing experience. Future research should focus on facilitating communication for new signers. Campus-wide dialogue can focus on the new signer experience with past and current new signers sharing perspectives on how welcoming or unwelcoming the university is towards them. Because this study occurred at a private university for the Deaf, native ASL signers are the majority culture while new signers are the minority. The majority, in an effort to preserve their culture, may feel the need for the minority to conform to the majority culture. This pressure to conform is applied to both hearing students and new deaf and hard of hearing signers who were elected to come to a bilingual university.
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If the university is to keep up with the changing times and an ever-increasing diverse society, changes in the student body, faculty and staff, overall campus climate, as well as the curriculum are necessary to continue to move forward. Barriers need to be confronted and what works should be the focus for improvement. In general, between 2009 and 2 anges in how diversity is viewed within this university. Earlier negative responses to diversity were overt and explicit. Currently, there is a move to a more Multicultural perspective where diversity is seen as enhancing one’s life, which is a positive change. But one also finds Color-Blind Racism with its implicit and covert negative views toward diverse groups. This kind of mixed method investigation can help identify local groups that may be overlooked when only more global instruments are employed. As in the larger culture, racism has not been eliminated; rather it has changed and reflects a more abstract liberalism. This viewpoint may lead one to blame the individual if they are not successful because everyone is believed to have equal opportunities and access. The university is to be congratulated on past efforts but warned to be aware of more implicit attitudes that may lead local groups to feel unwelcome.
REFERENCES Bonilla-Silva, E. (2004). From bi-racial to tri-racial. Ethnic and Racial Studies, 27, 931-950. Bonilla-Silva, E., & Dietrich, D. (2011). Race, racial attitudes, and stratification beliefs: Evolving directions for research and policy: The sweet enchantment of color-blind racism in Obamerica. The Annals of the American Academy of Political and Social Science, 643, 190-206. Charmaz, K. (2006). Constructing grounded theory: A practical guide through qualitative analysis. Thousand Oaks: Sage. Creswell, J. W. (2009). Research design: Qualitative, quantitative, and mixed methods approaches (3rd ed.). Los Angeles: Sage. Gallaudet University (2012). Fast facts 2012. http://www.gallaudet.edu/gallaudet_university/about_gallaudet/fast _facts.html Matthews, E. T., Aina, O., & Johnson, J. (2009). Shades of distinction: How students of color experience Gallaudet University. Report.
McClain, P. D., Carter, N. M., DeFrancesco Soto, V. M., Lyle, M. L., Grynaviski, J. D., Nunnally, S. C., Scotto, T. J., Kendrick, J. A., Lackey, G. F., & Davenport Cotton, K. (2006). Racial distancing in a southern city: Latino immigrants’ view of black Americans. Journal of Politics, 68, 571-584. McTighe, C. (1999). Centrality of diversity to the academy’s institutional mission. In C. McTighe Musil, M. Garcia, C. A. Hudgins, M. T. Nettles, W. E. Sedlacek, & D. G. Smith, (Eds.), To form a more perfect union (pp. 7-12). Washington DC: Association of American Colleges and Universities. Mills, J., Bonner, A., & Francis, K. (2006). The development of constructivist grounded theory. International Journal of Qualitative Methods, 5, 1-10. Monnat, S. M. (2010). Toward a critical understanding of gendered color-blind racism within the US welfare institution. Journal of Black Studies, 40, 637-652. Parasnis, I., & Fischer, S. D. (2005). Perceptions of diverse educators regarding ethnic-minority deaf college students, role models, and diversity. American Annals of the Deaf, 150, 341-349. Parasnis, I., Samar, V. J., & Fischer, S. D. (2005). Deaf students’ attitudes toward ethnic diversity, campus climate, and role models. American Annals of the Deaf, 150, 47-58. Richeson, J. A., & Nussbaum, R. J. (2003). The impact of multiculturalism versus colorblindness on racial bias. Journal of Experimental Social Psychology, 40, 417-423. Rosenblatt, P. C. (2009). Racism and black-white relationships in endof-life care in the United States: A speculative analysis. Illness, Crisis, and Loss, 17, 113-124. Shattell, M. M., & Villalba, J. (2008). Anti-immigration rhetoric in the United States: Veiled racism? Issues in Mental Health Nursing, 29, 541-543. Smith, D. G. (2009). Diversity’s promise for higher education: Making it work. Baltimore: The Johns Hopkins University Press. Twine, F. W., & Gallagher, C. (2008). The future of whiteness. Ethnic and Racial Studies, 31, 4-24. Ullucci, K. (2006). Review of racism without racists: Color-blind racism and the persistence of racial inequality in the United States. Urban Education, 41, 533-540.
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Appendix A Perceptions of Diversity Survey 1) Diversity encourages a deeper understanding of students and the ways that our identities influence learning. 2) When we commit to diversity, we are also paving the way for equal opportunities. 3) Past history with discrimination has influenced today’s society. 4) Everyone has the same opportunities. 5) The university promotes diversity. 6) Diversity education brings society together. 7) The university provides students, faculty, and staff with opportunities to learn from different cultures. 8) Diversity values differences more than commonalities. 9) My experiences at the university have encouraged me to pursue social interactions with others of different cultural or ethnic backgrounds. 10) I feel pressured to use ASL, even though it is not my primary language. 11) I feel comfortable approaching faculty who are of a different race/ethnicity than mine. 12) Minorities get unnecessary special privileges ahead of more qualified people. 13) The university should require students to take at least one cultural and ethnic diversity course as a graduation requirement. 14) Diversity is a distraction from major issues that threatens national unity and local communities. 15) Interacting with diverse groups will improve learning, build community involvement, and new attitudes of the mind and heart. 16) Diversity is the key to helping students understand and find their many identities. 17) Diversity influences how and what students learn. 18) Diversity is a non-issue—we all have equal access to resources. 19) The university plays an important role in helping all members of the community understand diversity. 20) Supporting diversity is the right thing to do. 21) Diversity creates a commitment to equality and equal opportunities. 22) Diversity depends on groups of people to build fairness and equality. 23) Support programs and financial aid are provided equally to all students. 24) I prefer to interact with students of the same race/ethnicity because I feel that students of different races/ethnicities do not understand my culture. 25) Instruction is modified to suit students’ language and learning styles. 26) Faculty sees all students as capable regardless of race/ ethnicity. 27) My sense of ethnic identity is strengthened by my sense of self and my community. 28) I do not understand why people of color eat together at the cafeteria or are often seen sitting and walking together around campus. 29) It is important that my professors use examples that are relevant to different race/ethnic groups. 30) My opinions are valued by others.
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31) Faculty use race/ethnic examples where appropriate. 32) There is diversity and equality in faculty and staff of color. 33) I feel that when I participate in class, I have the support of my classmates and faculty. 34) New changes will lead to the loss of tradition. 35) Students and faculty are accepting of individual differences. 36) There is increased confusion about identity categories (e.g. deaf/hard of hearing, race/ethnicity). 37) When the university tries to accommodate diverse groups, the result is lowered standards. 38) Students need a curriculum that helps them to analyze their identities, and increase opportunities to learn about other cultures. 39) My race gives me special privileges. 40) Being able to voice your opinion allows for different perspectives to be heard. Note: Survey responses were rated on the Likert (1 - 5) scale from strongly disagree (1) to strongly agree (5).
Appendix B Focus Group Questions 1) Diversity means similar and different things to everyone. What is your definition of diversity? 2) Based on your definition of diversity, do you feel that the university represents diversity?
From “Shades of Distinction: How Students of Color Experience the University” 2009 Campus Climate Survey In 2009, a Student Cultural Attitudes and Climate Survey was distributed to students on campus. The findings suggested strengths and areas of opportunity for improvement at the university. For example, students reported that their experiences encouraged them to initiate contact with people of different ethnicities or cultures. The following questions are meant to give us more insight on the 2009 findings that were found to be areas where the university can improve. 3) We have heard from some students that they feel that their professors ignore their comments or questions. Why do you think that students feel ignored by their professors? What behaviors by professors may lead students to believe they are being ignored? 4) We found in a 2009 survey that more White, Biracial, and Asian/Pacific Islanders are comfortable being in situations where they are the only person in their racial/ethnic group than African American students. What would make you comfortable in such situations? 5) We asked students whether they think that students should be required to take at least one course on the role of ethnicity and race in society as a condition for graduation. Do you think that completion of a course on ethnicity and race should be required of all students? 6) Some students believe that there is racial/ethnic separation on campus. What factors do you think contribute to this perception? 7) Not everyone agrees that there are friendships between students of different racial and ethnic groups on campus. Is there a strong presence of interracial and inter-ethnic friend-
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ships on campus? 8) There was a variety of responses about being able to recognize culturally biased behavior based at the university. Has your ability to recognize culturally biased behaviors been influenced during your time as a student? 9) A high number of students responded ‘No’ and ‘Don’t know’ when asked whether they stop themselves from using language that may be offensive to others. Do some students use offensive language? 10) A low percentage of Asian/Pacific Islanders reported that they initiate contact with people of different cultural and ethnic
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backgrounds. Do you interact with people of different racial/ ethnic groups? 11) There are differences among groups in feeling that they belong at this university. Why do you think that this difference among groups exists? Is there a difference in how people experience the university? 12) A high number of seniors and graduate students disagree that the quality of academic programs here at the university is excellent compared to freshmen, sophomores, and juniors. What do you think is the quality of the curriculum here at the university?
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18 Behavioral and Experiential Self-Regulations in Psychological Well-Being under Proximal and Distal Goal Conditions Peter Horvath, Vanessa McColl Department of Psychology, Acadia University, Wolfville, Canada
This study examined the relationship of goal-related components of cybernetic, behavioral, and experiential self-regulations to psychological well-being under two types of conditions, the pursuit of intrinsic goals in general and specific intrinsic goals for the academic term. In an online survey, undergraduates (N = 186) completed global measures of psychological well-being, behavioral and experiential self-regulations, and rated themselves on goal-related self-regulatory components. Correlations indicated that most of the cybernetic, behavioral and experiential self-regulatory variables were associated with each other and with well-being. In terms of the goal-related self-regulatory components, when pursuing intrinsic goals more generally, the experiential self-regulatory component of enjoyment of the activity predicted well-being. However, when pursuing intrinsic term goals, the cybernetic self-regulatory component of perceived goal progress and the behavioral self-regulatory component of self-reinforcement for goal progress predicted well-being. The findings extend theoretical conceptualizations of psychological well-being by integrating compatibilities between cybernetic, behavioral, experiential self-regulatory processes and motivational conditions. Keywords: Self-Regulation; Motivation; Goal Conditions; Psychological Well-Being
Introduction The present study examined the relationships of behavioral and experiential self-regulatory components to psychological well-being under proximal and distal goal conditions. Both experiential and cognitive-behavioral processes have been proposed to account for the antecedents of psychological wellbeing in theories of motivation and self-regulation (Sheldon & Elliot, 1999; Sheldon & Kasser, 1995, 1998). Striving for goals is one of the central features in cybernetic, behavioral, and experiential self-regulation. However, few studies have examined the compatibilities of such self-regulatory processes with different goal conditions for the promotion of well-being. As a consequence, our understanding of the relationship between selfregulation, goal striving, and well-being remains fragmented and incomplete. The present study makes use of construal-level theory (CLT; Liberman & Trope, 1998; Trope & Liberman, 2010; Trope, Liberman, & Wakslak, 2007) to examine these relationships under proximal and distal goal conditions. Construal-level theory proposes that individuals make use of general and abstract constructs to conceptualize psychologically distant objects, and specific and concrete constructs to conceptualize psychologically close objects. According to CLT, general constructs represent the core features of objects and goals. Specific constructs represent the peripheral features of objects and goals. Construal-level theory has also been applied to examining the psychological correlates of different types of
goals. For example, research has shown that general, abstract, and distal goals are associated with experiential attributes such as desirability, enjoyment, and interest. Whereas more specific, concrete, and proximate goals are associated with behavioral diensions such as the feasibility and efficiency to achieve goals (Trope et al., 2007). Accordingly, under distal goal conditions, we proposed that core aspects of motives would be activated which would be compatible with experiential self-regulation. Under proximal goal conditions, however, peripheral aspects of motives would be activated, compatible with behavioral and cybernetic self-regulation. One would expect that closer match on attributes shared by a goal condition and components in self-regulation would be adaptive and associated with greater psychological well-being. For example, specific goals in situations are compatible with cognitive and behavioral self-regulatory processes that depend on feedback and control. On the other hand, general or abstract goals have core attributes such as desirability that is compatible with experiential self-regulatory processes that involve intrinsic interests. Accordingly, one would predict that under circumscribed conditions, such as in the pursuit of short-term goals in specific situations, cybernetic and behavioral components in self-regulation, such as perception of goal progress and selfreinforcement, would be associated with well-being. In the pursuit of goals more generally, however, experiential components in self-regulation, such as enjoyment of an activity, would be associated with well-being.
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Motivational Content Current studies on motivation have drawn distinctions between motivational content (e.g., interests and goals) and processes of self-regulation, or the ways and reasons for acting on them (Deci & Ryan, 2000; Sheldon & Elliot, 1999; Sheldon & Kasser, 1995, 1998; Sheldon, Ryan, Deci, & Kasser, 2004). Motivational content has been formulated in various but complementary ways in the literature. Proponents of Self-Determination Theory (SDT) have differentiated between intrinsic goals which are pursued because they are inherently enjoyable and extrinsic goals which are pursued for secondary reasons (Deci & Ryan, 1987; Ryan & Deci, 2000). Carver and Scheier (1998) placed goal pursuits in a hierarchy, from ideal and general goals at the top to specific routines, programs, scripts, and behaviors at the bottom. The general goals are pursued through the execution of specific and concrete acts at the bottom of the hierarchy. A related differentiation considers whether one is pursuing distal or proximal goals (Locke & Latham, 2002; Zimmerman & Schunk, 2001). The external situation is seen as more salient for individuals pursuing proximal rather than distal goals. Others have differentiated between implicit and explicit goals and motives (Thrash & Elliot, 2002). Implicit motives are based on internal needs and are less in conscious awareness whereas explicit motives are consciously formulated. The former is better at predicting long-term behaviors and achievement whereas the latter is better at predicting short-term behaviors or what people will do in specific situations (Spangler, 1992).
Behavioral and Cybernetic Self-Regulation Self-regulation has been generally conceptualized as the management and control of behavior in order to acquire goals selected by the individual (Bandura, 1997; Carver & Scheier, 1998; Endler & Kocovski, 2000; Kanfer, 1970). Theories on self-regulation were developed within behavioral, cognitive, and cybernetic theories and models (Bandura, 1997; Carver & Scheier, 1998; Kanfer, 1970). The components of cybernetic and behavioral self-regulation include goal setting, planning, feedback, self-monitoring, self-evaluation, and self-reinforcement (Endler & Kocovski, 2000; Febbraro & Clum, 1998; Kocovski & Endler, 2000; Mezo, 2009). Striving for goals is a core aspect of self-regulation and is thought to energize and guide behavior (Carver & Scheier, 1998; Locke & Latham, 2002). Behavioral and cybernetic self-regulation share similar processes involving the control of behavior to acquire desired goals. In cybernetic regulation, however, there is relatively more emphasis on cognition and the role of information feedback to guide behavior, while in behavioral regulation there is relatively more focus on the use of motivational components such as self-reinforcement. However, unlike enjoyment in experiential self-regulation, in behavioral self-regulation the reward is externally applied and the consequent experience of pleasure is seen as differentiated from the act being reinforced. For example, one student might study for a course because of intrinsic interest in the material itself, whereas another student might use externally applied incentives to persist in his study. In both cybernetic and behavioral self-regulation, behavior is adjusted to eliminate discrepancies from set goals (Carver & Scheier, 1998; Endler & Kocovski, 2000). The proximity of behaviors to valued goals is a determinant of adjustment, self-
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worth, and positive affect (Ahrens, 1987; Hyland, 1987; Siegert, McPherson, & Taylor, 2004). In cybernetic theory, positive affect occurs when the person perceives that adequate progress is being made toward goals (Carver & Scheier, 1998). In contrast, negative affect occurs if the person does not perceive that adequate progress is being made. A meta-analysis of relevant research has confirmed that goal progress is associated with increased positive and decreased negative affect (Powers, Koestner, Lacaille, Kwan, & Zuroff, 2009). Perceived goal progress in behavioral self-regulation can lead to subsequent self-reinforcement (Endler & Kocovski, 2000; Kocovski & Endler, 2000). Positive self-evaluations and self-reinforcement for reaching goals result in positive affect (Ahrens, 1987; Endler & Kocovski, 2000; Kocovski & Endler, 2000). On the other hand, low frequencies of self-reinforcement in behavioral self-regulation are associated with emotional distress and depression (Kocovski & Endler, 2000).
Experiential Self-Regulation Self-Determination Theory describes the motivational and experiential self-regulatory processes involved in satisfying core and peripheral needs and desires (Deci & Ryan, 2000; Ryan & Deci, 2000). High self-determined motivation is associated with the capacity and freedom to select and pursue intrinsically interesting goals rather than extrinsic ones (Deci & Ryan, 2000; Owens, Mortimer, & Finch, 1996; Ryan & Deci, 2000). From the perspective of SDT, individuals have a propensity to satisfy basic or primary needs for autonomy, competence, and relatedness (Deci & Ryan, 1987; Ryan & Deci, 2000). Goals and interests that meet these basic psychological needs are intrinsically motivating and satisfying. In intrinsic motivation the reward is the spontaneous experience of interest and enjoyment (Deci & Ryan, 1995; Ryan & Deci, 2000). Examples of intrinsic motivation include the pursuit of goals for affiliation, personal growth, and community relations. In contrast, extrinsic motivation includes the pursuit of goals for wealth, fame, and self-image that at best indirectly satisfy basic needs. According to SDT, experiential self-regulation has been conceptualized to function along a controlled and externally regulated to an autonomously and internally regulated continuum (Deci & Ryan, 1987; Deci, Eghrari, Patrick, & Leone, 1994). Experiential self-regulations vary in the degree to which the person pursues motives and values that have been internalized and integrated all the way from amotivation and extrinsic regulation to intrinsic motivation (Ryan & Deci, 2000). To reflect these processes, global measures have been developed to assess six levels of experiential self-regulation from amotivation to intrinsic motivation (see Pelletier et al., 2007). Based on theoretical and empirical grounds, however, some researchers have also conceptualized autonomous and controlled regulation as separate experiential self-regulatory processes (Barbeau, Sweet, & Fortier, 2009; Koestner, Otis, Powers, Pelletier, & Gagnon, 2008). Autonomously regulated individuals feel free and empowered to choose intrinsically satisfying goals and are likely to enjoy their activities (Ryan & Deci, 2000; Sheldon & Elliott, 1999; Sheldon et al., 2004). Autonomous regulation is associated with positive self-esteem (Owens et al, 1996; Sheldon & Kasser, 1995) and psychological well-being (Ratelle, Vallerand, Chantal, & Provencer, 2004; Sheldon et al., 2004; Sheldon & Kasser, 1995). In contrast, individuals using
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controlled regulation choose their goals in response to external forces. They perceive external constraints or demands to which they feel compelled to conform. In controlled regulation the individual does not feel free to choose intrinsically satisfying goals. In such circumstances, the individual is less likely to be motivated, satisfied, or successful. The pursuit of extrinsic or externally imposed goals results in less effort, basic need fulfillment, and well-being (Crocker, Brook, Niiya, & Villacorta, 2006; Sheldon et al., 2004).
Self-Regulation and Goal Types Certain goal types or conditions appear to be more compatible with some forms of self-regulation than others. Behavioral and cognitive forms of self-regulation tend to be applied to the situational requirements of goal pursuits (Locke & Latham, 2002; Zimmerman & Schunk, 2001). Behavioral strategies and tactics make it more likely that goals will be reached in specific situations. For example, implementation planning has been found to increase progress on goals and to achieve behavioral change within short time intervals (Koestner et al., 2008). Perception of goal progress, in turn, has resulted in increased well-being within short time intervals (Sheldon & Elliot, 1999; Sheldon & Kasser, 1998). In contrast, experiential aspects of self-regulation, such as intrinsic enjoyment of an activity, appear to play a more prominent role in promoting adjustment and well-being in the pursuit of long-term goals. Experiential selfregulation has been found to predict well-being after a time interval of one year (Sheldon et al., 2004), whereas its effects on well-being in short time intervals of one or two-weeks were mixed (Sheldon & Kasser, 1995, 1998). These findings suggest that the effects of different types of self-regulations on wellbeing may depend on the types of goals individuals are pursuing and the situations to which they apply. The above reviewed findings point towards two observations. First, the conceptualizations of goals fall into two main types. More general, distal, and implicit goals, although not identical, appear to be similar constructs. Likewise, more specific, proximate, and explicit goals appear to be similar constructs. Second, different self-regulatory processes appear to have differential applicability and effectiveness in addressing these two types of goals. Some evidence suggests that experiential selfregulation might be more appropriate for general, distal, and implicit goal pursuits. On the other hand, behavioral and cognitive self-regulation has been successfully applied to specific, proximal, and explicit goals in more circumscribed situations. Accordingly, general and long-term goals reflect core attributes which appear to be compatible with experiential self-regulation. In contrast, specific and short-term goals contain situational requirements which appear to be compatible with cybernetic and behavioral self-regulations.
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self-regulations are used. Cybernetic and behavioral self-regulations, however, differ in their emphases on the use of information and external rewards to control behavior. Accordingly, their effects on well-being should be tested separately. On the other hand, components of experiential self-regulation, such as intrinsic enjoyment of an activity, are likely to be more effecttive in promoting well-being in the pursuit of goals more generally because they can sustain the individual emotionally over long periods of striving. We, therefore, proposed that perception of goal progress and self-reinforcement for progress, components in cybernetic and behavioral self-regulation, would be associated with psychological well-being in the pursuit of short-term goals. On the other hand, enjoyment of the activity, a component in experiential self-regulation, would be associated with psychological well-being in the pursuit of goals more generally. Our participants completed global measures on their typical modes of behavioral and experiential self-regulations, as well as measures of psychological well-being. They also listed important intrinsic goals they pursued more generally and in the short-term and rated their use of components found in cybernetic, behavioral, and experiential self-regulation, including perceptions of goal progress, self-reinforcement for goal progress, and enjoyment of goal pursuits. The study employed self-report measures of mental health, self-esteem, and general affect to form a composite index of psychological well-being. These measures are well-known indicators of subjective wellbeing (Koestner et al., 2008; Ratelle et al., 2004).
Hypotheses We hypothesized that in the pursuit of goals more generally, active components in experiential self-regulation, such as enjoyment of the activity, would be associated with psychological well-being. On the other hand, in more circumscribed situations, such as in the pursuit of short-term goals, active components in cybernetic and behavioral self-regulations, namely perception of goal progress and self-reinforcement for goal progress, would be associated with psychological well-being.
Method Participants A total of 186 volunteer undergraduates (144 females, 42 males), ages ranging from 18 to 44 years (M = 19.68, SD = 2.60) participated in the online study. Subsequently, two subsamples were formed to examine the relationships of goal conditions with psychological well-being under general and term goal conditions. The demographic profiles of the two subsamples are presented in Table 1.
The Present Study
Measures
We proposed that psychological well-being is related to compatibilities between self-regulatory processes and different types of goal pursuits. We make this proposal based on several considerations and findings in the literature. In specific situations, a sense of accomplishment might come from success on specific tasks. Positive feedback and consequent reinforcement for success likely promote self-esteem and other psychological benefits in circumstances where cybernetic and behavioral
Demographic Information. A questionnaire was used to obtain information on age, gender, marital status, ethnic background, year of university, and college major. Global Motivation Scale (GMS). Following Pelletier et al. (2007), a shortened version of the Global Motivation Scale (Guay, Mageau, & Vallerand, 2003) was used to assess global self-determined motivation or experiential self-regulation. This 18-item version is divided into six subscales (three items per
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Table 1. Demographic variables in the general goals and term goals subsamples. Subsamples
General Goals
Term Goals
Ethnicity Caucasian
79.8%
79.6%
Native Canadian
1.1%
2.2%
Asian
6.7%
6.5%
African
5.6%
4.3%
Other
5.6%
6.5%
Not Reported
1.1%
1.1%
Marital Status Married
1.0%
Common-Law
1.0%
1.1%
Divorced
1.0%
1.1%
Single
95.5%
96.8%
1.0%
1.1%
Not Reported
0.0%
University Level First Year
62.9%
59.0%
Second Year
13.5%
15.1%
Third Year
4.5%
6.5%
Fourth Year
14.6%
15.1%
Fifth Year
4.5%
4.3%
Psychology
17.0%
20.4%
Other
83.0%
79.6%
University Major
subscale) that represent the six subtypes of experiential selfregulation described by Deci and Ryan (1985): intrinsic motivation, integrated regulation, identified regulation, introjected regulation, external regulation, and amotivation. Participants were asked to indicate the extent to which each item corresponds to their own reasons for performing different activities using a 7-point Likert scale ranging from 1 (does not correspond at all) to 7 (corresponds exactly). The GMS was reported to have satisfactory internal consistency with an α coefficient of 0.87 (Ratelle et al, 2004). Global self-determination has been shown to have acceptable temporal reliability (0.72) over a six-week period and to predict success at a wide range of behaviors including controlling one’s emotions, exercising, and studying—activities that require self-regulation (Pelletier et al., 2007). Two composite experiential self-regulatory variables were formed following the descriptions given by Deci and Ryan (1987, 2000) and confirmed by principal components factor analyses in our study and in previous research (Barbeau et al., 2009). An autonomous regulation variable was created by summing the scores of the identified regulation, integrated regulation, and intrinsic motivation subscales and then dividing this score by three. Similarly, a controlled regulation variable was created by summing the scores for the external regulation and introjected regulation subscales and dividing by two. We included these two variables in our study to examine the construct validity of our goal-related ratings. Self-Reinforcing Subscale (SRS). The Self-Control and Self-Management Scale (SCMS; Mezo, 2009) is a 16-item global measure of the general use of behavioral self-regulation and its three components. Established through a combination of
rational and factor-analytic item derivation methods, six items measure self-monitoring, five items measure self-evaluation, and five items measure self-reinforcement. The SCMS is scored on a 6-point Likert scale, with higher scores indicating more self-control and self-management skills. The scale anchors range from 1 (very undescriptive of me) to 5 (very descriptive of me). Mezo (2009) reported a Cronbach α coefficient of 0.81 for the overall scale and moderate to high convergent validity with other measures. He also reported a Cronbach α of 0.78 and a test-retest correlation of 0.70 for the Self-Reinforcing Subscale (SRS) and significant correlations with other self-control and symptom measures in undergraduates. As our study mainly focused on the control and motivational aspects of behavioral self-regulation, we used only the Self-Reinforcing Subscale. An example of an item from the self-reinforcement scale is, “I congratulate myself when I make some progress”. We included this global variable in our study to examine the construct validity of our goal-related ratings. Goal Conditions. First, participants were provided with a definition of personal goals (Koestner et al., 2008) as well as a brief description of intrinsic goals that included some examples (see Ryan, Huta, & Deci, 2008; Wicker. Hamman, Reed, McCann, & Turner, 2005). Next, participants were asked to list their most important intrinsic goals (goals pursued more generally), providing at least three and a maximum of five. Participants were then also asked to list the most important intrinsic goal they were striving for that academic term. We examined the obtained lists of goals based on definitions of intrinsic and extrinsic goals given by self-determination researchers (Ryan et al., 2008; Wicker et al., 2005). We discovered that some participants not only listed intrinsic but also extrinsic general and term goals. Examples of intrinsic goals provided by the participants in the current study included, “help others”, “build strong relationships with friends and family”, and “make new friends”. Examples of extrinsic goals included, “get wealthy”, “high GPA”, and “pass everything”. Based on agreed upon definitions of intrinsic and extrinsic goals, two researcher independently coded the general and term goals as either intrinsic or extrinsic. For the general goals, if a participant gave even one extrinsic goal, their total goal list was rated as extrinsic. Otherwise it was coded as intrinsic. The inter-rater reliability coefficient for the coding of the term goals was 0.91. The inter-rater reliability coefficient for the coding of the general goals was 0.80. Subsequently, two selected goal subsamples were created for analyses. The first subsample was created to examine the hypothesis for general intrinsic goals. The second subsample was created to examine the hypothesis for the term intrinsic goals. In forming the two subsamples, participants with extrinsic goals of the same type (general or term) as those characterizing the particular goal subsample (general or term) were excluded, thereby strengthening the intrinsic goal type of the particular sample. By focusing on intrinsic goals, we could control this goal dimension (intrinsic vs extrinsic) and thereby better test the relationship of well-being to compatibilities between our main goal dimension of interest (general vs term) and different self-regulatory components. The subsequent general intrinsic goals subsample consisted of 89 participants (71 females, 18 males) between 18 to 44 years (M = 20.13, SD = 3.39). As described above, ninety-seven participants from the whole sample who listed at least one extrinsic general goal were excluded in forming this subsample.
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The term intrinsic goal subsample consisted of 93 participants (73 females, 20 males) between 18 to 44 years (M = 20.00, SD = 3.09). Similarly to the above criterion, 93 participants in the whole sample who listed an extrinsic term goal were excluded from this subsample. Although there was some overlap in the two subsamples, as all participants had been originally asked to list both their general and term goals, we did not feel this affected the results. Goal Progress. Participants were asked to rate on two separate scales how much “progress overall” or in general they had made towards their most important intrinsic goals and how much progress they had made towards their “intrinsic goal for the term”, using 9-point Likert rating scales, ranging from 0 (none) to 8 (a great deal). We expected that their goal selfratings would reflect the actual behavior of the participants. Feelings of Enjoyment. Using 8-point Likert scales, ranging from 1 (none) to 8 (a great deal), participants were asked to rate how much acting on their intrinsic goals generally and on their intrinsic goal for the term led to feelings of enjoyment. Three items were used to assess participants’ feelings of enjoyment generally from acting on their intrinsic goals: “Rate how much acting on your intrinsic goals typically leads to feelings of enjoyment”, “...feelings of pleasure”, and “feelings of satisfaction”. The sum of these three items was used to calculate a total score for feelings of enjoyment generally from acting on intrinsic goals, with higher scores reflecting greater degree of enjoyment. Similar items were used to assess participants’ feelings of enjoyment from acting on their intrinsic goal for the term: “Rate how much acting on your intrinsic goal for the term led to feelings of enjoyment”, “...feelings of pleasure”, and “...feelings of satisfaction”. The sum of these three items was used to calculate a total score for feelings of enjoyment from acting on their intrinsic goal for the term. Self-Reinforcement for Goal Progress. Participants were asked to rate separately how much the progress on their intrinsic goals generally and on their intrinsic goal for the term led to self-reinforcement. Participants rated their responses using 8-point Likert scales, ranging from 1 (none) to 8 (a great deal). The sum of three items was used to assess participants’ use of self-reinforcement for progress on their intrinsic goals in general: “Rate how much the progress on your intrinsic goals typically leads to self-reinforcement”, “...self-praise”, and “…selfrewards”, with higher scores reflecting more general use of self-reinforcement. The sum of three similar items was used to assess participants’ use of self-reinforcement for progress on their intrinsic goal for the term: “Rate how much the progress on your intrinsic goal for the term led to self-reinforcement”, “...self-praise”, and “…self-rewards”. Psychological Well-Being Index. Following previous methods (Sheldon & Elliott, 1999; Sheldon & Kasser, 1998; Sheldon et al., 2004), a composite index of psychological wellbeing was created from the four measures described below. The raw scores for each participant on each of the following four measures were obtained and then transformed into z-scores. The negative affect z-score was then subtracted from the sum of the mental health, self-esteem, and positive affect z-scores to obtain an overall index for the participant with higher scores indicating increased well-being. The Mental Health Inventory-5 (MHI-5; Berwick et al., 1991) was used to assess mental health. This measure was comprised of five items, three of which are aimed at depressive symptoms and well-being, while two questions measure symptoms of
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anxiety. Individual are asked to rate on a 6-point Likert scale ranging from 1 (all of the time) to 6 (none of the time) how often they had the various affective experiences in the last month. The total score is calculated by reversing the answers to the third and fifth items and summing up the scores. The scores range from 0 to 30, with higher scores indicating greater wellbeing. Scores less than or equal to 18 indicate severe depression (Cuijpers, Smits, Donker, ten Have, & de Graaf, 2009). Berwick et al. (1991) reported a Cronbach α of .82 for the MHI-5 and found that it successfully detected DSM psychological disorders. The Self-Esteem Scale (SES) was used to measure overall self-esteem as revised by Rosenberg, Schooler, and Schoenbach (1989). They selected 6 of the 10 items of the Rosenberg Self-Esteem Scale (Rosenberg, 1979) in their study. An example of an item used in this study is: “I feel that I’m a person of worth, at least on an equal plane with others”. The items are rated on a 4-point scale, ranging from 1 (strongly disagree) to 4 (strongly agree). Negatively worded items four and six were reverse-scored. Higher scores on this measure are indicative of feelings of self-acceptance, self-respect, and generally positive self-evaluation. This 6-item version of the Rosenberg SelfEsteem Scale has been shown to have acceptable internal reliability (α = 0.78) in a sample of adolescents (McCreary, Slavin, & Berry, 1996) and was associated with adolescent behavioral problems and depression (Rosenberg et al., 1989). The Positive and Negative Affect Schedule (PANAS; Watson, Clark, & Tellegen, 1988) consists of two 10-item scales measuring the two primary dimensions of mood—Positive Affect (PA) and Negative Affect (NA). Positive Affect reflects the extent to which a person feels enthusiastic, active, and alert, while Negative Affect reflects subjective distress and unpleasant engagement. On each of the 20 mood adjectives participants rated on a 5-point Likert scale the degree to which they generally experienced that specific mood from 1 (very slightly or not at all) to 5 (extremely). Watson et al. (1988) reported coefficient alphas of .88 and 0.87 for the PA and NA scales respectively in a sample of undergraduates. Both the PA and the NA scales have been shown to be associated with depressive symptoms (Crawford & Henry, 2004).
Procedure Potential participants for the study were recruited via email and campus advertisements and invited to participate in an online study investigating motivation, goal processes, and psychological well-being. Those interested to participate were directed to a survey website in order to complete an online questionnaire package. Before proceeding with the survey, potential participants were presented with an online consent form. Consenting participants then proceeded to complete the survey. Upon completion, the participants were directed to an online debriefing form which outlined the study in greater detail and provided contact information of the researchers. Of the 186 participants who completed the online study, based on their choice, 143 (76.9%) participants received a bonus point towards an undergraduate course, while 25 (13.4%) received $10 in cash. The remaining 18 (9.7%) participants either did not indicate their preferred form of compensation or failed to make arrangements to receive their cash prize.
Design and Data Analysis Data screening was conducted following the procedure out-
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lined by Tabachnick and Fidell (2007). As missing values were scattered randomly throughout the data matrix, the mean was used to estimate the missing item value and added to the scale prior to analysis. The data were then examined for univariate outliers using frequencies and z-scores. Scores were considered to be outliers if they had a z-score greater than +/− 3.29. As outlined by Tabachnick and Fidell (2007), univariate outliers were adjusted by reducing the value to 1 unit greater than the next highest value within the appropriate range. Linearity and normality were examined by checking skewness and kurtosis values. Multivariate outliers were examined using the Mahalanobis distance statistic. Finally, we checked for multicollinearity and singularity of the variables. The whole sample was sorted into two goal subsamples so that the association of different self-regulatory components with well-being could be examined under general and term intrinsic goal conditions. The processes involved were examined by means of correlations and regression analyses. All regression analyses were run on z-scores. Regression analyses examined the general goals subsample for associations of psychological well-being with the following goal-related self-ratings: general progress on goals, general use of self-reinforcement for progress on goals, and general feelings of enjoyment for progress on goals. Regression analyses examined the term goals subsample for associations of well-being with the following goal-related self-ratings: progress on the term goals, selfreinforcement for progress on the term goals, and feelings of enjoyment for progress on term goals.
Results In the whole sample (N = 186), preliminary tests for gender differences on all the variables found only one significant difference, with males scoring higher on psychological well-being than females (M = 1.31 vs. M = −0.38, t = 3.05, p < 0.01). Due to lack of gender differences among the variables, we collapsed the data across genders for the rest of the statistical analyses.
Analysis of the General Goals Subsample Table 2 presents the minimum and maximum values, means, standard deviations, and internal reliability coefficients of all of the variables for the general goals subsample. Means for all established scales, that is, the Self-Reinforcing Subscale, the MHI-5, the 6-item Rosenberg Self-Esteem Scale, and the PA and NA scales of the PANAS were within one standard deviation of those found in university samples (Mezo, 2009; Ogunyemi & Mabekoje, 2007; Rosenberg, 1979; Watson et al., 1988). Correlation of the Variables in the General Goals Subsample. One-tailed Pearson correlations were conducted to examine significant associations among the variables in the general goals subsample (see Table 3). We found a number of significant positive intercorrelations among the variables. There was somewhat of a trend for the two positive experiential self-regulatory variables, autonomous regulation and enjoyment, to have higher correlations with each other and with well-being in the general goals subsample than in the term goal subsample (also see Table 4). As expected, autonomous regulation was positively correlated with well-being. Rated general goal progress and the two self-reinforcement variables also showed significant positive correlations with each other and with wellbeing. General goal progress was not significantly correlated
Table 2. Alpha reliability and descriptive statistics for all variables in the general goals subsample (N = 89). Variable
α
1) Goal progress
-
2) Self-reinforcement for goal progress 0.77
Min
Max
M
SD 1.82
0
8
5.29
14
24
17.35 3.81
3) Enjoyment
0.85
14
24
20.09 2.99
4) Global self-reinforcement
0.73
5
25
16.54 4.07
5) Autonomous regulation
0.78 10.67 21.00 16.04 1.96
6) Controlled regulation
0.67
7) Well-being index
7.50 18.00 13.96 2.42
0.82 −9.79 5.69
0.32
Mental health
0.80
21.03 4.25
9
29
3.37
Self-esteem
0.85
11
24
19.69 3.13
Positive affect
0.84
22
47
35.61 5.52
Negative affect
0.88
10
42
20.61 6.78
Note: Goal progress = progress on intrinsic goals in general; Enjoyment = feelings of enjoyment of acting on intrinsic goals in general; Self-reinforcement for goal progress = self-reinforcement for progress on intrinsic goals in general; Global self-reinforcement = Self-Reinforcing Subscale.
Table 3. Bivariate correlations of all variables in the general goals subsample (N = 89). Variable 1) Goal progress
1
2
3
4
5
6
7
- 0.26** 0.36** 0.30** 0.14 −0.12 0.27*
2) Self-reinforcement for goal progress
0.58** 0.57** 0.35** 0.04 0.32**
-
3) Enjoyment
0.45** 0.47** −0.03 0.45**
-
4) Global self-reinforcement
0.36** 0.13 0.20*
-
5) Autonomous regulation
-
6) Controlled regulation
0.14 0.50** -
7) Well-being
−0.38** -
Note: Goal progress = progress on intrinsic goals in general; Enjoyment = feelings of enjoyment of acting on intrinsic goals in general; Self-reinforcement for goal progress = self-reinforcement for progress on intrinsic goals in general; Global self-reinforcement = Self-Reinforcing Subscale. *p < 0.05. **p < 0.01.
Table 4. Bivariate correlations of all variables in the term goals subsample (N = 93). Variable 1) Goal progress 2) Self-reinforcement for goal progress 3) Enjoyment 4) Global self-reinforcement 5) Autonomous regulation 6) Controlled regulation 7) Well-being
1
2
3
4
5
6
7
- 0.48** 0.57** 0.38** 0.36** 0.07 0.42** -
0.60** 0.57** 0.21* 0.00 0.36** -
0.30** 0.27** 0.07 0.29** -
0.32** 0.14 0.24** -
0.28** 0.43** -
−0.37** -
Note: Goal progress = progress on intrinsic term goals; Enjoyment = feelings of enjoyment of acting on intrinsic term goals; Self-reinforcement for goal progress = self-reinforcement for progress on intrinsic term goals; Global self- reinforcement = Self-Reinforcing Subscale. *p < 0.05. **p < 0.01.
with autonomous regulation or controlled regulation. Controlled regulation did not correlate significantly with most other variables, including autonomous regulation. It was negatively
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correlated with well-being. Overall, the correlations of the cybernetic, behavioral, and experiential goal-related ratings with the global variables supported their construct validity. Regression Analysis of the General Goal-Related SelfRegulatory Components. A regression analysis was used to test the association of psychological well-being with the three general goal-related self-regulatory components in the general goals subsample (N = 89). Ratings of cybernetic, behavioral, and experiential self-regulatory components related to the pursuit of goals in general were entered together into the regression to determine their unique contributions to psychological wellbeing. Only general enjoyment was found to have a significant beta (β = 0.36, p < 0.01), while general goal progress (β = 0.12, p > 0.20) and general self-reinforcement for goal progress were not significantly associated with well-being (β = 0.07, p > 0.50) in the overall regression equation [R2 = 0.216, F(3, 85) = 7.80, p < 0.001].
Analysis of the Term Goals Subsample Table 5 presents the minimum and maximum values, means, standard deviations, and internal reliability coefficients of all of the variables for the term goals subsample. As in the general goals subsample, the means for all established scales were within one standard deviation of those found in university samples (Mezo, 2009; Ogunyemi & Mabekoje, 2007; Rosenberg, 1979; Watson et al., 1988). The ratings of feelings of enjoyment in the term goal subsample, however, were considerably lower than those in the general goals subsample (also see Table 2). There were no other apparent differences between the general and term goals subsamples. Correlation of the Variables in the Term Goals Subsample. One-tailed Pearson correlations were conducted to examine significant associations among the variables in the term goals subsample (see Table 4). The pattern of significant correlations was similar to that found in the general goals subsample, but with a few exceptions. Again there were a number of significant positive intercorrelations among the variables. There was somewhat of a trend, however, for the behavioral and cybernetic regulation variables, including rated term goal progress, to Table 5. Alpha reliability and descriptive statistics for all variables in the term goals subsample (N = 93). Variable
α
Min
Max
M
SD
1) Goal progress
-
1
8
5.52
1.86
3
24
16.89 4.14
2) Self-reinforcement for goal progress 0.79 3) Enjoyment
0.92
8
24
16.89 3.90
4) Global self-reinforcement
0.79
4
25
15.51 4.36
5) Autonomous regulation 6) Controlled regulation 7) Well-being index
0.79 10.33 21.00 15.85 2.04 0.66
7.00 18.50 13.68 2.35
0.80 −9.59 6.43
0.26
3.38
Mental health
0.80
9
30
20.89 4.31
Self-esteem
0.85
12
24
19.73 3.10
Positive affect
0.85
21
47
35.04 5.83
Negative affect
0.89
10
42
20.41 7.05
Note: Goal progress = progress on intrinsic term goals; Enjoyment = feelings of enjoyment of acting on intrinsic term goals; Self-reinforcement for goal progress = self-reinforcement for progress on intrinsic term goals; Global self-reinforcement = Self-Reinforcing Subscale.
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have higher correlations with each other and with well-being than in the general goals subsample. Term goal progress was also significantly correlated with autonomous regulation. Controlled regulation was negatively correlated with well-being, not correlated with goal progress, and positively correlated with autonomous regulation. With regard to the latter finding, participants appear to have accessed some similar processes in these two forms of experiential self-regulation under short-term goal conditions. For the most part, the correlations of the cybernetic, behavioral, and experiential goal-related ratings with the global variables supported their construct validity. Regression Analysis of the Term Goal-Related Self-Regulatory Components. A regression analysis was used to test the association of psychological well-being with the three term goal-related self-regulatory components in the short-term goals subsample (N = 93). Ratings of cybernetic, behavioral, and experiential self-regulatory components related to the pursuit of short-term goals were entered together into the regression to determine their unique contributions to psychological wellbeing. Term goal progress was found to be significant (β = 0.33, p < 0.01), term self-reinforcement was marginally significant (β = 0.22, p < 0.08), while term enjoyment was not significantly associated with well-being (β = −0.02, p > 0.80) in the overall regression equation [R2 = 0.210, F(3, 89) = 7.87, p < 0.001].
Discussion The present study examined whether psychological well-being was associated with compatibilities between self-regulatory components and goal conditions. Consistent with construallevel theory, our findings indicated that enjoyment of the activity, an experiential self-regulatory component, accounted for psychological well-being in the pursuit of goals more generally. In contrast, in the pursuit of short-term goals, cybernetic and behavioral components in self-regulation, namely perception of goal progress and self-reinforcement for goal progress, accounted for well-being. The latter are notable findings given the fact that they occurred even in the pursuit of intrinsic goals, when one would expect extrinsic goals to be more consistent with the situational focus of cybernetic and behavioral regulation. These results suggest, therefore, that cognitive and behavioral self-regulations are generally applicable to managing various types of goals in specific situations. Overall, the two global experiential regulatory variables were more strongly associated with well-being than was global selfreinforcement. Consistent with past research, controlled regulation was negatively associated with well-being (Barbeau et al., 2009; Koestner et al., 2008; Sheldon et al., 2004). These effects are likely to be due to the positive and negative contributions of autonomous and controlled regulations, respectively, to the satisfaction of basic needs (Deci & Ryan, 1987; Ryan & Deci, 2000) and their relations to feelings of security and confidence (Ratelle et al., 2004). Controlled regulation had no associations with other benign processes, suggesting that it might contain various dysfunctional elements. The absence of significant correlations with enjoyment and positive reinforcement suggests that it is also likely to involve a mix of both pleasant as well as unpleasant experiences. Unlike autonomous regulation, controlled regulation appears to lack attributes which lead to enjoyment of activities and approach behaviors. These factors likely undermine its effectiveness to promote long-term satisfaction and well-being.
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Well-being has been shown to be the product of effective coping, as proposed by cognitive-behavioral and cybernetic theories (Bandura, 1997; Carver & Scheier, 1998, Kanfer, 1970). Individuals find cognitive and behavioral interventions helpful to cope with a variety of psychological problems (Febbraro & Clum, 1998). Our findings also suggest that such selfregulatory processes are related to health benefits. The contributions of cognitive and behavioural self-regulatory processes to well-being have also been recognized in the motivational literature (Sheldon & Elliot, 1999; Sheldon & Kasser, 1995, 1998). Sheldon and Kasser (1995) also suggest, however, that psychological health not only depends on how we achieve our goals but also why we seek them. While the cybernetic and behavioural self-regulations focus more on how to cope with specific tasks and situations, experiential self-regulations focus more on why we pursue goals. Our findings support but also extend such previous theorizing in showing that these various aspects of self-regulation are related. Autonomous regulation, a global experiential variable, and global self-reinforcement, a behavioral variable, were correlated with each other and with other self-regulatory processes. These findings and those of others suggest that experiential and behavioral self-regulatory processes are likely to be complementary to each other. For example, in studies of experiential self-regulation, implementation planning was found to play a pivotal role in making progress on short-term goals, which in turn, promoted psychologycal well-being (Koestner et al., 2008; Sheldon & Elliot, 1999; Sheldon & Kasser, 1998). As another example, motives have been shown to promote exercise participation through influencing behavioral and experiential self-regulation (Ingledew & Markland, 2008). Our findings also suggest the need for more comprehensive or encompassing theories of self-regulation to account for psychological well-being. Also pointing in this direction are the findings from positive psychology that a number of life activeties contribute to life satisfaction, including the pursuit of pleasure, engagement in activities, and finding meaning (Peterson, Park, & Seligman, 2005). The question arises as to how all these constructs might be related to each other with regard to the promotion of life satisfaction and well-being? Our findings suggest that experiences and activities that enhance well-being share similarities in their activation of pleasant experiences but might also have unique compatibilities with our internal and external environments which also have to be taken into consideration. Along this line of inquiry, future research could examine the differential contributions of other types of self-regulation to well-being, such as emotional regulation, under different types of goal conditions.
Study Limitations One aspect of our study was that the imbalance in the sex ratio might limit the generalizability of our findings to the general population. However, most of our measures did not reveal any significant differences between males and females. Another limitation of our study was that we examined self-regulatory processes only under intrinsic goal conditions. Consequently, one might argue that the reason we did not find that enjoyment was associated with well-being in the short-term goals subsample was because we had restricted the range of the enjoyment variable. However, this possibility can be ruled out because the SD of the enjoyment variable in the term goals subsample was
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actually larger than in the general goals subsample.
Conclusion In conclusion, our results were consistent with predictions from construal-level theory that compatibilities between selfregulatory processes and goal conditions would be related to psychological well-being. It makes sense to find that the impact of different self-regulations would be related to their similarities to the contents and conditions of our internal and external environments. Although each type of self-regulation appears to have its own niche, our study also indicated considerable associations among them through sharing pleasant experiences. This finding suggests that they are related building blocks in the overall management of well-being. Our study helps to ex- tend theoretical conceptualizations of well-being by integrating cybernetic, behavioral, and experiential self-regulatory proc- esses and types of goal pursuits found in the promotion of well-being. Our study points toward the need to further develop comprehensive psychological theories that can more fully ac- count for the various ways we acquire well-being and pursue life satisfaction. We hope that our findings and proposals have been a step toward this important goal.
Acknowledgement This study was supported by a Canadian Institutes of Health Research Master’s Award held by the second author.
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19 The Beliefs and Attitudes about Deaf Education (BADE) Scale: A Tool for Assessing the Dispositions of Parents and Educators* M. Diane Clark1#, Sharon Baker2, Song Hoa Choi1, Thomas E. Allen1 2
1 Gallaudet University, Washington DC, USA Mary K. Chapman Center, University of Tulsa, Tulsa, USA
This paper reports on the development of the Beliefs and Attitudes about Deaf Education (BADE) scale and presents psychometric information derived from the administration of the scale to a national sample of parents, teachers, and program administrators during Wave 1 data collection of the Early Educational Longitudinal Study (EELS). Initially the scale had 47 items; however, 26 items were eliminated during analysis because they were found to be either redundant or not contributing to the most significant underlying latent attitudinal factors. We examined the content of the items loading highly on the factors in this final analysis to determine appropriate subscale labels for the factors. These are as follows: 1) Literacy through Hearing Technologies and/or Visual Support for Speech Comprehension; 2) Visual Language and Bilingualism; 3) Listening and Spoken Language; and 4) Difficulties Associated with Hearing Parents Learning ASL. The BADE scale will be helpful to families with deaf children and the professionals working with them as they explore the different communication options and their own personal beliefs and attitudes toward deaf education. Keywords: Deaf; Educational Attitudes; American Sign Language; Educational Choice; Literacy
Introduction Decisions about how best to educate a deaf child are inextricably tied to the beliefs that decision-makers (parents and teachers primarily) hold about language, culture, innate capacities, pedagogy, normalcy, and diversity. Throughout history, fundamental questions about the nature of humankind and the nature of human knowledge (and the important role of language in the generation of knowledge) have led philosophers to diverge greatly in their understandings of many domains within the realm of human experience, including ethics, religion, epistemology, politics, the nature of reality, the role of the individual in society, and so forth. In turn, these have given rise to the emergence of a broad set of diverse approaches to education. Two philosophies, unique to deaf education, have existed regarding the education of deaf peoples for many centuries and can be traced back to early philosophers such as Aristotle, who wrote that one could not have intelligence without speech. Indeed, without speech, you were considered a barbarian and could not speak to God. Plato believed that language was the pathway to truth, but believed that Greek was the only true language that would lead you to true knowledge. An opposing *
Copies of the BADE Scale and its scoring manual can be downloaded at vl2.gallaudet.edu/Publications and Products/ASL Assessment Toolkit. Corresponding author.
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philosophy, not articulated until the Italian Renaissance in the 15th and 16th centuries in the writings of Rodolphus Agricola and Gerolamo Cardano, argued that deaf individuals could be taught to read and write (and thus acquire knowledge). This broader view was later expanded in the philosophical views of French philosophers of the 18th century, such as Rosseau, on the role of education and the nature of an individual’s relationship to society. Rosseau warned of the potential damaging effects of imposing societal norms on Man’s innate goodness (Doyle & Smith, 2007). The cultural perspective espoused by the 18th century French philosophers supports the use of natural sign languages (Ladd, 2002) and a Deaf epistemology (Hauser, O’Hearn, McKee, & Steider, 2010; Holcomb, 2010). This philosophy sees deaf individuals as visual learners who bring knowledge to bear about the most effective practices for deaf education, tending to focus on ASL/English Bilingual educational curricula (Nover, Andrews, Baker, Everhart, & Bradford, 2002; Simms & Thumann, 2007), historically rooted in the manual philosophy which dates back to the 1700s in France. Over the years, the power and influence of the two opposing philosophies, oralism and manualism, have been compared to a pendulum with the two philosophies on either side of the pivot and signed systems or total communication existing at the point
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of equilibrium. The higher the pendulum arcs and the stronger the force behind it, the more radical the beliefs and the more pronounced the eventual downswing to the opposing philosophy, spurring advocates on both sides to defend their beliefs and challenge opposing sides. Even when deaf education was in its infancy, there were controversies among the most prominent leaders who were steadfast in their advocacy for their particular system of beliefs. For example, in the 17th century Samuel Heinicke, a German teacher of the deaf and promoter of the oral method and the Abbe de l’Epée, a French teacher of the deaf and promoter of the manual method advocated for diametrically opposing methods. Although the controversy regarding the best communication method to teach language to deaf students began much earlier, the disagreements between these two prominent figures escalated the controversy. It began through a series of letters, each man trying to convince the other of the fallacy of his approach and reached a pinnacle in 1783, when the Academy of Zurich was asked to hold an impartial tribunal to review the two opposing philosophies and to determine which was superior (Easterbrooks & Baker, 2002). The Academy, however, did not hear from both sides, as Heinicke was not willing to divulge the details of his approach (Marvelli, 1973). The Academy’s decision was based on the evidence presented; the judgment was made that neither method was natural, but the manual method was considered better (Scouten, Warren, Burns, Ray, Basile, Avery, & Menkis, 1984). The controversy continued a century later in the United States between two hearing sons of deaf mothers: Alexander Graham Bell, a wealthy and politically powerful ally of the oral method and Edward Miner Gallaudet who supported the use of manual signs. Both men feuded over the two philosophies through published papers and public lectures. Bell felt passionately that the system of education of the deaf was severely flawed and stated that manual signs perpetuated isolation of deaf people from hearing society. Moreover, Bell believed that deaf schools encouraged intermarriage among deaf people, which potentially could lead to a “deaf race”. To improve the educational system in the United States, Bell made three recommendations: eliminate educational segregation in institutions, eliminate the use of sign language, and eliminate deaf teachers. On the surface Bell and Gallaudet appeared to be as diametrically opposed as did del’Epée and Heinicke; however, while neither de l’Epée nor Heinicke would falter from his beliefs, Gallaudet began to explore a middle ground approach. Eventually he agreed that the oral method might be useful for some students (Easterbrooks & Baker, 2002). The approach Gallaudet conceptualized used ASL as the language of instruction, emphasized English through reading and writing, and provided speech lessons to those who could benefit. He called his approach the Combined Method. Among his contemporaries, his approach was controversial, as they perceived the addition of speech to the curriculum as a threat. In 1886, Gallaudet convened a conference, focusing on developing a unifying communication philosophy that maintained manual signs, but added articulation and lipreading to the curriculum. He persuaded those in attendance to adopt a resolution calling for all schools for the deaf to embrace a balanced, combined approach—a forerunner of today’s ASL/English bilingual philosophy. Although Gallaudet’s advocacy for a combined approach gained momentum at the 1886 conference, by 1888 his efforts were thwarted by the International Congress on Education of the Deaf (ICED) held in Milan, Italy (Lane, 1989). The Congress
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passed a resolution claiming the superiority of the oral method in the education of the deaf. The resolution remained on the record for 122 years until the 2010 ICED conference in Vancouver, BC during which a vote occurred to rescind it. Deaf education today remains a polarized field. The legacy of controversy continues and despite efforts to blend communication techniques in various combinations, the issues that were debated in the 18th and 19th centuries, continue today. The controversy impacts educational outcomes for deaf students, who on average perform well below their hearing, same-age peers (Allen, 1986; Conrad, 1979; Marschark & Harris, 1996; Musselman, 2000). Some suggest that a cultural model with its emphasis on visual language will improve educational outcomes for deaf children (Holcomb, 2010; Simms & Thumann, 2007), and there is evidence to show that deaf individuals with early ASL backgrounds tend to be academically successful (Allen & Morere, 2012; Freel, Clark, Anderson, Gilbert, Musyoka, & Hauser, 2011; Morford, Wilkinson, Villwock, Piñar, & Kroll, 2011; Padden, 1980). The decision of which educational philosophy to follow has potentially long-lasting positive or negative outcomes for deaf children. So what are the attitudes of parents, teachers, and school administrators regarding these two philosophies, and what impact do these beliefs have on the educational choices made (and the successes or failures experienced) for deaf children? Up to now, research has not systematically investigated the attitudes of parents, teachers, and school administrators about their educational beliefs and attitudes. The lack of a reliable, valid measure of these beliefs is an impediment for studying their nature and prevalence, as well as their impact on education. As part of its Early Education Longitudinal Study (EELS), the NSF-funded Science of Learning Center on Visual Language and Visual Learning (VL2), undertook the design of a tool to remedy this lack. The result of this effort was the development of the Beliefs and Attitudes about Deaf Education (BADE) scale. This paper reports on the development of the BADE scale and presents psychometric information derived from the administration of the scale to a national sample of parents, teachers, and program administrators during Wave 1 of data collection of EELS.
Method Scale Development To develop the BADE scale, the researchers developed 47 items reflecting the range of views about Deaf education based on long standing issues found in deaf education and reflected in the introduction. These issues focus on communication choices, the language of instruction, and the use of technology. Additionally, there are the two views or models of deaf individuals also discussed in the introduction. In summary, the first model is that deaf people represent a linguistic minority and reflect a visual culture, which is referred to as a cultural model of deaf people while the model adopted by most hearing people, who do not interact with deaf people, is the medical model, where deaf people are viewed as needing to be fixed. Items were developed to reflect these various issues. A concerted attempt was made to maintain neutrality with respect to opposing philosophies and to include roughly equal numbers of statements representing different points of view. A 5-point Likert scale representing levels of agreement (1 = Strongly Disagree to 5 = Strongly Agree) was attached to each scale item. The respondents’ task was to indicate their level of agreement with each
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statement using the 5-point scale. The statements covered a range of topics, including: • Communication choices, such as ASL (e.g., Deaf and hard of hearing children can learn ASL), Cued Speech (e.g., Deaf and hard of hearing children can learn English if it is made accessible through a combination of residual hearing, speechreading, and Cued Speech as infants), spoken language (e.g., Because sign language hinders the development of listening and talking, young deaf or heard of hearing children should be allowed to develop spoken language initially without the influence of signs), and signed systems (e.g., Talking and signing at the same time provides children access to both a visual and an auditory language); • Technology (e.g., New technologies (e.g., cochlear implants) are effective in producing normal-like hearing ability in deaf children); • Medical interventions (e.g., Efforts initially should focus on medical interventions in order to try to reduce the negative effects of hearing loss); and • Culture and bilingualism(e.g., Being a member of a Deaf community with a unique culture and language enriches one’s life). The 47 items are presented as an Appendix to this paper.
The Early Education Longitudinal Study and Study Participants The EELS sample was recruited from schools that had agreed to become VL2 School Partners. These schools were invited to participate in a three-year longitudinal study to investigate, 3-, 4-, and 5-year-old deaf children’s cognitive, language, and literacy development during the critical period when they were transitioning into school. In turn, the schools that joined the project, recruited families to participate. Modeled after the US Department of Education’s Pre-Elementary Educational Longitudinal Study (PEELS) conducted by the National Center for Special Education Research (Markowitz et al, 2006), this longitudinal study included: 1) a comprehensive battery of direct assessments of cognitive skills, language skills, and emerging literacy skills; 2) a set of indirect assessments of social, communication, academic, and language development embedded in Parent and Teacher surveys targeted at providing ratings on project participants; 3) Parent Surveys, including (in addition to the indirect assessments and the BADE scale) questions on family background, literacy and language practices in the home, cochlear implant use and experience, and interactions between school and home; 4) Teacher Surveys, including (in addition to the indirect assessments and the BADE scale) questions about classroom practices; and 5) Program Administrator Surveys, including (in addition to the BADE tool), questions about school policies. All participants, including the children who were given a small toy worth less than $5.00, were compensated for completing the surveys. The types of schools included in the survey were public and private pre-schools, as well as early childhood programs. Schools were located in 23 states in various sized communities; 13% of the schools were in very large cities, 23% in large cities, 8% in medium-sized cities, 15% in suburbs, 17% in small cities or towns of fewer than 50,000 people, 21% in rural areas, and 2% were on an Indian reservation. The schools had relatively high levels of federal funding with 73% of schools receiving
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these funds. The programs participating in this longitudinal project varied, including both mainstream programs and deaf schools as reported by the school administrators. Many of the programs were centered based preschool programs that served primarily hearing children; 25% as reported by administrators, which served 40% of the children. Other programs were center based childcare programs that primarily served hearing children; 3% as reported by administrators serving 4% of the children. Center based preschool programs that primarily serve deaf or hard of hearing children were reported by 43% of the administrators and these programs served 70% of the children while 3% were child care programs for deaf and hard of hearing children (4% of the children.) An addition 13% were reported as home based programs for deaf and hard of hearing children, which served 21% of the children. Finally administrators reported that 14% of the programs were clinics that provided occupational and/or speech and language therapy, serving 23% of the children. Of the 251 Wave 1 participants, 159 children had parents who completed the parent survey. Of these children, 100 were from hearing families, and 59 had a least one deaf parent in the home. Languages used in the home included English (42%), Spanish (5%), ASL (43%), and signed English (10%). Please note that parents were able to report more than one home language. Of all of the children in the survey (n = 199), 57 had cochlear implants while 142 did not have a cochlear implant. Completed surveys from 62 teachers and 48 school administrators were received; these surveys were linked to a total of 191 children, owing to the fact that teachers and administrators came from classrooms or schools with more than one deaf student participant. For the current analysis, designed to evaluate the psychometric properties of the BADE scale, item response data from the teacher, parent, and administrators surveys were merged into a single data set containing 269 records.
Analytic Plan Our strategy for analyzing and refining the BADE scale included several steps. First, we analyzed the raw item responses with an Exploratory Factor Analysis (EFA) to determine the underlying latent structure. The EFA was computed using IBM SPSS, version 19.0. A principal component analysis was used to obtain the structure. A rotated component matrix was obtained by using a varimax rotation to maximize the distinctiveness of the factors and facilitate interpretation (Field, 2009). We evaluated the Scree plot, and selected factors with the highest Eigenvalues (greater than .4). We examined the content of items with the highest loadings on these factors and assigned labels to the resulting subscales. We subsequently conducted a reliability analysis of the resulting scales, and eliminated items demonstrating the lowest item to scale correlations. Finally, we re-ran the Factor Analysis with the reduced item set to confirm the stability of the derived scales.
Results Using the scree plot, it was determined that the elbow occurred at 4 factors. Subsequent analysis was based only on items loading significantly on these four factors. To create subscales that would have utility in determining prevalent attitudes of future respondents, we chose to retain only those items loading greater than .5 on each of the top four factors, resulting in
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highly distinct subscales. Using this criterion, 26 of the original 47 items were retained. Reliability analysis using Cronbach’s Alpha on each of the four subscales resulted in highly reliable scales: (Factor 1 α = .91, Factor 2 α = .89, Factor 3 α = .80 and Factor 4 α = .85). Given that we had eliminated 21 items as being either redundant or as not contributing to the most significant underlying latent attitudinal factors, and that the reliability analysis utilized unit scaling (raw item responses, unweighted by the resulting factor loadings), we re-ran the factor analysis to assess whether the relative orthogonality of the factors would be maintained with the reduced item set. As expected the strength of the four-factor structure was increased after deleting unreliable items, resulting in a set of four factors with item loadings highly similar to the first analysis and a structure that explained 61.3% of the total item variance. We examined the content of the items loading highly on the factors in this final analysis to determine appropriate subscale labels for the factors. These are as follows: Literacy through Hearing Technologies and/or Visual Support for Speech Comprehension (eigenvalue = 5.81, explaining 22.3% of the total variance); Visual Language and Bilingualism (eigenvalue = 5.09, explaining 19.6% of the total variance); Listening and Spoken Language (eigenvalue = 2.95, explaining 11.3% of the total variance); and Difficulties Associated with Hearing Parents Learning ASL (eigenvalue = 2.08, explaining 8% of the total variance). The overall structural model showing these four factors and the loadings of their associated items is presented in Figure 1. Finally, we developed simple subscale computational rules for users of the BADE instrument that entailed adding together the Likert ratings for all the items within each of the subscales and dividing by the number of items in the subscale. This yielded a set of four scores between 1 and 5 (the same as the Likert ratings themselves) that represented the average rating of respondents for items within each subscale. Subscale scores below three demonstrate a level of disagreement with the statements within the scale. Subscale scores above three indicate a level of agreement with the statements within the scale. Scores close to three indicate the lack of an opinion one way or another. A follow-up, post-hoc analysis was performed on the newly developed subscales. Table 1 presents the means and standard deviations for the BADE subscales broken down by the constituent caregiver groups (Parents, Teachers, and Administrators). In this longitudinal sample, there was strong agreement among all groups to items representing the Visual Language and Bilingualism subscale. Parents expressed mean levels of agreement to the Literacy through Hearing Technologies and/or Visual Support for Speech Comprehension scale that exceeded 3 points, whereas Teachers and Administrators were more likely to disagree with statements oriented to this philosophy. Respondents from all groups tended to disagree with statements indicating that learning ASL with English might pose a threat to later language development (Listening and Spoken Language), though, again, parents showed higher levels of agreement than the other two groups. All three groups showed quite low levels of agreement with statements suggesting that hearing parents would have difficulty learning ASL (Difficulties Associated with Hearing Parents Learning ASL.) While the factor analysis yielded orthogonal factors and helped sort statements into factors exhibiting the highest levels of within-factor communality and between factor uniqueness,
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the unit scaling proposed for easily computing interpretable subscale scores, undermines the orthogonality by using the unweighted item ratings directly in the computation of the scores. Table 2 presents the correlation matrix of the derived scores. It is clear that the scaling strategy proposed results in considerable co-linearity among the derived scores. However, the pattern of correlations among the subscale scores is quite interesting, and also quite predicable from the two opposing educational philosophies described at the beginning of this paper. The Literacy through Hearing Technologies and/or Visual Support for Speech Comprehension subscale correlated positively with both the Listening and Spoken Language subscale and the Difficulties Associated with Hearing Parents Learning ASL subscale, reinforcing the idea that a strong orientation toward literacy through hearing technologies, speech reading, and/or cued speech imply negative attitudes about bilingualism and low expectations about parents’ abilities to acquire sufficient sign skill to employ a rich visual language in the early childhood experiences of preschool deaf children. At the same time, the Visual Language and Bilingualism subscale demonstrated significant and moderately high negative correlations with all of the other subscales. Again, this finding reinforces the presence of a strong dichotomy of attitudes in the population (and speaks to the validity of the BADE scale for studying attitudinal differences among participant subgroups). Finally, the correlation between the perceived Difficulties Associated with Hearing Parents Learning ASL subscale and the Listening and Spoken Language was a substantial .61 and highly significant. Those who perceived ASL as a threat to later language development tended also to underrate a parent’s ability to master ASL. In effect, these two scales present an attitude of monolingualism.
Discussion The BADE scale includes 26 items and four subscales; Literacy through Hearing Technologies, Visual Language and Bilingualism, Listening and Spoken Language, and Difficulties for Hearing Parents to Learn ASL. The BADE scale was developed to allow parents, early interventionists, and teachers to better understand their own attitudes about best practices for young deaf learners. As such, if permits users to determine their current beliefs. The four subscales can stimulate dialogues about other possibilities that parents may be unaware of during the initial moments of learning that they have a child who has just “failed” their first test (Early Intervention: The Missing Link; http://www.youtube.com/watch?v=h5ZqKMgXciU). The scale helps parents to understand that there are multiple ways to view a child’s hearing status, that there are many communication opportunities for parents, and that they are not mutually exclusive. The scale can help parents manage their shock and possible fear that they child is disabled and will be unable to function fully in a “hearing world”. As such, the BADE scale was developed to reduce the stress and anxiety associated with having a young deaf learner. The results of the screening tool may be helpful in examining conflicting belief systems and to help frame discussion points among those involved in deaf children’s educational programs. Historically, hearing parents tend to choose a Literacy through Hearing Technologies and/or Visual Support for Speech Comprehension approach for their deaf children, and
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Figure 1. Path diagram of the four factors and their item loadings. Table 1. Means and standard deviations for bade subscales constituent caregiver groups.
Literacy through Hearing Technologies
Parents (N = 139)
Teachers (N = 45)
3.17(.83)
2.61 (.90)
Administrators (N = 41) 2.87 (.74)
Visual Language & Bilingualism
4.01 (.64)
4.12 (.61)
3.98 (.73)
Listening and Spoken Language
2.22 (.89)
1.53 (.63)
1.73 (.81)
Difficulties for Hearing Parents to Learn ASL
1.71 (.90)
1.37 (.62)
1.71 (.91)
Based on a Likert Scale, where 1 = Strongly Disagree and 5 = Strongly Agree.
Table 2. Correlation Matrix: Beliefs and Attitudes about Deaf Education Subscales.
L-H-T V-B L-S
V-B
L-S
DHPLASL
−.54**
.50**
.33**
−.50
**
−.43** .61**
(**Correlation is significant at the .01 level, 2-tailed; L-H-T = Literacy through Hearing Technologies and/or Visual Support for Speech Comprehension Subscale; V-B = Visual Language & Bilingualism Subscale; L-S = Listening and Spoken Language; DHPLASL = Difficulties for Hearing Parents to Learn ASL Subscale).
this choice has occurred despite efforts by early intervention providers to present all communication options in a neutral, non-biased way. Early intervention, however, is typically a
“medical” service provided by medical professionals; therefore, neutrality may be difficult to achieve and may be an unrealistic goal given the backgrounds of service providers. Regardless of these factors, there are most likely other underlying reasons influencing hearing parents during this decision-making process that involve their beliefs and attitudes. Hearing parents naturally want their children to be a part of their own cultural heritage and linguistic milieu; varying from this norm would be challenging as has been explained recently in the bestselling book: Far From the Tree: Parents, Children and Their Search for Identity by Solomon (2012). According to Solomon, when parents produce a child they hope that their own lives will continue in their children. Parents of children who fall Far from the Tree are unprepared when their children are born with or acquire unfamiliar needs. Further, although
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some parents take pride in how different their children are from them, most are prone to endless sadness at this difference. As a result, Solomon states that “parenthood abruptly catapults parents’ in a permanent relationship with a stranger and the more alien the stranger, the more negative the attitudes” (pg.16). Hearing parents’ response initially to the identification of their child’s hearing loss and the decisions they make regarding communication philosophies and educational placement are most likely a result of wanting to give their deaf children opportunities to be Nearer to the Tree or to be aligned with their own culture and value system. Although professionals providing information and counseling to families strive to maintain neutrality, they bring their own set of beliefs and attitudes to this process and likely influence families’ decisions. Exploring one’s own beliefs and attitudes including from where they originated (e.g., from family members or personal experiences, from university preparation programs) and how they have changed or crystallized maybe a useful exercise. Further, exploring one’s beliefs and attitudes toward children whose linguistic needs fall far from the tree may bring new insights. When service providers, teachers, and administrators beliefs and attitudes are in contrast with the family’s, the BADE tool may be useful to analyze where they diverge and may serve as a springboard for further discussion of vertical identities and horizontal identities. Vertical identities, as Solomon (2012) explains, tend to be those which could be described as falling within the family’s accepted cultural norms and expectations, many of which have been passed down from generation to generation. Language, according to Solomon, is typically a vertical identity because it is normally transmitted from parent to child, and parents tend to want their children to communicate using the shared language of the home. Vertical identities also include attributes and values that are passed down (e.g., ethnicity, hair color, DNA, cultural expectations). Horizontal identities, which tend to be foreign to parents, are typically not found in the families’ heritage or culture and therefore, fall outside the verticality of the familiar (e.g., prenatal influences, values and preferences that the child does not share with the family, recessive genes). While vertical identities emerge from families, horizontal identities are usually acquired from a peer group. In the case of deaf children who sign and have hearing parents, instead of language being vertical and transmitted from parent to child, it is most often horizontal where outsiders and peers become the language models while parents are acquiring communication skills. Using the BADE scale can open a dialogue between physicians, audiologists, early interventionists, educators, and parents. It can provide an opportunity to discuss a variety of communication options, including the pros and cons related to each choice. In this way, parents can explore multiple options at a time when many of them are grieving the loss of an “ideal” child who is like them. For most hearing parents, the first deaf person they meet is their own child (Benedict, 2013) who has just “failed” their first test—they cannot hear. This emotional situation can be framed as a dialogue about possibilities that are researched based. Clearly, early interventionists and teachers need new tools to assist parents in choosing early communication approaches that take full advantage a child's intact sensory potential. Further, early communication approaches must be carefully monitored to ensure that children are acquiring language on a normal trajectory; otherwise the result of lack of
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early access to a fully-functioning language system may lead to severe academic delays. New emerging research is revealing that ASL/English bilingualism (Mayberry & Locke, 2003; Pénicaud et al., 2013) leads to successful cognitive and linguistic development for a child who is deaf or hard of hearing. This ASL/English bilingualism maybe bimodal, where the child learns both speech and sign language (Nussbaum, Scott, & Simms, 2012) at the same time to take advantage of the epigenetic benefits of accessible early language (Pénicaud et al., 2013). Depending on family wishes and the success of hearing restoration, these children may elect to drop sign language if their spoken language development provides them academic language and effective progress in their education. If the child is not able to depend solely on spoken language for academic success, they are optimally positioned to take advantage of both sign and spoken languages given the benefits of early ASL/ English bilingualism. Limitations and future research. This longitudinal sample is predominantly from center-based programs that serve deaf and hard of hearing children. As such, many of the programs had a strong bilingual philosophy. In addition 68% of the parents reporting using ASL at home, even if they themselves were not native signers. Given these characteristics of the sample, future research could administer the BADE to parents of children who are more English-only in their educational philosophy. This data could then be used in a confirmatory factor analysis to determine whether or not the items load on the same factors when parents have selected more listening and spoken language educational programs. Conclusion. The BADE scale provides a mechanism to frame future opportunities for deaf and hard of hearing children who most often are born to hearing families. This scale can help parents, early interventionists, and teachers analyze their own attitudes and beliefs in order to better meet the needs of young deaf learners. If parents and early interventionist/teachers attitudes differ, the BADE scale can provide a point of reference for discussion and dialogue about what each expects to occur for the child. Moreover, the BADE scale can be used to connect to recent efforts, which provide more information about the benefits of early sign language (http://vl2.gallaudet.edu, http://www.youtube.com/watch?v=h5ZqKMgXciU, and http://www.jaclynvincent.com). This information can help parents navigate possibilities for language choice and educational placements that reflect the full range of possibilities. As the deaf baby is often the first deaf person most hearing parents meet, they tend to be unaware of deaf culture and the benefits of visual language. The BADE scale can provide an opening to choices that are often not reflected by those in the medical profession.
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The Beliefs and Attitudes about Deaf Education (BADE) Scale: A Tool for Assessing the Dispositions of Parents and Educators
Appendix A. Beliefs about Deaf Education Questionnaire Items (47 Original Items) 1) Children less than six years old should receive general services for developmental delays and not be labeled with a specific disability. 2) Learning in the regular classroom through an interpreter produces higher levels of learning than a deaf education classroom with a teacher of the deaf. 3) Learning two languages would be too great a challenge for young deaf or hard of hearing children. 4) Deaf or hard of hearing children should enter hearing classrooms as soon as possible in order for them to learn grade-level information along with their hearing peers. 5) Talking and signing at the same time provides children access to both a visual and an auditory language. 6) Young deaf and hard of hearing children can learn fingerspelling as infants. 7) Deaf or hard of hearing infants and toddlers should receive early intervention services primarily through training provided to their parents/guardians in natural environments. 8) Many hearing parents do not learn to sign because they have chosen another communication approach for their child. 9) It is a positive experience to have parents of deaf or hard of hearing children meet deaf adult. 10) Talking combined with Cued Speech (CS) and/or speechreading provides children visual and auditory access to language. 11) Because sign language hinders the development of listening and talking, young deaf or hard of hearing children should be allowed to develop spoken language initially without the influence of signs. 12) If children have early access to spoken language through hearing without visual supports then they will development better later language skills. 13) If children use hearing aids, they will learn language through their residual hearing regardless of the level of hearing loss. 14) Using any visual supports while talking is confusing and hinders the development of auditory access to language. 15) ASL is a visual language aids, they will learn language through their residual hearing regardless of the level of hearing loss. 16) With amplification (hearing aids or a cochlear implant) and focused early intervention, deaf children will be able to attend regular classes in elementary school without needing an interpreter or transliterator. 17) New technologies (e.g., cochlear implants) are effective in producing normal-like hearing ability in deaf children. 18) Language can be learned visually; therefore, American Sign Language (ASL) is an appropriate communication approach for young children. 19) Cued Speech is an appropriate communication approach for young children. 20) Families must focus on a child’s medical diagnosis and concentrate on therapeutic interventions during the first three years. 21) Hearing parents cannot learn ASL; therefore, it is much more effective to help them learn English-based signs or Cued Speech. 22) Hearing parents cannot learn ASL; therefore, the focus should be on the child’s oral language skills. 23) Parents must make choices about which communication
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approach to use with their young child. 24) Efforts initially should focus on medical interventions in order to try to reduce the negative effects of hearing loss. 25) If children have early access to spoken language through residual hearing and/or vision (e.g., speechreading, Cued Speech) they will development better later language skills. 26) If children have early access to sign, they will develop better later language skills. 27) Many hearing parents do not learn to sign because they are overwhelmed by other demands on their resources (e.g., other children, finances, other conditions of the child). 28) Cued Speech, because it provides an accurate visual representation of oral language, can map the brain of young deaf and hard of hearing children, thus giving them an advantage for later developing literacy. 29) All deaf or hard of hearing children should be educated in the regular classroom with hearing peers regardless of age. 30) ASL, because it is a visual language, can map the brain of young deaf and hard of hearing children thus giving them an advantage for later developing literacy. 31) Enrollment in a residential school for the deaf should occur as early as possible. 32) Academic content can be best learned through ASL. 33) Academic content can be best learned through the language in which the child will be reading so that they will have access to the same vocabulary and language skills in print and in class. 34) Parents and teachers of deaf or hard of hearing children should use a combination of all techniques in order to make sure the child is not limited by one approach. 35) Enrollment in a residential school for the deaf should only be selected when all other placements have failed (e.g., hearing preschool, regular kindergarten, public school mainstreamed classrooms). 36) Deaf and hard of hearing children can learn ASL. 37) made accessible through a combination of residual hearing, speechreading and Cued Speech as infants. 38) Being able to read and write is more important than being able to listen and speak. 39) Learning American Sign Language isolates young children from the hearing world. 40) Being a member of a Deaf community with a unique culture and language enriches one’s life. 41) A bilingual environment that includes ASL provides full access to language and communication. 42) Deaf and hard of hearing children’s behavior problems come mostly from frustration caused by lack of communication. 43) Deaf and hard of hearing children can become fluent in English (reading and writing) if given early access to language through ASL in the first year of life. 44) Special schools for the deaf provide a language-rich educational experience that cannot be replicated in a public school. 45) Deaf and hard of hearing children who do not have access to ASL when young struggle academically throughout their lives. 46) Deaf and hard of hearing children can become fluent in English (reading and writing) if given access to spoken language through hearing, speechreading, and/or Cued Speech in the first year of life. 47) Full access to language and communication is possible for deaf children without the use of ASL.
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20 How Emotional Context Influences Facial Preferences and Impressions Satomi Hara1,2, Kentaro Katahira3,4, Kazuo Okanoya2,3,4,5*
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1 College of Arts and Sciences, The University of Tokyo, Tokyo, Japan ERATO, Okanoya Emotional Information Project, Japan Science Technology Agency, Saitama, Japan 3 Center for Evolutionary Cognitive Sciences, The University of Tokyo, Tokyo, Japan 4 Emotional Information Joint Research Laboratory, RIKEN Brain Science Institute, Saitama, Japan 5 Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan
Individuals change their evaluations of human faces depending on the valence of the stimuli presented with the faces. The present study investigated whether repeatedly presenting picture stimuli in pairs would evoke various emotions that would influence the subjects’ preferences for and impressions of facial stimuli. The subjects’ preferences for the facial stimuli did not differ consistently between before and after the facial stimuli were presented in tandem with emotional pictures. The direction of the change differed depending on the sex of the participant and the sex of face stimulus, even when the face was paired with a picture of the same valence. The emotional pictures appeared to have an effect on the emotions experienced in response to the face stimuli: the male participants, who were likely to feel pleasant emotions toward the pleasant pictures, were also likely to feel positive emotions toward the face stimuli paired with those pictures. Moreover, the female participants, who were likely to feel unpleasant emotions toward the unpleasant pictures, were also likely to feel afraid of the male faces paired with those pictures. These results suggest that the ability of an emotional stimulus to affect our preferences for and impressions of a face stimulus, as well as the degree of this effect, are highly sensitive to factors such as the sex of the participant and the sex of facial stimulus. Keywords: Facial Preference; Facial Impression; Emotional Pictures; Evaluative Conditioning
Introduction Preference is a critical factor that determines human behavior in various daily situations. Preference has a great influence on many aspects of our everyday decisions, such as what to eat, with whom to spend time, and what to buy. Thus, knowing how preferences are formed and manipulated is closely related to understanding human behavior and decision-making. To address this, many researchers have been studying a phenomenon called evaluative conditioning (EC). EC is a specific form of classical conditioning that refers to a change (either positive or negative) in one’s evaluation of an initially neutral stimulus (a conditioned stimulus: CS) due to the valence of a stimulus presented in tandem with the CS (an unconditioned stimulus: US). Since EC was first observed by researchers such as Razran (1954) and Staats & Staats (1957), a wide range of areas of psychology, including social psychology (e.g., Olson & Fazio, 2001), learning psychology (e.g., Baeyens, Eelen, Crombez, & Van den Bergh, 1992), and consumer psychology (e.g., Bierley, McSweeney, & Vannieuwkerk, 1985), have been focused on this phenomenon. Researchers have used stimuli of several domains, such as visual, auditory, and gustatory, to show that diverse types of *
Corresponding author.
stimuli can function as CS or US (see De Houwer, Thomas, & Baeyens, 2001 for a review). Many of these studies have adopted pictures of human faces as CS. Baeyens et al. (1992) showed that faces initially rated as neutral became preferred after they were presented in pairs with highly preferred faces, and less preferred when presented with faces with low preference scores. Additionally, Hermans, Vansteenwegen, Crombez, Baeyens, & Eelen (2002) used electric shocks and adjectives that described either positive or negative personalities as US and found that the preference scores for the faces paired with the negative adjectives or with the electric shocks decreased, whereas the preference scores for the faces paired with positive adjectives increased. However, the emotions and impressions that people experienced in their everyday lives are much more complicated than simple terms such as “like”, “dislike”, “good” or “bad” or the disgust and avoidance produced by temporary punishments. In various situations, we become happy, angry, and sad and feel much more diverse emotions. Therefore, to profoundly understand how preferences are formed and manipulated in daily and social contexts, one must consider the influence of these types of complex and various emotions on the formation of preference. Nevertheless, no research has yet shown that such emotional stimuli can change individual preferences for CS.
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Therefore, in this study, we investigated whether US that induce complex and various types of emotions could change subjects’ preferences for paired CS. We used the International Affective Picture System (IAPS) developed by Lang, Bradley & Cuthbert (2008) as US. The IAPS is a database of pictures depicting a wide range of human experiences, which are scored using three criteria: valence, arousal, and dominance. Although this database was originally standardized using Western samples, many studies of Japanese samples (e.g., Katahira, Fujimura, Okanoya, & Okada, 2011; Fujimura, Katahira, & Okanoya, 2013) have confirmed that the images evoke similar emotions in individuals from both cultures. For the CS, we used pictures of human faces, which are socially important. We investigated whether the subjects’ preferences for these faces would change according to the valence of IAPS pictures that were repeatedly paired with the faces. Although it has been confirmed that pleasant IAPS pictures can serve as appetitive stimuli and unpleasant IAPS pictures can be aversive stimuli in an instrumental conditioning paradigm (Katahira, Fujimura, Okanoya, & Okada, 2011), it is not yet known whether these pictures can function as US in the EC paradigm. There were four between-subject conditions that involved pairing the emotional pictures and the face stimuli: three experimental conditions and one control condition. The experimental conditions involved pairing a face stimulus with either a pleasant emotional picture (pleasant condition), an unpleasant emotional picture (unpleasant condition), or with a pleasant picture in half of the repetitions and with an unpleasant picture in the other half (pleasant-unpleasant condition). The control condition involved pairing a face stimulus with a picture with no particular emotional valence (neutral condition). Thus, we investigated how the subjects’ preferences for the faces in each condition differed before and after the face stimulus and the emotional picture were presented in tandem. We hypothesized that the emotional pictures would have the same effect as the other stimuli in previous studies: the faces in the pleasant condition were expected to be preferred, those in the unpleasant condition to be less preferred, and those in the neutral condition to remain neutral. The pleasant-unpleasant condition is a novel condition created for the current study, and we expected it to affect preferences in three possible ways. First, faces in this condition might be greatly preferred due to the enhancement of the effect of the pleasant pictures by the unpleasant pictures. Second, the opposite pattern might occur: faces in this condition might be much less preferred due to the enhancement of the effect of the unpleasant pictures by the pleasant pictures. Third, the preference might not change due to a neutralizing effect between the unpleasant and pleasant pictures. We asked the subjects to what degree they felt a particular type of emotion, such as sadness or happiness, in response to the face stimuli after the conditioning. The responses to this question were used to assess the relationship among the emotions induced by the pictures, the changes in the preference rating, and the emotions evoked by the face stimuli.
Methods Participants A total of 53 Japanese university students (26 male and 27 female) participated in the study. The average age was 19.2 years (SD = .76, range = 18 - 20). All the experimental procedures were approved by the Ethics Committee of the University
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of Tokyo.
Stimuli The face stimuli (8 males and 8 females) were selected from a database that consisted of 49 male and 51 female faces, according to the data generated by a pilot study. The database was developed by the JST ERATO Okanoya Emotional Information Project (Fujimura and Okanoya, unpublished). In the pilot study, 11 participants aged 16 - 25 years (6 male and 5 female, average age 21.4 years) were shown each of the 100 face pictures in the database and rated how much they liked each face one a score of 1 to 9 (1: do not like it at all; 5: neutral; 9: like it very much). Among the pictures of comparatively young faces, we chose those that constantly received ratings close to 5. The emotional pictures (30 pleasant, 30 unpleasant, and 20 neutral) were selected from the IAPS database using the valence ratings and arousal data in Lang et al. (2008).
Procedures The experimental program was created with Inquisit ver. 3.0.6.0 by Millisecond Software and was presented on an LCD monitor. The participants were required to perform the necessary tasks by pressing a keyboard. The experiment consisted of 4 parts: a pre-conditioning preference rating phase, a conditioning phase, a post-conditioning preference rating phase, and an emotion rating phase. In the pre-conditioning preference rating phase, we measured the baseline preference of each participant for each face stimulus using a method similar to those of Field (2006) and Johnsrude, Owen, Zhao & White (1999). We presented 2 of the 8 male or female face stimuli in turn, and we asked the participants to state which stimulus was preferred. Each of the possible pairs was presented twice: one on the left and the other on the right the first time, and the former on the right and the latter on the left the second time. Thus, each participant performed 112 trials in total. The preferred stimulus in each trial received 1 point, and the other received 0; thus, each face stimulus received a total of 0 to 14 points. The order between and within the male and female stimuli was randomized for each participant. This binary rating method was considered superior because when the participants were asked to rate the same stimuli again in the post-conditioning phase, they would be less likely to be influenced by memories of the ratings they had given to the stimuli in the pre-conditioning phase. During the conditioning phase, we repeatedly presented each face stimulus paired with an emotional picture. The combinations used to create pairs of these two stimuli consisted of 3 experimental conditions and 1 control condition. The experimental conditions involved pairing a face stimulus with either a pleasant emotional picture (pleasant condition), an unpleasant emotional picture (unpleasant condition), or a pleasant picture in half of the repetitions and an unpleasant picture in the other half (pleasant-unpleasant condition). The control involved pairing a face stimulus with a picture with no particular emotional valence (neutral condition). Eight male and female face stimuli were divided into the 4 conditions so that each condition contains one male face and one female face. The assignment of face stimuli was counterbalanced between the participants. The flow of one trial is shown in Figure 1. First, a face stimulus appeared on either the right or left side of the screen.
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1s
2.5 s
3s
Figure 1. The flow of the screen in the conditioning phase. The sample face stimulus and emotional picture were taken from other source materials to avoid showing materials of the databases used in the present study.
One second later, an emotional picture appeared on the opposite side of the screen. After another 2.5 seconds, these two stimuli disappeared simultaneously, and the screen remained empty for 3 seconds. During this interval, the participant rated the subjective level of pleasantness or unpleasantness of the emotional picture that had been presented on a scale of 1 to 9 (1: very unpleasant; 5: neutral; 9: very pleasant). After the interval, the next trial began. Each face stimulus was presented in tandem with an emotional picture 10 times, the number that was expected to produce the most effective conditioning according to Baeyens et al. (1992). The face stimuli in the pleasant, unpleasant, and neutral conditions were paired with 10 different pleasant, unpleasant, and neutral pictures, respectively. The face stimuli in the pleasant-unpleasant condition were paired with 5 pleasant pictures and 5 unpleasant pictures. Each of the 30 pleasant, 30 unpleasant, and 20 neutral pictures was presented twice, once with a male stimulus and once with a female stimulus. Thus, each participant performed 160 trials in total. All the trials were divided into 5 sessions, for a total of 32 trials, and between the sessions, the participants could take a break of the desired length. Because the order in which the stimuli were presented and the timing of the rating were somewhat complicated, there was a practice session of 13 trials before the 5 experimental sessions. The practice session employed different face stimuli and emotional pictures from those used in the 5 experimental sessions. In the post-conditioning preference rating phase, we measured the preference (after conditioning) for each face stimulus following the same method as in the pre-conditioning phase. In the emotion rating phase, we investigated whether and to what degree the participants felt emotions while observing the face stimuli. The face stimuli were presented singly beneath one of 4 words: “sad”, “scared”, “happy”, or “delighted”, and the participants were asked to what degree they experienced the feeling of the depicted word while observing the face (1: not at all; 5: very much). Each of the 16 stimuli (8 male and 8 female) was presented with each of the 4 emotional words, for a total of 64 trials. The order in which the face stimuli and the words within each face were presented was randomized for each participant.
Statistical Analyses R and anovakun ver. 4.3.1, an ANOVA function that runs on R software, was used for the statistical analyses. The significance level was set at α = .05 for the ANOVA, and post-hoc comparisons were conducted using a modified Bonferroni method.
Results Ratings for the Emotional Pictures A 2 (sex of participant: male vs. female) × 3 (type of emotional picture: pleasant, unpleasant, or neutral) ANOVA was used to analyze the ratings for the emotional pictures in the conditioning phase. The results revealed a significant main effect of the type of emotional picture (F(2,102) = 733.59, p < .001) and a significant sex × type interaction (F(2,102) = 15.49, p < .001). The post-hoc comparison of the sex × type interaction (Figure 2) revealed that both the male and female participants gave significantly higher ratings (more pleasant) to the neutral pictures than to the unpleasant ones (male: F(1,51 = 16.55, p < .001; female: F(1,51) = 18.29, p < .001). Similarly, both sexes gave significantly higher ratings to the pleasant pictures than to the neutral ones (male: F(1,51) = 14.09, p < .001, female: F(1,51) = 21.82, p < .001) or to the unpleasant ones (male: F(1,51) = 17.43, p < .001, female: F(1,51) = 22.93, p < .001). The female participants gave significantly higher ratings to the pleasant pictures and significantly lower ratings to the unpleasant ones compared with the male participants (pleasant: F(1,51) = 17.77, p < .001; unpleasant: F(1,51) = 10.11, p < .01). In addition, a one-sample t-test performed to compare the ratings given to the neutral pictures by the male and female participants revealed no significant difference from the most neutral rating, 5 (male: t(25) = −.87, p = .39; female: t(26) = 1.55, p = .13). These results suggest that all of the pleasant, unpleasant and neutral pictures had the expected valence for both the male and female participants. A comparison of the male and female participants, however, revealed that the females rated the pleasant pictures more positively and the unpleasant pictures more negatively than the males, suggesting that the emotional pictures may have produced a somewhat greater effect on the females than on the males.
Preference Ratings for the Face Stimuli A 2 (sex of participant: male vs. female) × 2 (sex of stimulus: male vs. female) × 4 (condition: pleasant, unpleasant, pleasantunpleasant, or neutral) × 2 (time: pre-conditioning vs. postconditioning) ANOVA was performed to analyze the preference ratings for the face stimuli. The results showed a significant sex of stimulus × condition × time interaction (F(3, 312) = 12.77, p < .05), although none of the 8 conditions (sex of stimulus [2] × condition [4]) differed significantly between the pre-conditioning and the post-conditioning ratings, according to the post-hoc comparison. Figure 3 shows the average preference scores calculated for the male and female participants,
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Figure 2. The average valence rating of the emotional pictures. The error bars represent the s.e.m. **p < .01, ***p < .001.
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tional ratings for the face stimuli. The results showed a significant main effect of the rated emotion (F(3,312) = 4.14, p < .01) and significant interactions between the sex of the participant × emotion (F(3,312) = 2.65, p < .05), the sex of the stimulus × emotion (F(3,312) = 5.08, p < .01) and the sex of the participant × the sex of the stimulus × emotion (F(3,312) = 7.47, p < .001). The post-hoc comparisons of the cubic interaction revealed different patterns between the male and female participants (Figure 5). The female participants evaluated the male and female stimuli differently (Figure 5(a)): for “sad” (F(1,53) = 6.44, p < .05) and “scared” (F(1,53) = 11.76, p < .01), they gave higher ratings to the male stimuli than to the female stimuli; oppositely, for “happy” (F(1,53) = 15.02, p < .001) and “delighted” (F(1,53) = 10.21, p < .01), the female participants gave higher ratings to the females than to the males. The ratings of the male participants, in contrast, did not differ between the male and female stimuli (Figure 5(b)). This finding indicates that the female participants were more likely to experience positive emotions toward the female stimuli and negative emotions toward the male stimuli, whereas the male participants felt the same way toward both the male and female stimuli. The lack of any significant effects of the paired picture condition (pleasant, unpleasant, pleasant-unpleasant, or neutral) indicates that there was no significant difference in the emotional ratings among the conditions, although the emotional rating was conducted after the conditioning process. However,
Figure 3. The difference between the pre- and post-conditioning preference scores for the face stimuli. The error bars represent the s.e.m.
the male and female face stimuli, the conditions of pairing, and the pre-conditioning and post-conditioning ratings. These results indicate that the preference scores did not change in the same direction within each condition. Especially in the pleasant-unpleasant condition, the female faces received higher scores and the male face received lower scores in the postconditioning rating compared with the pre-conditioning rating (although these differences did not reach statistical significance). In addition, to examine the possibility that the pre-conditioning score (minimum: 0, maximum: 14) affected the change in the preference score (post-conditioning score minus preconditioning score), we calculated the Pearson product-moment correlation coefficient between the pre-conditioning scores and the averages of the change in the preference scores; the result showed a strongly negative correlation (n = 15, r = −.92, p < .001; Figure 4). This result indicates that the face stimuli that received lower scores in the pre-conditioning rating tended to be rated more highly in the post-conditioning phase. The opposite was also true: the face stimuli that received higher scores in the pre-conditioning rating tended to receive lower scores in the post-conditioning rating.
Emotional Ratings of the Face Stimuli A 2 (sex of participant: male vs. female) × 2 (sex of stimulus: male vs. female) × 4 (condition: pleasant, unpleasant, pleasant-unpleasant, or neutral) × 4 (rated emotion: sad, scared, happy, or delighted) ANOVA was used to analyze the emo-
Figure 4. The correlation between the pre-conditioning scores and the average change in the preference scores (from post-conditioning score to pre-conditioning score).
Figure 5. The difference between males and females in the emotions experienced toward the face stimuli. The female participants felt strongly positive emotions in response to female stimuli and negative emotions in response to male stimuli. In contrast, the male participants felt the same way toward both the male and female stimuli. The error bars represent the s.e.m. *p < .05, **p < .01, ***p < .001.
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the degree to which a participant experiences an emotional picture as pleasant or unpleasant varies between individuals. There was a noteworthy correlation between the pleasant-unpleasant ratings for the emotional pictures and the emotional ratings for the face stimuli. The correlation was calculated separately for the sex of the participant and the stimulus and between the personal averages of the emotional ratings for the 4 kinds of emotion and those of the ratings for the emotional pictures that were paired with each face stimulus in the conditioning phase. As a result, the male participants produced partially consistent correlations irrespective of the sex of the face stimulus (Figures 6(a) and (b)): with regard to the pleasant condition face stimuli, the emotional ratings for “happy” and “delighted” showed positive correlations with the ratings for the pleasant pictures paired with those face stimuli (male stimulus, “happy”; n = 26, r = .40, p < .05: male stimulus, “delighted”; n = 26, r = .26, p = .20: female stimulus, “happy”; n = 26, r = .42, p < .05: female stimulus, “delighted”; n = 26, r = .43, p < .05: Figure 6(a)). With regard to the pleasant-unpleasant condition face stimuli, the emotional ratings for “happy” and “delighted” were also positively correlated with the ratings for the pleasant pictures paired with those face stimuli (male stimulus, “happy”; n = 26, r = .31, p = .13: male stimulus, “delighted”; n = 26, r = .52, p < .01: female stimulus, “happy”; n = 26, r = .52, p < .01: female stimulus, “delighted”; n = 26, r = .48, p < .05: Figure 6(b)). That is, in both conditions in which the face stimuli were paired with pleasant pictures at least 5 times, the more that participants experienced pleasant emotions in response to the pleasant pictures, the more they experienced positive emotions in response to the face stimuli paired with those
pictures. In contrast, the female participants’ responses to the male stimuli of the unpleasant and pleasant-unpleasant conditions exhibited negative correlations between the emotional ratings for “scared” and the ratings for the unpleasant pictures (a smaller value indicates a more unpleasant response) that were paired with them (unpleasant condition; n = 27, r = −.38, p < .05: pleasant-unpleasant condition; n = 27, r = −.38, p < .05: Figure 6(c)). In both conditions in which the male stimuli were paired with unpleasant pictures at least 5 times, the more that the female participants experienced unpleasant emotions in response to the unpleasant pictures, the more they felt “scared” of the male stimuli that were paired with those pictures.
Discussion The purpose of the current study was to consider the influence of emotional pictures on the preference for face stimuli presented in tandem with the emotional pictures and the emotions experienced toward such stimuli. Based on the hypothesis that the emotional pictures would produce the same effects as those of stimuli used in previous studies, the face stimuli that were paired with pleasant pictures (pleasant condition) were predicted to be preferred, and those paired with unpleasant pictures (unpleasant condition) were predicted to be less preferred. One of the purposes of this study was to investigate the effects of face stimuli paired with both pleasant and unpleasant pictures. However, the preference scores for the face stimuli in each condition did not differ significantly before and after the conditioning process. Therefore, we would primarily like to discuss
Figure 6. The correlation between subjective emotional reactions to emotional pictures and to face stimuli after the conditioning process. Panels a and b show the responses of the male participants to both the male and female face stimuli; panel c shows the response of the female participants to the male stimuli alone. This figure indicates that the more that the male participants experienced pleasant emotions in response to the pleasant pictures, the more they experienced positive emotions in response to the face stimuli paired with those pictures. The more that the female participants experienced unpleasant emotions in response to the unpleasant pictures, the more they felt “scared” of the male stimuli paired with those pictures.
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the reasons for the results differing from our expectations. One possible reason is the considerable variance in the pre-conditioning scores. In previous studies that adopted human face stimuli as CS (Baeyens et al., 1992; Hermans et al., 2002), the participants were asked to evaluate many more face stimuli before the conditioning process than in this study; the purpose was to enable the researchers to choose as the CS the face with the most neutral score for each participant. This method was likely chosen because preferences for human faces are more susceptible to individual differences than are other stimuli. Previous studies thus employed a truly neutral face stimulus for each participant; therefore, there was little difference between the preference scores before conditioning. In contrast, we selected in advance face stimuli with stably neutral ratings by performing a pilot study and used them for all of the participants in the main experiment. Therefore, the preference scores for the face stimuli prior to conditioning varied considerably, depending on the participant and the stimulus. In addition, even the average scores within each of the 4 conditions were not equal: the average score in the pleasant condition was slightly higher than 7 (the middle score), and the average score in the unpleasant condition was slightly lower than 7. The strongly negative correlation between the pre-conditioning scores and the variation in the preference scores provide evidence that the above factor contributed to the difference between the results and the expected patterns. There are several possible causes of the correlation. A bias may have been introduced by the phenomenon that when the minimum score is limited, those who receive a low score in the first measurement will be more likely to receive a higher score in the second measurement, and vice versa. It is also possible that initially high or low evaluations of faces are difficult to manipulate or are likely to change in a definite direction (first high, then negative and first low, then positive), irrespective of the valence of the paired US (pleasant or unpleasant). Regardless of the cause, it is likely that the variance in the pre-conditioning ratings and the differences among the averages in each condition influenced the variations, as this correlation indicates, and thus made the direction of the preference change in each condition unclear. Nonetheless, it is quite suspicious that we observed such a simple effect as expected although the influence stated above was excluded, considering that there were no constant tendencies at all within the conditions such that the preference scores of the pleasant condition face stimuli increased as those of the unpleasant condition face stimuli decreased. This finding suggests that the influence of emotional stimuli on preferences for faces is not necessarily identical to the influence of simple positive or negative stimuli, which were used in the previous studies. Emotional pictures may produce different effects, depending on the sex of the participant and the stimulus. The results of the emotional ratings, on the other hand, suggest that the emotional pictures influenced the emotions experienced in response to the face stimuli. The male participants who were likely to feel pleasant emotions toward the pleasant pictures were also likely to feel positive emotions, such as “happy” and “delighted”, toward the face stimuli in the pleasant and pleasant-unpleasant conditions, in which the face stimuli were paired with pleasant pictures at least 5 times. The female participants who were likely to experience unpleasant emotions toward the unpleasant pictures were also likely to feel “scared” of the male face stimuli in the unpleasant and pleasant-un-
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pleasant conditions, in which the face stimuli were paired with unpleasant pictures at least 5 times. This difference between the sexes suggests that the emotions that are readily attached to faces by conditioning may vary between males and females: males may be susceptible to conditioning between pleasant emotions and face stimuli, whereas females may be susceptible to conditioning between unpleasant emotions and male faces in particular, which must be avoided for safety under certain circumstances. Moreover, the female participants experienced positive emotions, such as “happy” and “delighted”, more strongly in response to the female face stimuli than to the male face stimuli. The females also experienced negative emotions, such as “sad” and “scared”, more strongly in response to the male stimuli than to the female stimuli. The male participants, however, exhibited almost identical responses to the male and female stimuli. This result can be interpreted in several possible ways: it may reflect how males and females initially feel in response to unknown face stimuli or how they feel after unknown face stimuli are presented in tandem with emotional pictures, regardless of their valence. However, both interpretations indicate that this difference between the sexes reflects differences between males and females in the conditioning effect of emotional pictures on faces. In this study, the emotional pictures produced no significant changes in the preference for the face stimuli presented in pairs with themselves. The influence of the emotional pictures on this preference may not have been as powerful and simple as the effects of the stimuli used in the previous studies, such as the liked and the disliked stimuli and the electric shocks, which changed the preference for CS in a constant direction irrespective of the sex of the participant or the stimulus. Concerning the emotions felt in response to the face stimuli, the emotional pictures did have an effect, the strength of which may have depended on the sex of the participant and the stimulus. Therefore, to investigate how emotion-evoking stimuli affect our preferences and impressions of other stimuli, we must perform detailed analyses that consider such conditions. Additionally, larger samples than that of the present study are necessary to examine the difference between the sexes. In future research, more sophisticated experimental procedures and detailed analyses will be needed to clarify the relationship between stimuli that evoke complicated emotions and our preferences and emotions in response to other people and things.
Acknowledgements We thank Maiko Fujimori for providing us with the database of facial stimuli. This work was supported in part by funding from the Japan Science and Technology Agency, Exploratory Research for Advanced Technology, Okanoya Emotional Information Project, and Grants-in-Aid for Scientific Research, no. 24700238.
REFERENCES Baeyens, F., Eelen, P., Crombez, G., & Van den Bergh, O. (1992). Human evaluative conditioning: Acquisition trials, presentation schedule, evaluative style and contingency awareness. Behaviour Research and Therapy, 30, 133-142. Bierley, C., McSweeney, F. K., & Vannieuwkerk, R. (1985). Classical conditioning of preferences for stimuli. Journal of Consumer Re-
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search, 12, 316-323. De Houwer, J., Thomas, S., & Baeyens, F. (2001). Associative learning of likes and dislikes: A review of 25 years of research on human evaluative conditioning. Psychological Bulletin, 127, 853-869. Field, A. P., (2006). I don’t like it because it eats sprouts: Conditioning preferences in children. Behaviour Research and Therapy, 44, 439455. Fujimura, T., Katahira, K., & Okanoya, K. (2013). Contextual modulation of physiological and psychological responses triggered by emotional stimuli. Frontiers in Psychology, 4, 212. Hermans, D., Vansteenwegen, D., Crombez, G., Baeyens, F., & Eelen, P. (2002). Expectancy-learning and evaluative learning in human classical conditioning: Affective priming as an indirect and unobtrusive measure of conditioned stimulus valence. Behaviour Research and Therapy, 40, 217-234.
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Conditioned preference in humans: A novel experimental approach. Learning and Motivation, 30, 250-264. Katahira, K., Fujimura, T., Okanoya, K., & Okada, M. (2011). Decision-making based on emotional images. Frontiers in Psychology, 2, 311. Lang, P. J., Bradley, M. M., & Cuthbert, B. N. (2008). International affective picture system (IAPS): Affective ratings of pictures and instruction manual. Technical Report A-8, Gainesville, FL: University of Florida. Olson, M. A., & Fazio, R. H. (2001). Implicit attitude formation through classical conditioning. Psychological Science, 12, 413-417. Razran, G. (1954). The conditioned evocation of attitudes (cognitive conditioning?). Journal of Experimental Psychology, 48, 278-282. Staats, A. W., & Staats, C. K. (1957). Meaning established by classical conditioning. Journal of Experimental Psychology, 54, 74-80.
Johnsrude, I. S., Owen, A. M., Zhao W. V., & White, N. M. (1999).
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21 Profile Performance of Working Memory in Children of Elementary Schools Rita de Cássia Coutinho Vieira Fornasari, Tais Ferreira De Lima, Sylvia Maria Ciasca Department of Neurology, Research Laboratory of Learning and Attention Disorders (DISAPRE), School of Medical Sciences, State University of Campinas (UNICAMP) Campinas, São Paulo, Brazil
Objective: To compare the performance of working memory in children of 5 years and 1 month to 6 years and 11 months of public and private Elementary Schools. Methods: 34 subjects were evaluated for both genders composing the GI and GIII public education aged 5 - 6 years; GII and GIV private education aged 5 - 6 years, with an average age of 6 years and 11 months. All subjects were submitted to the Working Memory Assessment Protocol. Results: There were statistically significant differences between the public school and private school in tests of verbal span of serial repetition in direct order with words like phonology and semantics and different words with different semantics and phonology. Between groups, a statistically significant difference occurred between GIII and GIV in verbal span, free recall for polysyllabic words with different semantics and complex phonology; between GI and GII, GIII and GII, GIII and GIV, the verbal span of words with phonology and different semantics, and between GIII and GIV in verbal span of words with the same phonology and semantics. The variables in these groups are age and type of school. Conclusion: With advancing age and grades, the developments of working memory and best performance of working memory were for public school children aged 6 years. Keywords: Working Memory; Language; Children; Elementary School
Introduction The literacy process involves the phonological structure of oral language, the conceptual organization, lexical representation and working memory, which accesses and retrieves the graphical representations related to speech sounds (Mezzomo & Mota Dias, 2010). Working memory whose function is to maintain, for a short period of time, the information that is being processed, and it leaves no traces and does not produce files (Baddeley, Andersen, & Eysenck, 2011) consisting of the conscious representation and temporal manipulation of the information necessary to perform complex cognitive operations such as learning, language comprehension and reasoning (Morgado, 2005). The model of Baddeley (2000) suggests that working memory is a system composed of four components. The central executive handles tasks of higher cognitive demand and has four functions: to coordinate performance on two tasks (e.g., simultaneously store and process information), choose a task, strategy or operation; attend to relevant information and inhibit irrelevant information, and enable and retrieve long-term memory (Anderson & Lyxell, 2007). The phonological component (phonological loop) keeps the information verbally coded for a short period of time and refeeding it through a subcomponent, the Articulatory loop (Baddeley & Hitch, 1974; Bueno & Oliveira, 2004). The visual-spatial sketchpad performs the processing and maintenance of visual and spatial information related to the
objects and spatial relationships between them. At the same time, it plays an important role in the formation and manipulation of mental images (Baddeley, 2006). A fourth component recently included the model and the Episodic Buffer acted as a retainer responsible for the integration of information from the phonological loop and the visuo-spatial layout information from long-term memory (Baddeley, 2000). During childhood, the phonological component of working memory develops and is linked to the development of language, being observed in everyday speech and the child’s vocabulary that increase in size and complexity, thus underlining the role that memory on language in their semantic and pragmatic aspects (Scheuer, 2009). For acquisition and phonological development, the child makes use of perception, production and organization of the rules, i.e. the child to acquire the phoneme, also learns its distribution in syllables and words (Lamprecht, 2004). Up to 6 years, it is expected that the child has established a complete inventory phonological (Wertzner, Amaro, & Galea, 2007). Mota-SoaresKeske and Linassi (2004) argue that changes in phonological working memory can have flaws in the organization and production of speech sounds and it has been associated with phonological disorders and speech and language. Rodrigues and Befi-Lopes (2009) described and analyzed the relationship between phonological working memory and language development in children with normal language development. The resulting figure shows the relationship between lexi-
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cal and phonological structure and phonological working memory in children with normal development. Lobo, Acrani and Avila (2008) state that the evaluation of the performance of phonological working memory may provide us relevant data on language ability and language development of children with and without communication disorders. This study aimed to compare the performance of working memory among children 5 years and 6 years of public and private elementary school.
Method Context The research was conducted inpreschool and elementary schools (1st year) from the city of Capivari, state of São Paulo, Brazil namely: Colegio EAC—Kindergarten and Elementary Education—private, EMEI Professor Lenita Camargo Figueiredo and EEF José Benedito P. Antunes, both public schools.
Participants With the approval of the Research Ethics Committee (REC) of the School of Medical Sciences, No. 08088112.4.0000.5404, participated in this study 34 subjects aged 5 - 6 years, of both genders, students from preschool and 1st grade of public and private education in the city of Capivari, state of São Paulo, Brazil, divided into 4 groups: GI (5 yrs 1 mth to 5 yrs 11 mths) and GIII (6 yrs 1 mth to 6 yrs 11 mths) from the public, GII (5 yrs 1 mth to 5 yrs 11 mths) and GIV (6 yrs 1 mth to 6 yrs 11 mths) in private. For the formation of groups was performed speech screening with parents and/or guardians to clarify questions about the development and overall health of the child and the designation, made by teachers, good students without learning disabilities and attention. Inclusion criteria for the choice of research subjects were signatures of the term of free and informed consent (IC); subjects aged five to six years; provide speech and language development within the normal range, and subjects who did not complaints of visual and auditory acuity. Were excluded from the study subjects presented: speech complaints, such as language delay, articulation disorders and phonological and/or phonetic; complaints of inattention; attend or have attended speech therapy, and parents or guardians did not authorize participation in research.
Materials For the evaluation of the subjects using the Working Memory Protocol Assessment (WMPA) (Ferreira, 2011). This protocol evaluates auditory skills performance tests in serial repetition in direct order, evidence of free recall and verbal span tests. Proofs of serial repetition have alternation between the number of syllables of words and how to semantics and phonology of the same, being linguistically balanced according to the complexity of speech articulation, word length and degree of familiarity of the words in the English language. The visual ability is assessed with tests of visual span in the forward and reverse order. This protocol has a total of 6 trials, 5 trials subdivided into up to 5 items. The time of application of the Protocol was around 20 minutes.
Procedures In the performance of the Working Memory Protocol Assessment (Ferreira, 2011) the evidence of auditory memory were applied orally, in which the researcher guided the subject to hear the order given and repeat according to the variations of each test and subtest. In the visual memory tests, the subjects were given colored cards, in which the researcher asked the subjects to visualize the order presented, and they should play in the forward and in reverse order. The maximum score of this test is 144 points to be obtained in the correct performance of 100% of the words.
Data Analysis For this study was performed by descriptive and inferential statistics using SPSS for Windows (version 20.0). Descriptive analyzes were performed to characterize the groups and inferential analyzes to compare the performance between the groups (Fisher’s Exact Test, Kruskal-Wallis and Mann Whitney), considered the significance level of 5%, i.e., p < 0.05. The Mann-Whitney aims to investigate possible differences in working memory performance between groups. The Kruskal-Wallis nonparametric test is used to compare three or more independent samples, indicating whether there is a difference between at least two of them. Fischer’s Exact Test comparing small samples in two independent groups and determines the exact probability of occurrence of an observed frequency. The results indicate that statistically significant differences are marked in bold and asterisk (*). In this study, we used a significance level of 5% (0.05), i.e., when the calculated significance value (p) is less than 5%, meaning that the difference or relationship is statistically significant, and when the value calculated significance (p) is equal to or greater than 5%, meaning that the ratio or difference is not statistically significant.
Applied Tests To better understand the following tables the names of each test and subtest were transformed into acronyms applied as shown in the table below (Figure 1).
Results Characterization of Groups This study was conducted with the participation of 34 subjects divided into four groups, with group GI consists of 8 subjects of both sexes with ages ranging from 5 years and 1 month to 5 years and 11 months from the public school the GII consists of 8 subjects of both sexes with ages ranging from 5 years and 1 month to 5 years and 11 months from the private schools, the GIII group consisting of 9 subjects of both sexes with age ranging from 6 years and 1 month to 6 years and 11 months from the public school system and GIV group consisting of 9 subjects of both sexes with ages ranging from 6 years and 1 month to 6 years and 11 months from private schools. Table 1 presents the frequency of the number of subjects in each group per grade, and GIII and GIV a higher number of subjects. The average age among the subjects in grades is shown in
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Serial repetition in direct order - 3 syllable words with different semantics and equal phonology. Serial repetition in direct order - 5 syllable words with different semantics and equal phonology. Serial repetition in direct order - 3 three syllable words with different semantics and equal phonology. Serial repetition in direct order - 3 syllable words with different phonology and equal semantics. Serial repetition in direct order - 5 syllable words with different phonology and equal semantics. Serial repetition in direct order - 3 syllable words with different semantics and phonology. Serial repetition in direct order - 5 syllable words with different semantics and phonology. Serial repetition in direct order - 7 syllable words with different semantics and phonology. Free recall - polysyllabic words with different semantics and complex phonology. Free recall - words with different phonological and equal semantics (color). Free recall - two-syllable words with different semantics and equal phonology.
A1 A2 A3 B1 B2 C1 C2 C3 2A 2B 2C 2D
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Table 2, which is 6.11 years in pre-school and first year (p = 0.00), analysis of the Mann-Whitney test. Table 3 shows the performance of working memory among groups. Note statistically significant difference in the subtest (A2) of serial repetition in direct order for five syllable words with equal phonology and semantics different (p < 0.02*), in the verbal span test (3A) of two-syllable words with phonology and different Semantics (p < 0.00*) and the verbal span (3B) for two-syllable words with the same phonology and different semantics (p < 0.02*). In the other tests and subtests, there were no statistically significant differences between schools. Table 2. Comparison between the age and grade. Grade
Average
N
SD
Pre-School
5.64
16
0.26
First Year
6.53
18
0.31
Total
6.11
34
0.53
Free recall - words with different semantics and phonology. Free recall - polysyllabic words with different semantics and phonology. Verbal span - syllable words with different semantics and phonology. Verbal span - syllable words with different semantics and equal phonology.
2E 3A 3B 4A
Visual span - direct order.
4B
Visual span - reverse order.
5A
Repeat no words - two syllables.
5B
Repeat no words - three syllables
6
Recall in reverse order.
Notes: (N) no. of subjects; (SD) Standard Deviation, p = 0.00, Mann-Whitney test.
Table 3. Comparison of working memory among schools. Schools Public
Figure 1. Abbreviation of the subtests of the evaluation protocol of working memory. Table 1. Frequency of subjects per group and grade. Grade
f
Total
Pre-School
First Year
8
0
8
GI
Private
Test
A
SD
A
SD
p-value
A1
2.68
0.50
2.32
0.81
0.13
A2
1.56
0.30
1.26
0.36
0.02*
A3
1.91
0.57
1.53
0.84
0.22
B1
3.00
0.00
2.94
0.24
0.32
B2
1.74
0.75
1.76
0.59
0.96
C1
2.53
0.74
2.06
0.91
0.12
C2
1.32
0.77
0.79
0.64
0.05
C3
0.03
0.12
0.06
0.17
0.55
2A
2.35
0.86
1.76
0.97
0.06
2B
4.06
1.52
3.12
1.50
0.09
2C
2.65
1.06
2.29
0.92
0.30
2D
2.59
1.12
2.06
1.14
0.14
2E
2.29
0.92
2.35
1.46
0.99
%
50
0
24
f
8
0
8
%
50
0
24
3A
3.65
0.61
2.71
0.85
0.00*
f
0
9
9
3B
3.18
0.64
2.53
0.80
0.02*
%
0
50
26
4A
3.65
1.00
3.59
1.12
0.84
f
0
9
9
4B
2.76
1.09
2.82
1.07
0.79
%
0
50
26
5A
1.47
1.07
1.65
0.93
0.55
f
16
18
34
5B
1.76
0.75
1.29
0.92
0.09
%
100
100
100
6
1.82
0.88
2.18
1.24
0.53
Total
47.00
7.56
41.12
8.38
0.05
G II
G III
G IV
Total Notes: (f) frequency, (%) percentage; (GI) Public School: 5.1 - 5.11 years; (GII) Private School: 5.1 - 5.11 years; (GIII) Public School: 6.1 - 6.11 years; (GIV) Private School : 6.1 - 6.11 years.
Notes: (A) Average, (SD) Standard Deviation; (*) Statistically significant difference (p < .05).
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Table 4 shows the comparison of the performance of working memory among groups. Table 5, p < 0.05, shows statistically significant results for the test of free recall of two-syllable words with different semantics and complex phonology (2A), resulting in a statistically significant difference in GIII and GIV (p = 0.01*), the subtest (3A) of the verbal span for two-syllable words with different semantics and phonology resulting statistically significant difference in GI and GII (p = 0.03*), GIII and GIV groups (p = 0.04*) and in GII and GIII (p = 0.04*), this group is no different between the ages, in the subtest (3B) of the verbal span for two-syllable words with different semantics and phonology equal no statistically significant difference in GIII and GIV (p = 0.02*). In the other tests and subtests is no significant difference between groups.
The development of children’s oral language and communication are related to the development of working memory, as Table 4. Comparison of working memory among groups. Groups GII
GIII
GIV
Test
A
SD
A
SD
A
SD
A
SD
A1
2.62
0.44
2.31
1.00
2.72
0.57
2.33
0.66
A2
1.50
0.27
1.38
0.35
1.61
0.33
1.17
0.35
A3
2.06
0.68
1.25
1.04
1.78
0.44
1.78
0.57
B1
3.00
0.00
2.87
0.35
3.00
0.00
3.00
0.00
B2
1.31
0.70
1.69
0.70
2.11
0.60
1.83
0.50
C1
2.25
0.96
1.88
1.09
2.78
0.36
2.28
0.71
C2
1.25
0.65
0.75
0.65
1.39
0.89
0.83
0.66
C3
0.06
0.18
0.06
0.18
0.00
0.00
0.06
0.17
2A
2.25
1.04
2.25
1.04
2.44
0.73
1.33
0.71
2B
4.00
1.69
3.38
1.30
4.11
1.45
2.89
1.69
2C
2.50
0.93
2.38
0.74
2.78
1.20
2.22
1.09
2D
2.50
1.20
2.00
1.41
2.67
1.12
2.11
0.93
2E
2.13
0.99
2.38
1.77
2.44
0.88
2.33
1.22
3A
3.63
0.52
2.63
0.92
3.67
0.71
2.78
0.83
3B
2.88
0.35
2.50
0.93
3.44
0.73
2.56
0.73
4A
3.38
0.92
3.87
0.99
3.89
1.05
3.33
1.22
4B
2.50
0.93
2.63
1.19
3.00
1.22
3.00
1.00
5A
1.50
1.20
1.88
0.99
1.44
1.01
1.44
0.88
5B
1.88
0.83
1.25
0.89
1.67
0.71
1.33
1.00
6
1.88
0.64
1.87
1.46
1.78
1.09
2.44
1.01
Total
45.06
7.35
41.19
10.50
48.72
7.75
41.06
6.62
Notes: (A) Average, (SD) Standard Deviation.
Groups GI Test
A
GII SD
A
GIII SD
2A 3A
3.63
0.52
2.63
3A
2.63
GIV
A
SD
A
SD
p-value
2.44
0.73
1.33
0.71
0.01*
0.92
3A
3B
Discussion
GI
Table 5. Comparison of the performance of working memory among groups with p < 0.05.
0.92
0.03* 3.67
0.71
3.67
0.71
3.44
0.73
2.78
0.83
0.04* 0.04*
2.56
0.73
0.02*
Notes: (A) Average, (SD) Standard Deviation; (*) Statistically significant difference (p < 0.05).
this allows the formal and informal learning, acquire new knowledge and integration of information. Thus the language and working memory develop with age (Befi Rodrigues-Lopes, 2009). The overall results of this study demonstrated better performance of the subjects of public schools for all tests of WMPA (Ferreira, 2011) with data with significant differences between groups GIII and GIV, which are formed by subjects aged 6 years in first grade, with the variable type of school. The hypothesis raised by the authors, which further supports these results is that the subjects of public schools showed more interest and attention during the implementation of the protocol and the environment of this school was more favorable, with respect to the noise level, compared to private school. This is corroborated by studies Gindri et al. (2005) stating that the educational process is important for the development of the child, taking into consideration the importance of learning processes in the development of higher mental functions, which explains the better performance in this range age. In relation to GI and GII, the result was significant for verbal span test, being the age of 5 years subject to the variable type of school, and GI and GII public school private school. In a study of Brazilian children aged 4 - 10 years the authors observed the effects of age, extension, education and lexically, and the length effect was observed with the decrease in the repetition of words with 2 - 5 syllables, all ages. The effect of education was only observed in children from 5 years. This is due to the influence of reading and writing that can make phonological processing and phonological awareness child. (Santos & Bueno, 2003). Regarding the type of school a study in Bahia does not corroborate with the finding of this research, it shows that children 3 - 12 years attending public and private schools when they were evaluated in sequential memory of syllables, the results indicated that the Children are capable of repeating 2 of 3 sequences of 3 syllables, children aged 6 years repeated 2 of the sequences of 4 syllables and 9 years old were able to repeat the 3 sequences, concluding that there is progress in the performance of working memory (the respect to phonological loop) according to increasing age (Corona, Pereira, Ferrite, & Rossi, 2005). In the study by Ferreira (2011) compared the performance of working memory in children with Attention Deficit Disorder and Hyperactivity Disorder (ADHD) and children without
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Profile Performance of Working Memory in Children of Elementary Schools
complaints learning and attention, 7 - 11 years enrolled in public education, the results concluded that children with ADHD had worse performance on all memory tests compared to children without learning complaints and attention, which may be related to the performance of attention and executive functions, leading to a loss of all cognitive abilities. Analyzing the data in Table 3, the results show a statistically significant difference in retesting serial two-syllable words with different semantics and phonology equal to public school with an average of 1.56, and in contrast to private school had an average of 1.26. According to a study of Rodrigues and Befi-Lopes (2009) changes the phonological working memory in relation to phonological storage are related to the similarity of the effect of phonological word length, since word sequence are less similar reminded of the word sequences are not similar showing that it is verbal information represented by a specific phonological system rather than another system such as visual or semantics. Andrade (2002) shows that the effect of phonological similarity with words with similar sounds final hinder access to meaning, thus impairing their memory. This research corroborates the result of the study Mousinho, Correa (2009) showed that the school can contribute to the skills of phonological processing, since the children have good oral and assessed a storage system adequate information because they have no changes. In tests of verbal span for words phonology and equal semantics the results were statistically significant for the public school with an average of 3.65. In contrast to private school had an average 2.71 (p = 0.00), in the verbal span of two-syllable words with different semantics and equal phonology public school had an average 3.18 and private school had an average 2.53 (p = 0.02). These results correlate with the effect of phonological similarity, which has been cited above. Ferreira and Sagrilo (2012) assessed children male and female and observed better performance on verbal span in both genders in the repetition of two-syllable words with different phonology and semantics than in two-syllable words with equal phonology and different semantics. According to Andrade (2002) subjects with ADHD showed better recall of words with semantic similarity, since it compensates for the difficulty caused by phonological similarity and that access to the meaning of each word can also facilitate your recall. These data corroborate the findings of this research in relation to semantic similarity. With regard to schooling there has been previous reference to its importance for the performance of working memory. Table 5 is a comparison between the groups, which have a variable age and type of school. The results show statistically significant differences in tests of free recall of polysyllabic words with complex phonology and different semantics between GIII and GIV, noting that the age of the subjects is the same for the two groups (six years) and the variable type of school is different. In verbal span test 3A, the results indicate a statistically significant difference in GI (average 3.63) and GII (average 2.63) with p = 0.03. The age variable is different in verbal 3A span between GII and GIII, and GIII presents subjects with higher age (6 years) correlating again that age helps the development of language and memory (GINGRICH et al., 2005). In the test of verbal span 3B, two-syllable words with different semantics and equal phonology, the difference was statisticcally significant between groups GIII (average 3.44) and GIV (average 2.56), p = 0.02, and the variable type of school.
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Other studies correlate the sound information in working memory with school performance, reading level and age. The maturation of working memory skills improved significantly in children from 1st grade compared to children from preschool (GINGRICH et al., 2005, 2007). The effect of word length, in a study conducted by Rodrigues and Befi-Lopes (2009) shows that the best performance in the repetition of sequences of words whose time articulating to pronounce phonemes, syllables, words or pseudowords is less. This effect would occur because items that are pronounced more quickly are less likely to decline in phonological working memory before your total repetition is performed, easing the process of reverberation. According to Cunha and Capellini (2010) the performance of working memory in children from 1st to 5th grade in public school is better over school grades, influencing the reading. These studies corroborate the findings of this research. Repeat testing of non-words and visual span showed no statistically significant differences in this study, but several studies have demonstrated the importance of words not in the development of language and working memory. According to Rodrigues and Befi-Lopes (2009), the ability to not words facilitates the acquisition of new vocabulary and sentence comprehension with higher syntactic complexity and working memory allows the acquisition of metalinguistic skills such as grammatical sentences judgment tasks and conscience phonological. Ferreira (2011) in comparative studies of children with ADHD and children without complaints learning and attention shows that the recall tests no words there was no statistically significant difference, but the performance was higher for children without learning. In this type of task the children do not use support semantic or lexical aspects to remember. Probably make use of phonological aspect for memory, suggesting that working memory depend not only attention, but also of phonological processing. Regarding visual span Barbosa et al (2010) in studies with children from 2nd and 3rd grade of elementary school investigated the relationship between the skills of visual memory and spelling and concluded that the acquisition of spelling rules is related to good memory ability visual. The recall test in reverse order not statistically significant in this study. According to the study by Ferreira (2011) among children with ADHD and children without complaints learning and attention differences were observed between these groups with better performance for children without learning complaints and attention corroborating Andrade (2002), as is not an everyday task, requiring greater use of attention.
Conclusion Data from this study showed that the subjects of the public had superior performance in all tests that assessed working memory compared to subjects in private and that performance was higher for subjects aged 6 years since the school age, and assisted in the development of language and memory.
REFERENCES Anderson, U., & Lyxell, B. (2007). Working memory deficit in children with mathematical difficulties: A general or specific deficit? Journal of Experimental Child Psychology, 96, 197-228.
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Andrade, E. R. (2002). Memória de trabalho verbal e visual em crianças com transtorno do déficit de atenção/hiperatividade. Ph.D. Thesis, São Paulo (SP): Universidade de São Paulo. Baddeley, A. D. (2000). The episodic buffer: A new component of working memory? Trends in Cognitive Sciences, 4, 417-423. Baddeley, A. D., Anderson, M., & Eysenck, M. (2011). Memória. Porto Alegre: Artmed. Baddeley, A. D., & Hitch, G. J. (1974). Working memory. In G. A. Bower (Ed.), Recent advances in learning and motivation. New York: Academic Press. Baddeley, A. D. (2006). Working memory: An overview. In Working memory and education, Amsterdan: Elsevier Press. Barbosa, P. M. F., Bernardes, N. G. B., Misorelli, M. I., & Chiappetta, A. L. M. L. (2010). Relação da memória visual com o desempenho ortográfico de crianças de 2a e 3a séries do ensino fundamental. Revista CEFAC, 12, 598-607. Bueno, O. A. (2004). Memória e amnésia. In Neuropsicologia hoje, São Paulo: Artes Médicas. Corona, A. P., Pereira, L. D., Ferrite, S., & Rossi, A. G. (2005). Memória sequencial verbal de 3 e 4 sílabas em escolares. Revista PróFono, 17, 27-36. Cunha, V. L. O., & Capellini, S. A. (2010). Análise psicolinguística e cognitivo-linguística das provas de habilidades metalinguísticas e leitura realizadas em escolares de 2a a 5a série. Revista CEFAC, 12, 772-783. Gindri, G., Keske-Soares. M., & Mota, H. B. (2005). Comparação do desempenho de crianças pré-escolares e de 1a série em tarefas envolvendo a memória de trabalho. Revista da Sociedade Brasileira de Fonoaudiologia, 10, 201-206. Gindri, G., Keske-Soares. M., & Mota, H. B. (2007). Memória de trabalho, consciência fonológica e hipótese de escrita. Revista PróFono, 19, 313-322. Ferreira, T. L. (2011). A avaliação da memória de trabalho auditiva e
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visual em crianças com o déficit de atenção e hiperatividade. Thesis, Campinas (SP): Universidade Estadual de Campinas. Lamprecht, R. R. (2004). Aquisição fonológica do Português: Perfil de desenvolvimento e subsídios para terapia. Porto Alegre (RS): Artmed. Lobo, F. S., Acrani, O. I., & Ávila, C. R. B. (2008). Tipo de estímulo e memória de trabalho fonológica. Revista CEFAC,10. Mezzomo, C. L., Mota, H. B., & Dias, R. F. (2010). Desvio fonológico: Aspectos sobre a produção, percepção e escrita. Revista Sociedade Brasileira de Fonoaudiologia, 15. Morgado, I. (2005). Psicologia delaprendizaje y la memoria: Fundamentos y avances recientes.Revista de Neurologia. Barcelona, 40, 289-297. Mota, H. B., Keske-Soares, M., & Linassi, L. Z. (2004). Habilidades de memória de trabalho e o grau de severidade do desvio fonológico. Revista Pró-Fono, 1, 75-82. Mousinho, R., & Correa, J. (2009). Habilidades linguístico-cognitiva em leitores e não leitores. Revista Pró-Fono, 21, 113-118. Rodrigues, A., & Befi-Lopes, D. M. (2009). Memória operacional fonológica e suasrelações com o desenvolvimento da linguagem infantil. Revista Pró-Fono, 21, 63-69. Sagrilo, M. C. P., & Ferreira, T. L. (2012). Diferença entre span verbal e visual nos gêneros. Revista CEFAC, 15. Santos, F. H., & Bueno, O. F. (2003). Validation of the Brazilian children’s test of Pseudowords repetition in Portuguese speakers aged 4 to 10 years. Brazilian Journal of Medical and Biological Research, 36, 1533-1547. Scheuer, C. I. (2005). Memória e linguagem. In L. P. Ferreira, D. M. Befi-Lopes, & S. C. O. Limongi (Eds.), Tratado de fonoaudiologia (2nd ed.). São Paulo: Roca. Wertzner, H. F., Amaro, L., & Galea, D. E. (2007). Phonological Performance measured by speech severity indices compared with correlated factors. São Paulo Medical Journal, 125, 309-314.
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22 Left-Right and Up-Down Mirror Image Confusion in 4-, 5- and 6-Year-Olds Izumi Uehara Department of Psychology, Ochanomizu University, Tokyo, Japan
Young children under the age of 8 - 9 years tend to confuse left-right mirror images, and it is thought that their linguistic skills play a crucial role in this phenomenon. However, other aspects of this confusion, such as whether children confuse up-down mirror images or whether the meaningfulness of the stimulus influences matching performance, remain unclear. The present study examined the confusion of left-right and up-down reversed images by 4-, 5- and 6-year-olds using meaningful and meaningless figures in a task in which sample and comparison stimuli were presented simultaneously. Children performed more accurately when presented with meaningful figures and confused both up-down and left-right reversed figures, although they did so less frequently in response to up-down than to left-right reversed figures. Reversal confusion was greatest in 4-year-olds and no significant differences were observed between 5and 6-year-olds. These findings suggest that the ability to discriminate reversed images may be associated with the development of a wide range of cognitive abilities including theory of mind, executive function, and suggestibility. Keywords: Preschool Children; Left-Right and Up-Down Mirror Image Confusion; Meaningfulness
Introduction It is well-known that young children under 8 - 9 years of age experience difficulty when discriminating left-right mirror images (e.g., Bryant, 1973; Cohn & Stricker, 1979; Cronin, 1967; Davidson, 1935; Jordan & Jordan, 1974; Thompson, 1975). A number of previous studies have used letters, such as “b” versus “d” and “p” versus “q”, to investigate reversal discrimination and, as a result, it is thought that there may be a correlation between the reading and writing skills of children and their performance on left-right reversal discrimination tasks (Cohn & Stricker, 1979; Cubelli & Della Sala, 2009; Davidson, 1935; Fisher, Bornstein, & Gross, 1985; Jordan & Jordan, 1974, 1990; Terepocki, Kruk, & Willows, 2002). McMonnies (1992a; 1992b) found that mirror image confusion in children is correlated with factors other than linguistic skills and suggested that left/right body awareness may be a latent factor. Jean-Paul and Youssef (2012) suggested that other tasks, such as those that require writing a letter in a specific location on a sheet of paper, may also influence the mirror writing of children. Furthermore, meaningfulness has some influence on mirror image discrimination. Mandler and Stein (1974) found that children 7 - 8 years of age recognize reversals of meaningful pictures more accurately than expected, although this study did not include meaningless pictures as control stimuli. Outside of this classic study, the relationship between the meaningfulness of a stimulus and mirror image confusion lacks supporting evidence and, to date, the causes of mirror image confusion in children and the mechanisms underlying this phenomenon remain unclear. Thus, it is important to explore the
possible factors other than linguistic skills such as reading and writing, that influence mirror image confusion in preschool children who have not yet fully developed reading and writing skills. A number of previous studies have used lines and figures to investigate the discrimination of images by preschool children (Bryant, 1973; Corballis & Zalk, 1977; Cronin, 1967; Rude1 & Teuber, 1963; Thompson, 1975). However, the type of stimuli that elicit confusion in preschool children and the extent of such confusion remain ambiguous. Likewise, the discrimination of up-down mirror images is much less documented than is left-right reversal discrimination. Several initial studies indicate that up-down discrimination is easier for young children than left-right discrimination (Davidson, 1935; Huttenlocher, 1967; Rude1 & Teuber, 1963; Thompson, 1975), but these studies do not clarify whether preschool children confuse up-down reversals in a matching-to-sample task involving novel stimuli. Additionally, virtually no studies have investigated up-down discrimination in young children. Thus, the extent to which children confuse up-down reversed images and the age at which such confusion occurs compared with the extent to which they confuse left-right reversed images and the age at which that confusion occurs remain ambiguous. Thus, the present study examined the extent to which preschool children confuse original figures with left-right and up-down reversals of these images and whether their performance in response to meaningful versus meaningless figures differs. To compare responses to left-right and up-down reversed images, each child was asked to perform a simultaneous matching-to-sample task by selecting a stimulus from a set of
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Method Participants This study included 42 4-year-olds (12 boys and 30 girls; mean age: 4 years and 2 months; range: 3 years and 8 months to 4 years and 6 months), 41 5-year-olds (24 boys and 17 girls; mean age: 5 years and 2 months; range: 4 years and 7 months to 5 years and 6 months), and 45 6-year-olds (26 boys and 19 girls; mean age: 6 years and 2 months; range: 5 years and 7 months to 6 years and 6 months) from a nursery school in a suburb of a large city near Tokyo. All were middle-class, Japanese-speaking children. This study was conducted under the supervision of the school, and written consent from the parents of participants was obtained through the school prior to the participation of their children. All children who participated in this study did so voluntarily and none dropped out before the study was completed.
Materials Ten stimulus sheets (210 mm × 297 mm) were used for the test (explained in the next section), and four were used for practice trials that were performed before the test trials. A sample stimulus was presented in the upper half of each stimulus sheet, and six comparison stimuli were presented in the lower half in a 2 × 3 layout (see Figure 1). The six comparison stimuli were comprised of the same figure as the sample stimulus (in the upper half), a left-right reversal of the sample stimulus, an up-down reversal of the sample stimulus, and three figures that appeared similar to the sample stimulus. Each of the three figures differed from the sample stimulus in a few respects. For example, if the sample were a shirt, one of the comparison figures would have a crooked sleeve and another would not have a collar (Figure 1). Thus, 10 sample stimuli and 60 (10 × 6) comparison stimuli were used for the test trials, whereas four sample stimuli and 24 (4 × 6) comparison stimuli were used for the practice trials. The 10 sample stimuli in the test trials consisted of five meaningful figures and five meaningless figures used by a previous study (Uehara, 2012) in which seven elementary school children (aged 7.6 - 9.3 years) correctly chose all the meaningful and meaningless figures. Meaningful figures included a shirt, a cup, and a boot, and meaningless figures were geometrical figures
consisting of lines and curves (Figure 1). The four sample stimuli in the practice trials were simple meaningless figures and were never used in the test trials. All figures were prepared by computer software and hard copies were used for the experiment. The presentation order of the 10 test sheets was randomized across participants, and the locations of the six comparison figures on each sheet were also randomized for each participant.
Procedure Each participant performed the task in a quiet classroom during his or her free time during the regular school day. Before the test trials, each subject completed four practice trials and received feedback after each response. By the end of the practice trials, the researcher confirmed that each participant understood the task requirements: namely, to choose the figure that looked most similar to the sample. For the test trials, the researcher presented each child with 10 figure sheets one at a time. The researcher asked the child to choose the comparison figure that was most similar to the sample figure by asking the child, “Which figure looks most like this figure?” Children responded by pointing with their finger. The test trials did not include feedback concerning the accuracy of the response; rather, the same verbal prompt was given each time, “Well, then, next.” All participants finished the test trials in approximately 3 - 5 minutes.
Results Preliminary analyses did not reveal any sex differences in accuracy or error type; thus, sex was not considered in the following analyses.
Effects of Age and Meaningfulness on Matching-to-Sample Performance The mean correct response rate of the children was plotted as a function of age and meaningfulness (Figure 2), and only an exact match-to-sample response was considered correct. A three (age: 4-, 5-, or 6-year-old) × two (meaningfulness: meaningful or meaningless) analysis of variance (ANOVA) revealed statistically significant main effects for age (F[2,125] = 53.7, Mean percentage of correct answers
comparison stimuli that included both left-right and up-down reversed stimuli.
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Figure 1. Illustration of the placement of stimuli on a test sheet. A sample stimulus was placed on the upper half of the paper, and six comparison stimuli were placed on the lower half. a) An example of meaningful stimuli. b) An example of meaningless stimuli.
4-year-old
5-year-old Age
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Figure 2. The mean correct response rate plotted as a function of age (4-year-olds, 5-year-olds, and 6-year-olds) with meaningfulness (meaningful or meaningless figures) as a parameter. Error bars indicate standard errors.
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Left-Right and Up-Down Mirror Image Confusion in 4-, 5- and 6-Year-Olds
p < .01, partial η2 = .46) and meaningfulness (F[1,125] = 8.79, p < .01, partial η2 = .07). No significant interaction between age and meaningfulness was observed (F[2,125] = .46 p > .05, partial η2 = .00). Post hoc multiple comparison tests for age (Tukey HSD, p = .05) revealed a significantly poorer performance by 4-year-olds compared with 5-year-olds and 6-year-olds and by 5-year-olds compared with 6-year-olds. These findings indicate that older children performed better than younger ones and that children performed more accurately in response to meaningful than to meaningless figures.
Analysis of Errors: Choice of Left-Right Mirror Images To investigate whether children erroneously chose the left-right reversed stimuli more frequently than expected by chance (chance level: 16.7%), one-sample t-tests were conducted. Children in each age group chose the left-right reversed stimuli significantly more frequently than chance in response to both meaningful and meaningless stimuli: 4-year-olds for meaningful stimuli: t(41) = 7.37, p < .01; 4-year-olds for meaningless stimuli: t(41) = 9.40, p < .01; 5-year-olds for meaningful stimuli: t(40) = 4.40, p < .01; 5-year-olds for meaningless stimuli: t(40) = 4.65, p < .01; 6-year-olds for meaningful stimuli: t(44) = 4.29, p < .01; 6-year-olds for meaningless stimuli: t(44) = 2.08, p < .05). In other words, when children failed to choose the exact match, they chose the left-right reversed stimulus more frequently, regardless of meaningfulness. Differences in the choice of left-right mirror images according to age and meaningfulness were also assessed. The mean response rate of the children when choosing left-right reversed stimuli was plotted as a function of age and meaningfulness (Figure 3). A three (age: 4-, 5-, or 6-year-old) × two (meaningfulness: meaningful or meaningless) ANOVA revealed a statistically significant main effect for age (F[2,125] = 14.8, p < .01, partial η2 = .19) but not for meaningfulness (F[1,125] = 1.71, p > .05, partial η2 = .01) or for the interaction between these two factors (F[2,125] = 1.94 p > .05, partial η2 = .03). Post hoc multiple comparison tests for age (Tukey HSD, p = .05) revealed a significantly greater number of choices of the left-right reversed stimulus by 4-year-olds than by 5-year-olds
and 6-year-olds. No significant difference was found between 5-year-olds and 6-year-olds. These findings indicate that young children aged 4 - 6, especially 4-year-olds, often confused figures with their left-right mirror images regardless of meaningfulness.
Analysis of Errors: Choice of Up-Down Mirror Images To investigate whether children erroneously chose the up-down reversed stimulus more frequently than expected by chance (chance level: 16.7%), one-sample t-tests were performed. Only the 4-year-olds chose the up-down reversed stimulus significantly more frequently than would be expected by chance regardless of meaningfulness: for meaningful stimuli: t(41) = 3.83, p < .01; for meaningless stimuli: t(41) = 8.02, p < .01. The 5-year-olds and 6-year-olds chose the up-down stimulus significantly more frequently than would be expected by chance in response to meaningless but not meaningful stimuli; 5-year-olds for meaningful stimuli: t(40) = 1.53, p > .05; 5-year-olds for meaningless stimuli: t(40) = 4.39, p < .01; 6-year-olds for meaningful stimuli: t(44) = .16, p > .05; 6-year-olds for meaningless stimuli: t(44) = 5.83, p < .01. In other words, when children failed to choose the exact match, 4-year-olds chose the up-down reversed figures more frequently than expected by chance regardless of meaningfulness, whereas 5-year-olds and 6-year-olds chose the up-down reversed stimulus more frequently than expected by chance only in response to meaningless figures. The mean response rate of children choosing the up-down reversed stimuli was plotted as a function of age and meaningfulness (Figure 4). A three (age: 4-, 5-, or 6-year-old) × two (meaningfulness: meaningful or meaningless) ANOVA revealed statistically significant main effects for age (F[2,125] = 10.1, p < .01, partial η2 = .14) and meaningfulness (F[1,125] = 36.7, p < .01, partial η2 = .23). The interaction of these two factors was not significant (F[2,125] = .38, p > .05, partial η2 = .00). Post hoc multiple comparison tests for age (Tukey HSD, p = .05) indicated a significantly greater number of choices of the up-down reversed stimulus by 4-year-olds compared with 5-year-olds and 6-year-olds. No significant difference was 100
90 80 70 60 50 30
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Figure 3. The mean response rate of children choosing left-right reversed figures plotted as a function of age (4-year-olds, 5-year-olds, and 6year-olds) with meaningfulness (meaningful or meaningless figures) as a parameter. Error bars indicate standard errors.
4-year-old
5-year-old Age
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Figure 4. The mean response rate of children choosing up-down reversed figures plotted as a function of age (4-year-olds, 5-year-olds, and 6-year-olds) with meaningfulness (meaningful or meaningless figures) as a parameter. Error bars indicate standard errors.
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observed between 5-year-olds and 6-year-olds. These findings indicate that children, regardless of age, chose up-down reversed figures more frequently in response to meaningless than meaningful figures and that 4-year-olds chose meaningful up-down reversed figures more frequently than did older children.
Analysis of Errors: Left-Right Reversed Stimuli versus Up-Down Reversed Stimuli The relative frequencies of choosing left-right and up-down reversed stimuli were compared. For meaningful figures, a three (age: 4-, 5-, or 6-year-old) × two (reversal direction: left-right or up-down ) ANOVA revealed statistically significant main effects for age (F[2,125] = 12.5, p < .01, partial η2 = .17) and reversal direction (F[1,125] = 33.8, p < .01, partial η2 = .21). The interaction between these two factors was not significant (F[2,125] = 1.14, p > .05, partial η2 = .02). Post hoc multiple comparison tests for age (Tukey HSD, p = .05) indicated a significantly greater number of choices of reversed stimuli by 4-year-olds than by 5-year-olds and 6-year-olds, but no significant difference was found between 5-year-olds and 6-year-olds. In other words, children, regardless of age, chose meaningful left-right reversed figures more often than they chose meaningful up-down reversed figures when they failed to choose the exact match. Additionally, 4-year-olds chose both meaningful left-right and up-down reversed stimuli more frequently than did 5-year-olds and 6-year-olds. In terms of meaningless figures, a three (age: 4-, 5-, or 6-year-old) × two (reversal direction: left-right or up-down) ANOVA revealed a statistically significant main effect for age (F[2,125] = 23.8, p < .01, partial η2 = .28). No main effects for reversal direction (F[1,125] = .01, p > .05, partial η2 = .00) and no interactions between these two factors (F[2,125] = 2.02, p > .05, partial η2 = .03) were observed. Post hoc multiple comparison tests for age (Tukey HSD, p = .05) indicated a significantly greater number of choices of the up-down reversed stimulus by 4-year-olds than by 5-year-olds and 6-year-olds, but no significant difference was found between 5-year-olds and 6-year-olds. In other words, the difference in the selection of meaningless left-right and up-down reversed figures was not significant, and 4-year-olds chose both meaningless left-right and up-down reversed stimuli more frequently than did 5-yearolds and 6-year-olds.
Discussion The present study investigated confusion in preschool children when selecting left-right and up-down mirror images of figures by including meaningful and meaningless figures within the same paradigm. Consistent with previous studies, left-right reversal confusion was frequently observed in children regardless of meaningfulness. Specifically, 4-year-olds confused original figures with their up-down reversals regardless of meaningfulness, whereas 5-year-olds and 6-year-olds confused only meaningless figures. With regard to meaningful figures, children confused the originals with their left-right reversals more frequently than with their up-down reversals; this difference was not significant for meaningless figures. This type of confusion was more frequently observed in 4-year-olds compared with 5-year-olds and 6-year-olds, and we found no difference in the confusion of 5-year-olds and 6-year-olds.
Matching-to-sample performance improved with age between 4 and 6 years, and children performed more accurately for meaningful than meaningless figures. The present study provides new basic data and insights regarding reversal confusion in young children, and these data suggest that several critical aspects of phenomenon have been overlooked in children. First, up-down reversal confusion in children has rarely been investigated, and knowledge concerning this phenomenon is very limited. In the present study, preschool children confused not only left-right but also up-down reversed images. Additionally, up-down reversal confusion decreased earlier than did left-right reversed confusion. As left-right reversal confusion, such as in mirror writing, is commonly observed when children begin to learn to write, research tends to focus on its relationship to linguistic skills. However, up-down reversal confusion in writing tasks has rarely been investigated in children. The current findings suggest differential associations between up-down reversal confusion and left-right reversal confusion, on the one hand, with linguistic development, on the other, such that up-down confusion depends on factors other than linguistic skills, such as directional or visuospatial sense, whereas left-right confusion depends more on linguistic skills. Less frequent reversal confusion for meaningful relative to meaningless figures suggests that meaningfulness influences difficulty during the differentiation of stimuli. Thus, if children are encouraged to find meaning in shapes or figures, they might be less confused by reversed shapes. Previous studies indicate that children younger than 8 - 9 years tend to confuse left-right reversed letters. Based on the present findings, the ability to find meaning in a word or to imagine a word from a letter may contribute to avoidance of left-right reversal confusion. However, the ability to only pronounce and/or copy the target letter may not be enough to reduce confusion about the left-right reversal of a letter. The difference in performance between 4-year-olds and older children suggests that the development of reversed image discrimination may be related to other types of cognitive functioning. Similar abilities known to be related to age differences are theory of mind (e.g., Perner, et al., 2007; Perner & Ruffman, 1995), appearance-reality distinction (e.g., Flavell, Green, & Flavell, 1986; Sapp, Lee, & Muir, 2000), suggestibility (e.g., Bruck & Ceci, 1999; Leichtman & Ceci, 1995; Uehara, 2000), executive function (e.g., Lyons & Zelazo, 2011; Zelazo & Frye, 1998), and other functions (e.g., Gerstadt, Hong, & Diamond, 1994; Povinelli, Landau, & Perilloux, 1996; Uehara, 1998). However, the relationships among these abilities remain unclear. Zelazo (2004) proposed that reflective consciousness develops together with metacognitive skills and that this development could lead to the control of thought, emotion, and action. The development of metacognition and/or self-reflective consciousness may be one factor involved in the changes in performance that have been observed over a wide range of cognitive abilities, including reversal differentiation. In this manner, the use of conscious metacognitive judgment may lead to an avoidance of confusion when stimuli have similar appearances, such as with reversed images. Further investigation is necessary to elucidate the specific mechanisms underlying this process. In conclusion, the present study demonstrates that, although the documented relationship between left-right confusion and linguistic skills is important, other factors also play critical roles in reversal confusion in young children.
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Left-Right and Up-Down Mirror Image Confusion in 4-, 5- and 6-Year-Olds
Acknowledgements This research was supported by MEXT KAKENHI Grant Numbers 19730457. I thank Ikuya Murakami for his thoughtful comments on earlier versions of this paper and his help in submitting this paper. Most of all, I am grateful to the children and teachers at the nursery school for their cooperation.
REFERENCES Bruck, M., & Ceci, S. J. (1999). The suggestibility of children’s memory. Annual Review of Psychology, 50, 419-439. Bryant, P. E. (1973). Discrimination of mirror images by young children. Journal of Comparative and Physiological Psychology, 82, 415-425. Cohn, M., & Stricker, G. (1979). Reversal errors in strong, average, and weak letter namers. Journal of Learning Disabilities, 12, 533-537. Corballis, M. C., & Zalk, M. C. (1977). Why do children confuse mirror-image obliques? Journal of Experimental Child Psychology, 24, 516-523. Cronin, V. (1967). Mirror-image reversal discrimination in kindergarten and first-grade children. Journal of Experimental Child Psychology, 5, 577-585. Cubelli, R., & Della Sala, S. (2009). Mirror writing in pre-school children: A pilot study. Cognitive Processing, 10, 101-104. Davidson, H. P. (1935). A study of the confusing letters b, d, p, and q. Journal of Genetic Psychology, 47, 458-468. Fisher, C. B., Bornstein, M. H., & Gross, C. G. (1985). Left-right coding and skills related to beginning reading. Journal of Developmental & Behavioral Pediatrics, 6, 279-283. Flavell, J., Green, F., & Flavell, E. (1986). Development of knowledge about the appearance-reality distinction. Monographs of the Society for Research in Child Development, 51, i+iii+v+1-87. Gerstadt, C., Hong, Y. J., & Diamond, A. (1994). The relationship between cognition and action: Performance of children 3 1/2 - 7 years old on a Stroop-like day-night test. Cognition, 53, 129-153. Huttenlocher, J. (1967). Discrimination of figure orientation: Effects of relative position. Journal of Comparative and Physiological Psychology, 63, 359-361. Jean-Paul, F., & Youssef, T. (2012). Unraveling the mystery of mirror writing in typically developing children. Journal of Educational Psychology, 104, 193-205. Jordan, B. T., & Jordan, S. G. (1974). Jordan left-right reversal test. Child Psychiatry and Human Development, 4, 178-187. Jordan, B. T., & Jordan, S. G. (1990). Jordan left-right reversal test: An analysis of visual reversals in children and significance for reading problems. Child Psychiatry and Human Development, 21, 65-73. Leichtman, M. D., & Ceci, S. J. (1995). The effects of stereotypes and suggestions on preschoolers’ reports. Developmental Psychology, 31, 568-578.
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Lyons, K. E., & Zelazo, P. D. (2011). Monitoring, metacognition, and executive function: Elucidating the role of self-reflection in the development of self-regulation. Advances in Child Development and Behavior, 40, 379-412. Mandler, J. M., & Stein, N. L. (1974). Recall and recognition of pictures by children as a function of organization and distractor similarity. Journal of Experimental Psychology, 102, 657-669. McMonnies, C. W. (1992a). Reversals and left/right confusion. Journal of Behavioral Optometry, 3, 31-34. McMonnies, C. W. (1992b). Visuo-spatial discrimination and mirror image letter reversals in reading. Journal of the American Optometric Association, 63, 698-704. Perner, J., Kloo, D., & Gornik, E. (2007). Episodic memory development: Theory of mind is part of re-experiencing experienced events. Infant and Child Development, 16, 471-490. Perner, J., & Ruffman, T. (1995). Episodic memory and autonoetic consciousness: Developmental evidence and a theory of child amnesia. Journal of Experimental Child Psychology, 59, 516-548. Povinelli D. J., Landau, K. R., & Perilloux, H. K. (1996). Self-recognition in young children using delayed versus live feedback: Evidence of a developmental asynchrony. Child Development, 67, 1540-1554. Rudel, R. G., & Teuber, H. L. (1963). Discrimination of direction of line in children. Journal of Comparative and Physiological Psychology, 56, 892-898. Sapp, F., Lee, K., & Muir, D. (2000). Three-year-olds’ difficulty with the appearance-reality distinction: Is it real or is it apparent? Developmental Psychology, 36, 547-560. Terepocki, M., Kruk, R. S., & Willows, D. M. (2002). The incidence and nature of letter orientation errors in reading disability. Journal of Learning and disabilities, 35, 214-233. Thompson, G. B. (1975). Discrimination of mirror-image shapes by young children. Journal of Experimental Child Psychology, 19, 165176. Uehara, I. (1998). No transfer of visuomotor learning of button-pressing from right to left hands in right-handed four-year-olds. Perceptual & Motor Skills, 87, 1427-1440. Uehara I. (2000). Differences in episodic memory between four- and five-year-olds: False information versus real experiences. Psychological Reports, 86, 745-755. Uehara, I. (March, 2012). Differentiation of left-right reversal figures and letters by young children. The 23rd Annual Meeting for of the Japan Society of Developmental Psychology, Nagoya. (in Japanese) Zelazo, P. D. (2004). The development of conscious control in childhood. Trends in Cognitive Sciences, 8, 12-17. Zelazo, P. D., & Frye, D. (1998). Cognitive complexity and control: II. The development of executive function in childhood. Current Directions in Psychological Science, 7, 121-125.
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23 The Relationship between Consciousness of Professional Role and Work Autonomy of Rural Teachers from Sichuan Province Tianmei Zhou1*, Jiewei Chen2, Li Luo3 1
School of Educational Science, Neijiang Normal University, Neijiang, China 2 School of Foreign Languages, Neijiang Normal University, Neijiang, China 3 School of Geography & Resources Science, Neijiang Normal University, Neijiang, China
The paper has discussed the characteristics of consciousness of professional role of rural teachers and the relationship between consciousness of professional role and work autonomy. By randomly sampling, a survey is conducted among 265 primary and secondary school teachers from Sichuan province. It is found that the whole consciousness of professional role of rural teachers from Sichuan province is above average; the role consciousness of their collaborators and facilitators is the highest; the role consciousness of their social and economic status is the lowest. From the characteristics of different groups of teachers, there is no difference in gender, teaching age and education background, but there are significant differences between teachers of urban and rural areas, backbone teachers and nonbackbone teachers, teachers in key middle schools and non-key middle schools, and among teachers who teach Chinese, mathematics, foreign languages, Politics, History, Chemistry, Biology, Geography and teachers in primary and middle schools. Consciousness of professional role of teachers is significantly related to work autonomy. That is to say, consciousness of professional role of teachers can positively or negatively predict work autonomy. Keywords: Rural School Teachers; Consciousness of Professional Role; Work Autonomy
Introduction Professional role is divided according to the role of groups and is the role of the social members playing in professional positions (Ding & Zhang, 1992). Consciousness of professional role, the individual’s ideology, is the realistic, clear, stable and organized reflection to the job, which refers to awareness, cognition and understanding to individual’s professional role status, professional role norms, professional role behavior (Feng, 2006). For the connotation of teacher professional role consciousness, most researchers regard that it is teachers’ cognition and understanding of their professional role, that is, the teachers’ awareness of role is their own cognition to the teachers’ professional norms and is the social role expectations reflecting in the teachers’ mind (Jiang, 2008); The more comprehensive definition is Liang Yuhua’s view. He regards it as the teachers’ perceiving, cognizing, understanding and experiencing to their own role status, corresponding role behavior standards and role playing (Liang & Pang, 2005). It includes three basic structures: cognizing and understanding their role positions, understanding their norms, as well as cognizing and experiencing the role playing role. They influence and interact mutually and form a whole that cannot be separated. Many practices and studies have found that teachers’ educational concept is one of the important factors to improve the teachers’ diathesis and educational conduct, especially the pro*
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fessional role of teachers which has influence on the teachers’ professional development, and even the children’s growth and development. Most studies have focused on the research that how the teacher’s role consciousness “should be”, but ignore the research on the status quo of the teachers themselves and their opinions. Even if there are some studies about it, fewer researchers have investigated rural middle school teachers’ professional role consciousness. So, the research is to investigate the status quo of the rural middle school teachers’ consciousness of professional role and to provide targeted strategies for the rural teachers’ pre-service education and teachers’ on-thejob training. The research will be beneficial to guide teachers in rural areas to correctly perceive themselves, examine their attitude towards profession, and find profession’s significance for themselves. It will also help enrich the education of researches in rural teachers in our country and provide empirical evidence for the research on the specialization of teaching profession. Job autonomy is that the job gives the individual of freedom, independence and discretion to schedule work and to decide how to work, which is one of the five core characteristics of job (Fang & Ding, 2007). It refers to “the degree the individual gains freedom, independence and discretion in work schedule and working program decision” (Menlo Hackman & Oldham, 1980). In the field of education, the work autonomy of teachers is also very important. It is the autonomy to their own subjective world or inner self, which is their psychological characteristics to adjust positively and control the educational and tea-
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ching activities driven by intrinsic motivation, under the guidance of certain social norms and educational purpose (Yao & Shen, 2010). A lot of studies show that teachers’ work autonomy has close relationship with their work motivation, satisfaction, stress, job burnout (or separation from service), anxiety, specialization, creativity, sense of responsibility and so on (Yang, Xia, & Huang, 2009). Teachers’ consciousness of occupational role occupies the core status in the teachers’ educational concept, which affects teachers’ other educational concepts and education behaviors directly. So, the second purpose of this study is to investigate the close relationship between teachers’ professional role consciousness and teachers’ work autonomy as well as the prediction effect.
Methods Participants The researchers collected 280 questionnaires and 265 are valid. In detail, there are 45 elementary school teachers, 177 junior middle school teachers and 43 senior middle school teachers; 119 male teachers and 147 female teachers; 191 rural teachers and 69 urban teachers. There are 85 samples selected randomly from Neijiang rural teachers and 180 selected from Sichuan “national training of the backbone teachers in disaster areas’ rural junior middle schools”.
Research Materials Teachers’ professional role consciousness questionnaire: The study adopts the self-designed questionnaire of middle school teachers’ professional role consciousness. The questionnaire includes 3 parts, 6 dimensions, and 23 items. Three parts include teachers’ cognizing and understanding of their role status (social economic status, knowledge imparter and executor, researcher and curriculum developer, collaborator and facilitator), understanding of their role norms as well as cognizing and experiencing of the role playing. The six dimensions are role consciousness of social and economic status, role consciousness of knowledge imparter and executor, role consciousness of researcher and curriculum developer, role consciousness of collaborator and facilitator, consciousness of professional role norms and consciousness of professional role experience. In the present research, every factor of the scale’s α coefficient is between .54 to .89 and half reliability is between .56 to .84. The whole scale’s α coefficient is .90, and half reliability is .85. It means that the questionnaire has good reliability. Exploratory factor analysis shows that the rate of the 6 factors’ cumulative variance contribution is 60.79%, which proves its validity. It is a five-point Likert scale. The minimum score of each tested item is 1 point, and the top score is 5 points. Higher values indicate higher degree of professional role consciousness approval. Teachers’ work autonomy questionnaire: The study adopts Teachers’ work autonomy questionnaire developed by Yang Bing et al. (Yang, Xia, & Huang, 2009), which contains 28 items, 6 factors: the autonomy of school operation management, the autonomy of professionalization and curriculum reform, the autonomy of classroom teaching, the autonomy of student performance assessment, the autonomy of carrying out extracurricular activities, and the autonomy of student behavior management. The Cronbach’s α coefficients of the questionnaire and each dimension are: .89, .89, .75, .74, .91, .70 and .94, the α
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coefficient of the whole questionnaire is .90; the 6 factors’ cumulative variance contribution rate is 55.36%. Both the reliability and the validity of the scale meet the requirement of psychometrics. The questionnaire uses Likert-5 points scoring system from 1 to 5; the higher the scores, the stronger job autonomy. Demographic variables questionnaire: This questionnaire mainly records personal data, including gender (male and female), region (urban and rural), teachers’ titles (primary teacher, secondary teacher, senior teacher), teaching subjects (Chinese, Math, English, Politics, History, Chemistry, Biology, Geography, and so on), school types (key and non-key middle schools), teacher’s types (backbone or non-backbone teachers).
Procedure and Data Analysis In the form of questionnaire investigation, investigators were assumed by the trained principals or class teachers. Questionnaires were retrieved on the spot after teachers finished. The data are processed by SPSS12.0 statistics software.
Results The General Situation of Rural Teachers’ Professional Role Consciousness Mean comparison found that overall, the average score of the consciousness of rural teachers’ professional role (3.77 ± .52) is greater than 3. The six-dimension scores of rural teachers from high to low in turn are as follows: role consciousness of rural teachers’ collaborators and facilitators (4.35 ± .84), consciousness of occupational role norms (4.34 ± .71), role consciousness of knowledge imparters and executors (3.80 ± .68), role consciousness of researchers and curriculum developers (3.70 ± .74), consciousness of professional role experience (3.26 ± .82), role consciousness of status (3.08 ± 3.08). It shows that Sichuan rural teachers’ recognition of consciousness of professional role is above average. The recognition of role consciousness of their collaborators and facilitators is the highest and the recognition of consciousness of their economic and social status is the lowest.
The Comparisons of Sichuan Rural Teachers’ Consciousness of Professional Role among Different Groups The rural teachers’ role consciousness of collaborators and facilitators and understanding of role norms are obviously higher than urban teachers’. To the contrary, the rural teachers’ role consciousness of status is obviously lower. There are no regional differences in role consciousness of knowledge imparters and executors, role consciousness of researchers and curriculum developers and consciousness of occupational role experience. Rural backbone teachers’ consciousness (role consciousness of knowledge imparters and executors, role consciousness of researchers and curriculum developers, role consciousness of collaborators and facilitators, and consciousness of professional role norms) is obviously higher than the non-backbone teachers’. The key middle school teachers’ consciousness (role consciousness of researcher and curriculum developers, role consciousness of collaborators and facilitators and consciousness of occupational role norms) is distinctly lower than the general middle school teachers’. The role consciousness of knowledge
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imparters and executors and consciousness of professional role norms of the rural teachers who teach Chinese, Math and English are distinctly higher than those teachers who teach Politics, History, Chemistry, Biology, Geography and other subjects. There are no differences in consciousness of professional role between the primary school and middle school teachers, except for role experience. To investigate the consciousness differences between primary and middle school teachers, and teachers with different titles, the researchers use LSD post hoc tests (Table 1) and find that: the consciousness of professional status of rural senior high school teachers is distinctly higher than primary and secondary school teachers’ (P < .05), but role consciousness of knowledge imparter and executor is significantly lower than theirs. For the role consciousness of knowledge imparter and executor, role consciousness of collaborator and facilitator, and consciousness of professional role norms, secondary school teachers’ are significantly higher than primary and senior high school teachers’ (P < .05). For the role consciousness of collaborator and facilitator, and consciousness of occupational role norms, primary school teachers’ are distinctly higher than senior high school teachers’ (P < .05). Additionally, senior teachers are significantly higher than teachers in the second rank of teaching in the role consciousness of collaborator and facilitator as well as consciousness of occupational role norms (P < .05).
Correlations between Rural Teachers’ Consciousness of Professional Role and Work Autonomy The result (Table 2) shows that there are significantly positive correlations between teachers’ role consciousness of status and each dimension of work autonomy, and between consciousness of occupational role experience and each dimension of work autonomy. And other dimensions of professional role consciousness are positively related to the autonomy of student performance assessment, of student behavior management, of carrying out extra-curricular activities and of class teaching, and are negatively related to the autonomy of school operation management and of professionalization and curriculum reform. On the basis of the above correlation analysis, the researchers apply regression analysis to put dimensions of work autonomy as the dependent variables and dimensions of professional role as predicting variables. The result (Table 3) shows that teachers’ role status, researcher and developer, collaborator and facilitator, role norms, and role experience can significantly predict the different dimensions of work autonomy. Specifically, teachers’ role consciousness of status can significantly and positively predict five dimensions (except class teaching) of work autonomy (between β in .207 ~ .475, P < .05); role norms can positively predict two dimensions of autonomy of student performance assessment and the autonomy of carrying out extra-curricular activities( between β in .287 ~ .305, P < .01), and can negatively predict the autonomy of professionalization and curriculum reform (β = −.304, P < .01; teachers’ role experience can positively predict two dimensions of carrying out extra-curricular activities and class teaching (between β in .167 ~ .270, P < .05); teachers’ role consciousness of collaborator and facilitator an positively predict two dimensions of autonomy of class teaching and the autonomy of student behavior management (between β in .286 ~ .420, P < .001); lastly, teachers’ role consciousness of researcher and curriculum developer can negatively predict the autonomy of school operation man-
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agement (β = −.279, P < .01). The total explanation rate of teacher’s role consciousness to different dimensions of work autonomy is 5.1% ~ 18.1%.
Discussion Characteristics of Rural Teachers’ Consciousness of Professional Role This study shows that the overall approval of Sichuan rural teachers’ consciousness of professional role is on the average, role consciousness of collaborator and facilitator being the highest and consciousness of social and economic role status being the lowest. It states that due to the dynamics and rapid change of the modern social knowledge, teachers are no longer the owner and imparter of the knowledge. Rural teachers have changed their role cognition on authority representatives and pure knowledge imparter of knowledge. They gradually set up the equal consciousness that the students are the facilitators of the study, and that they are the students’ mentors and facilitators on study. In the meantime, implementation of new curriculum reform in our country has obtained certain achievements in the recent ten years; however, in the process of implementation,” the teachers’ participation is far from what reform advocates expected”, which means teachers should become a researcher and developer of the new curriculum, but not merely the receivers, practitioner and consumer of the new curriculum (Wu, 2009). Additionally, because of the restrictions of their own objective conditions and subjective factors, rural teachers cannot or are unwilling to actively participate in the new curriculum reform, rural teachers’ approval of the consciousness as the role of curriculum developer and researcher is not high, and they can’t grasp the role norms accurately and comprehensively. The teachers are also full of confusion on the role norms, which are their own role rights, responsibilities, and conduct standards. At the same time, salary is a special concern for the teachers. In recent years, salary increases year by year, but rural teachers’ income growth is so small that many teachers can’t feel the change of the income and they are not satisfied with the income gap between urban and rural areas (Zhang & Ye, 2010). Additionally, because of rural teachers’ work environment and working pressure, their approval of consciousness on the social and economical status is the lowest. From the perspective of different group characteristics, the rural teachers’ consciousness of professional role has no significant difference in gender, teaching aging, and education background, but has prominent difference in the urban and rural teachers, backbone and non-backbone teachers, key schools and non-key schools, Chinese-Math-English and other subjects’ teachers as well as primary and middle school teachers. 1) The consciousness differences between urban and rural, key and non-key schools may be related to the strong enforcement of new curriculum reform and the high social expectation to the urban and key school teachers. These make the teachers constantly reposition and adapt to their professional role, so that urban and key middle school teachers’ approval of consciousness of researcher and developer, collaborator and facilitator, and role norms are significantly lower than rural and non-key middle school teachers’. 2) The consciousness of professional role for the rural backbone teachers is significantly higher than the non-backbone teachers’, which is due to backbone teachers’ own diathesis, more training and study opportunities. On the one hand, the backbone teachers have good ideological and
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Table 1. Comparison to Sichuan rural teachers’ professional consciousness. Scale
1
2
3
4
5
6
City
3.30 ± .60
3.61 ± .97
3.53 ± .74
4.04 ± .94
4.00 ± .88
3.30 ± .75
Country
3.00 ± .71
3.86 ± .95
3.75 ± .75
4.46 ± .77
4.46 ± .58
3.26 ± .84
t
2.95**
−1.78
−1.93
−3.54***
−5.13***
.30
Backbone Teachers
3.08 ± .67
3.94 ± .82
3.88 ± .64
4.64 ± .50
4.59 ± .40
3.22 ± .82
Non-Backbone Teachers
3.07 ± .70
3.52 ± 1.10
3.33 ± .81
3.73 ± 1.04
3.79 ± .87
3.35 ± .79
t
.12
3.46**
5.74***
9.47***
9.97***
−1.21
Key Middle School
3.17 ± .61
3.65 ± .93
3.48 ± .74
3.97 ± .92
3.88 ± .87
3.30 ± .75
Non-Key Middle School
3.05 ± .70
3.83 ± .95
3.78 ± .72
4.46 ± .78
4.48 ± .58
3.24 ± .84
−1.35
Chinese-Math-Foreign Teachers
3.09 ± .69
3.87 ± .92
3.75 ± .73
4.40 ± .85
4.42 ± .66
3.24 ± .84
Other Subjects Teachers
3.11 ± .68
3.50 ± 1.30
3.51 ± .70
4.13 ± .80
4.10 ± .78
3.35 ± .75
−1.8
2.3
Primary School Teachers
2.94 ± .76
Junior Middle School Teachers Senior Middle School Teachers
−6.16
***
1.23
*
−4.14
***
t
t
−2.82
**
.55
*
−.77
1.92
1.87
2.48
3.79 ± 1.25
3.53 ± .84
3.82 ± 1.18
4.06 ± .88
3.38 ± .98
3.05 ± .68
3.88 ± .83
3.84 ± .68
4.65 ± .49
4.58 ± .40
3.21 ± .81
3.34 ± .49
3.31 ± .95
3.20 ± .69
3.45 ± .84
3.40 ± .80
3.32 ± .62
*
5.51
**
12.62
***
57.33
***
66.69
***
.89
F
3.33
Teachers in the Second Rank of Teaching
2.98 ± .76
3.69 ± 1.01
3.61 ± .81
4.20 ± .99
4.23 ± .78
3.19 ± .76
Teachers in the First Rank of Teaching
3.10 ± .64
3.86 ± .92
3.74 ± .71
4.42 ± .76
4.37 ± .67
3.31 ± .80
Teachers of High-Ranking
3.21 ± .57
3.88 ± .81
3.84 ± .58
4.53 ± .52
4.52 ± .48
3.29 ± .95
2.72
.55
F
1.93
1.04
1.64
3.13
*
Note: 1 = consciousness of status; 2 = consciousness of knowledge imparter and executor; 3 = consciousness of researcher and curriculum developer; 4 = consciousness of collaborator and facilitator; 5 = consciousness of professional role norms; 6 = consciousness of professional role experience.
Table 2. The correlation values between rural teachers’ consciousness of professional role and work autonomy. Scale
1
2
3
***
−.081
Autonomy of Professionalization and Curriculum Reform
.181**
Autonomy of Student Performance Assessment
.244***
Autonomy of School Operation Management
Autonomy of Student Behavior Management
.287
.227
***
4
5
6
−.109
−.143
*
−.143
*
.155*
−.102
.030
−.106
−.153
.078
.155*
.201**
.247***
.256***
.099
***
***
***
.128*
.316
***
.266
.391
.361
Autonomy of Carrying out Extra-Curricular Activities
.227***
.265***
.228***
.265***
.254***
.285**
Autonomy of Class Teaching
.177**
.174**
180**
.282***
.259***
.194**
Note: 1 = consciousness of status, 2 = consciousness of knowledge imparter and executor; 3 = consciousness of researcher and curriculum developer, 4 = consciousness of collaborator and facilitator; 5 = consciousness of professional role norms, 6 = consciousness of professional role experience.
political quality, noble teacher’s ethics cultivation, healthy body and mind diathesis, solid professional knowledge, systematic education theory, practiced business skills, and consciousness of actively carrying out creative teaching (Xie, 2010); On the other hand, in the recent ten years, our country provides backbone teachers with training and study opportuni-
ties through kinds of channels, which develop their personal theories that help them criticize and rethink the role, promote understanding and grasping of the role recognition, and even are good for achieving the accordance between role behavior and role playing, between educational thinking mode and practical teaching mode. 3) The rural Chinese-Math-English teach-
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Table 3. Factors and parameters of regression analysis for teachers’ professional role consciousness predicting work autonomy. Dependent Variables
Independent Variables
β
R2 (adjusted)
t
F ***
Autonomy of School Operation Management
1 3
.479 −.279
.069 .104
4.82 −3.09***
13.17***
Autonomy of Professionalization and Curriculum Reform
1 5
.308 −.304
.025 .051
2.75** −2.67**
6.89***
Autonomy of Student Performance Assessment
5 1
.287 .274
.059 .104
3.68*** 3.49**
13.89***
Autonomy of Student Behavior Management
4 5
.420 .266
.142 .181
6.57*** 3.42**
25.91***
Autonomy of Carrying out Extra-Curricular Activities
6 5 1
.270 .305 .207
.068 .107 .120
3.16** 3.18** 2.08*
11.23***
Autonomy of Class Teaching
4 6
.286 .167
.078 .097
4.12*** 2.40*
13.07***
Note: 1 = consciousness of status; 3 = consciousness of researcher and curriculum developer; 4 = consciousness of collaborator and facilitator; 5 = consciousness of professional role norms; 6 = consciousness of professional role experience.
ers’ consciousness of professional role is higher than other subjects’ teachers which may be related to the current educational system. Under the current educational system, students, parents and schools pay more attention to Chinese, Math and English than other subjects, which makes the Chinese-Math-English teachers’ status higher than other subjects’ teachers and approve more their consciousness of professional role. 4) The survey shows reasons for a significant difference in the consciousness of professional role between primary and middle school teachers. Firstly, from the point of the demands of students development, senior high school education is the important stage of the whole basic education that is not only the basis for further study to the students and lay a solid foundation for students’ lifelong development, but also the key period to cultivate high quality human resources. So, senior high school teachers have higher consciousness of role status than primary and junior middle school teachers. In the meantime, senior high school students’ sense of independence and critical thinking is in the developing period, so the consciousness of senior high school teachers as the imparter and practitioner of knowledge and teaching material is lower than primary and junior middle school teachers’. Secondly, maybe quality education is carried out more fully and education reform reflects more lively in primary school. While the entrance examinations are prior in junior and senior high school, and evaluation system has not changed too much today, primary school teachers truly feel the changes of the whole atmosphere in classroom, curriculum, and school brought by the teachers’ role transformation, so their understanding of the consciousness of cooperator and facilitator, and professional role norms is significantly higher than senior high school teachers’. 5) There is no difference in gender, teaching aging and education background in rural teachers’ consciousness of professional role, which shows teachers from every age bracket are faced with the approval of teacher’s professional role. The reasons are that (Shen, 2005): on the one hand, from the perspective of teachers’ professional development, teachers will encounter difficulties and setbacks in the professional development process, and will experience hard times which create doubt, negation and other imbalance mentality to the original approval of professional role, and even professional burnout for some teachers. On the other hand, the educational reform and
the transformation of the teachers’ role are strongly advocated in recent years, which may be a new problem for every teacher. Especially today when the society develops rapidly and network technology is widely used, old teachers or bachelor-degree teachers are faced with the psychological stress brought by professional role transformation and anxiety produced by professional approval that can not be established, so their problems are never smaller than a young or college-degree teacher’. All these require teachers to establish or improve the approval of the professional role.
The Relationship Analysis between Consciousness of Professional Role and Work Autonomy of the Rural Teachers This study shows that the higher the consciousness of job status, the better the role experience, the stronger the teachers’ work autonomy, which can positively predict the teachers’ work autonomy. That is because self consciousness is the medium to take part in various social practice activities. If the teachers improve their consciousness of professional role, the initiative of self shaping will be enhanced and the education-teaching autonomy which is the intrinsic psychological motivation for the teachers to work will get more attention. This study results show that there are negative correlations between five dimensions of consciousness (consciousness of imparter and executor, of researcher and developer, of collaborator and facilitator, of role norms) and two dimensions of work autonomy (work autonomy of school operation management, work autonomy of professionalization and curriculum reform). In the meantime, rural teachers’ consciousness of researcher and developer as well as role norms can negatively predict the work autonomy of school operation management and work autonomy of professionalization and curriculum reform. Maybe that is because under the current system of education management in our country, schools apply administration management and the leaders determine and execute the school operation management, so teachers as the researcher and developer can enhance the teaching related work autonomy in student performance assessment, student behavior management, carrying out extra-curricular activities, and class teaching, and can weaken
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the autonomy of school operation management. In the mean time, because of kinds of tests and entrance examinations pressure in different stages in primary and middle schools, teachers can not appropriately understand and grasp the consciousness of role norms, and so lack autonomy of teacher professionalization and curriculum reform.
Acknowledgements This article is Sichuan province philosophy and social sciences key research base, one of the achievements for the project of Sichuan teachers education research center, Sichuan rural teachers’ professional role consciousness research (TER2009017).
REFERENCES Ding, S. S., & Zhang, X. S. (1992). Social role theory. Shanghai Academy of Social Sciences Press, 60-65. Feng, L. P. (2006). A study on the stability of professional role consciousness of the young and middle adulthood teacher in university. Central South University Master Degree Thesis, 15-16. Liang, Y. H., & Pang, L. J. (2005). The concerning teachers’ role consciousness: The connotation, structure and value. Journal of Education Science (China), 21, 39-42.
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Jiang, P. (2008). Research on the role awareness of beginning teachers in primary school. Liaoning Normal University Master Degree Thesis, 11-12. Fang, K. K., & Ding, X. H. (2007). Education job autonomy and job satisfaction. Tsinghua Journal of Education, 28, 40-47. Menlo Hackman, J. R., & Oldham, G. R. (1980). Work redesign, Menlo Park A: Addison-Wesley, 128-136. Yao, J. H., & Shen, J. L. (2010). Construction and revision of teaching intrinsic autonomy questionnaire for primary and middle school teachers. Journal of Psychological Development and Education (China), 3, 302-307. Yang, B., Xia, L. X., & Huang, X. T. (2009). The development of teacher work autonomy scale in China. Journal of Southwest University (Social Sciences Edition), 35, 17-20. Wu, L. K. (2009). Why do teachers alienate new curriculum reform, Journal of Research in Educational Development, 4, 47-50. Zhang, P., & Ye, Z. M. (2010). The bottom view: the new curriculum reform of rural teachers. Journal of Education Research Monthly (China), 7, 53-56. Xie, L. P. (2010). The recognition of define of the back-bone teachers. Journal of the New Curriculum Teaching Research Version, 18, 8485. Shen, Z. F. (2005). A research on the professional role-identity of Shanghai primary and middle school teachers. Journal of Psychological Science, 28, 723-726.
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24 Development of Deterministic Thinking Scale Based on Iranian Culture Jalal Younesi, Akram Alsadat Mirafzal University of Social Welfare and Rehabilitation Sciences, Tehran, Iran
One of major cognitive distortions is deterministic thinking. This type of thinking ignores any possibility or probability in conclusion about the events. Any consequence of event may be thought such as: 2 × 2 = 4. Equality is a dominant factor among all conclusions of this kind of distortion. In Islamic perspective, the distortion is seen as a destructive factor for ruining balance of fear and hope, which is to be an important sign of people’s faith. The distortion emerges in cognitive rigidity in the mind which may be mother of all distortions. Cognitive rigidity is a main reason for depression and other psychosocial maladjustment. The scale with 36 items was developed in first phase of this study. Its validity and reliability were measured among men and women. It had reasonable and significant correlation with Beck Depression Inventory (p ≤ .05) and also showed reasonable internal reliability (α = .8218). Through factor analysis, five factors appeared in this type of thinking to be related to General deterministic thinking, Deterministic thinking in interaction with people, Absolute view in thinking, Deterministic thinking in prediction of future and Deterministic thinking in negative events. Keywords: Deterministic Thinking; Cognitive Distortions; Balance of Fear and Hope; Islamic Culture; Cognition
Introduction Plato’ idealism insists that our perceptions determine the reality that we experience. This reminds us the “Plato’s Cave”, which is reality to be defined as the figures that one sees outside the cave (Leahy, 1996). The approach that “reality is determined by cognition” has a long history in Western philosophy. For example, Kant’s (1782/1988) philosophy of mind was based on the view that reality is never directly knowable, but rather is “known” through “categories of thinking” (Leahy, 1987). According to Kant, all knowledge was based on the “categories”, which today we would call schemas, and the reality was never directly knowable but only to know through the schemas. This is not a notion which merely to be stated in western philosophy because there are same points from religious perspective. For instance, Prophet Mohammad (S) wishes in his praying “may Allah show me the reality as it is” (Younesi, 2005; Younesi, Asgary, & Bahrami, 2009). Human being is sometimes described remoteness from the reality in Quran as “being arrogant when to see himself needless” (Quran, 95; 6,7) while “only the god is needless” (Quran, 112; 2). In point of psychopathology, how people think about themselves or the world around them seems to make a major difference to their level of vulnerability to stress, anxiety and depression. This is more than simply being optimistic or pessimistic—there are certain thinking methods which help people to cope better than others (Warner, 2000). It is reasonable to see cognitive therapy as the attempt to get the patient to unchain himself from inappropriate cognitions and to see
the reality as it is (Beck, 2008; Beck et al., 1979; Leahy, 1996). These wrong cognitions are named cognitive distortions. They are inaccurate thoughts or ideas which to maintain negative thinking and help to maintain negative emotions. The theory of cognitive distortions was first proposed by Burns (1989). Eliminating these distortions and negative thought is said to improve mood and discourage maladies such as depression and chronic anxiety (Beck, 1983). There are many cognitive distortions which have a major role in forming depression and anxiety (Beck et al., 1979; Beck et al., 1983; Burns, 1989; Teasdale, 1993; Teasdale & Bernard, 1993; Clarck & Fairburn, 1997; Smit, Rosenfield, & Mcdonald, 2006; Del Missier, Ferrante, & Costantini, 2007). Some of these distortions include (Sommers-Flanagan 2004; Leahy, 1996): Arbitrary Inference, Selective Abstraction, Personalization, Dichotomous Thinking, Labeling and mislabeling, Magnification and minimization, overgeneralization, etc. One of major cognitive distortions is deterministic thinking (Younesi & Mirafzal, 2007). This type of thinking ignores any possibility or probability in conclusion about the events and to be able to create many cognitive distortions because any distortion leads to conclusion; and distortion of deterministic thinking to rule out any probability or possibility in concluding (Younesi, Younesi, & Asgary, 2008). Any consequences of events may be thought such as: 2 × 2 = 4. Equality is a dominant factor among all conclusions of this kind of thought, i.e.: divorcing from wife = misery. The distortion emerges in cognitive rigidity in the mind and may be mother of all distortions (Younesi, 2005). Cognitive rigidity is a
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main reason for depression and other psychosocial maladjustment (Beck, 1980; Weissar & Beck, 1992). In religious perspective, which is sometimes essential to be considered in cognitive therapy for some people (SommersFlanagan, 2004), this distortion is seen as destructive factor for ruining balance of fear and hope (Younesi, 2005; Younesi & Mirafzal, 2007) because any exception for consequences of bad or good events is to be ruled out by deterministic thinking. There is an strong comment from most important religious leaders of Islam for keeping the balance of fear and hope as sign of faith and mental health (for example: Imam Ali (S), ground sons of great prophet Mohammad
(Al tamimi Al madi & Abdolvahed, 1979; Faizol Al Islam & Alinaghi, 1973; Koleini & Seghet Al Islam, 1980). In prediction of consequences of favourite or undesirable events, any deterministic thinking about the events has been rejected in Holy Quran: “sometimes undesirable event may bring you luck and sometimes desired one to bring you un luck” (Quran, 2, 216). So being too disappointed or too hopeful in relation with the events, either positive or negative is not accepted in this perspective. Since prediction of any event is not certainly possible in this view, even prediction of “god’s will” is not promising in Shiite perspective (Arafeh praying, Imam Hossein , Ghommi, 1989). This view is called “bada” in Shiite belief which means everything can be initiated from beginning. There is a sentence in Islamic culture which is widely used by people in western and eastern countries when to confront with events, that is: “Insha Allah” means “If the God Wants”. The sentence is in opposite direction of deterministic thinking because any consequence of events to come back to will of God which god only to know (Younesi, 2005). Similarly in scientific approach, accepting or rejecting hypothesis by P value of zero is avoided in spite of possessing firm experimental reasons. The main reason for the approach is that some scientists believe in no absolute reality which can be imperfect because our perception of events and realities to be not from beginning or final state. Creatures and events are identified partially from not initiating or ending (Jaafari, 1982): “You don’t aware of what to be gradually creating in world of creature.” (Quran, 16, 8). “What are in the earth or sky to request from god and every day he to be in position of creating” (Quran, 55, 29). In this philosophy, creation is not finished and to be expected new creation so in this ongoing job to be not possible prediction of life’s events surely. Development of an instrument which can be able to measure the rate of deterministic thinking based on religious perspective and Islamic culture to be the aim of the study. Measuring of deterministic thinking is milestone for studying the nature of depression and anxiety or other maladjustment (Younesi, 2005).
Material and Method Based on characteristics of balance in fear and hope and comments of religious leaders (above references) and characteristics of cognitive rigidity (Beck, 1980; Weissar & Beck, 1992), items of deterministic thinking scale were developed. First of all 52 items were made which to refer to prediction of the events and behaviors. The items include: Behaviors of people in future i.e.: “Behaviors and reactions of people will be predicted certainly”. Positive and negative events in future i.e.: “in spite of solid reasons, nobody can predict bad and good events of life defi-
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nitely”. Forgiveness such as: “It is sensible to forgive bad behaviors of individuals when we do not believe the behaviors to be repeated certainly”. Behaviors of couples such as: “if somebody has behaved well frequently with his/her partner, he/she will do certainly as the same as before”. Will of God such as: “Nothing is certain in this world, even God’s will; because it is possible to change the God’s will by praying”. Future of human beings i.e.: “If human beings have more knowledge, they will able to predict events of life absolutely positive”. Social relationship: “Certain conclusion from reactions and behavior of people is one of major pathology in social relationship”. The content validity of the Scale was approved by five experts including: Clinical Psychologist, Psychometric, expert in Islamic Knowledge, counselor and psychologist with profession in Islamic culture. The instrument is responded by four options: I agree totally, I agree partially, I disagree totally, I disagree partially. Beck’ depression Inventory (BDI) [Beck 1968] is utilized for measureing the congruent validity. 97 men and women were examined by the scale and BDI in a pilot study who were collected randomly in Tehran. Using factor analysis, RISREL and other statistical analysis, reliability and validity of the scale were measured and necessary modifications to be implemented. Moreover 600 men and women randomly involved in a main study who to be questioned by developed deterministic thinking scale.
Results Table 1 demonstrates demographic data of subjects in pilot study: Table 2 shows the results of Pearson correlation between Deterministic thinking scale (DTS) and BDI: After measuring reliability, 14 items were omitted from the scale in pilot study and reliability coefficient 38 items of the scale was .8218. Two items of DTS were removed by RISREL analysis. DTS was computed by Principal Component Analysis. The results of Component analysis shown in Table 3: Five factors emerged in the scale with 36 items which were named based on contents of the items: 1) General deterministic thinking (9 items) 2) Deterministic thinking in interaction with people (8 items) 3) Absolute view in thinking (7 items) 4) Deterministic thinking in prediction of future (6 items) 5) Deterministic thinking in negative events (6 items) In additional study 50 subject including 25 men and same number women answered DTS by one week interval in Tehran. The Reliability over time of the scale was (r = .87; p ≤ .5). DTS was reanalyzed by factor analysis in the main study which 300 couples to answer the scale. The results showed Table 1. The demographic data of subjects in pilot study. Female
Male
Married
Single
Age of subjects (mean)
50
47
50
47
31.6 (SD 10.67)
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Table 2. The results of Pearson correlation between DTS and BDI. Number of subjects
DTS
BDI
97
1
.33*
Note: *(p ≤ .01)-two tailed.
Table 3. The results of component analysis in the study. Initial Eigen values Components
Total
% of V
Cum%
1
5.596
14.725
14.725
2
2.990
7.867
22.593
3
2.378
6.257
28.849
4
2.061
5.423
34.272
5
1.745
4.592
38.865
repeatedly five factors to exist in DTS and to possess significant factorial loading. In Table 4, statistical characteristics of discovery and confirmatory factor analysis of DTS were shown.
Discussion The results show that DTS to enjoy good reliability and validity. The congruent validity of scale which emerged with Beck Depression Inventory to show reasonable correlation (./33, p ≤ .01 ). This finding has harmony with views of many psychologists and cognitive therapists who to insist on role of cognitive distortions as main factor of developing depression (Gertner, 2003; Baron, 2000; Rottenstreich & Hsee, 2001; Leahy, 1996; Sommers-Flanagan & Sommers-Flanagan, 2004; Beck, 2008; Beck, Epstein, & Harrison, 1983; Teasdale, 1993). Moreover it was predictable to see such correlation between two instruments because of similarities between deterministic thinking and cognitive rigidity (Younesi, 2005). In other hand, it is clear that Cognitive rigidity to be a main reason for depression and other psychosocial disorders (Beck, 1975; Weissar & Beck, 1992). In another study, Younesi, Asgary, & Bahrami (2008) found significant negative correlation between Enrich marital satisfaction inventory and DTS. It seems that deterministic thinking as a cognitive distortion to be devastating factor either in depression or marital relationship of couples. It is apparent that cognitive distortions to have eminent role in decreasing of marital satisfaction (Klaff, 2007; Shapiro, 2007; Gottman, Coan, Carrère, & Swanson, 1998; Fincham, Harold, & Gano-Philips, 2000). Momeni (2008) measured sensitivity of DTS among happy and unhappy couples who to request the family court for divorce. He found significant and reasonable sensitivity of DTS for distinguishing these two groups of couples. Results of factor analysis appeared five factors which to confirm either main or pilot study. First factor as a general one counts 14.725 of variance and to include 9 items. These items measure the whole view of subjects towards life in angel of determinism, i.e.: “if humans are not able to conclude certainly about life events, the anarchy and chaos will rule on the life”. Second factor which counts 7.86 of variance and to refers to
Deterministic thinking in interaction with people to contain 8 items, i.e.: “It is always possible to have precise prediction from actions and behaviors of people”. Third factor which is related to absolute view in thinking consisting of 7 items and to count 6.26 of variance, i.e.: “if a person behaved badly with somebody, he/she will certainly repeat it again.” The fourth factor is named Deterministic thinking in prediction of future to comprise 6 items and counting 5.42 of variance, i.e.: “It is possible to predict behaviors and reactions of people definitely.” Finally, fifth factor is named Deterministic thinking in negative events and to take account 6 items, counting 4.59 of variance, i.e.: “if some bad events happen in the life, it is equal of big misfortune”. It seems that DTS to be able to measure different angles of deterministic thinking. This characteristic of the scale corresponds with variety roles of cognitive distortions which to have negative impact psychosocial life of people (Baron, 2000; Rottenstreich & Hsee, 2001; Warner, 2000; Smit, Rosenfield, & Mcdonald, 2006). There are some similarities between items of factors involved in DTS and some cognitive biases which to be found by some authors. For instance, cognitive bias of focusing effect is similar with items of factor 5 & 3. The focusing effect is a cognitive bias that occurs when people place too much importance on one aspect of an event, causing an error in accurately predicting the utility of a future outcome. People focus on notable differences, excluding those that are less eye-catching, when making predictions about happiness or handiness (Del Missier, Ferrante, & Costantini, 2007; Schkade & Kahneman, 1998). Also some authors suggested the neglect of probability bias, a type of cognitive bias, is the tendency to completely disregard probability when making a decision under uncertainty and is one simple way in which people regularly violate the normative rules for decision making Baron, 2000; Rottenstreich & Hsee, 2001). This bias is comparable with some items of DTS in factors 2 & 4 which to ignore any probability in conclusions. One of the unique features of DTS which makes it different from other scales of measuring cognitive distortions, to consider principal of balancing between fear and hope (Al tamimi Al madi & Abdolvahed, 1979; Faizol Al Islam & Alinaghi, 1973; Koleini & Seghet Al Islam, 1980; Younesi, 2005; Younesi & Mirafzal, 2007). So, there was an attempt to measure deterministic thinking either positive or negative events in development of the items of the scale. The author and his colleagues were studied relation between deterministic thinking (DT) and mental health, communicational skills and marital satisfaction. The results showed that to exist the negative correlation between DTQ and communicational skills among couples (Maghsoudzade, 2010); reverse correlation between DTQ and forgiveness scale (Borooghani, 2010); negative correlation between DTQ and Enrich Marital Satisfaction Scale (Younesi & Bahrami, 2009), negative correlation between DTQ and hope scale (Rah Anjam, 2010) and positive correlation between DTQ and marital conflicts scale (Momeni, 2008). These researches indicate that DT plays a destructive role the interactions of people in family and society circumstances, addressing DT in cognitive therapy can help clients to reduce their anxiety and depression (Younesi, Younesi, & Asgary, 2008). It is suggested that the role of DT in producing social phobia and hopelessness and helplessness as milestones of depression be investigated. Moreover it is suggested to investigate between
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Table 4. Statistical characteristics of discovery and confirmatory factor analysis of DT. Discovery
Confirmatory
Factors
Special value
Percent of value
Reliability coefficient
Standard coefficient
T
R2
First
4/68
13/01
0/71
0/37
4/68
0/14
Second
3/42
9/51
0/61
−0/24
4/68
0/10
Third
1/79
4/98
0/70
−0/52
4/68
0/38
Fourth
1/55
4/31
0/59
0/52
4/68
0/38
Fifth
1/49
4/16
0/64
0/48
4/68
0/23
Note: X2 = 2/51; p = 0/28; KMO = 0/793; Bartlett test = 3867/8; CFI = 0/99; GFI = 0/99; p = 0/001; AGFI = 0/21; RMSEA = 0/99.
attachment style, and DT to be carried out in future.
Acknowledgments The author would like to thanks the research section of University of Social welfare and rehabilitation Sciences for funding this study in phase 1 & 2.
REFERENCES Al tamimi Al madi, A. (1979). Ghorar Al hekam and dorar Al kalam. Beirut: Institute of Al ailami Press. Baron, J. (2000). Thinking and deciding (3rd ed.). Cambridge: Cambridge University Press. Beck, A. T. (2008). The evolution of the cognitive model of depression and its neurobiological correlates. American Journal of Psychiatry, 165, 969-977. Beck, A. T. (1975). Cognitive therapy and the emotional disorders. International Universities Press Inc. Beck, A. T., Epstein, N., & Harrison, R. (1983). Cognition attitudes and personality dimentions in depression. British Journal of Cognitive Psycholtherapy, 1, 1-16. Beck, A. T., Rush, A. J., Show, B. F., & Emery, G. (1979). Cognitive therapy of depression. New York: Guilford Press. Borooghani, M. (2010). Prediction of forgiveness by deterministic thinking among couples who are volunteers for divorce. Unpuplished M.Sc. Thesis, Tehran: University of Social Welfare and Rehabilitation Sciences. Burns, D. D. (1989). The feeling good handbook. New York: William Morrow and Co. Clarck, D., & Fairburn, M. (1997). Practice of cognitive behavior therapy. London: Oxford Press. Del Missier, F., Ferrante, D., & Costantini, E. (2007). Focusing effects in predecisional information acquisition. Acta Psychologica, 125, 155-174. Faizol Al Islam, A. (1973). Translation and explanation of Nahjo Al balagheh. Tehran: Islamieh Press. Fleck, L., & Weiss, K. (2003). The art of fact. Evolutionary Antropology, 12, 168-172. Fincham, F. D., Harold, G. T., & Gano-Philips, S. (2000). The longitudinal association between attributions and marital satisfaction. Journal of Family Psychology, 14, 267-285. Gertner, J. (2003). The future pursuit of happiness. New York times magazine. Ghommi, & Sheikh, A. (1989). Mafatih Al Janan. Tehran: Loghman Press. Gottman, J. M., Coan, J., Carrère, S., & Swanson, C. (1998). Predicting marital happiness and stability from newlywed interactions. Journal of Marriage and the Family, 60, 5-22.
Jaafari, & Mohammad, T. (1981). Scientific cognition in perspective of Quran. Islamic Culture Press. Klaff, F. (2007). Children of divorce. In F. Shapiro et al. (Eds.), Handbook of EMDR and family therapy processes. Hoboken, NJ: John Wiley and Sons. Koleini, & Seghet Al Islam (1980). Osool Al Kaffi. Tehran: Mostafavi Press. Leahy, T. H. (1987). A history of psychology. Main currents in Psychological thought. McGraw-Hill, NJ: Prentice-Hall International Edition. Leahy, R. L. (1996). Cognitive therapy: Basic principles and applications. Bergen County, NJ: Northvale. Maghsoudzade, M. (2010). Prediction of marital satisfaction of shaded sons and spouses by Rate of deterministic thinking and communication skills. Unpuplished M.Sc. Thesis, Tehran: University of Social Welfare and Rehabilitation Sciences. Momeni, A. (2008). Measuring sensitivity of deterministic thinking scale among happy and unhappy couples. Unpublished M.A. Dissertation in Clinical Psychology, Tehran: Islamic Azad University. Center of Sciences and Researches. Rah Anjam, H. (2010). Prediction of hope rate by deterministic thinking among in students of Azad Universities of Tehran. Unpuplished M.Sc. Thesis, Tehran: University of Azad (Central branches). Rottenstreich, Y., & Hsee, C. K. (2001). Money, kisses, and electric shocks: On the affective psychology of risk. Psychological Science, 12, 185-190. Schkade, D. A., & Kahneman, D. (1998). Does living in California make people happy? A focusing illusion in judgments of life satisfaction. Psychological Science, 9, 340-346. Shapiro, F. (2007). EMDR and case conceptualization from an adaptive information processing perspective. In F. Shapiro et al. (Eds.), Handbook of EMDR and family therapy processes. Hoboken, NJ: John Wiley and Sons. Smit, Jasper, A. J., Rosenfield, D., & Mcdonald, R. (2006). Cognitive mechanism of Social anxiety reduction: An examination of specificity and temporality. Journal of Counsulting and Clinical Psychology, 74, 1203-1212. Sommers-Flanagan, J., & Sommers-Flanagan, R. (2004). Counseling and psychotherapy. Theories in context and practice. Hoboken, NJ: John Willy. Teasdale, J. D. (1993). Emotion and two kinds of thinking: Cognitive Therapy and applied Cognitive Sciences. Behavioural Research and Therapy, 31, 339-354. Teasdale, J. D., & Bernard, P. J. (1993). Affect, cognition and change. Remodeling depressive thought. Hillsdale, NJ: Erlbaum. Younesi, J., & Mirafzal, A. (2007). Development of deterministic thinking questionnaire. Paper Presented to 10th European Congress of Psychology. Prague. Younesi, J., Younesi, M., & Asgari, A. (2008). Prediction of rate of marital satisfaction among Tehranian couples by deterministic thinking.
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Paper Presented to 28th International Congress of Psychology, Berlin. Younesi, J. (2005). The major role of cognitive misconceptions “equality in thinking” in psychological disorders. A Journal of Social Sciences And Humanities. The Research Institute of Seminary & University (HAWZEH VA DANESHGAH), 10, 8-29. Younesi, J., & Bahrami, F. (2009). Prediction of rate of marital satisfaction among Tehranian couples by deterministic thinking. Journal
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of Iranian Psychologists, 14, 34-43. Warner, R. (2000). The environment of schizophrenia. London & Philadelphia: Brunner-Routledge. Weissar, M. E., & Beck, A. T. (1992). Hopelessness and suicide. International Review of Psychiatry, 4, 177-184.
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25 Development and Evaluation of the Posttraumatic Growth Status Inventory Tatjana Alexander1, Rainer Oesterreich2 1
Department of Rehabilitation Psychology, Albrecht-Ludwigs-University of Freiburg, Freiburg, Germany 2 Department of Quantitative Methods, University of Technology, Berlin, Germany
Posttraumatic growth reflects beneficial psychological processes in persons with traumatic experiences. Existing measures of growth were criticized due to their retrospective self-report format that may cause biases in capturing the growth processes in individuals with several specific kinds of trauma, such as physical or psychological disabilities of close family members, bereavement and some others kinds of traumatic experience. In this case, the feelings of guilt may prevent the persons from being aware of the favorable personal changes. The objective of this study was to develop and to evaluate an alternative measuring instrument that uses a status quo response format instead of retrospective items and covers additional areas of growth-related changes. The samples comprised 440 adult persons with traumatic experience, including 181 parents of children with mental and/or physical disabilities. Exploratory and confirmatory factor analyses revealed a 7-factors solution, corresponding to the following subscales: Relationships to Others, New Possibilities, Personal Strength, Appreciation of Life, Spiritual Changes, Generativity, and Openness. Results showed good reliability and concurrent validity. The PGSI is recommended particularly for use in longitudinal studies as well as in samples of persons whose trauma relates to a severe psychological or physical disability in their families. Keywords: Posttraumatic Growth; Coping; Resources; Inventory
Introduction In the past decade, the possibilities of multifaceted positive psychological outcomes, as a consequence of a traumatic life experience, such as an onset of severe health problems in a person her/himself or in a close family member, bereavement or experience of violence, became more and more the objective of theoretical and empirical research work. The approaches to describe the underlying psychological changes led to creating scientifically-founded concepts like posttraumatic growth (PTG, Calhoun, & Tedeschi, 1999; Tedeschi & Calhoun, 2004), adversarial growth (Linley & Joseph, 2004), thriving (O’Leary & Ickovics, 1995), benefit finding (Affleck & Tennen, 1996), and stress-related growth (Park, 1996). From these terms, describing comparable processes in the aftermath of a traumatic event, the term “posttraumatic growth” seems to be the most established. The concept ‘posttraumatic growth’ serves as an expression for processes of changing life orientations and priorities as well as the achievement of a new level of feelings and selfawareness. These processes are initiated by the attempts to adapt to highly challenging life circumstances that can produce high levels of psychological distress. The person’s struggle with the new reality in the aftermath of trauma is essential in influencing the degree and the individual profile of posttraumatic growth. Eventually, the processes of growth involve a movement beyond pre-trauma levels of adaptation, they represent rather ongoing development as a static outcome (Tedeschi & Cal-
houn, 2004). Persons often characterize the corresponding changes as valuable enrichment in their lives. The following domains of perceived personal growth processes were discussed in empirical literature: changes in self like feelings of being strong and more self-assured, a new sense of increased closeness in relationships with others, open-mindedness, religiosity/spirituality changes, as well as alterations in philosophy of life including increased life appreciation and the attempt to live each day to the fullest (Schaefer & Moos, 1992; Calhoun & Tedeschi, 1999; Tedeschi & Calhoun, 2004; Danoff-Burg & Revenson, 2005). In order to capture growth processes, studies use the Posttraumatic Growth Inventory (PTGI, Tedeschi, & Calhoun, 1996), the Benefit Finding Scale (BFS, Antoni et al., 2001; Tomich & Helgenson, 2004), or the Stress-Related Growth Scale developed by Park and collaborators (SRGS, Park, Cohen, & Murch, 1996). These measures differ in regard to the following aspects which will be addressed in turn: a) the target population, for whom the particular measure was designed, b) priority at the focal point in the assessment procedure, c) the degree to which a measure allows for the differentiation between various growth domains, (d) and general connotation of the items. a) The first discrepancy concerns the target population. Whereas the PTGI and the SRGS were developed for and are commonly applied in populations with different kinds of traumatic experience, the BFS was originally designed specially for using with individuals whose trauma relates to severe medical conditions, primarily actual or past cancer. Recently, this measure
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was also used to capture beneficial psychological changes in family caregivers (Kim, Schulz, & Carver, 2007). b) When regarding the content, the growth measures differ slightly in the focal point in the assessment procedure. All three measuring instruments represent the growth facets relationships to the others, and personal strength, respectively. However, the Benefit Finding Scale only contains a great number of items capturing family relationships growth and acceptance. In contrast, the PTGI as well as the SRGS, but not the BF measures religious/spiritual changes. Furthermore, the PTGI includes items that relate to “life appreciation” and “new possibilities” growth domains, which are not covered sufficiently by the SRGS and the BFS. At last, the SRGS is a single measure which comprises several items capturing self-understanding and affect-regulation as additional growth aspects. c) The degree to which each of the measures allows for the differentiation between various growth domains depends on the dissimilarity in items content and on the underlying factorial structure of the questionnaires, which may serves as a foundation for composition of separate subscales. For the PTGI, the stability of a five-factor structure was proved in empirical studies (Tedeschi & Calhoun, 1996; Maercker & Langner, 2001; Taku et al., 2008). Less unambiguous were the results of factor analyses on the BFS and the SRGS items. Various investigations revealed different factorial solutions [Antoni et al., 2001 (BFS, 1 factor); Weaver et al., 2008 (BFS, multiple factor models); Kim, Schulz, & Carver, 2007 (BFS, 6 factors); Park, Cohen, & Murch, 1996 (SRGS, 1 factor); Armeli, Gunthert, & Cohen, 2001 (SRGS, 8 factors); Maercker & Langner, 2001 (SRGS, 1 factor)]. As a consequence, no established subscales were created; the total scores only had been commonly used in studies as a global growth assessment. d) The fourth difference concerns the general connotations of each of the separate items. The BFS inquires about things “The disease taught me to do or to feel”, suggesting a somewhat passive role for the affected persons, whereas the PTGI and the SRGS ask for changes, which “one has experienced as a result of traumatic events”, seeing respondents as more “active” subjects. On the whole, existing measures of growth proved to be very useful in the research on positive adaptation and beneficial psychological processes in the aftermath of significant traumatic events. Nevertheless, they were also criticized in the literature due to several limitations. The main criticism arises out of the retrospective self-report format: All currently available measures ask for subjective experiences of trauma related changes; they do not capture the “status quo” of growth processes. The retrospective measurement of changes implies, that people can correctly compare their actually attributes with their pre-trauma characteristics. However, the recollection of how they were prior to the time of traumatic life event may be distorted due to cognitive biases. For example, McFarland and Alvaro (2000) observed that traumatic event victims tended to derogate their pre-event characteristics. Another study addressed the issue, whether current methods of measuring PTG (i.e., linked questions to stressful event) generally create a positive bias which may undermine the data validity (Smith & Cook, 2004). In order to examine positive biases in self-reported growth, Smith and Cook compared reports of growth from two groups of individuals. In the first group, participants completed the Posttraumatic Growth Inventory in relation to a specific stress-
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ful event. In the second group, PTGI questions were not linked to specific events. Instead, participants were instructed to generally think about the past 4 years, and indicate the degree to which specific, personal changes occurred. In the “unlinked group” only, individuals exposed to traumatic events reported greater growth in Personal Strength and Relationships to Others than participants who did not experience a traumatic event within last four years. The authors conclude that current measurements may actually underestimate PTG to a small but significant degree. Linking questions about PTG to specific stresssors could influence participants to be cautious about attributing their growth experiences to a stressful event. Furthermore, due to a retrospective item format, current growth scales are less appropriate in measuring the beneficial growth processes in individuals whose traumatic experience is related to several specific conditions like a physical disease or a psychological disorder in their families. In this case, the feelings of guilt may prevent the persons from being aware of the favorable personal changes (Peters & Jackson, 2009; Johnson, O’Reilly, & Vostanis, 2006; Alexander & Wilz, 2010). Qualitative research demonstrates several concrete examples of such intrapsychic ambivalence. For instance, a mother of a child with severe health-related problems reported barriers to acknowledge positive changes: “The harm of my child cannot be profitable for me in any way” (Schirmer & Alexander, 2013). Another criticism of the currently available growth scales is that they do not cover all potentially relevant growth domains (e.g., Park & Lechner, 2006). Thus, according to findings from qualitative research, positive changes often occur in areas like more attentiveness for one’s own needs and feelings (Mohr et al., 1999), self-care (e.g., Siegel & Schrimshaw, 2000; Pakenham, 2007; Affleck et al., 1987), open-mindedness and the way one treats others, particularly the pleasure in supporting others and in sharing one’s own knowledge and helpful life experience (Cadell & Sullivan, 2006; Danoff-Burg & Revenson, 2005; Updegraff et al., 2002). The last mentioned intrapersonal changes often occur in relation to several specific kinds of trauma, including experience concerned to severe physical or psychological health conditions in the family (e.g. Alexander & Wilz, 2010; Barskova & Oesterreich, 2009). None of the existing growth measures includes subscales which address the corresponding growth areas. In regard to these criticisms, the goal of the study was to develop and to evaluate a Status Quo Measure of Posttraumatic Growth that should overcome several problems of the existing questionnaires. Firstly, the item format of a newly developed inventory should allow to avoid or to reduce cognitive biases during information recall up to a substantial degree. In order to sidestep potential response distortions caused through interfered feelings of guilt or shame (which arise particularly often in people whose traumatic experience relates to a misery of their close relatives, such as a physical disease or a severe psychological disorder), the items should inquire what a respondent currently senses, feels, thinks and/or does, without building an explicit connection to a definite critical life event. Secondly, a new measure of growth was supposed to differentiate between separate growth domains, including growth areas highlighted in current empirical literature on beneficial growth processes in relatives of chronically disabled persons. On the whole, the new measuring instrument (the Posttraumatic Growth Status Inventory, PGSI) should facilitate a multidimensional construct-adequate capturing of complex intra-personal growth-related proc-
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esses in individuals with different kinds of traumatic experience. In order to estimate the concurrent validity of the PGSI, we aimed for capturing the correlations between the PGSI subscales and the psychological health indicators as well as corresponding correlations between the PGSI and several measures of coping behavior. As demonstrated in empirical investigations, posttraumatic growth has been found to be positively linked to several criteria of psychological health and to the adaptive coping strategies, in case a sufficiently long period of time has passed since the initial traumatic event (Siegel & Schrimshaw, 2007; Ho, Chan, & Ho, 2004; Lechner et al., 2006; Mc Millen & Cook, 2003; Morris, Shakespeare-Finch, & Scott, 2007; Schmidt et al., 2012; Kountrouli, Anagnostopoulos, & Potamianos, 2012). Further studies showed significant negative relationships between the posttraumatic growth and maladaptive, dysfunctional coping, like substance abuse and behavioral disengagement (Urcuyo et al., 2005; Milam, 2004; Loiselle et al., 2011). In view of the results from these studies, we resolved to use the mental health- and coping-related variables as appropriate criteria in testing the concurrent validity of the PGSI in the final stage of the study. We expected negative associations of the PGSI with depression, anxiety, physical complaints and maladaptive coping strategies. In contrast to this, we hypothesized, that the correlations between the PGSI and different adaptive coping strategies, such as active coping, seeking for social support and regenerative coping would be positive.
Method Participants and Procedure The general purpose of this study was to develop a measuring instrument of posttraumatic growth that, due to its status quo item format (as well as capacity to capture additional growth areas), may be particularly appropriate for using with individuals who experienced several specific kinds of trauma, such as a physical disease or a psychological disorder in a close family member. In addition to this, the questionnaire should be, overall, applicable in studies focusing on beneficial psychological processes in the aftermath of different kinds of serious traumatic experience. Consequently, in the stage of item selection and the initial psychometric screening, we decided to select participants with a broad array of significant psychological traumas. In the second stage, the psychometric properties and the factorial structure of the newly developed inventory were repeatedly tested, especially in samples of individuals with disease-related traumata. In accordance with this procedure, the data collected from sample one were used to complete the item selection, to identify the factorial structure underlying the newly developed Posttraumatic Growth Status Inventory and to screen psychometric properties of the separate PGSI subscales. The first sample consisted of 118 university students and 96 employed adults with different kinds of significant traumatic experience. Several advertisements at the university and an advertisement at a local newspaper provided information about the project. Due to the fact that the whole questionnaire packet was somewhat long and required ca. sixty minutes to fill-out all measures, the participants could pick up the questionnaire at the university and complete it at home. In an attempt to reduce the missing data and to foster the motivation, all participants received ten Euros
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and a brief anonymous feedback concerning their individual test scores in comparison with the norm values of the used measuring instruments (when available) and the mean values from the whole sample. Sample two was recruited in order to test the stability of the initial factorial solution that was identified in sample one, and to provide empirical evidence concerning the validity and the reliability of the newly developed Posttraumatic Growth Status Inventory. As mentioned above, an important aim of the study was to develop a measure of posttraumatic growth that should be suitable to capture growth processes in individuals whose trauma relates to their close relatives’ highly stressful experience, such as a mental or a physical disability in their families. Consequently, the second sample should include individuals with this kind of trauma. To recruit the eligible participants, we contacted professionally moderated self-help groups for parents of children with different kinds of disabilities as well as several doctors’ offices. One hundred eighty-one parents of children with mental or physical disabilities and 45 adult persons whose trauma related to their own severe medical conditions gave their consent to participate in the study and completed the questionnaires. The corresponding return rate resulted in 92%. To foster commitment, similar to sample one, the participants received anonymous detailed feedback regarding their individual test scores in comparison with the mean values from their reference group as well as the information about the main results of the whole study, after completion of the investigation.
Measures Demographics and Information about Traumatic Events All participants responded to several questions concerning demographic information. As preview research demonstrated the role of emotional support as an important predictor on posttraumatic growth and, generally, positive psychological adjustment (Barskova & Oesterreich, 2009; Taylor & Stanton, 2007), the respondents were also asked to which extent they have the possibility to talk with a supportive person about their problems in a confidential way, if necessary. In addition, participants of sample one (mixed sample of university students and employed adults with different kinds of traumatic experience) were asked to provide information about the traumatic life event they had experienced within the past five years, including the nature of the event and the time elapsed since the event. Participants of the sample two (whose trauma was related to either their own severe medical condition or to their child mental or physical disability) were asked about the time elapsed since the diagnosis and the extent to which the awareness of the diagnosis was upsetting for them, with scores ranging from 0 (hardly upsetting) to 3 (completely upsetting). Coping To assess what coping strategies participants preferred in dealing with stressful events in their lives, we used the Brief COPE questionnaire (Carver, 1997). The Brief COPE includes 14 subscales: active coping, planning, positive reframing, acceptance, use of humor, turning to religion, using emotional support, using instrumental support, self-distraction, denial, venting, substance use, behavioral disengagement, and self-blame. Response options ranged from 0 (I don’t do this at all) to 3 (I do this a lot). Previous research has demonstrated the internal
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reliability and convergent validity of the Brief COPE subscales (Carver, 1997; Muller & Spitz, 2003). Several subscales of the questionnaire may be classified as adaptive, functional coping behavior (e.g., active coping, planning, and using emotional support), the others capture rather maladaptive, dysfunctional co-ping (e.g., substance use, behavior disengagement, and selfblame). In order to estimate the degree to which participants use regenerative coping that is not captured by the Brief COPE, we composed a short scale consisting of 4 items (e.g., “I learn specific relaxation techniques”). The internal consistency of this additional short scale was acceptable (Cronbach’s alpha of .71 in sample one and Cronbach’s alpha of .73 in sample two). Health Indicators The Impact of Event Scale-Revised (IES-R; Weiss & Marmar, 1997) was applied to capture the degree of the posttraumatic stress disorder symptoms (PTSD) in the aftermath of traumatic events. The IES-R is a 22-item scale assessing intrusive thoughts, avoidance, and hyperarousal symptoms consistent with PTSD. Participants were asked to focus on the time immediately after their traumatic experience and then indicate how much they were distressed or bothered during this time by each “difficulty” listed. Items were rated for frequency of occurrence on a 5-point scale ranging from 0 (“not at all”) to 4 (“extremely”). The convergent validity of the IES-R was examined in previous studies by assessing the correlations between the IES-R and the PTSD checklist and could be classified as “high” (Creamer, Bell, & Failla, 2003). Somatization, depression and anxiety subscales from the Brief Symptom Inventory (BSI, Derogatis, 1993) were used to assess recent mental health status. The somatization subscale captures psychological distress resulting from the perception of body dysfunction (e.g., cardiovascular, gastrointestinal, and respiratory). The depression subscale addresses symptoms of clinical depressive syndrome, such as withdrawal of interest in life activities, dysphoric affect, and loss of energy. Typical anxiety symptoms measured with the anxiety subscale are nervousness, restlessness, and tension. Previous studies have revealed satisfactory internal reliability of above .70 and the good convergent validity for the separate BSI subscales (Derogatis & Melisaratos, 1983; Derogatis, 1993). Concordant to the results from the previous research, the internal reliabilities of the BSI subscales reached in our study (in the sample two) adequate values of .84, .86, and .83 for anxiety, depression, and somatization subscales, respectively. To receive additional information concerning participants’ somatic complaints, we applied the Freiburg Complaint List (the FBL-R, Batra, Slifkin, & Fahrenberg, 1995). The FBL-R is a self-report standardized questionnaire that lists different general as well as specific physical complaints including tiredness, pain, sensory, cardiovascular, and gastrointestinal symptoms. The respondents were asked how often they experience each of the different somatic complaints mentioned in the questionnaire. The total score of the FBL-R was used in our study as an indicator of the self-reported physical well-being. Prior research provided empirical evidence for the concurrent validity of the Freiburg Complaint List. In a representative sample of adults, highly significant correlations were found between FBL-R scores and indicators of illness, health concern, and utilization of health services (Fahrenberg, 1995).
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Posttraumatic Growth Participants of sample one responded to the initially 48 items which should constitute the newly developed Posttraumatic Growth Status Inventory. Some of the items were adapted from existing scales, and others were generated from the relevant empirical and theoretical literature and from the interviews with individuals facing various traumatic events (for authors’ quailtative research and literature review see Barskova & Oesterreich, 2009; Schirmer & Alexander, 2013). A substantial part of the persons (n = 45) who were interviewed in the stage of the item generation, were individuals with a traumatic experience related to severe physical conditions or psychological disabilities of their close relative (a child or a spouse living in the same home). Each item from the initial item pool was rated using a 7-point Likert scale, ranging from 1 (does not apply) to 7 (completely applies). Items addressed the following nine potential growth domains: appreciation for life (e.g., “Every day is special to me”), relationships to others (e.g., “I know I can depend on others in difficult times”), new possibilities (e.g., “I know from experience that difficult and fearful events can bring about various unexpected possibilities”), personal strength (e.g., “I can handle difficulties well”), spirituality (e.g., “I have a pronounced religious or spiritual faith”), openness (e.g., “I enjoy listening to others opinions even when they contradict what my convictions are”), treating others (e.g., “I enjoy sharing my experiences to help others to find a solution to their problems”), sustainability (e.g. “Sometimes, I reflect how my life would be after the next five years”), and world view (e.g., “I am interested in other cultures”). In the second sample, respondents completed the final form of the newly developed PGSI that contained 36 items. Participants of both samples also completed the Posttraumatic Growth Inventory (PTGI, Tedeschi, & Calhoun, 1996). The PTGI is a 21-item questionnaire that measures the degree of the positive changes experienced in the aftermath of a traumatic event. The PTGI contains five subscales. The internal consistency for the total score and separate subscales of the PTGI has been reported as satisfactory (Cronbach’s Alpha coefficient for the total score = .90; Relating to others = .85; Personal Strength = .72; New Possibilities = .84; Spiritual Change = .85; and Appreciation of Life = .67). Further, women were found to receive higher scores than men (Tedeschi & Calhoun, 1996).
Data Analyses Data analyses procedure included seven major stages. First, the exploratory factor analysis (EFA) was conducted among the data of sample one. All 48 items from the original pool were entered into the exploratory factor analysis. The purpose of this phase was to specify a statistically and meaningfully viable model of the factor structure underlying the newly developed questionnaire and to identify items with inappropriate item parameters that should be eliminated. At stage two, in light of the results of the exploratory factor analysis, item selection took place, followed by the labeling of the factors and specification of subscales’ composition in phase 3. During stage four, we completed a brief preliminary assessment of the PGSI subscales internal consistency and estimated their correlations with corresponding subscales of the retrospective posttraumatic growth measure from Tedeschi and Calhoun (1996) as measures for criterion validity. After this, the correlations between the PGSI sub-
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scales and post-event symptoms of posttraumatic stress disorder, such as avoidance, intrusions and hyperarousal, were calculated. In terms of concurrent validity, we expected that the PGSI subscales would be positively associated with symptoms of posttraumatic stress disorder experienced immediately in the aftermath of a traumatic event. At stage 5, using the data of the sample two, we conducted the Confirmatory Factor Analysis (CFA) upon the remaining thirty-six items to examine the construct validity and the stability of the factorial solution. Further, we tested the criterion and concurred validity as well as the Cronbach’s Alpha reliability of the finally 36-item version of the Posttraumatic Growth Status Inventory (stage 6 and stage 7) in sample two. Similarly to the procedure in sample one, the criterion validity was estimated by analyzing the correlations between the newly developed PGSI subscales and the “classical” measure of posttraumatic growth from Tedeschi and Calhoun (1996). The concurrent validity was assessed in this final stage by calculating the correlations between the PGSI subscales and psychological health indicators as well as corresponding correlations between the PGSI and several measures of coping behavior. As it is recommended in the guidelines on estimating the validity of the measures comprising of the multiple subscales (APA, 1999; Crocker & Algina, 1986), we used several kinds of potentially associated variables in order to provide a possible differentiated picture of concurrent validity for each separate subscale. By reason that the validity estimation procedure of this kind bears a predominantly descriptive character, we refrained from the application of the alpha error corrections, as it is common in the initial testing of the psychometric properties of the newly developed measuring instruments with a multi-factorial structure (APA, 1999; Crocker & Algina, 1986). Confirmatory Factor Analysis An import part of this study was the application of the confirmatory factor analysis (CFA) in sample 2 to examine construct validity and stability of the factorial solution of the PGSI. In contrast to the EFA, the aim of which is simply to identify the factor structure underlying the set of variables, the goal of the CFA is to test a hypothesized factor structure or statistical model and to assess its fit to the data. The estimation of model fit was based on multiple criteria that reflected statistical and practical considerations. The reported goodness-of-fit statistics include chi-square value, the normed chi-square (chi square/df), as well as the Goodness of Fit Index (GFI) and the Root Mean Square Error of Approximation (RMSEA). The statistically significant chi square indicates that a significant proportion of variance in the data remains unexplained by the model; however a statistically significant chi-square can often be produced as an artifact of sample size and small variations in the data (Hu & Bentler, 1995). The normed chi-square (chi square/df) should fall within the levels of 1.0 to 3.0 for acceptable fit (Carmines & McIver, 1981). The RMSEA expresses the lack of fit due to reliability and also model (mis)specification. RMSEA should be smaller than .08 for acceptable fit, values ranging from .08 to .10 indicate mediocre fit, and those greater than .10 indicate poor fit (Byrne, 2001; MacCallum, Browne, & Sugawara, 1996). The GFI is the Goodness of Fit Index. The GFI can be classified as absolute index of fit because it basically compares the hypothesized model (i.e., factorial structure) with no model at all. The GFI varies from 0 to 1, but theoretically can yield meaningless
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negative values. By convention, GFI should by equal to or greater than .90 to accept the model (Jöreskog & Sörbom, 1984; Loehlin, 2004). By this criterion the present model is accepted.
Results Step 1: Item Selection and Preliminary Assessment of Validity and Reliability of the Newly Developed Subscales Based on the Data from the Sample One The Descriptive Characteristics of Sample One As reported above, sample one consisted of 118 undergraduate students who experienced a highly stressful event during the past five years as well as 96 employed adults who also stated that they were traumatized by a personally significant event within the same 5-years period of time. The average age in this sample was 32 years; sixty-five percent of the respondents were women (n = 140) and thirty-five percent were men (n = 74). The events the study participants had experienced were categorized as follows: a) bereavement (25%); b) serious disease of close relatives (19%); c) severe enduring interpersonal conflicts with one significant person (14%); d) completely change of the familiar surroundings (12%); e) personal illness or accident (6%); f) grave work-related or academic problems (6%); g) social abuse (by a group of people) (4%); h) a victim of violence (4%); i) injury-producing accidents in immediate family (3%); j) pregnancy-related problems (2%); k) witness of violence (1%); l) bankruptcy (1%); m) tsunami (.5%); n) other (2.5%). On the average, participants’ most stressful event occurred 35.78 months (SD = 21.05), i.e., approximately three years prior to data collection. Item Selection Based on Results of the Exploratory Factor Analysis All 48 items from the original pool were entered into an exploratory factor analysis using principal components extraction and oblique rotation. The oblique rotation was chosen by reason that, corresponding with previous research (Tedeschi & Calhoun, 1996; Maercker & Langner, 2001), the different domains of posttraumatic growth were expected to be correlated. The factor solution was determined by the number of factors generated with eigenvalues greater than 1, as well as by theoretical considerations. Because the factor solutions for students and non-students were virtually identical, data from the sub-samples of participated students and employed adults with traumatic experience were combined. Eight factors had an eigenvalue greater than one. Examination of the pattern of factor loadings revealed 8 items that had factor loadings less than .30. These items were dropped. The remaining forty items were subjected to another exploratory factor analysis. Results of this second factor analysis were principally the same as the original factorial solution. Each item loaded highest on its respective factor and had relatively low loadings (<.30) on all other factors. Corresponding to the content of the items which constituted the separate factors, the factors were labeled as following: relationships to others, personal strength, new possibilities, spirituality/religiosity, openness, generativity, appreciation for life, and sustainability. Eight subscales with the similar labels as those of the separate factors were composed based on the results from the factor analysis. As a next analysis step, the Pearson inter-correlations between the separate subscales were calculated. Somewhat sur-
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prisingly, the sustainability subscale showed very low correlations with other subscales of the questionnaire, a part of which was even non-significant negative, indicating that sustainability does not constitute a facet of posttraumatic growth. Consequently, the four items of this subscale were also eliminated. For the remaining seven inventory subscales (Table 1), positive statistically significant inter-correlations were demonstrated (Table 2). Preliminary Assessment of the Psychometric Properties of the PGSI The thirty-six items of the resulting Posttraumatic Growth Status Inventory (PGSI) are listed in Table 1, along with the scale names. Response options of the items are “does not apply”, “hardly applies”, “somewhat applies”, “partially applies”, “applies”, “more applies”, and “completely applies”. The short definitions of the seven subscales are as follows. The relationships to others subscale refers to warm, trustfully relationships to other people, the generativity subscale reflects pleasure in supporting others and in sharing one’s own knowledge and helpful life experience, the appreciation of life area links to
active lifestyle and the attempt to live each day to the fullest, and the openness area relies to open-mindedness, philosophic or scientific interests. Finally, three further subscales capture sense of personal strength, appreciation for religious/spiritual things, and recognition of new possibilities for one’s life, respectively. Cronbach’s alpha coefficients of the total PGSI score and its separate subscales exceeded in sample one the recommended criterion of .70 for acceptable instrument internal reliability (Nunnaly & Bernstein, 1994). The Cronbach’s alpha of the total PGSI score reached a value of .92, indicating a high degree of internal reliability. The known-groups validity of the PGSI was estimated via dichotomizing the variable “IES values” by a median split and comparing the PGSI subscales means of persons whose reported IES values in the first weeks after a critical event were high with those of persons with low IES values. In accordance to the expectations, the PGSI values of individuals with a high level of PTSD symptoms following a stressful event were higher than the posttraumatic growth scores of persons who did not suffer from pronounced stress disorder symptoms, with the exception of the subscale “personal strength”. T-tests for independent
Table 1. The composition of the PGSI subscales. Subscale
Items
Area: Relationships to Others
r1. I make no secret about my feelings. (1) r2. I accept the fact that I need others. (6) r3. I have sympathy for others. (13) r4. I invest a lot in my relationships. (17) r5. I know I can depend on others in difficult times. (24) r6. I know a lot about how good people can be. (29)
Area: Generativity
g1. I enjoy teaching someone something new. (2) g2. I enjoy sharing my experiences to help others to find a solution to their problems. (8) g3. I can identify with others feelings. (11) g4. Occasionally I help others with conflict of interests to arrive at a satisfactory solution. (25) g5. If I have the chance, I help others by offering ways for improvement and positive criticism. (33)
Area: Personal Strengths
p1. I am inclined to change the things that need to be changed. (3) p2. I can handle difficulties well. (5) p3. I have a strong sense of self-confidence. (9) p4. I am strong enough to master unseen and unusual problems. (22)
Area: Appreciation of Life
a1. Every day is special to me. (4) a2. Life is interesting and colorful for me. (12) a3. I have more distinct ideas about what is important in life now than a couple of years ago. (19) a4. I do a lot with my life. (35)
Area: Spirituality/Religiosity
s1. I have an appreciation for religious things. (15) s2. I have an appreciation for spiritual things. (18) s3. I have thought a lot about religions and religious topics. (26) s4. I have a pronounced religious or spiritual faith. (32)
Area: New Possibilities
n1. My lifestyle is changing and developing. (7) n2. I have gained new interests for sometime now. (10) n3. Sometimes I accomplish something that others find important and extraordinary. (14) n4. I know from experience that difficult and fearful events can bring about various unexpected possibilities. (27) n5. I have been walking on a different path in my life for sometime now. (30) n6. New opportunities are available to me that I did not even notice a couple of years ago. (36)
Area: Openness
o1. I enjoy discussing topics which concern the development of society. (16) o2. I have a feeling of unity with nature. (20) o3. I enjoy listening to others opinions even when they contradict what my convictions are. (21) o4. I have thought a lot about the meaning of life. (23) o5. I enjoy reading philosophic or scientific literature. (28) o6. I have understanding for people whose lifestyles are completely different than mine. (31) o7. I am interested in other cultures. (34)
Note: The numbers in brackets correspond to the item numbers in the final version of the whole inventory.
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Table 2. Intercorrelations between the PGSI subscales in sample one (N = 214). Relationships to Others Generativity
.578
Generativity
Personal Strength
Spirituality/Religiosity
Openness
Personal Strength
.346**
.373**
Spirituality/Religiosity
.278**
.192**
.107*
Openness
.490**
.444**
.316**
.462**
**
**
**
.268**
.486**
.398**
.337**
.497**
Appreciation of Life New Possibilities
.626
Appreciation of Life
**
.396**
.429
.367**
.603
.646**
Note: *p < .05; **p < .01.
samples showed that these differences were significant for the PGSI total score (t = 1.90; p < .05) as well as the following subscales: relationships to others (t = 1.75; p < .05), generativity (t = 1.93; p < .05), openness (t = 3.01; p < .01), and new possibilities (t = 1.74; p < .05). Table 3 contains more detailed information concerning the size of bivariate correlations between three main kinds of PTSD symptoms (intrusions, avoidance and hyperarousal) and different PGSI subscales. The total score of PGSI was significant positively related to intrusion and hyperarousal symptoms, experienced during the first weeks after a traumatic event, however, neither PGSI total score nor any of the PGSI subscales were statistically significant associated with avoidance symptoms. Further, Pearson correlations between the PGSI subscales and the corresponding subscales from the retrospective growth measuring instrument of Tedeschi and Calhoun (1996) were computed as estimates of criterion validity. For generativity and openness PGSI areas, the total score of the PTGI measure from Tedeschi and Calhoun was used as criterion value. All correlation coefficients were highly statistically significant, they ranged from r = .35 (for generativity subscale) to r = .78 (for religiosity/spirituality subscale), indicating sufficient criterion validity. The results are summarized in Table 4.
Step 2: Estimating Stability of the Factorial Solution and Assessing the Psychometric Properties of the PGSI Based on the Data from Sample Two Descriptive Characteristics of Sample Two A second sample of individuals with traumatic experience was recruited with the aim to evaluate the psychometric properties of the newly developed Posttraumatic Growth Status Inventory in groups of individuals whose trauma related to enduring stress conditions. This sample consisted of two subgroups. The first subgroup included 110 parents of children with serious mental disabilities (Down syndrome; n = 56, autism or Asperger syndrome; n = 54) as well as 71 parents of visually handicapped children. Thirty-four percent of all children had other comorbid physical disabilities, such as congenital heart defects, epilepsy, cerebral palsy, sensory problems, and others. The second subgroup of sample two included n = 45 individuals whose traumatic experience was related to their own severe medical condition. The parents were on the average forty-one years old, the majority was well-educated (13.58 years of formal education, on the average) and 142 (78%) were married. Seventy-five percent were mothers and twenty-five percent were fathers. Seven years
passed on the average since the child’s diagnosis. The mean age of the children was ten years. The individuals with a disease-related trauma (n = 45) were on the average thirty-nine years, with the mean of formal education of 13.72 years. Seventy-nine percent were men. Similarly to the sub-sample of parents, the diagnosis dated back approximately 7 years. The most frequently documented illnesses in this subgroup were HIV, cardiac diseases and cancer. In the entire sample, the majority of participants (78%) characterized the first awareness of the diagnosis as a “definitely upsetting” event. The explorative analyses of relationships between the PGSI and respondents’ demographic characteristics yielded a weak statistically significant correlation between PGSI total score and gender (r = .16), indicating that women’s values were slightly higher than those of the men. Table 5 demonstrates the means for PGSI subscales depending on the kind of the traumatic event. Confirmatory Factor Analysis and Estimation of Reliability In order to estimate the stability of the factorial solution gained based on the exploratory factor analysis upon the data from sample one, we conducted the confirmatory factor analysis (CFA) in the second mixed sample of individuals with traumatic experience using maximum likelihood method. On the whole, the initial seven-factorial model demonstrated a reasonably good fit to the data: the RMSEA = .078; chi square = 1385 (df = 584; p = .00); chi square /df = 2.37; GFI = .965. Figure 1 shows the results the CFA including the factor loadings of the separate items and the subscales composition. Cronbach’s alpha coefficients are displayed in Table 5. Internal consistency reliabilities were sufficiently high and, similarly to the analogous estimations in sample one, the recommended criterion of .70 for acceptable instrument internal reliability (Nunnaly & Bernstein, 1994) was exceeded for all PGSI subscales. The Cronbach’s alpha reliability of the total PGSI score was with .93 very high. Analysis of Criterion Validity, Correlations between PGSI and Indicators of Mental Health In order to examine the criterion validity of the PGSI-subscales, we calculated the correlations with corresponding subscales of the “classical” measure of trauma-related changes from Tedeschi and Calhoon (1996). The external validity criterion for the generativity and openness domains was the total score of the Tedeschi and Calhoon’s questionnaire. The results (Table 4) provide good support for criterion validity (r = .32 for life apprecia-
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Table 3. Correlations between PGSI subscales and PTSD symptoms in sample one (N = 214). Relationships to Others IES Intrusions
.12
*
Generativity .13
*
Personal Strength
Spirituality/ Religiosity
−.08
.08
Openness .25
**
Appreciation of Life
New Possibilities
PGSI Total
.01
.10
.14*
IES Avoidance
.06
.09
−.04
.02
.04
.08
.07
.07
IES Hyperarousal
.07
.05
−.20**
.23**
.22**
−.03
.10
.11*
IES Total
.11*
.11*
−.15*
.14*
.22**
.03
.12*
.14*
Note: In sample one (N = 214) Cronbach’s alpha coefficients of the three IES subscales reached values of .80, .72, and .80, of the IES total the value of .85. *p < .05; **p < .01.
Table 4. Criterion validities of the PGSI subscales in sample one (N = 214) and sample two (N = 226). Relationships to Others
Generativity
Personal Strength
Spirituality/ Religiosity
Openness
Appreciation of Life
New Possibilities
PGSI Total
Sample One
.58**
.35**
.47**
.78**
.41**
.60**
.66**
.67**
Sample Two
.63**
.37**
.40**
.74**
.40**
.32**
.58**
.59**
Note: The coefficients represent Pearson correlations between PGSI subscales and corresponding subscales of PTGI from Tedeschi and Calhoun (1996). For generativity and openness subscales, the correlations with the total score of the PTGI were calculated.
Table 5. The means and standard deviations for PGSI subscales and PGSI total in both sub-samples of sample two, and Cronbach’s alpha reliabilities of the PGSI subscales. Relationships Generativity Personal Spirituality/ Openness M Appreciation New Possibilities to Others M (SD) M (SD) Strength M (SD) Religiosity M (SD) (SD) of Life M (SD) M (SD)
PGSI Total M (SD)
Parents
28.58 (5.84)
26.56 (4.44)
20.29 (4.07)
15.89 (7.01)
33.67 (6.70)
19.42 (4.32)
27.02 (6.55)
171.42 (28.51)
Disease Related Trauma
28.29 (6.61)
25.30 (5.58)
18.68 (4.80)
14.43 (6.73)
35.10 (7.82)
19.39 (4.64)
27.07 (7.63)
168.28 (32.64)
Total Sample Female Male
28.92 (6.09) 27.21 (6.11)
26.89 (4.36) 24.73 (5.47)
20.23 (4.15) 19.13 (4.71)
15.83 (7.09) 14.88 (6.79)
33.79 (6.72) 33.43 (7.69)
19.64 (4.46) 18.58 (4.33)
27.80 (6.63) 24.97 (6.64)
173.10 (28.93) 162.93 (31.79)
Cronbach’s Alpha
.79
.81
.83
.91
.75
.78
.80
.93
Note: “Parents”: Parents of children with mental or physical disabilities (n = 181). “Disease related trauma”: Individuals with a severe medical condition (n = 45). Cronbach’s alpha coefficients represent the reliabilities of the PGSI subscales in the whole sample two (N = 226).
tion subscale to r = .74 for religiosity/spirituality subscale). To test whether the PGSI-subscales are substantially associated with depression, anxiety and somatization symptoms, we analyzed the Pearson correlations of the PGSI-subscales with the BSI and the FBL. The results are illustrated in Table 6. The PGSI areas were almost without any exemption statistically significant inversely associated with BSI anxiety subscale (r = −.15 to r = −.38). Additionally, all PGSI domains with exemption of the religiosity/spirituality domain were statistically significant inversely related to BSI depression symptoms (r = −.20 to r = −.53). Further, all PGSI areas with exemption of the “new possibilities” subscale showed statistically significant negative correlations with BSI somatization scale (r = −.16 to r = −.30) as well as with psychosomatic symptoms measured with the FBL (r = −.12 to r = −.30). On the whole, these results indicated that a higher level of posttraumatic growth was related to a low level of anxiety, depression and somatization symptomatology. Analysis of Relationships between the PGSI and Frequency of Using Different Adaptive and Maladaptive Coping Strategies In order to test concurrent validity, Pearson correlations be-
tween PGSI subscales and different coping strategies were calculated. As discussed in the literature on stress and coping, one and the same coping strategy may be more or less adaptive, depending on the special kind of the major stressful event and on the individual life situation (Meichenbaum, 1985; Antonowsky, 1987; Connor-Smith & Flachsbart, 2007). Taking into consideration this knowledge from previous research with a long tradition, we decided to accomplish two separate analyses on the relationships between PGSI growth domains and coping strategies, because of the very different nature of traumatic events in both subgroups (parents of children with mental and/or physical disabilities and individuals whose trauma related to their own severe medical conditions). The results from the corresponding analyses are presented in Table 7. Correlations between PGSI and Coping Strategies in the Parents Sub-Sample In the sub-sample of 181 parents of children with mental and/ or physical disabilities, the data analyses yielded the following empirical results. Both, the relationships to others and generativity PGSI subscales were positively associated to several potentially adaptive coping strategies, including active coping,
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Figure 1. Confirmatory factor analysis, factorial structure of the PGSI. Table 6. Correlations between PGSI subscales and mental health indicators in sample two (N = 226). Relationships to Others
Generativity
Personal Strength
Spirituality/ Religiosity
Openness
Appreciation of Life
New Possibilities
PGSI Total
BSI Anxiety
−.33**
−.27**
−.35**
−.15*
−.20**
−.38**
−.15*
−.33**
BSI Depression
−.37**
−.32**
−.46**
−.08
−.20**
−.53**
−.27**
−.40**
BSI Somatization
−.30**
−.24**
−.24**
−.17**
−.16**
−.29**
−.11
−.27**
FBL Psychosomatic Complaints
−.29**
−.18**
−.30**
−.12*
−.19**
−.33**
−.10
−.27**
Note: In the sample two (N = 226), Cronbach’s alpha coefficients of the three BSI subscales reached the values of.84, .86, and .87, of the FBL the value of .92. *p < .05; **p < .01.
Planning, positive reframing, turning to religion, as well as using emotional and instrumental support. On the other side, there were statistically significant negative correlations of these PGSI areas with two kinds of dysfunctional coping behavior; substance use and behavioral disengagement. The personal strength subscale showed similar correlations with adaptive and dysfunctional coping strategies.
Beyond this, the personal strength area was significant negatively associated with self-blame (r = −.29) and positively associated with acceptance that ranks among potentially adaptive coping behavior (r = .14). The religiosity/spirituality subscale was not associated with active coping and planning. However, data analyses offered positive associations between religiosity/spirituality PGSI area and other adaptive coping strategies
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Table 7. Correlations between PGSI subscales and frequency of using different coping strategies, in both subgroups of sample two (parents of children with disabilities, n = 181, and persons with a severe medical condition, n = 45). Relationships to Others
Generativity
Personal Strength
Spirituality/ Religiosity
Openness
Appreciation of Life
New Possibilities
PGSI Total
Active Coping
.25** [.29*]
.20** [.12]
.33** [.40**]
.11 [−.21]
.23** [.10]
.39** [.35*]
.33** [.40*]
.34** [.26*]
Planning
.15* [.09]
.23** [.33*]
.17* [.23]
.01 [.10]
.29** [.04]
.15* [.21]
.21** [.04]
.23** [.18]
Positive Reframing
.34** [.39**]
.36** [.39**]
.50** [.53**]
.12 [.28**]
.40** [.42**]
.51** [.55**]
.51** [.42**]
.52** [.56**]
Acceptance
−.03 [.02]
−.08 [.14]
.14* [.07]
.05 [.24]
.16* [.10]
*
*
.07 [.02]
.10 [−.09]
.09 [.09]
**
Humour
−.01 [.00]
.08 [.25]
.06 [.16]
.07 [.38 ]
.16 [.45 ]
.07 [.03]
.09 [.14]
.10 [.32*]
Religion
.16* [.01]
.13* [−.19]
−.01 [−.29*]
.77** [.63**]
.35** [.03]
.15* [.11]
.21** [.23]
.39** [.14]
Using Emotional Support
.53** [.40**]
.35** [.07]
.14* [.18]
.22** [−.08]
.37** [.15]
.24** [.28*]
.37** [.40**]
.44** [.27*]
Using Instrumental Support
.55** [.34*]
.44** [−.03]
.23** [.12]
.18* [−.23]
.38** [.05]
.22** [.15]
.26** [.30*]
.44** [.14]
Denial
−.09 [.12]
−.00 [−.30*]
−.13 [−.38**]
.08 [−.06]
−.05 [−.09]
−.20** [−30*]
−.10 [−.05]
−.08 [−.21]
**
Self-Distraction
−.06 [.00]
−.06 [.05]
−.10 [.13]
−.12 [.02]
−.05 [.17]
−.21 [.13]
−.11 [.09]
−.14* [.11]
Venting
.17* [.00]
−.05 [.00]
−.08 [−.11]
.16* [.03]
.04 [.12]
.13 [−.11]
.22** [.03]
.13* [.01]
Substance Use
−.14* [−.10]
−.21** [−.17]
−.20** [−.29*]
−.05 [.10]
−.08 [.23]
−.15* [−.27*]
−.05 [−.07]
−.15* [−.07]
Behavioural Disengagement
−.21** [−34*]
−.15* [−.36*]
−.23** [−.28*]
.01 [−.09]
−.08 [−.31*]
−.23** [−.44**]
−.11 [−.35*]
−.17* [−.41*]
Self-Blame
−.04 [−.20]
−.01 [−.15]
−.29** [−.35*]
.04 [−.07]
.07 [−.06]
−.27** [−32*]
−.07 [−.05]
−.08 [−.20]
Regenerative Coping
.17* [.37**]
.08 [.39**]
.16* [.27*]
.09 [.08]
.27** [.53**]
.27** [.37**]
.29** [.24]
.26** [.43**]
Availability of a Confident
.44** [.40**]
.30** [.12]
.23** [.32*]
.19** [.06]
.27** [.07]
.37** [.37**]
.27** [.41**]
.40** [.31*]
Note: The coefficients without any brackets represent the Pearson correlations in the sub-sample of parents. The coefficients in square brackets represent the corresponding Pearson correlations in the sub-sample of persons with a disease-related trauma. *p < .05, **p < .01.
(r = .22 for using emotional support and r = .18 for using instrumental support). The correlations between this PGSI subscale and maladaptive coping strategies were not significant. The openness PGSI domain was positive statistically significant related to eight adaptive coping strategies (active coping, planning, positive reframing, acceptance, turning to religion, using emotional and instrumental support, and humour) and it was not related to any kind of dysfunctional coping behavior. The appreciation of life and the new possibilities PGSI subscales showed positive associations with six adaptive coping strategies (active coping, planning, positive reframing, turning to religion, using emotional and instrumental support). In addition, for the appreciation of life area, but not for the new possibilities PGSI area, the negative statistically significant correlations with four maladaptive coping strategies (denial, substance use, behavioral disengagement, and self-blame) were demonstrated. Five of seven growth subscales (relationships to others, personal strength, openness, life appreciation, and new possibilities) as well as the PGSI total score were positively correlated with regenerative coping (r = 16 to r = .29). Finally, the PGSI total score was positive, statistically significant associated to six potentially adaptive coping strategies (active coping, planning, positive reframing, turning to religion, using emotional and instrumental support) and it was significant negatively correlated with two kinds of dysfunctional coping (sub-
stance use and behavioral disengagement). Correlations between PGSI and Coping Strategies in the Sub-Sample of Persons with Their Own Disease-Related Trauma Following correlation patterns between PGSI areas and different kinds of coping behavior were demonstrated in the subsample of 45 persons with a severe medical condition (Table 7). The relationships to others and the new possibilities PGSI subscales were positively associated to the four different potentially adaptive coping strategies (active coping, positive reframing, using emotional and instrumental support). They were also negatively related to behavioral disengagement (r = −.34 and r = −.35); the correlations with other potentially maladaptive coping strategies were not significant. The personal strength and the appreciation of life PGSI areas were positively correlated with active coping and positive reframing, both of these subscales were also negative, statistically significant related to three potentially dysfunctional coping strategies (substance use, behavioral disengagement, and self-blame). The generativity and the openness PGSI domains showed positive, statistically significant correlations with positive reframing. Beyond this, the generativity subscale was positively associated with planning (r = .33), and the openness domain with coping through humorous handing of stressful life situations (r = .45). Both generativity
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and openness subscales were negatively related to behavioral disengagement (r = −.36 and r = −.31). The religiosity/spirituality subscale was positively correlated with three adaptive coping strategies (positive reframing, humour, and turning to religion). However, similarly to findings from the parents sub-sample, it was not associated with any dysfunctional coping strategies. For five PGSI areas (with exemption of religiosity/spirituality and new possibilities subscales, respectively), positive statistically significant correlations with regenerative coping were demonstrated (r = .27 to r = .53). Are There Systematic Differences in Pattern of Correlations between PGSI and Various Coping Strategies across both Groups: Parents of Children with Mental and/or Physical Disabilities vs. Individuals with a Disease-Related Trauma? Data analyses revealed several similarities in patterns of correlations between both subgroups constituting the second sample: parents of children with mental and/or physical disabilities vs. individuals with their own disease-related trauma. Thus, the personal strength and life appreciation subscales were most consistently negative correlated with maladaptive coping strategies in both groups. Alike, the “relationships to other” PGSI subscale showed consistent positive associations with adaptive coping behavior in parents as well as in the outpatients group. Interestingly, statistical analyses offered also several differences in pattern of correlations between both subgroups. Whereas functional coping strategies “planning”, as well as “coping through active seeking emotional and instrumental support” were consistently positive correlated with PGSI factors in the parents sample, they were not statistically significant associated to the most of PGSI factors in the sample of persons with their own disease-related trauma. By contrast, coping through humorous handling of burdensome life situations was more frequently linked to PGSI subscales for the outpatients sample than for the sample of parents. Additionally, denial and behavioral disengagement as maladaptive coping strategies were definitely more strongly related to PGSI subscales in the outpatients group than in parents of children with disabilities. Regarding differences in the relative impact of the separate PGSI domains, the generativity and openness subscales yielded a stable pattern of positive, statistically significant correlations with several kinds of adaptive coping behavior in parents’ sample, but not in the sample of individuals whose traumatic experience was related to their own severe medical condition.
Discussion The aims of the study described in this paper were to develop and to evaluate a measuring instrument that allows for capturing the current status in processes of growth in the aftermath of traumatic experience. Unlike contemporary available retrospective growth questionnaires (the PTGI, the SRGS and the BSI), the new measure was designed to estimate the actual profile of different growth related aspects. Accordingly, when completing the PGSI, respondents do not need to remember their crucial experience and to recall how they were prior to the stressful event; they should simply describe their actual behavior, thinking and feeling. This kind of item format was chosen in order to avoid distortion through potential cognitive biases, documented in previous investigations (McFarland & Alvaro, 2000; Smith & Cook, 2004). Additionally, taking into account findings from recent empirical literature on posttraumatic growth (Cadell &
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Sullivan, 2006; Danoff-Burg & Revenson, 2005; Updegraff et al., 2002; Pakenham, 2007), the initial item pool contained items asking for self-awareness, world view and the way of treating others, beside the items focused on already well-known growth areas (such as relationships to others, personal strength, and appreciation of life) as they are addressed in the currently most established retrospective measure of PTG from Tedeschi and Calhoun (1996). The findings provide evidence of sound reliability, as well as good convergent and concurrent validity of the Posttraumatic Growth Status Inventory subscales. The results of the confirmatory factor analysis yielded support for stability of the initial factorial solution. Interestingly, five extracted factors, e.g. personal strength and appreciation of life, correspond to the growth facets which were identified in factor analyses upon growth related items in other studies (e.g., Tedeschi & Calhoun, 1996). This attests to the soundness and satisfying validity of the construct ‘posttraumatic growth’. The PGSI contains seven subscales and permits the capturing of personal changes in the following growth domains: relationships to others, spirituality/religiosity, appreciation of life, generativity, openness, personal strength, and new possibilities. In comparison to the “classical” retrospective posttraumatic growth measure from Tedeschi and Calhoun (1996), the PGSI assesses growth associated processes in two additional areas, generativity and openness. The 7-stage item response format permits a precise differentiation between various degrees in the distinct growth related characteristics. Comparison of mean PGSI scores showed significant differences between participants who suffered from less or more symptoms of posttraumatic stress disorder in the first time after a traumatic event. Thereby, the known-groups validity of the newly developed questionnaire could be demonstrated. Further, the acceptability of the PGSI is demonstrated by minimal missing data (2.7% in sample one and 2.4% in sample two). On the whole, the study provides empirical evidence for good psychometric properties and practicability of the newly developed growth status inventory. A particular strength of the PGSI is its applicability in samples of individuals whose trauma evolved from the confrontation with suffering of others, for example, parents of children with psychological and physical disabilities, persons who witnessed violence, and, generally, care-givers and close relatives of people with life-threatening illnesses. As shown in other studies, (e.g., Alexander & Wilz, 2010), feelings of guilt may account for barriers to acknowledge beneficial trauma-related changes in these populations. In the stage of the item generation, those participants of our study, whose traumatic experience related to their family members (child’s, spouse’s, or parent’s) severe health conditions or disabilities, reported in individual semi-structured interviews about the comparable difficulties to reflect on possible beneficial trauma-related change due to moral considerations. A measuring instrument, like the PGSI, that focuses solely on current experience, without any connection to past live events, can help to sidestep the corresponding barriers and to attenuate the tendency to distortions due to social desirability. This reduction of corresponding distortions may partially explain the fact, that the internal consistencies of the PGSI subscales were higher in our study than the internal consistencies of comparable subscales of the retrospective-oriented PTGI questionnaire (e.g., in sample two, .83 vs. .73 for the subscale “personal strength” and .78 vs. .72 for the subscale “life appreciation”). Altogether, the results of our study imply that the
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validity of individual reports on growth related processes could be increased by the means of using item format which focuses on the actual experience and not on perceived inner changes. Additionally, the newly developed measure may be very useful for capturing positive personal changes in samples of individuals whose trauma relates in a particular degree to experience of stigmatization, like potentially stigmatizing diseases (e.g., mental disorders, HIV) as well as social or sexual abuse. As documented in empirical literature, the proceeding of the stigma-associated feelings of “spoiled identity” (Goffman, 1986) often lead to inducing the re-examination of old values and priorities and to efforts of creating a new definition of self identity. The active establishment of an alternative identity as a positive adjustment instead of a resignation requires openness to a new experience and enhanced tolerance towards other ways of life and other ways of communication. Since the PGSI contains a separate openness subscale which addresses this special component of positive individual psychological changes, this inventory may be more appropriate in capturing the corresponding processes than the conventional posttraumatic growth and benefit finding measuring instruments. Although a part of our study’s participants were individuals who experienced traumas with such stigmatization potential, further research is required to provide additional evidence concerning the applicability of the PGSI in these specific populations. Another area of application for the PGSI may be longitudinal studies designed to investigate different stages in processes of posttraumatic growth in persons with enduring stress conditions subsequent to an acute traumatic event, such as a case of severe disability-related health problems in a person her/himself or in a close family member. Two groups of persons with analogous kinds of traumatic experience were participants of our study: parents of children with psychological and physical disabilities as well as individuals whose trauma related to their own severe medical conditions. In both samples, good psychometric properties of the PGSI were demonstrated. Additionally, the data analyses offered the ability of the PGSI to differentiate between individuals with dissimilar kinds of traumatic experience. The pattern of correlations between the separate PGSI subscales and various potentially adaptive and maladaptive coping strategies were partially different in parents and outpatients samples. Thus, “coping though active seeking instrumental or emotional support” and “planning” were more consequently related to the separate growth domains in the parents sample than in the sample of individuals with an illness-related trauma. It may point to important differences in potential adaptive significance of coping behavior. For parents caring for children with mental disabilities, positive personal changes in terms of growth may involve acquirement of such essential skills as mobilization of their social networks for help in caring the child and for informational support. The efforts to mobilize the social environment would be inevitably related to the necessity to overcome feelings of shame due to the ‘particular kind’ of the child’s disability and to accept the new after-child-diagnosis life situation. To undergo this experience could require personal strength and individual development in terms of personal growth. Attention-grabbing is also another systematic dissimilarity, and precisely in use of denial as a coping strategy that was more consistently negatively linked to PTG areas in the outpatients’ sample than in the parents’ sample. What may imply denial for persons raising children with autism or Down syndrome? It could basically imply the recognizing the feeling that “my child
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is o.k.”. In fact, this kind of perception neither necessarily leads to dysfunctional behavior, nor it should be an indication of resistance to the processes of trauma-related growth. Conversely, if persons with a severe disease respond with denial to their diagnosis or to their physical symptoms, it may be frequently linked to a lack of compliance with medical treatment as well as to the insistence on several old maladaptive unhealthy habits as a phenomenon that is opposite to personal changes in terms of stress-related growth.
Limitations and Considerations Despite generally promising study results, several limitations should also be kept in consideration concerning the findings reported above. First, a mixed sample of undergraduate students and adults with significant traumatic experience were used at the stage of item selection. It might stand to reason to query whether the students can be representative for the population of traumatized individuals. However, it is not unusual, to use the students samples at the initial phase in the development of psychological measuring instruments (Stanton et al, 2000; Tedeschi & Calhoun, 1996). Furthermore, students are comparable to the general population pertaining to experience with trauma (Vrana & Lauterbach, 1994). Second, a cross-sectional study design was used to evaluate the psychometric properties of the PGSI. A cross-sectional investigation does not permit any unambiguous conclusions in terms of causality. Consequently, the direction of relationships between separate PGSI areas and indicators of mental health, such as anxiety, depression and psychosomatic symptoms as well as between PGSI and different coping strategies remained unclear. Future longitudinal studies with repeated measurements are warranted to test corresponding causation hypotheses. Additional longitudinal studies may also be necessary to provide more information about the alterability of the PGSI values across various periods of time. A further limitation relates to the issue of the potential unambiguousness of the construct “posttraumatic growth” in terms, as it could be captured by the newly developed questionnaire. How can we be sure that the PGSI items assess the posttraumatic growth processes as a result of an individual’s traumatic experience, given the fact that the participants are asked to describe their behavior, thinking and feelings, without the explicit reference to the traumatic event? Indeed, it is a general difficulty with the operationalisation of complex psychological constructs that we can seldom be fully confident of definite sources/triggers for the multifaceted psychological processes, like intrapersonal growth. A number of common cognitive biases, such as illusory correlation, subjective validation, social desirability bias, or backfire effect (Tversky & Kahnemann, 1974; Fiedler, 1991; Danton & Ortegren, 2011; Sanna, Schwarz, & Stocker, 2002), may contribute to misattribution, if the respondents were explicitly asked about perceived causes of their inner changes. The PGSI refrains from asking about subjective attribution of reported inner growth processes to a concrete severe traumatic experience. However, there is other, implicit evidence of potential relationships. Firstly, the PGSI focuses on seven areas, which are well-documented in empirical and theoretical literature as domains of posttraumatic growth. Accordingly, high statistically significant correlations between the separate PGSI subscales and the corresponding PTGI growth
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areas were demonstrated in our data analyses. Secondly, the PGSI is designed to be applied in studies with individuals who experienced verifiable psychological traumas, like a physical or mental disability in their close relatives, their own severe medical conditions or other kinds of trauma. Thirdly, the comparison of the PGSI scores from different measuring times, as well as from the interventional and the control groups, should provide additional evidence about links between trauma-related experiences and corresponding changes in the processes of intra-psychical growth. Due to a specific item format focusing on current state, the PGSI offers the potential to capture slight positive as well as inverse-directed alterations in processes of posttraumatic growth with a higher precision than the alternative existing “retrospective” growth scales. However, this particular feature of the newly developed inventory should be examined in more detail in further investigations. To summarize, the study provides empirical evidence for good psychometric properties and practicability of the newly developed Posttraumatic Growth Status Inventory. The PGSI is recommended particularly for use in longitudinal studies as well as in samples of persons whose trauma relates to a severe psychological or physical disability in their families.
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of coping strategies, social support, and attachment style with posttraumatic growth in cancer survivors. Journal of Health Psychology, 17, 1033-40. Siegel, K., & Schrimshaw, E. W. (2000). Perceiving benefits in adversity: Stress-related growth in women living with HIV/AIDS. Social Science and Medicine, 51, 1543-1554. Siegel, K., & Schrimshaw, E. W. (2007). The stress moderating role of benefit finding on psychological distress and well-being among women living with HIV/AIDS. AIDS Behaviour, 11, 421-433. Smith, S. G., & Cook, S. L. (2004). Are reports of posttraumatic growth positively biased? Journal of Traumatic Stress, 17, 353-358. Stanton, A. L., Kirk, S. B., Cameron, C. L., & Danoff-Burg, S. (2000). Coping through emotional approach: Scale construction and validation. Journal of Personality and Social Psychology, 78, 1150-1169. Taku, K., Cann, A., Calhoun, L. G., & Tedeschi, R. G. (2008). The factor structure of the Posttraumatic Growth Inventory: A comparison of five models using confirmatory factor analysis. Journal of Traumatic Stress, 21, 158-164. Taylor, S. E., & Stanton, A. L. (2007). Coping resources, coping processes, and mental health. Annual Review of Clinical Psychology, 3, 377-401. Tedeschi, R. G., & Calhoun, L. G. (2004). Posttraumatic growth: Conceptual foundations and empirical evidence. Psychological Inquiry, 15, 1-18. Tedeschi, R. G., & Calhoun, L. G. (1996). The Posttraumatic Growth Inventory: Measuring the positive legacy of trauma. Journal of Traumatic Stress, 9, 455-471. Tedeschi, R. G., & Calhoun, L. G. (2006). The foundations of posttraumatic growth: An expanded framework. In: L. G. Calhoun, & R. G. Tedeschi (Eds.), Handbook of posttraumatic growth: Research and practice (pp. 3-23). Mahwah, NJ: Erlbaum. Tomich, P. L., & Helgeson, V. S. (2004). Is finding something good in the bad always good? Benefit finding among women with breast cancer. Health Psychology, 23, 16-23. Tversky, A. & Kahneman, D. (1974). Judgment under uncertainty: Heuristics and biases. Science, 185, 1124-1131. Updegraff, J. A., Taylor, S. E., Kemeny, M. E., & Wyatt, G. E. (2002). Positive and negative effects of HIV infection in women with low socioeconomic resources. Personality and Social Psychology Bulletin, 28, 382-394. Urcuyo, K. R., Boyers, A. E., Carver, C. S., & Antoni, M. H. (2005). Finding benefit in breast cancer: Relations with personality, coping, and concurrent well-being. Psychology and Health, 20, 175-192. Vrana, S., & Lauterbach, D. (1994). Prevalence of traumatic events and posttraumatic psychological symptoms in a nonclinical sample of college students. Journal of Traumatic Stress, 7, 289-302. Weaver, K. E., Llabre, M. M., Lechner, S. C., Penedo, F., & Antoni, M. H. (2008). Comparing unidimensional and multidimensional models of benefit finding in breast and prostate cancer. Quality of Life Research, 17, 771-781. Weiss, D. S., & Marmar, C. R. (1997). The impact of event scale— Revised. In J. Wilson, & T. M. Keane (Eds.), Assessing psychological trauma and PTSD (pp. 399-411). New York: Guilford.
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26 Interpersonal Dependency Inventory: Its Construct Validity and Prediction of Dysphoric Mood and Life Functioning via Negative Life Events 1
Masayo Uji1*, Yukihiro Takagishi2, Keiichiro Adachi3, Toshinori Kitamura4 Department of Bioethics, Kumamoto University Graduate School of Life Sciences, Kumamoto, Japan 2 Department of Human Psychology, Kansai University of International Studies, Miki, Japan 3 Department of Psychology, Kobe Shoin Women’s University, Kobe, Japan 4 Kitamura Mental Health Institute Tokyo, Akasaka, Japan
Previous Dependency Inventory (JIDI) as well demonstrates how the interpersonal attitudes assessed by the JIDI generate interpersonal negative life events (NLEs) and therefore results in dysphoric moods and poor life functioning. The subjects of this study were 467 Japanese university students. The JIDI was administered at Time 1, and the Clinical Outcomes in Routine Evaluation-Outcome Measure (CORE-OM) was administered at Time 2 for the purpose of assessing dysphoric mood and life functioning. NLEs occurring between Times 1 and 2 were evaluated. The three-factor structure of the JIDI was confirmed by confirmatory factor analysis. The structural equation modeling demonstrated that of the three factors, only one, “emotional reliance”, predisposed individuals to dysphoric mood and poor life functioning, both directly and indirectly, via interpersonal NLEs. Although the other two factors did not increase vulnerability to interpersonal NLEs or dysphoric mood, “lack of social self-confidence” worsened general functioning, and “assertion of autonomy” led to poor functioning in close relationships, both directly. Furthermore, “assertion of autonomy” decreased anxiety levels. As to gender differences, simultaneous analysis of multi-groups showed that female subjects were more likely to become anxious following interpersonal NLEs. Keywords: Japanese Version of the Interpersonal Dependency Inventory; Factor Structure; Negative Life Events; Mental Health Problems
Introduction The Interpersonal Dependency Inventory Japanese Short Form (JIDI) was developed by McDonald-Scott (1988) by modifying the original Interpersonal Dependency Inventory (IDI: Hirschfeld et al., 1977). Among the 48 items in the original version, those for which it was difficult to define corresponding Japanese expressions were removed from the JIDI, resulting in 23 JIDI items. The reliability and internal consistency of the JIDI were confirmed (McDonald-Scott, 1988). Despite the differences between the IDI and JIDI in terms of language and number of items, the two instruments are both able to assess the concepts described below. Hirschfeld et al.’s (1977) concept of interpersonal dependency derives from the psychoanalytic theory of object relations, the social learning theory of dependency, and the ethological theory of attachment, resulting in the ability of the developed inventory (the IDI) to evaluate both expressed behaviors and intrapsychic elements such as thoughts, beliefs, and feelings. As with the original version, the JIDI consists of three factors, *
Corresponding author.
“emotional reliance”, “lack of social self-confidence”, and “assertion of autonomy”. According to Hirschfeld et al. (1977), the first factor, “emotional reliance”, reflects the notions of attachment and dependency: “Attachment-related items express a wish for contact with and emotional support from specific other persons, as well as expressing a dread of loss of that person. Dependency-related items involve a general wish for approval and attention from others” (Hirschfeld et al., 1977). Examples of items in this category include “I need to have some person who puts me above all others”, and “I have always had a terrible fear that I will lose the love and support of people I desperately need” (Hirschfeld et al., 1977). The items that comprise the second factor, “lack of social self-confidence”, express one’s “wishes for help in decisionmaking, in social situations, and in taking initiative”. McDonald-Scott (1988) further explains the two psychological processes behind these behaviors. The first is the fear of whether specific others will give their approval, and the other is difficulty with autonomous behaviors due to a lack of self-confi-
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dence in one’s own judgment. Sample items are “When I have a decision to make, I always ask for advice”, and “It is hard for me to ask someone for a favor” (Hirschfeld et al., 1977). The items that constitute the third factor, “assertion of autonomy”, “tend to deny either attachment or dependency”. McDonald (1988) wrote that individuals who score highly on this factor have an intense need to rely on others; however, because of the fear of rejection, these emotional needs are either suppressed or denied. Examples of inventory items include, “When I am sick, I prefer that my friends leave me alone”, and “I don’t need anyone” (Hirschfeld et al., 1977). This category can be regarded as a defense against dependence shown by the significant correlation between “assertion of autonomy” and “interpersonal sensitivity” (Hirschfeld et al., 1977). Interpersonal sensitivity indicates fear of disapproval or rejection. This study had three aims. The first was to confirm the hypothesized three-factor structure of the JIDI (Figure 1). The second was to determine whether the three factors of the JIDI cause dysphoric mood and poor life functioning. With regard to the second aim, the relationship between these three factors and mental health indices has been demonstrated by calculating the correlations between them (Hirschfeld et al., 1977; McDonald-Scott, 1988). Previous researchers (Hirschfeld et al., 1977; McDonald-Scott, 1988) demonstrated almost the same results: the two factors “emotional reliance” and “lack of social self-confidence” were related to negative mental health indices such as depression and anxiety. This relation was not found for “assertion of autonomy”. In this study, we focused on the process whereby high “emotional reliance” or high “lack of social self-confidence” results in negative mental health outcomes. More specifically, we used structural equation modeling (SEM) to examine whether these processes are associated with negative life events (NLEs).
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Several studies have examined the tendency of specific personality types to generate NLEs (Bolger & Schilling, 1991; Daley, Hammen, Davila, & Burge, 1998; Magnus, Diener, Fujita, & Pavot, 1993; McLennan & Bates, 1993; Ormel & Wohlfarth, 1991) as well as depression (Daley et al., 1997; Davila, Hammen, Paley, & Daley, 1995; Hammen, 1991). Personality describes a wide range of mental activities, such as cognitions, emotions, and attitudes, and also influences behavioral patterns. Simons, Angell, Monroe, and Thase (1993) noted that cognitive factors influence not only the definition and severity evaluation of NLEs, but also the actual triggering of NLEs by way of an individual’s behavior. Thus an individual’s personality influences how the NLE is defined, how its intensity is evaluated, the nature of the emotional reaction it elicits, and what kinds of coping behaviors are chosen. To achieve the second aim of this study, we examined whether interpersonal dependency as a personality trait impacts one’s tendency to generate interpersonal NLEs, and consequently, to result in negative mental health outcomes. Concerning the pathways from each JIDI factor to mental health indices, we hypothesized that people with either high “emotional reliance” or “lack of social self-confidence” provoke interpersonal NLEs (Figure 2: W1 and W3) that eventually undermine mental health, for the following reasons. With regard to the first factor, excessive “emotional reliance” would result in the experiencing of intense needs and expectations that others cannot fulfill. This would increase the individual’s levels of dependency, manipulation, and control of specific others. Feeling overwhelmed, the specific others may then keep their distance from him or her. The individual may experience feelings of rejection, resulting in an interpersonal NLE. Concerning the second factor, if one is lacking in social self-confidence, they may repress their opinions in order to maintain the favor of others. As a result, they may not be respected, and may sometimes be disregarded, because they seem to be too submissive toward others. This in turn might lead to stress in interpersonal relationships, and possibly the development of resentment toward others. In contrast to the two factors mentioned above, the third factor, “assertion of autonomy”, would offer protection from interpersonal NLEs (Figure 2: W5) because it involves avoiding interaction with others. However, an alternative hypothesis is possible. Beck’s (1983) concept of autonomy seems to be e24
W1
Emotional reliance
Interpersonal NLE W2 W3 W7
Lack of social self -confidence
W5
e25
W4 Outcome index Assertion of autonomy
Figure 1. The three-factor structure model of the JIDI.
(CORE-OM subcategory score)
W6
Figure 2. The hypothesis pathway from each JIDI factor to negative mental health outcomes.
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closely related to the JIDI’s “assertion of autonomy” in terms of an individual’s attitudes. Beck (1983), however, does not specify whether or not he sees autonomy as a defense against dependency, and writes that although an individual in “the autonomous mode” has his or her “own set of internal standards, goals, criteria for achievement”, as well as a “high level of selfconfidence and self-esteem”, he or she is “less sensitive to others’ needs and wishes” and tends to be “dogmatic” and “authoritarian.” Some “assertion of autonomy” items in the JIDI, such as “I hate it when people offer me sympathy” or “I rely on myself”, infer rejection or hatred for affectionate care rather than independence. Based on these characteristics, people who score highly on this factor might have difficulty recognizing their need for others, and therefore also lack empathy for others’ feelings. These characteristics suggest that such individuals would encounter antipathy from others. Indeed, Daley et al. (1997) used Beck’s Sociotropy-Autonomy Scale (SAS) to demonstrate that in contrast to an individual with sociotropy, one with high autonomy tends to cause interpersonal stress in others even after psychiatric status is taken into account. Therefore, we hypothesized that as with the first and second factors, the third factor, “assertion of autonomy”, would cause interpersonal NLEs. We also hypothesized that there are direct pathways from all three factors to negative mental health outcomes (Figure 2: W2, W4, W6). The third factor, “assertion of autonomy,” could also cause dysphoric mood and poor life functioning, because individuals scoring highly on this factor are not able to seek help from others when they need it. This makes it difficult for them to accomplish their goals, leading to feelings of anxiety and depression as well as poor life functioning (Figure 2: W6). Indeed, there is also evidence of a close relationship between autonomy and undermined mental health. For instance, Bieling, Beck, and Brown (2000) write that the concept of autonomy consists of two factors: first, “sensitivity to others’ control”, and second, “independent goal attainment”. The JIDI’s “assertion of autonomy” seems to be closely related to the first factor, which was presented as having a positive correlation with psychopathology by Bieling et al. (2000). In this study, we not only examined correlations, but also aimed to verify the causal relationship between “assertion of autonomy” and impaired mental health (Figure 2: W6). The third aim of this study was to assess the gender differences regarding the above pathways. Prior studies have shown that women are more likely to report interpersonal stresses than men (Mezulis, Funasaki, Charbonneau, & Hyde, 2010; Rudolph & Hammen, 2003; Kendler, Thornton, & Prescott, 2001). From this, it can be assumed that either women are more sensitive in recognizing interpersonal conflicts, or they actually experience interpersonal NLEs more often. If the former is the case, the above hypothesized pathway from interpersonal dependency to negative mental health through interpersonal NLEs could be identified more clearly among women. On the other hand, men might be less likely to recognize interpersonal NLEs, and therefore among male subjects it might not be difficult to identify an indirect pathway from JIDI subscales to negative mental health indices by way of interpersonal NLEs. Rather, we might only find a direct pathway. An additional hypothesis is that women are more likely to place an emphasis on interpersonal relationships, and socially, it is more acceptable for them to depend on others. Therefore, we theorized that they would score more highly than male sub-
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jects on assessments of “emotional reliance”. Furthermore, negative mental health indices could be more strongly influenced by JIDI subscales as well as interpersonal NLE scores among women as compared to men. To summarize, the purposes of this study were as follows: 1) to confirm the hypothesized three-factor structure of the JIDI using confirmatory factor analysis (CFA); 2) to examine whether the factors that comprise the JIDI caused dysphoric mood and poor life functioning directly or indirectly via interpersonal NLEs, using SEM; and 3) to determine whether the pathways varied with gender.
Methods Procedures This study consisted of self-reported questionnaires conducted on two occasions. The JIDI (evaluated on the first occasion), and Clinical Outcomes in Routine Evaluation-Outcome Measure (CORE-OM) and an assessment of interpersonal NLE (evaluated on the second occasion), were included in the questionnaires. In this study, Time 1 represents the first occasion and Time 2 represents the second occasion. The interval between the Time 1 and Time 2 was six weeks.
Participants Four hundred sixty-nine students from two universities, two nursing schools, and one vocational school in Kumamoto attended both Times 1 and 2. Of these students, two declined to participate, resulting in a study population of 467 students. Questionnaires were distributed to the students during classes. The subjects’ mean (SD) age was 19.3 (3.5), and the numbers of female and male respondents were 342 and 125, respectively. The research protocol was approved by the Ethical Committee of Kumamoto University (Institutional Review Board). Participation was voluntary, and subjects were assured of anonymity. For the purpose of anonymity, aliases were used.
Measurements JIDI (McDonald-Scott, 1988) As noted in the introduction, the JIDI was developed as a revision of the IDI (Hirschfeld et al., 1977). The JIDI consists of 23 items in total: six for “emotional reliance”, nine for “lack of social self-confidence”, and eight for “assertion of autonomy”. Each item is rated from 1 (strongly disagree) to 5 (strongly agree). Therefore, the total score of the JIDI ranges from 23 to 115. Higher scores indicate greater identification with each of the three factors. McDonald-Scott (1988) attested to the JIDI’s reliability and internal consistency.
Clinical Outcomes in Routine Evaluation-Outcome Measure (CORE-OM: Evans et al., 2002) The CORE-OM was developed as a standardized brief outcome measure for use in both routine clinical practice and psychotherapy research (Evans et al., 2002). The reliability and validity of the Japanese version of the CORE-OM have been demonstrated (Uji, Sakamoto, Adachi, & Kitamura, 2012). Of the 34 items, eight dysphoric mood items (four anxiety and four depression) and twelve life functioning items (four close functioning, four general functioning, and four social functioning) were chosen for this study. Each item is rated from 1 (strongly
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disagree) to 5 (strongly agree). Higher scores indicate more serious mental problems. Therefore, the total scores of each subcategory (anxiety, depression, close functioning, general functioning, and social functioning) range from 4 to 20.
The Influence of Gender on the JIDI Subscale Scores
Interpersonal NLEs
Pearson’s Correlations of Each JIDI Subscale with Mental Health Consequences as Well as with Interpersonal NLEs
The following ad hoc question was used to assess interpersonal NLEs: “Please evaluate the distressful experiences you had in the past two weeks in terms of relationships with the following people: 1) your friends, 2) your boyfriend/girlfriend, 3) your mother, 4) your father, 5) faculty members, and 6) your coworkers”. Each interpersonal relationship was evaluated with a score ranging from 0 (no distressful experience) to 100 (extremely distressful experience). Therefore, the total score of the interpersonal NLE assessment ranges from 0 to 600.
There was no gender influence identified on any JIDI subscale score (Table 1).
Regarding the correlations between each JIDI subscale and mental health consequences, almost all the CORE-OM subcategory scores were found to be significantly correlated with the JIDI subscales, the exception being non-significant correlations between “assertion of autonomy” and both anxiety and general functioning (Table 1). Concerning the correlations between each JIDI subscale and interpersonal NLEs, only “assertion of autonomy” did not have a significant correlation with interpersonal NLEs (Table 1).
Statistical Analysis To examine whether the JIDI fit the hypothesized three-factor model (Figure 1), we conducted a CFA. Furthermore, to assess whether our hypothesized pathways from each JIDI factor to negative mental health outcomes (Figure 2) fit the data, we conducted SEM. To examine the gender influence on the parameters in Figure 2, simultaneous analyses of multi-groups were conducted. A critical ratio with a magnitude of 1.96 or more indicates a significant difference (p < 0.05) in the parameters between the pair of subgroups. SPSS version 21.0 and Amos version 21.0 were used for CFA and SEM. The fit of the hypothesized models to our data (Figures 1 and 2) was evaluated using the following indices: Goodness of Fit Index (GFI), Adjusted Goodness of Fit Index (AGFI), and Root Mean Square Error of Approximation (RMSEA) (Arbuckle & Wothke, 1995).
Results CFA of the JIDI The model that presumed the covariance between “lack of social self-confidence” and “assertion of autonomy” to be zero demonstrated the best fit (GFI = 0.88, AGFI = 0.85, RMSEA = 0.08). The covariance between “emotional reliance” and “lack of social self-confidence,” as well as that between “emotional reliance” and “assertion of autonomy,” were significant (p < 0.01).
The Pathways from JIDI Subscales to Negative Mental Health Outcomes The results of SEM are shown in Table 2. “Emotional reliance” was the only factor that generated interpersonal NLEs (Figure 2: W1, standardized causal coefficient (scc) was 0.34 0.35 (p < 0.001)), which in turn resulted in increased anxiety and depression levels and decreased close and social functioning (Figure 2: W7, sccs were 0.20 (p < 0.001), 0.18 (p < 0.001), 0.16 (p < 0.001), and .22 (p < 0.001), respectively). There were also direct pathways from “emotional reliance” to these mental health outcome indices (Figure 2: W2) (scc was 0.43 (p < 0.001) for anxiety, 0.37 (p < 0.001) for depression, 0.23 (p < 0.001) for close functioning, and 0.34 (p < 0.001) for social functioning). In contrast, “emotional reliance” had no impact on general functioning, either directly or indirectly. “Lack of social self-confidence” directly lowered general functioning (Figure 2: W4, scc was 0.41, p < 0.001). In comparison, “assertion of autonomy” lowered close functioning (Figure 2: W6, scc was 0.18 (p < 0.001), whilst alleviating anxiety (Figure 2: W6, scc was −0.15, p = 0.006). The fitness of the hypothesized model to our data (Figure 2) for each mental health index was acceptable: GFI: 0.86 - 0.87, AGFI: 0.83 - 0.84, and RMSEA: 0.07). Simultaneous analyses of multi-groups were conducted to determine the gender influence on each parameter. The only difference between the genders was that the influence of interpersonal NLEs on anxiety was significantly higher among female respondents (critical ratio: 2.29).
Table 1. Differences in mean scores (SD) between females and males and correlations between JIDI subscale scores and CORE-OM subscale scores. Emotional reliance
Lack of social self-confidence
male
16.2 (4.5)
27.2 (6.3)
16.7 (6.1)
female
15.5 (4.4)
27.4 (6.3)
15.9 (5.9)
0.11
0.68
0.22
anxiety
0.37**
0.23**
−0.04
depression
0.35**
0.24**
0.15**
social functioning
0.33**
0.20**
0.18**
general functioning
0.20**
0.33**
0.03
**
0.15
**
0.23**
0.15
**
0.04
Mean scores (SD) p value
Correlations with the CORE-OM subcategory scores
close functioning Correlation with Interpersonal NLEs
0.24
**
0.28
Assertion of autonomy
Note: **p < 0.01.
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Table 2. SEM results. CORE-OM subcategory
N
W4
W5
Anxiety
405 0.35*** 0.43*** 0
W1
0
0
Depression
402 0.35*** 0.37*** 0
0
0
Close functioning
405 0.35*** 0.23*** 0
0
0
General functioning 406 0.35 Social functioning
Absolute value of critical ratio > 1.96 between male and female groups in Figure 2
standardized causal coefficient (scc) in Figure 2
***
W2
0
W3
0
0.41
405 0.34*** 0.34*** 0
0
***
W6
W7
GFI AGFI RMSEA
−0.15** 0.20*** 0.87
0.84
0.07
W7: female (scc was 0.26) > male (scc was 0.07)
0.18*** 0.87
0.84
0.07
none
0.18*** 0.16*** 0.87
0.83
0.07
none
0
0
0
0
0.86
0.83
0.07
none
0
0
0.22***
.87
.84
0.07
none
Note: **p < 0.01, ***p < 0.001.
Discussion CFA of the JIDI The result of the CFA supported the hypothesized three-factor structure of the JIDI. Despite the fact that “assertion of autonomy” showed no significant correlation with “lack of social self-confidence”, it was significantly correlated with “emotional reliance”. Therefore, as McDonald-Scott (1988) noted, an intense need for others could underlie both “emotional reliance” and “assertion of autonomy”. The difference is that an individual with high “emotional reliance” is able to recognize their needs, while an individual with high “assertion of autonomy” is apt to deny their needs because of fear of disapproval and rejection by significant others. The other significant correlation, between “emotional reliance” and “lack of social self-confidence”, can be interpreted as follows: people with high levels of “emotional reliance” always need others’ approval and care, which means that they do not have sufficient “social self-confidence”. If they have high “social self-confidence” and no need for others’ approval, then they do not have to be so reliant on others.
Lack of Significant Influences of Gender on the JIDI Subscales Contrary to our hypothesis, there were no gender differences in the evaluation of the JIDI subscales. In traditional Japanese society, men were required to be masculine and assertive, and women feminine and passive. However, in contemporary times, these socially required gender roles are less widely recognized, which has hypothetically led to the lack of differences between genders in JIDI subscale scores.
The Direct and Indirect Influences of “Emotional Reliance” on Dysphoric Mood and Poor Life Functioning As predicted, “emotional reliance” triggered interpersonal NLEs, which in turn led to dysphoric mood and poor life functioning. The exception was the lack of impact of “emotional reliance” on general functioning. An individual with high “emotional reliance” seems to be deficient in the “capacity to be alone” (Winnicott, 1958), and seeks instant gratification through a dependence on others. These attitudes and behaviors may provoke interpersonal NLEs, and eventually result in dysphoric mood and poor life functioning. Therefore, the deteriorated mental health experienced by those with high “emotional
reliance” can be partially due to these individuals’ cognitive styles, attitudes, and behaviors. The direct pathways from “emotional reliance” to dysphoric mood and poor life functioning were also determined.
Absence of Significant Influences of “Lack of Social Self-Confidence” on Generation of Interpersonal NLEs or Dysphoric Mood, and Its Negative Impact on “General Functioning Level” Despite the significant Pearson’s correlations of “lack of social self-confidence” with anxiety, depression, social functioning, close functioning and interpersonal NLEs, the SEM results showed that “lack of social self-confidence” provoked none of these. The reason for this discrepancy may be that SEM takes into account all factor relationships, such as correlations within the three JIDI subscales. There would be an alternative reason why “lack of social self-confidence” did not influence interpersonal NLEs: an individual with severe “lack of social self-confidence” tends to be ego-centric, and thus does not have the mental capacity to recognize interpersonal conflicts. Concerning life functioning, individuals demonstrating “lack of social self-confidence” showed reduced general functioning. This may be due to their self-esteem being low, which is related to impaired ego functioning (Bellak, Hurvich, & Gediman, 1973), causing the individuals to lose their capacity to deal with daily activities.
The Absence of a Significant Impact of “Assertion of Autonomy” on Interpersonal NLEs, and Its Impact on Dysphoric Mood and Close Functioning As noted, “assertion of autonomy” can be regarded as a defense against “emotional reliance,” thus functioning as a strategy to avoid interpersonal NLEs that are followed by dysphoric mood. However, as noted in the introduction, it is conceivable that individuals who assert their autonomy will invite the antipathy of others. However, the dispositions of these individuals do not take into account others’ feelings, and therefore they might be more likely to disregard interpersonal NLEs. Furthermore, “assertion of autonomy” directly alleviated anxiety. While this may be interpreted as a positive occurrence, it can also be interpreted in a different way: it is possible that an individual who does not report anxiety is simply denying its existence. An individual with a high level of “assertion of autonomy” may lack the ability to recognize their own weakness and may be prone to using reaction formation (Freud, 1926) as a defense mechanism. Although “assertion of autonomy” did
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not provoke interpersonal NLEs or dysphoric mood, it lowered close functioning. Individuals who cannot respect or seek help from others because of a fear of rejection cannot establish trustworthy or intimate relationships.
The Impact of Gender on the Pathways The only difference between males and females was the impact of interpersonal NLEs on anxiety. This means that even though males experienced interpersonal NLEs, they did not necessarily become as anxious as females. This can be interpreted that males tend to avoid recognizing anxious feelings caused by interpersonal conflicts.
Application to Clinical Settings When we see patients who suffer from depressive mood, anxiety, or other mental symptoms, it is crucial to evaluate their personalities. In particular, the cognitive patterns, attitudes, and behaviors of patients with an intense “emotional reliance” on others are apt to elicit interpersonal distresses, resulting in undermined mental health. Therefore, removal of symptoms alone is not sufficient. It is necessary to provide support enabling these patients to obtain insight into their own personalities, thus helping to prevent future relapse. On the other hand, individuals with a high level of “assertion of autonomy” tend to repress or deny interpersonal distresses or dysphoric moods. In the same way, those with a “lack of social self-confidence” cannot recognize interpersonal distresses, and focus predominantly on low self-esteem in a masochistic way. Therefore, we have to consider the possibility of existing interpersonal conflicts and negative emotions in these individuals’ psyches. With regard to gender, females seem to be more likely to recognize their anxiety in regard to interpersonal NLEs. For males, anxious feelings are less likely to be indicators of interpersonal NLEs.
Limitation In this study, we defined NLEs within interpersonal relationships; however, it is uncertain whether the reported NLEs were provoked by the respondents’ cognitive and behavioral patterns. Therefore, further research based on face-to-face interviews or clinical records are required.
Conclusion The results of this study showed that “emotional reliance” can cause dysphoric mood and poor functioning in a manner mediated by interpersonal NLEs. The two JIDI factors that did not provoke interpersonal NLEs, “lack of social self-confidence” and “assertion of autonomy”, directly reduced “general functioning” and “close functioning”. Intense dependency as well as a lack of the ability to depend on others appears likely to undermine an individual’s mental health.
Acknowledgements We would like to express deep gratitude to respondents of this study. This research received no specific grants from any funding agency in the public, commercial, or not-for-profit sectors. There is no conflict of interest to declare.
REFERENCES Arbuckle, J. L., & Wothke, W. (1995). Amos 4.0 user’s guide. Small Waters Cooperation. Beck, A. T. (1983). Cognitive therapy of depression: new perspectives. In P. J. Clayton, & J. E. Barnett (Eds.), Treatment for depression: Old controversies and new approaches (pp. 265-290). New York: Raven Press. Bellak, L., Hurvich, M., & Gediman, H. (1973). Ch. 5: General considerations and rationale for the selection of the 12 ego functions. In Ego functions in schizophrenics, neurotics, and normals (pp. 74-79). New York: Wiley. Bieling, P. J., Beck, A. T., & Brown, G. K. (2000). The sociotropyautonomy scale: Structure and implications. Cognitive Therapy and Research, 24, 763-780. Bolger, N., & Schilling, E. A. (1991). Personality and problems of everyday life: The role of neuroticism in exposure and reactivity to daily stressors. Journal of Personality, 59, 355-386. Daley, S. E., Hammen, C., Burge, D., Davila, J., Paley, B., Lindberg, N., & Herzberg, D. S. (1997). Predictors of generation of episodic stress: A longitudinal study of late adolescent women. Journal of Abnormal Psychology, 106, 251-259. Daley, S. E., Hammen, C., Davila, J., & Burge, D. (1998). Axis II symptomatology, depression, and life stress during the transition from adolescence to adulthood. Journal of Counseling and Clinical Psychology, 66, 595-603. Davila, J., Hammen, C., Paley, B., & Daley, S. E. (1995). Poor interpersonal problem solving as a mechanism of stress generation in depression among adolescent women. Journal of Abnormal Psychology, 104, 592-600. Evans, C., Connell, J., Barkham, M., Margison, F., McGrath, G., MellorClark, J., & Audin, K. (2002). Towards a standardized brief outcome measure: Psychometric properties and utility of the CORE-OM (clinical outcomes in routine evaluation-outcome measure). British Journal of Psychiatry, 180, 51-60. Freud, S. (1926). Inhibitions, symptoms and anxiety. In J. Strachey, & A. Freud (Eds.), The standard edition of the complete psychological works of Sigmund Freud (pp. 77-175). London: The Hogarth Press. Hammen, C. (1991). Generation of stress in the course of unipolar depression. Journal of Abnormal Psychology, 100, 555-561. Hirschfeld, R. M. A., Klernman G. L., Gough, H. G., Barrett, J., Korchin, S. J., & Chodoff, P. (1977). A measure of interpersonal dependency. Journal of Personality Assessment, 41, 610-619. Kendler, K. S., Thornton, L. M., & Prescott, C. A. (2001). Gender differences in the rates of exposure to stressful life events and sensitivity to their depressogenic effects. American Journal of Psychiatry, 158, 587-593. Magnus, K., Diener, E., Fujita, F., & Pavot, W. (1993). Extraversion and neuroticism as predictor of objective life events: A longitudinal analysis. Journal of Personality and Social Psychology, 65, 10461053. McDonald-Scott (1988). Interpersonal dependency inventory Japanese short form: Its development and statistical test. The Japanese Journal of Nursing Research, 21, 451-460. (in Japanese) McLennan, J., & Bates, G. W. (1993). Vulnerability to psychological distress: Empirical and conceptual distinctions between measures of neuroticism and negative affect. Psychological Report, 73, 13151323. Mezulis, A. H., Funasaki, K. S., Charbonneau, A. N., & Hyde, J. S. (2010). Gender differences in the cognitive vulnerability-stress model of depression in the transition to adolescence. Cognitive Therapy and Research, 34, 501-513. Ormel, J., & Wohlfarth, T. (1991). How neuroticism, long-term difficulties, and life situation change influence psychological distress: A longitudinal model. Journal of Personality and Social Psychology,
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60, 744-755. Rudolph, K. D., & Hammen, C. (2003). Age and gender as determinants of stress exposure, generation, and reactions in youngsters: A transactional perspective. Child Development, 70, 660-667. Simons, A. D., Angell, K. L., Monroe, S. M., & Thase, M. E. (1993). Cognition and life stressors in depression: Cognitive factors and the definition, rating, and generation of negative life event. Journal of Abnormal Psychology, 102, 584-591.
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Uji, M., Sakamoto, A., Adachi, K., & Kitamura, T. (2012). Psychometric properties of the Japanese version of the clinical outcomes in routine evaluation-outcome measure. Comprehensive Psychiatry, 53, 600-608. Winnicott, D. (1958). The capacity to be alone. In M. M. Khan (Ed.), The maturational process and the facilitating environment (pp. 2936). London: Horgarth Press.
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27 Construction and Validation of the Gender Apperception Test-GAT for Children Silvana B. Gaino1, Francisco Baptista Assumpção Jr.2, Gerson Silva Santos Neto2, Victor Galvao3 1
Health Sciences Center, Federal University of Bahia’s Reconcavo, Santo Antonio de Jesus, Brazil 2 Institute of Psychology, University of Sao Paulo, São Paulo, Brazil 3 Universidade Federal do Reconcavo da Bahia, Cruz das Almas, Brazil
Objective: This study had objectives as the construction and validation of an instrument to assess the factors associated to the formation of gender identity considering the role of toys and childish games, easily applicable and possible to be used in a wide range of contexts with children aged from 4 to 6 years old. Method: The Gender Apperception Test (GAT—originally TAG in BR-Portuguese), formed by 51 items, was applied in 303 children (171 boys and 132 girls) from public and private schools. Results: The internal consistency of the items was very satisfactory presented in Cronbach’s Alphas of 0.92. Conclusions: GAT’s psychometric parameters were satisfactory, indicating that this is an alternative way for empirical investigations and applied works in different institutions, capable of guiding measures intended to assess and keep up with the development of children’s gender identity concept. Keywords: Gender Identity; Toys and Games; Children Evaluation
Introduction The concern for studies about the activity of plays and games has been growing on scientific literature, especially last years. One of the reasons for the increase of researches over this theme is due to the impact of discussions made by Evolutionist Psychology, which has studied the plays and games under the hypothesis that these are continually adapted and also adaptive for the species for containing phylogenetic and ontogenetic aspects that bring possible relations between culture and phylogenesis. The activity of plays and games can be found in human’s children as much as in others mammal’s puppies, and this is directly related to internal motivation of these to such activity, being characterized by a set of behaviors that indicate developmental processes and aspects (Hansen et al., 2007). Vygotsky (1989) used to claim that through observation and by the studies of playing, it is possible to detect and create zones of proximal development and, consequently, provide children with qualitative jumps on cognitive, social, affective, and physical development, as well as on the formation of personality (Carvalho, 1989; Morais, 2004; Coll, Marchesi, & Palacios, 2009). According to Kishimoto (1988), the play is characterized as a set of behaviors that has a purpose in itself, arising naturally, and it does not feature as an obligation remaining itself mainly only by the pleasure found by the child while playing. Pellegrini and Smith (1998) agree with this concept and emphasize that its importance would be linked to its own process rather than its later benefits. In posterior studies Morais and Otta (2003) identified aspects that could influence the play, then they introduced a concept
called “playful zone”, corresponding the space in which occurs the play composed by three elements: 1) the child with their experiences, resources, motivations, pressures, and social conditions surrounding him/her; 2) the physical space in which the child is inserted, as well as the toys available; and 3) the temporal space, namely, the amount of time dedicated to the play and how the child manages this time and the apprehended familiar beliefs. Such elements would influence the play endowing the child with peculiar characteristics. On the context of Psychology, the play started to be investigated by Spencer (1966), Kagan (1977) and Groos (1976) who emphasized in their studies the play being a product of an energy excess of the child. As the play started growing in importance due to the results presented, the studies involving the Developmental Psychology, the Clinical Psychology, the Psychology of Education, and the Psychology of Health began to increase considerably, amongst other areas. However, Cordazzo, Martins, Macarini & Vieira (2007) gathered studies related to the play and the concentration areas of these studies, and so verified the need of general development of the child, as therapeutic activity, as space of expression of feelings and emotions, besides investigations about the play of children presenting various pathologies during their development, focusing the benefit that this activity may bring to the adhesion and maintenance of the treatment, as well as the subjective elaboration and coping of these pathologies. Regarding the contributions from Evolutionary Psychology to these areas, it is highlighted its investigations about the gender differences and its relations with the play. The gender iden-
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tity, according to the evolutionary conceptions, is a key element in personality development, as it influences the way of being, acting, and thinking of individuals and it is also constituted into the set of beliefs, attitudes, and stereotypes that the child will form about its own gender and has its origins in biological, psychological, and social antecedents (Papalia & Olds, 1998). In this sense, the gender identity is referred to the individual notion of belonging to one of the genders, either male (boy, man) or female (girl, woman). Overall, the concept of gender appeared more often on researches from the moment they began discussing the sociocultural aspects versus biological aspects presented in behavior and the social influences experienced. Thus, such influences can differently structure the definition of being a woman or being man in a society built historically (Gobbi, 1996). Another definition of gender, defended by Scott, is taken as a “social organization of sexual difference”, being one constitutive element of social relationships based on noticed differences between sexes, providing a way of decoding the meaning and to comprehend the complex connections amongst the several ways of human interaction. Amid the multiplicity of researches, for Otta, Ribeiro, and Bussab (2003), it was noted a crescent volume of these that have been documenting sexual differences, which surely arise in human biology and evolve to sexual characterizations, pointing to the fact that these are not arbitrary characteristics of western culture. In almost all cultures, women are more responsible for child care, and men for activities belonging to public domain (Otta, Ribeiro, & Bussab, 2003). In this sense, to Delgado (2003), the familiar environment will play a fundamental role in the construction of the gender identity. The process of becoming a woman and becoming a man begins even before formally entering in a school, showing that precocious influences may be favoring the presented behaviours. Thus, Beraldo (1993) and Bichara (1994) consider that the child starts showing some stereotyped preferences and linked to gender identity around their 3 years old, which shows how influent the family can be in his/her formation. The segregation and classification of sex would not be, therefore, only a reflex of individuals’ preferences, but a group phenomenon that would start in the family (Maccoby, 1988). This statement was also important for Silva’s et al. (2006) studies who claim that gender brings behaviours and cultural meanings as characteristics about what is to be “feminine” or “masculine”, taking into account sex as a physiological and anatomical aspect determined by biology that uses for classification “male” and “female”. The base for gender differentiation is biological, but the constructions in process, and the way it is processed, are symbolic and social. Therefore, it is necessary to place the discussion into a wider and more integrated perspective, thus allowing an expanded view of the phenomenon of gender differentiation and self-categorization, in order to comprehend how the biological and cultural factors interact. The main restriction regarding the evaluation of this phenomenon is due to the absence of valid instruments for such purpose. Hitherto, the studies and researches performed have been based on either direct or indirect observation of the activity of playing and toy’s choice made by boys and girls in several contexts. Some of these were made by Pontes, Magalhães, & Martin (2008), who investigated the children’s choices of toys made of palm straw, considering the gender influence and the composition of the dyad mother-child. Cordazzo and Vieira
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(2007) on the other hand made a research about playing games and its implications in the learning and development processes, whereas Oliveira, Vieira, & Cordazzo (2008) pointed the play as a health promoting agent in child development. As for studies and researches that took into account the gender identity, one conducted by Wanderlind et al. (2006) intended to identify the existing differences of gender identities in the play of scholar and preschooler children in the context of a playroom. Another study, but under the evolutionary psychology perspective, Hansen et al. (2007) publicized one paper in which was evaluated the play and its implications for child development. Despite the increase of studies and researches about gender identity and the possible factors associated with its formation, especially after the advent of Evolutionary Psychology, there is still one gap concerning the lack of instruments able to assist in the assessment of this construct, as these must attend the psychometric parameters and its theoretical postulates. In regards to Brazil, the situation is yet more complicated, since the absence of instruments to standardize and organize the evaluation in this area has limited possible advances. Thereby, this study aimed to develop and validate an instrument of gender apperception, easily applicable that could be used in as many environments frequented by children as possible, such as schools, clinics, day care center, shelters, etc. Then, the Teste de Apercepção de Gênero (TAG)—or the Gender Apperception Test (GAT)—was developed, whose process of construction and validation is described below.
Method Developing the Test The cards composing the TAG, which also confer to the deck a playful aspect, were elaborated from the analyses of literature about toys and child’s games and its relations with the formation and development of gender identity manifested by children, and also considering the opinion of boys and girls, via an oral interview, in which boys and girls have indicated their preferences for toys and child’s games. In this last case, only 2 toys and 2 games (the firsts said by each child) were considered to compose their opinion. The cards present drawings of toys and games chosen, according to frequency, randomly arranged, but always considering a set of one “male” card, one “female” card, and one ‘neutral’ or for both genders card. It was decided to use cards rather than real toys because these drawings represent the real thing, with the advantage of being more practical and time-saver to assess the formation and development of the gender identity. Moreover, for having an easier and more practical application, it is easier to work with impaired children. As pointed previously, the play and games have been investigated both in human’s infants and in other mammal’s pups, which have presented a direct relation with internal motivation of these, and are characterized by a set of behaviours that indicate developmental aspects and processes (Alexander & Hines, 2002; Otta, Ribeiro, & Bussab, 2003; Wanderlind et al., 2005; Hansen et al., 2007; Cordazzo & Vieira, 2007; Cordazzo et al., 2008; Oliveira, Vieira, & Cordazzo, 2008). One of the concerns in constructing such instrument was related to how easily it could be applied on different populations of children. Then, the drawings were made considering the main toys and games, id est., the ones that are most played,
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regardless the social background of the child, considering possible influences on the formation of their personality, and also taking into account some other aspects, such as types of wheeled vehicles (bicycle, cars, trucks), dolls (Barbie-style, herostyle), or, for instance, sets of make-up and tools. In order to identify these items, children were consulted, as well as professionals from Psychology, Psychiatry, and Education. Thus, it was obtained at first a total of 87 cards, that contained drawings of toys and games of boys, girls, and shared by both, which were presented, after being randomly shuffled, 3 cards at a time, to 100 children (50 male and 50 female), aged 4 to 6 years, from São Paulo and Bahia. This was done to check the relevance of each card and also the coverage of application in various social and cultural contexts. After that application and further analyses of frequency of choice, some cards were dropped due to their inferior score, and then the number of cards was reduced to 54, which were applied again the same way, but with a higher sample (300 children). Again, analyses made, 3 cards were dropped, remaining only the cards with higher frequency. It was used an answer sheet, where the choices were recorded, based on the preference of each child, and to facilitate this data record numbers were assigned to each card, and this assignment was also random. Next, aiming to verify whether the proposed cards and instructions presented were comprehensible (semantic analysis), the instrument was applied in 148 children, aged 4 to 6 years, from São Paulo and Bahia. Later, the same sample was requested to answer one questionnaire to indicate who (boy, girl, or both) usually play with the toy or game depicted by each card, which also would give hints about the understanding of the instruction. Figure 1 below shows, as samples to illustrate the items, 3 cards from the final deck of the TAG: the ball (male), hideand-seek (for both), and a doll (female).
The Sample The sample used for validation was composed of 303 children (171 boys and 132 girls) from the states of São Paulo and Bahia, inserted in public or private schools (Tables 1 and 2), mean age = 5.04 years, SD = 0.835 and scholar level varying from kindergarten to 1st year of basic education (Table 3).
Proceedings After compliance with ethical requirements approved by the Ethical Committee of the Maria Milza College in Researches with Human Beings (FAMAM)—Protocol nº 131/10, contact was made with institutions located in the states of São Paulo and Bahia that would cede space for the execution of this research. It was only considered data from children under the
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Table 1. Participant’s sex distribution. Sex
Frequency Valid percentage Cumulated percentage
Male
171
56.4
56.4
Female
132
43.6
100.0
Total
303
100.0
Table 2. Participant’s distribution by state. Estate
Frequency Valid percentage Cumulated percentage
Bahia
121
39.9
39.9
São Paulo
182
60.1
100.0
Total
303
100.0
Table 3. Participant’s distribution by age. Age
Frequency Valid percentage Cumulate percentage
4 anos
99
32.7
32.7
5 anos
92
30.4
63.0
6 anos
112
37.
100.0
Total
303
100.
criteria for this research (age, in typical development, and not showing any disability to understand what was being required) and whose parents or caregivers had signed the consent form. The instrument was administered individually, in a proper place provided by the institution for this activity, which took 8 minutes on average.
Data Analyses Data treatment and statistical analyses were made using the software SPSS (Statistical Package for the Social Sciences, v. 17.0 for Windows). Initially it was ran an analysis of principal components (PCA), without rotation and treating omissions through pairwise, in order to verify the matrix factorability generated and how many components could be extracted. The Kaiser-Meyer-Olkin (KMO), the Bartlett’s Test of Sphericity, and the matrix correlation determinant were calculated, as well as the scree-plot was analysed to identify the number of factors to be extracted. Then, the factorial analysis was run through the principal axis factoring (PAF) and oblimin rotation—as it allows orthogonal factors, when existent, to appear, and it also does not force dependence among factors, but only allows it. Moreover, it was suppressed factorial charges lower than 0.30 to assure that each item would represent the underlying construct to the factor. The Cronbach’s alpha was used to calculate the precision (Pasquali & Primi, 2003; Pasquali, 2005).
Results Figure 1. Sample cards from the final deck.
The KMO measure of sampling adequacy and the Bartlett test for Sphericity indicated that the data were suitable for fac-
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tor analysis, with the former having a value of 0.916 (Table 4), considered to be excellent (Hair Jr. et al., 2005). Considering the scree-plot (Figure 2) and the eigenvalues—with values equal or higher than 1—it is indicated to extract 2 factors, which explain 79.93% of total variance. Through parallel analysis with the software Monte Carlo analysis (Table 5), it was confirmed that could be extracted 2 factors (Kalos & Whitlock, 1986; Galvão, 2005). The first factor is related to gender identity and is composed by 34 items, indicated as being representative by toys and games typically played either by boys or girls, and the second factor related to cards representing toys and games played by both composed by 17 items. The TAG had a Cronbach’s alpha equal to 0.92, which is very good too.
Discussion and Conclusion The objective of this study was to build and validate the TAG, easy to use, which could be used in various contexts. Thus, it was started with the assumption that the instrument would be formed by a factor representative of what is to be a girl or boy. However, the factor analysis indicated that the items should be grouped in two factors: the first would be reTable 4. KMO and Bartlett’s test of sphericity. Kaiser-Meyer-Olkin Test (KMO)
0.916
Approx. Chi-Square
8508.230
Df
136
Sig.
0.000
Bartlett’s Test of Sphericity
Table 5. Parallel analysis of Monte Carlo. Components Eigenvalues 1
2
3
(...)
Empirical
9.622
3.966
0.846
(...)
Aleatory
1.4373
1.3411
1.2704
(...)
Figure 2. Scree plot.
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lated to gender identity, understood as “features, behaviours, and cultural meanings about belonging to feminine or masculine” (Silva et al., 2006). The second factor was interpreted as “neutral” cards—or for both genders—once it would involve the possibility for children to choose cards that could represent toys and games for both boys and girls, and how they act according to their beliefs, in other words, how they test and experience the different roles existent on society, developing skills giving rise to the appearance of toys and games that increasingly mimic the “real world” and the games of rules (Vygotsky, 1991). The “neutral” factor was represented by 17 cards of the TAG. Initially, the TAG was composed by eighty seven cards, but thirty six were excluded, and then the final version stayed with 51 items. Such exclusion did not reduce the quality of its content, as some of these items had a correspondent among the remaining cards. For instance, “rag doll”, which was eliminated, had “barbie doll”, as a semantic correspondent to the concept of “doll”. The psychometric features of the TAG were considered satisfactory, and it can contribute to both researches on this topic as to assist monitoring the development of the concept of gender identity and its relations to general development in children considered under typical development, as much as in children presenting delays or impairments in their development, including supplementing information derived from other instruments. The objective of validating an instrument of apperception gender was achieved with solid psychometric standards. In this study area expanding, which does not have a measurement tool to assess the development of the concept of gender identity, the TAG is an alternative for both empirical research and applied work, with possible use in different contexts and populations. Literature has often pointed to the importance of monitoring the different factors involved in child development, not only as a way of preventing and promoting health, but also as an attempt to better understand the dynamics of the same. For the construction of the TAG was considered: the indications of the children themselves regarding their opinion to what they considered as toys or games for boys, girls or both, as well as the perception they had on them, and discussions with and analyses of professionals in Psychology, Psychiatry and Education. Thus, the TAG aims to fill in some gaps in other assessment instruments used with children, and therefore the TAG may also be used as a tool to evaluate the influence of different development environments as a whole, facilitating the understanding of characteristics, behavior and cultural meanings. Despite the contributions the TAG can bring, some limitations should be identified in its future uses. Obviously, because it is a new instrument, whose items were based on interviews with children, as well as in studies and research conducted to date and which were based on direct or indirect observation of play and toy choices made by boys and girls in various contexts, the TAG has not indicated the effectiveness of its application in other contexts involving different populations of children yet. Future researches intending to evaluate the formation of the concept of gender identity may be based on approaches that guided the construction of the TAG, considering the different categories that were used, which would result in other instruments or scales that addressed one factor or multifactorial parameters most basic concern, as well as analysis of the items (difficulty and discrimination), the validity and reliability of the instrument (Pasquali, 2003).
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Factors directly or indirectly associated to the concept of gender identity could also be better explored by investigating in greater detail the different environments of inclusion of children, such as family environment, which according to Delgado (2003) will play a role in the construction of gender identities. The survey conducted by Cordazzo, Martins, Macarini & Vieira (2007) regarding studies related to play and areas of concentration of these studies, confirms the need for further research involving the evaluation of the importance of play for the overall development of the child, besides investigations on the play of children with different pathologies during its development. Thus, the TAG is presented as a new potential tool to research and comprehend the notion of the concept of gender identity. Nonetheless, further research should be conducted to expand knowledge in this area and improvements in the instrument itself.
Acknowledgements The cartoons composing the card deck were drawn by Elizângela Matias (Belê) inspired by characters of social media.
REFERENCES Alexander, G. M., & Hines, M. (2002). Sex differences in response to children’s toys in nonhuman primates (Cercopithecus aethiops sabaeus). Evolution and Human Behavior, 23, 467-479. http://biososial.org/wp-content/uploads/2010/03/Alexander-Hines-20 02.pdf Beraldo, K. E. A. (1993). Gênero de brincadeiras na percepção de crianças de 5 a 10 anos [Gender of plays in 5 - 10 years old children’s perception.] São Paulo, SP: IPUSP. Bichara, I. D. (1994). Um estudo etológico da brincadeira de faz-deconta em crianças de 3 - 7 anos [An ethological study of play of pretending in 3 - 7 years old children.] Unpublished Doctoral’s dissertation, Sao Paulo: University of Sao Paulo. Carvalho, A. M. A. (1989). Brincar juntos: Natureza e função da interação entre crianças [Playing together: Nature and function of interaction among children.] In C. Aides (Ed.), Etiologia de animais e de homens/Human and animal Ethology (pp. 199-210). São Paulo: Edicon/EDUSP. Coll, C., Marchesi, A., & Palácios, J. (2009). Desenvolvimento psicológico e educação: Psicologia Evolutiva [Psychological development and education: Evolutionary Psychology.] Porto Alegre: Artmed. Cordazzo, S. T. D., Martins, G. D. F., Macarini, S. M. and Vieira, M. L. (2007). Perspectivas no estudo do brincar: Um levantamento bibliográfico [Perspectives in the study of play: A bibliographical survey.] Aletheia, 26, 122-136. http://pepsic.bvsalud.org/pdf/aletheia/n26/n26a11.pdf Cordazzo, S. T. D., & Vieira, M. L. (2007). A brincadeira e suas implicações nos processos de aprendizagem e de desenvolvimento [The play and its consequences in development and learning processes.] Estudos e pesquisas em Psicologia, 1, 89-101. http://www.revispsi.uerj.br/v7n1/artigos/pdf/v7n1a09.pdf Cordazzo, S. T. D., Westphal, J. P., Tagliari, F. B., Vieira, M. L., & Oliveira, A. M. F. (2008). Metodologia observacional para o estudo do brincar na escola [Observational metodology to study the play in the school.] Avaliação Psicológica, 7, 427-438. http://pepsic.bvsalud.org/pdf/avp/v7n3/v7n3a14.pdf Delgado, A. C. C. (2003). Culturas infantis e dimensões da socialização no cotidiano de uma creche domiciliar [Children cultures and dimensions of socialization in the routine of a home day care.] Caderno de Educação, 21, 101-118. http://periodicos.ufpel.edu.br/ojs2/index.php/caduc/index Galvão, M. (2005). Análise quantitativa de riscos com simulação de
Monte Carlo [Quantitative analysis of risks with Monte Carlo’s simulation.] www.mundopm.com.br/download/montecarlo.pdf Gobbi, M. A. (1996). Lápis vermelho é de mulherzinha: Desenho infantil, relações de gênero e educação infantil. [Red pencil is for girls: Infantile drawing, gender relations and infantile education.] Master’s Thesis, Campinas (SP): Unicamp. Groos, K. (1976). The play of animals: Play and instinct. In J. S. Bruner, A. Jolly, & K. Sylva (Eds.), Play. Its role in development and evolution (pp. 65-67). Middlesex: Penguin Books. Hair Júnior, J. F., Anderson, R. E., Tatham, R. L., & Black, W. C. (2005). Análise multivariada de dados [Multivariate analysis of data.] Porto Alegre: Bookman. Hansen, Macarini, Martins et al. (2007). O brincar e suas implicações para o desenvolvimento infantil a partir da Psicologia Evolucionista [The play behaviour and its implications for child development according to evolutionary psychology.] Revista Brasileira de Crescimento e Desenvolvimento humano, 17, 133-143. http://pepsic.bvsalud.org/pdf/rbcdh/v17n2/14.pdf Kagan, G. et al. (1977). Introdução: Algumas perspectivas históricas [Introduction: Some historical perspectives.] In: Desenvolvimento e personalidade da criança (pp. 1-10). São Paulo: Harper e Row do Brasil. Kalos, M. H., & Whitlock, P. A. (1986). Monte carlo methods: Basics. New York: Wiley-Interscience Publication. Kishimoto, T. M. (1988). O brincar e suas teorias [The play and its theories.] São Paulo: Pioneira. Maccoby, E. (1988). Gender as a social category. Developmental Psychology, 24, 755-765. Morais, M. L. S., & Otta, E. (2003). Entre a serra e o mar [Between the sierra and the sea]. In A. M. A. Carvalho, C. M. C. Magalhães, F. A. R. Pontes, & I. D. Bichara (Eds.), Brincadeira e cultura: Viajando pelo Brasil que brinca (pp. 127-157). São Paulo: Casa do Psicólogo. Morais, M. L. S. (2004). Conflitos e(m) brincadeiras infantis: Diferenças culturais e de gênero [Conflicts in children’s play: Cultural and gender differences.] Doctoral Dissertation, Sao Paulo (SP): University of Sao Paulo. Oliveira, L. D. B., Vieira, M. L., & Cordazzo, S. T. D. (2008). “Brincar” como agente promotor de saúde no desenvolvimento infantil [“The play” as promotional agent of health in the child development.] Revista de Ciências Humanas, 42, 193-215. https://periodicos.ufsc.br/index.php/revistacfh/article/view/2178-458 2.2008v42n1-2p193/13335 Otta, E., Ribeiro, F. L., & Bussab, V. S. R. (2003). Inato versus adquirido: A persistência da dicotomia [Innate vs. Acquired: The persistence of the dichotomy.] Revista de Ciências Humanas, 34, 283-311. https://periodicos.ufsc.br/index.php/revistacfh/article/view/25381/22 302 Pasquali, L. (2005). Análise fatorial para pesquisadores [Factorial analysis for researchers]. Brasília: LabPam. Pasquali, L. (2003). Psicometria: Teoria dos testes na psicologia e na Educação [Psychometry: Test’s theory in Psychology and Education.] Petrópolis, RJ: Vozes. Pasquali, L., & Primi, R. (2003). Fundamentos da teoria de resposta ao item—TRI [Basic theory of Item Response Theory—IRT]. Avaliação Psicológica, 2, 99-110. http://pepsic.bvsalud.org/pdf/avp/v2n2/v2n2a02.pdf Papalia, D. E., & Olds, S. W. (1998). O mundo da criança [The child’s world.] São Paulo: Markon Brooks. Pellegrini, A. D., & Smith, P. K. (1998). The development of play during childhood: Forms and possible functions. Child Psychology & Psychiatry Review, 3, 51-57. http://onlinelibrary.wiley.com/doi/10.1111/1475-3588.00212/pdf Pontes, F. A. R., Magalhães, C. M. C., & Martin, W. L. B. (2008). Preferência de crianças no brinquedo de miriti: A influência do gênero e composição da díade [Children’s preferences for Miriti toys: The influence of gender and dyad composition.] Revista Brasileira de Cre-
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scimento e Desenvolvimento Humano, 18, 170-178. http://pepsic.bvsalud.org/pdf/rbcdh/v18n2/08.pdf Silva, L. I. C., Pontes, F. A. R., Silva, S. D. B., Magalhães, C. M. C., & Bichara, I. D. (2006) Diferenças de gêneros nos grupos de brincadeira na rua: A hipótese de aproximação unilateral [Gender differences in the groups of street play: The hypothesis of unilateral approach.] Psicologia Reflexão Crítica, 19, 114-121. http://www.scielo.br/pdf/prc/v19n1/31300.pdf Scott, J. W. (1995). Gênero: Uma categoria útil de análise histórica [Gender: A useful category of historical analysis.] Educação e Realidade, 20, 71-99. https://archive.org/details/scott_gender Spencer, H. (1966). Principles of biology. The works Herbert Spencer. Osnabrüg: Otto Zeller.
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Vygotsky, L. (1991). A formação social da mente: O Desenvolvimento dos processos psicológicos superiores [The social formation of the mind: The development of superior psychological processes.] São Paulo, SP: Martins Fontes. Vygotsky, L. (1989). O papel do brinquedo no desenvolvimento [The role of toy in human development.] In: M. Cole, V. John-Steiner, S. Scribner, & E. Souberman (Eds.), A formação social da mente (pp. 105-118). São Paulo: Martins Fontes. Wanderlind, F., Martins, G. D. F., Hansen, J., Macarini, S., & Vieira, M. L. (2006). Diferenças de gênero no brincar de crianças pré-escolares e escolares na brinquedoteca [Gender differences in play of prescholar and scholar’s children at toy-library.] Paideia, 16, 263-273. http://www.scielo.br/pdf/paideia/v16n34/v16n34a14.pdf
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28 Teachers’ Knowledge and Misconceptions of Attention Deficit/Hyperactivity Disorder Keetam D. F. Alkahtani Department of Special Education, College of Education, King Saud University, Riyadh, KSA
Teachers can play a key role in identifying and supporting students with Attention Deficit/Hyperactivity Disorder (ADHD). In order to fulfill this important role, it is imperative for teachers to have explicit knowledge about ADHD. The overall aim of this study is to investigate teachers’ knowledge and misconceptions of ADHD. Four hundred and twenty-nine (429) teachers participated. The Knowledge of Attention Deficit Disorder Scale (KADDS) along with a demographic questionnaire was used as the survey instruments to collect data. Descriptive statistics and correlation test were used to analyze the data. Results indicated that teachers’ knowledge of ADHD was insufficient. Teachers’ level of knowledge of ADHD was positively related to their prior training and experience with ADHD (i.e., the number of ADHD courses taken in college or graduate level, and the number of workshops pertaining to ADHD). Teachers’ level of knowledge of ADHD also correlated positively with their level of confidence in teaching a student with ADHD. In spite of a few limitations, the results of this study are valuable for identifying areas where there is a misperception or lack of knowledge among teachers. Keywords: Attention Deficit/Hyperactivity Disorder (ADHD); Teachers’ Knowledge; Misconceptions of ADHD
Introduction Attention Deficit/Hyperactivity Disorder (ADHD), defined by the American Psychiatric Association as a disorder is characterized by a persistent pattern of inattention and/or hyperactivity-impulsivity that is more frequently displayed and more severe than is typically seen in individuals at a comparable level of development (APA, 2000). ADHD is one of the most commonly diagnosed psychiatric disorders of childhood. The American Psychiatric Association, in 2000, estimated the prevalence rate of ADHD to be 3% - 7% among school-age children (APA, 2000). Additionally, in 2004, the American Academy of Pediatrics reported that 6% - 9% of school students have ADHD (AAP, 2004). Given the rate of children with ADHD, most researchers estimated that in every mainstream classroom there will be at least one child with ADHD (Barkley, 2006; DuPaul & Stoner, 2003; DuPaul & Weyandt, 2006; Goldstein et al., 2011). Children with ADHD have significant problems with attention, hyperactivity, and impulsivity which usually cause serious impairments in many areas of functioning (e.g., interpersonal and social relationships, and academic performance). Children with ADHD are often non-compliant with commands, disruptive in the classroom, and impulsive in their behaviors. These children tend to be lagging behind academically and can require extra time and energy from their teachers. Because of these problematic behaviors, teaching children with ADHD can be a hard task for most teachers (Selikowitz, 2004).
Having knowledge of ADHD can increase teachers’ confidence in teaching and managing children with ADHD (Curtis et al., 2006; DuPaul & Stoner, 2003). ADHD has intrigued researchers and become the most researched of all the developmental behavioral disorders. Conversely, ADHD continues to generate controversy. Cooper and Ideus (2002) asserted that “unfortunately, to date, some of the popular debate about [ADHD] has generated far more heat than light” (p. vii). Over the past decade, most published research studies in the area of ADHD have focused on etiology, assessment, and treatment of this disorder. There are also researches concerned with children with ADHD in educational settings. However, only a small number of studies have been conducted to examine teachers’ knowledge and misperception of ADHD. These researches were undertaken following the release of the guidelines for diagnosing children with ADHD (Jerome et al., 1994; Pelham & Evans, 1992). The Diagnostic and Statistical Manual of Mental Disorders, Fourth Edition, Text Revised (DSM-IV-TR) states that symptoms of ADHD must be presented in two or more settings, such as home and school (APA, 2000). Teachers are valuable sources of information with regard to diagnosis of ADHD because of their daily contact with children in a variety of settings (Bussing et al., 1998; Pelham & Evans, 1992). Teachers are frequently involved in the assessment process. According to Carey (1999) more than half of the primary care pediatricians used school reports to arrive at their
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diagnosis of child with ADHD. The goal of diagnosis should not be the diagnosis itself, rather plan interventions that based on the information gathered in the assessment phase (Du-Paul & Stoner, 2003). Therefore, teachers should have accurate knowledge with which they can effectively participate in the process of the assessment and treatment decision-making for children with ADHD. Unfortunately, few studies that have attempted to assess teachers’ knowledge of ADHD suggest that teachers often lack knowledge of ADHD and they tend to have substantial misperceptions about the nature, course, causes and outcomes of ADHD (Barbaresi & Olsen, 1998; Jerome et al., 1994; Sciutto et al., 2000; Snider et al., 2003; Vereb & DiPerna, 2004; West et al., 2005; Weyandt et al., 2009). It was also found that teachers have received little, if any, training related to ADHD (Bussing et al., 2002; Jerome et al., 1994; Sciutto et al., 2000; Kos et al., 2004). This is alarmingly considered that teachers are primarily responsible for referring children with ADHD for assessment, and their frequent involvement in the treatment process (Barkley, 2006; Bussing et al., 2002). This research attempts to further previous studies that investigated teachers’ knowledge of ADHD. Specifically, this research investigated three questions. The questions are: • What is the teachers’ level of knowledge of ADHD? • Is there relationship between teachers’ level of knowledge of ADHD and their prior training and experience with ADHD (the number of ADHD courses taken in college or graduate level, and the number of workshops pertaining to ADHD)? • Is there relationship between teachers’ level of knowledge of ADHD and their level of confidence in teaching a student with ADHD?
Method This is a descriptive research using self-reported questionnaire method. Survey research provide a broad overview of information collected from representative sample of a large population so that inferences can be made about their knowledge, attitudes, characteristics, or behaviors (Cresswell, 2008). This type of research is quantitative in nature and often grounded upon existing practice which allows “making careful descriptions of educational phenomena” (Gall et al., 2007: p. 300). Previous researchers considered survey design as an efficient method in collecting original data to measure teachers’ knowledge about ADHD (Bekle, 2004; Brooka et al., 2000; Canu & Mancil, 2012; Ghanizadeh, et al., 2006; Kos et al., 2004; Jerome et al., 1994; Ohan et al., 2008; Sciutto et al., 2000; Snider et al., 2003; Vereb & DiPerna, 2004; West et al., 2005; White et al., 2011). Self-reported questionnaire method has been chosen, as it is the best available method to achieve the aim of this research.
Procedure The The Knowledge of Attention Deficit Disorders Scale (KADDS) was obtained from Professor Mark Sciutto, who granted permission for the use of KADDS in this research. Permission to conduct this research was obtained from the research department at the middle region. The participants were recruited from thirty-seven (37) randomly selected schools in the middle region. A total of two thousand (2000) questionnaires were administered to preschool through ninth grade
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school teachers. A letter was attached to each questionnaire. The letter explains the purpose of the study and thanking teachers for their cooperation. It was emphasized in the letter that taking part in this study is voluntary, and teachers are not required to identify themselves or their schools on the questionnaire. No incentive was provided for participation. Of the two thousand (2000) questionnaires distributed, four hundred and thirty-one (431) were returned. Two questionnaires were not usable due to substantial missing data. The total number of usable questionnaires for data analysis was four hundred and twenty-nine (429); a usable response rate of more than twenty one percent (21.45%).
Data Collection The Knowledge of Attention Deficit Disorders Scale (KADDS) and a demographic questionnaire were used to collect data from four hundred and twenty-nine (429) teachers. The KADDS is a 36-item rating scale developed by Sciutto and colleagues (Sciutto et al., 2000) to measure teachers’ knowledge and misperceptions of Attention-Deficit/Hyperactivity Disorder. Items in the KADDS questionnaire phrased as statements about ADHD with three option response format: true (T), false (F) or don’t know (DK). These items divided into three specific areas: symptoms/diagnosis of ADHD (9 items), the treatment of ADHD (12 items), and general knowledge about the nature, causes and outcome of ADHD (15 items). The KADDS format allows for the differentiation between what teachers do not know from their misperception of ADHD (Sciutto et al., 2000; Soroa et al., 2013). The KADDS is considered to be “one of the most widely used instruments to assess the level of knowledge of teachers regarding ADHD, and is the first instrument whose indices of reliability and validity were published in this field” (Soroa et al., 2013: p. 156). Internal consistency of the KADDS total score, in previous studies, has ranged from 0.82 to 0.89 (Herbert et al., 2004; Sciutto et al., 2000; Soroa et al., 2013). Cronbach’s alpha value for the current study was 0.76 which indicate an adequate internal consistency.
Results and Discussion Data gathered from the demographic questionnaire and KADDS were analyzed using a computer statistical software program, Statistical Package for the Social Sciences (SPSS). Descriptive statistics were used to describe characteristics of the study participants. The mean age of the participants was 34.18 (range, 23 - 59 years), with a standard deviation of 7.61. Participants reported an average of 10.48 years of teaching experience (standard deviation = 7.45; range, 1 - 39 years). As shown on Table 1, forty four and a half percent (44.5%, n = 191) of the participants were male, and fifty five and a half percent (55.5%, n = 238) were female. In terms of participants’ education, the vast majority had a bachelor’s degree (96.5%, n = 414); while less than four percent (3.3%, n = 14) were holding a master degree. Of the 429 participants, 389 (90.7%) were general education teachers, and 40 (9.3%) were special education teachers. The number of respondents from urban areas was 379 (88.3), while 35 (8.2%) from suburban, and 15 (3.5%) from schools located in rural areas. Teachers’ overall percentage score of correct responses (items answered correctly) was 17.2% which reflect poor knowledge of ADHD. Incorrect responses (items answered incorrectly) percentage was 23% which indicate misperceptions
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Table 1. The demographic characteristics of the participants (N = 429). Variable
Frequency (n) Percentage (%)
Gender Male
191
44.5
Female
238
55.5
Bachelor degree.
414
96.5
Master degree.
14
3.3
Doctoral degree.
0
0
General education teacher.
389
90.7
Special education teacher.
40
9.3
15
3.5
Educational Level
Educational Role
School Location Rural. Suburban.
35
8.2
Urban.
379
88.3
of ADHD. Don’t know responses (items that teachers admitted they just don’t know) percentage was 59.8% which point to a lack of knowledge of ADHD among teachers. Teachers’ overall percentage score of the correct, incorrect, and don’t know responses are presented graphically in Figure 1. In order to examine teachers’ knowledge within each of the KADDS subscales, their responses were grouped to represent the three subscales of KADDS. Table 2 presents teachers’ responses on the first subscale which include 15 items assessing general knowledge about the nature, causes and outcome of ADHD. Nearly seventeen (16.8%) of the teachers responded correctly, while (26.2%) responded incorrectly, and (57%) responded “don’t know” to these items. The highest proportion of correct responses (30%, n = 129) and also the lowest incorrect responses (4%, n = 17) were on item 32, “The majority of ADHD children evidence some degree of poor school performance in the elementary school years”, which signify that only less than the third of the teachers knew that most children with ADHD have difficulty with academic performance. The lowest proportion of correct responses (3.5%, n = 15) and also the highest incorrect responses (68.1%, n = 292) were on item 22, “If an ADHD child is able to demonstrate sustained attention to video games or TV for over an hour, that child is also able to sustain attention for at least an hour of class or homework”, which indicate that the majority of teachers have misconceptions about the change of ADHD symptoms across tasks and settings. The majority of teachers (76.7%, n = 329) selected “don’t know” option to answer item 28, “There are specific physical features which can be identified by medical doctors (e.g. pediatrician) in making a definitive diagnosis of ADHD”, which point out that more than two-third of the teachers showed lack of knowledge about the fact that there is no medical examination to confirm the diagnosis of ADHD. Table 3 presents teachers’ responses on the second subscale of KADDS which include 9 items assessing symptoms/diagnosis of ADHD. Eighteen and one-tenth percent (18.1%) of the teachers responded correctly, while (22.8%) responded incorrectly, and (59.1%) responded “don’t know” to these items. The highest proportion of correct responses (38.9%, n = 167) was on item 9, “ADHD children often fidget or squirm in their seats”, which indicate that less than half of the teachers were
Figure 1. Teachers’ overall percentage score of the correct, incorrect, and don’t know responses on the KADDS.
aware of one of the hallmark symptoms of ADHD. The lowest proportion of correct responses (13.3%, n = 57) and also the highest incorrect responses (19.6%, n = 84) were on item 11, “It is common for ADHD children to have an inflated sense of self-esteem or grandiosity”, which show that less than onefourth of the teachers thought mistakenly that children with ADHD have an inflated self-esteem. The majority of teachers (77.9%, n = 334) selected “don’t know” option to answer item 16, “Current wisdom about ADHD suggests two clusters of symptoms: One of inattention and another consisting of hyperactivity/impulsivity”, which point out that more than two-third of the teachers showed lack of knowledge about the subtypes of ADHD. Table 4 presents teachers’ responses on the third subscale of KADDS which include 12 items assessing the treatment of ADHD. Sixteen and six-tenth percent (16.6%) of the teachers responded correctly, while (20.4%) responded incorrectly, and (63%) responded “don’t know” to these items. The highest proportion of correct responses (26.3%, n = 113) was on item 10, “Parent and teacher training in managing an ADHD child are generally effective when combined with medication treatment”, which indicate that only about the fourth of the teachers knew that an effective treatment of ADHD should be multifaceted and comprehensive. The highest proportion of incorrect responses (26.8%, n = 115) was on item 23, “Reducing dietary intake of sugar or food additives is generally effective in reducing the symptoms of ADHD”, which show that more than one-fourth of the teachers hold a misperception about the effectiveness of the diet on the symptoms of ADHD as they thought mistakenly that the symptoms of ADHD will reduce with the reduction of sugar and or food additives in the diet of children with ADHD. The lowest proportion of both correct responses (7%, n = 30) and incorrect responses (4.4%, n = 19) were on item 35, “Electroconvulsive Therapy (i.e. shock treatment) has been found to be an effective treatment for severe cases of ADHD”. Responses on this item revealed that although less than five percent of the teachers have a misperception, only seven percent were aware that there is no evidence of the effectiveness of this type of treatment for children with ADHD. Item 35 also has the highest percentage (88.3%, n = 379) for don’t know responses, pointing to lack of knowledge among the majority of the teachers. Percentage of teachers’ score of the correct, incorrect, and don’t know responses on the KADDS subscales are presented graphically in Figure 2. Two-tailed Pearson correlation analysis was computed to in-
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Table 2. Participants’ responses on the first subscale of KADDS which include 15 items pertain to general knowledge about the nature, causes and outcome of ADHD (N = 429). Items
CA
Number of responses Correct
Incorrect
Don’t Know
50 (11.7%)
318 (73.7%)
1. Most estimates suggest that ADHD occurs in approximately 15% of school age children.
F
62 (14.5%)
4. ADHD children are typically more compliant with their fathers than with their mothers.
T
69 (16.1%)
53 (12.4%)
303 (70.6)
6. ADHD is more common in the 1st degree biological relatives (i.e. mother, father) of children with ADHD than in the general population.
T
81 (18.9%)
49 (11.4%)
296 (69.7%)
13. It is possible for an adult to be diagnosed with ADHD.
T
57 (13.3%)
60 (14.1%)
309 (72.1%)
17. Symptoms of depression are found more frequently in ADHD children than in non-ADHD children.
T
47 (11 %)
62 (14.5%)
318 (74.5%)
19. Most ADHD children “outgrow” their symptoms by the onset of puberty and subsequently function normally in adulthood.
F
29 (6.8%)
78 (18.2%)
320 (74.6%)
22. If an ADHD child is able to demonstrate sustained attention to video games or TV for over an hour, that child is also able to sustain attention for at least an hour of class or homework.
F
15 (3.5%)
292 (68.1%)
121 (28.2%)
24. A diagnosis of ADHD by itself makes a child eligible for placement in special education.
F
30 (7.0%)
104 (24.2%)
292 (68.1%)
27. ADHD children generally experience more problems in novel situations than in familiar situations.
F
50 (11.7%)
54 (12.6%)
323 (75.3%)
28. There are specific physical features which can be identified by medical doctors (e.g. pediatrician) in making a definitive diagnosis of ADHD.
F
23 (5.4%)
73 (17%)
329 (76.7%)
29. In school age children, the prevalence of ADHD in males and females is equivalent.
F
28 (6.5%)
78 (18.2%)
320 (74.6%)
30. In very young children (less than 4 years old), the problem behaviors of ADHD children (e.g. hyperactivity, inattention) are distinctly different from age-appropriate behaviors of non-ADHD children.
F
38 (8.9%)
79 (18.4%)
309 (72%)
31. Children with ADHD are more distinguishable from normal children in a classroom setting than in a free play situation.
T
64 (14.9%)
42 (9.8%)
322 (75.1%)
32. The majority of ADHD children evidence some degree of poor school performance in the elementary school years.
T
129 (30%)
17 (4%)
283 (66%)
33. Symptoms of ADHD are often seen in non-ADHD children who come from inadequate and chaotic home environments.
T
68 (15.9%)
40 (9.3%)
320 (74.6%)
CA = Correct Answer; T = True; F = False.
Table 3. Participants’ responses on the second subscale of KADDS which include 9 items pertain to symptoms/diagnosis of ADHD (N = 429). Items
CA
Number of responses Correct
Incorrect
Don’t Know
47 (11.2 %)
272 (63.4%)
3. ADHD children are frequently distracted by extraneous stimuli.
T
109 (25.4%)
5. In order to be diagnosed with ADHD, the child's symptoms must have been present before age 7.
T
68 (15.9%)
49 (11.4%)
296 (71.3%)
7. One symptom of ADHD children is that they have been physically cruel to other people.
F
59 (13.8%)
75 (17.5%)
291 (68.5%)
9. ADHD children often fidget or squirm in their seats.
T
167 (38.9%)
36 (8.4%)
225 (52.4%)
11. It is common for ADHD children to have an inflated sense of self-esteem or grandiosity.
F
57 (13.3%)
84 (19.6%)
287 (66.9%)
14. ADHD children often have a history of stealing or destroying other people’s things.
F
72 (16.8%)
42 (9.8%)
314 (73.4%)
16. Current wisdom about ADHD suggests two clusters of symptoms: One of inattention and another consisting of hyperactivity/impulsivity.
T
65 (15.2%)
27 (6.3%)
334 (77.9%)
21. In order to be diagnosed as ADHD, a child must exhibit relevant symptoms in two or more settings (e.g., home, school).
T
68 (15.9%)
45 (10.5%)
311 (72.5%)
26. ADHD children often have difficulties organizing tasks and activities.
T
111 (25.9%)
26 (6.1%)
289 (67.4%)
CA = Correct Answer; T = True; F = False.
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Table 4. Participants’ responses on the third subscale of KADDS which include 12 items pertain to the treatment of ADHD (N = 429). Items
CA
Number of responses Correct
Incorrect
Don’t Know
F
51 (11.9%)
66 (15.4%)
312 (72.7%)
8. Antidepressant drugs have been effective in reducing symptoms for many ADHD children.
T
54 (12.6%)
56 (15.2%)
309 (72.2%)
10. Parent and teacher training in managing an ADHD child are generally effective when combined with medication treatment.
T
113 (26.3%)
37 (8.6%)
279 (65.1%)
12. When treatment of an ADHD child is terminated, it is rare for the child's symptoms to return.
F
58 (13.5%)
78 (18.2%)
292 (68.1%)
15. Side effects of stimulant drugs used for treatment of ADHD may include mild insomnia and appetite reduction.
T
69 (16.1%)
32 (7.5%)
328 (76.5%)
18. Individual psychotherapy is usually sufficient for the treatment of most ADHD children.
F
55 (12.8%)
60 (14%)
312 (73.1%)
20. In severe cases of ADHD, medication is often used before other behavior modification techniques are attempted.
T
64 (14.9%)
34 (7.9%)
330 (76.9%)
23. Reducing dietary intake of sugar or food additives is generally effective in reducing the symptoms of ADHD.
F
37 (8.6%)
115 (26.8%)
272 (63.4%)
25. Stimulant drugs are the most common type of drug used to treat children with ADHD.
T
34 (7.9%)
65 (15.2%)
327 (76.2%)
34. Behavioral/Psychological interventions for children with ADHD focus primarily on the child’s problems with inattention.
F
36 (8.4%)
90 (21%)
303 (70.6%)
35. Electroconvulsive Therapy (i.e. shock treatment) has been found to be an effective treatment for severe cases of ADHD.
F
30 (7%)
19 (4.4%)
379 (88.3%)
36. Treatments for ADHD which focus primarily on punishment have been found to be the most effective in reducing the symptoms of ADHD.
F
78 (18.2%)
39 (9.1%)
311 (72.5%)
2. Current research suggests that ADHD is largely the result of ineffective parenting skills.
CA = Correct Answer; T = True; F = False.
tively with their level of confidence in teaching a student with ADHD.
Conclusion
Figure 2. Percentage of teachers’ score of the correct, incorrect, and don’t know responses on the KADDS subscales.
vestigate the relationship between teachers’ level of knowledge of ADHD and their prior training and experience with ADHD (i.e., the number of ADHD courses taken in college or graduate level, and the number of workshops pertaining to ADHD ). The result of the correlational analysis was statistically significant (r = 0.311, p < 0.01). This result shows a strong positive correlation between teachers’ level of knowledge of ADHD and their prior training and experience with ADHD. Two-tailed Pearson correlation analysis was also carried out to examine the relationship between teachers’ level of knowledge of ADHD and their level of confidence in teaching a student with ADHD. The result of the correlational analysis was statistically significant (r = 0.631, p < 0.01). This result shows that teachers’ level of knowledge of ADHD correlated posi-
Teachers have a major role in the identification and assessment of students with ADHD. This study was intended to examine teachers’ knowledge and misperceptions of ADHD. Three major study findings emerged. First, teachers’ scores on KADDS were fairly low, pointing to a significant lack of knowledge about ADHD. Second, teachers’ level of knowledge of ADHD was positively related to their prior training and experience with ADHD. Third, teachers’ level of knowledge of ADHD correlated positively with their level of confidence in teaching a student with ADHD. Results from this study concur with the findings of previous studies (Bekle, 2004; Brooka et al., 2000; Canu & Mancil, 2012; Ghanizadeh et al., 2006; Kos et al., 2004; Jerome et al., 1994; Ohan et al., 2008; Sciutto et al., 2000; Snider et al., 2003; Vereb & DiPerna, 2004; West et al., 2005) showing that teachers lack adequate knowledge. Results from this study also bring light to the fact that teachers need to be educated and supported to further their professional development regarding ADHD through in-service training. Teachers who are knowledgeable about ADHD are better prepared to be in a position to offer adequate teaching, assistance, and support for children with ADHD (Goldstein et al., 2011; Lerner et al., 1995). The limitations of this study that deserve consideration in future investigations include the instrumentation used to collect data. Sciutto and colleagues provide cited references for each item of KADDS. However, the existing research on ADHD is
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Teachers’ Knowledge and Misconceptions of Attention Deficit/Hyperactivity Disorder
conflicting (Barkley, 2006; Cooper & Ideus, 2002; Richard, 2000; Weiss & Hechtman, 1993). Thus, using scientific literature to construct and support the KADDS is problematic. In addition, the KADDS, being a self-reported measure, is possibly subjective in nature. This research is also limited by the use of correlation analysis. This type of statistical analysis provides understanding the nature of relationships between variables, but it does not indicate what causes the relationship which limits drawing conclusions about outcomes and causes. Although the sample size was large (n = 429), there were a large number of unreturned questionnaires (78.55%). The generalizability of the results is limited by low response rate (21.45%) and the fact that only one geographical region was included in this study. In spite of these limitations, the results of this study are valuable for identifying areas where there is a misperception or lack of knowledge among teachers.
Acknowledgements I would like to thank Professor Mark Sciutto who kindly gave his permission for the use of KADDS in this research. I also gratefully acknowledge that this research project was supported by a grant from the Research Center for the Humanities, Deanship of Scientific Research, King Saud University.
REFERENCES AAP, American Academy of Pediatrics (2004). ADHD: A complete and authoritative guide. Elk Grove Village, I1: Author. APA, American Psychiatric Association (2000). Diagnostic and statistical manual of mental disorders (4th ed.). Washington, DC: Author. Barkley, R. (2006). Attention deficit hyperactivity disorder: A handbook for diagnosis and treatment. New York: Guilford Press. Bekle, B. (2004). Knowledge and attitudes about Attention-Deficit Hyperactivity Disorder (ADHD): A comparison between practicing teachers and undergraduate education students. Journal of Attention Disorders, 7, 151-161. Brooka, U., Watembergb, N., & Gevac, D. (2000). Attitude and knowledge of attention deficit hyperactivity disorder and learning disability among high school teachers. Patient Education and Counseling, 40, 247-252. Bussing, R., Schoenberg, N., & Perwien, A. (1998). Knowledge and information about ADHD: Evidence of cultural differences among African-American and white parents. Social Science & Medicine, 46, 919-928. Bussing, R., Gary, F., Leon, C, Garvan, C., & Reid, R. (2002). General classroom teachers’ information and perceptions of attention deficit hyperactivity disorder. Behavioral Disorder, 27, 327-339. Canu, W., & Mancil, E. (2012). An examination of teacher trainees’ knowledge of attention-deficit/hyperactivity disorder. School Mental Health, 4, 105-114. Carey, W. (1999). Problems diagnosing attention and activity. Pediatrics, 103, 664-667. Curtis, D., Pisecco, S., Hamilton, J., & Moore, D. (2006). Teachers perceptions of classroom intervention for children with ADHD: A cross-cultural comparison of teachers in the United States and New Zealand. School Psychology Quarterly, 21, 171-196. Cooper, P., & Ideus, K. (2002). Attention deficit/hyperactivity disorder: A practical guide for teachers. London: David Fulton Publishers Ltd. Creswell, J. (2008). Educational research: Planning, conducting, & evaluating quantitative and qualitative research. Upper Saddle River, NJ: Merrill Prentice Hall. DuPaul, G., & Stoner, G. (2003). ADHD in the schools assessment and intervention strategies. New York: The Guilford Press.
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DuPaul, G., & Weyandt, L. (2006). School-based intervention for children with attention deficit hyperactivity disorder: Effects on academic, social, & behavioural functioning. International Journal of Disability, Development and Education, 53, 161-176. Barbaresi, W., & Olsen, R. (1998). An ADHD educational intervention for elementary schoolteachers: A pilot study. Developmental and Behavioral Pediatrics, 19, 94-100. Gall, M., Gall, J., & Borg, R. (2007). Educational research: An introduction (8th ed.). New York, NY: Pearson Education. Ghanizadeh, A., Bahredar, M., & Moeini, S. (2006). Knowledge and attitudes towards attention deficit hyperactivity disorder among elementary school teachers. Patient Education and Counselling, 63, 84-88. Goldstein, S., Naglieri, J., & DeVries, M. (2011). Learning and Attention Disorders in Adolescence and Adulthood: Assessment and Treatment (2nd ed.). John Wiley & Sons. Herbert, J., Crittenden, K., & Dalrymple, K. (2004). Knowledge of Social Anxiety Disorder Relative to Attention Deficit Hyperactivity Disorder Among Educational Professionals. Journal of Clinical Child and Adolescent Psychology, 33, 366-372. Jerome, L., Gordon, M., & Hustler, P. (1994). A comparison of American and Canadian teachers’ knowledge and attitudes towards Attention Deficit Hyperactivity Disorder (ADHD). Canadian Journal of Psychiatry, 39, 563-567. Lerner, J., Lowenstein, B., & Lerner, S. (1995). Attention deficit disorders: Assessment and teaching. Pacific Grove, CA: Brooks/Cole. Kos, J., Richdale, A., & Jackson, S. (2004). Knowledge about attention deficit hyperactivity disorder: A comparison of in-service and preservice teachers. Psychology in the Schools, 41, 517-526. Ohan, J., Cormier, N., Hepp, S., Visser, T., & Strain, M. (2008). Does knowledge about attention-deficit/hyperactivity disorder impact teachers’ reported behaviors and perceptions? School Psychology Quarterly, 23, 436-449. Pelham J., & Evans, W. (1992). Teacher ratings of DSM-III-R symptoms for the disruptive behavior disorders: Prevalence, factor analysis, & conditional probabilities in a special education sample. School Psychology Review, 21, 285-300. Richard, M. (2000). Dispelling the myths and misconceptions about ADHD. In: B. Guyer (Ed.), ADHD: Achieving success in school and life. Boston: Allyn and Bacon. Soroa, M., Gorostiaga, A., & Balluerka, N. (2013). Review of Tools Used for Assessing Teachers’ Level of Knowledge with Regards Attention Deficit Hyperactivity Disorder (ADHD). In S. Banerjee (Ed.), Attention Deficit Hyperactivity Disorder in Children and Adolescents. Sciutto, M., Terjesen, M., & Bender, A. (2000). Teachers’ knowledge and misperceptions of Attention-Deficit/Hyperactivity Disorder. Psychology in the Schools, 37, 115-122.
Sciutto, M. J., & Eisenberg, M. (2007). Evaluating the evidence for and against the overdiagnosis of ADHD. Journal of Attention Disorders, 1, 106-113. Selikowitz, M., (2004). ADHD: The facts. Oxford: Oxford University Press. Snider, V., Busch, T., & Arrowood, L. (2003). Teacher knowledge of stimulant medication and ADHD. Remedial and Special Education, 24, 46-56. Vereb, R., & DiPerna, J. (2004). Teachers’ knowledge of ADHD, treatments for ADHD, & treatment acceptability: An initial investigation. School Psychology Review, 33, 421-428. West, J., Taylor, M., Houghton, S., & Hudyma, S. (2005). A comparison of teachers’ and parents’ knowledge and beliefs about attentiondeficit/hyperactivity disorder (ADHD). School Psychology International, 26, 192-208.
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Psychology Handbook
Weiss, G., & Hechtman, L. (1993). Hyperactive children grown up. New York: Guilford Press. Weyandt, L., Fulton, M., Schepman, S., Verdi, G., & Wilson, K. (2009). Assessment of teacher and school psychologist knowledge of attention-deficit/hyperactivity disorder. Psychology in the Schools, 46, 951-960.
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Permissions The contributors of this book come from diverse backgrounds, making this book a truly international effort. This book will bring forth new frontiers with its revolutionizing research information and detailed analysis of the nascent developments around the world. We would like to thank all the contributing authors for lending their expertise to make the book truly unique. They have played a crucial role in the development of this book. Without their invaluable contributions this book wouldn’t have been possible. They have made vital efforts to compile up to date information on the varied aspects of this subject to make this book a valuable addition to the collection of many professionals and students. This book was conceptualized with the vision of imparting up-to-date information and advanced data in this field. To ensure the same, a matchless editorial board was set up. Every individual on the board went through rigorous rounds of assessment to prove their worth. After which they invested a large part of their time researching and compiling the most relevant data for our readers. Conferences and sessions were held from time to time between the editorial board and the contributing authors to present the data in the most comprehensible form. The editorial team has worked tirelessly to provide valuable and valid information to help people across the globe. Every chapter published in this book has been scrutinized by our experts. Their significance has been extensively debated. The topics covered herein carry significant findings which will fuel the growth of the discipline. They may even be implemented as practical applications or may be referred to as a beginning point for another development. Chapters in this book were first published by Scientific Research Publishing Inc.; hereby published with permission under the Creative Commons Attribution License or equivalent. The editorial board has been involved in producing this book since its inception. They have spent rigorous hours researching and exploring the diverse topics which have resulted in the successful publishing of this book. They have passed on their knowledge of decades through this book. To expedite this challenging task, the publisher supported the team at every step. A small team of assistant editors was also appointed to further simplify the editing procedure and attain best results for the readers. Our editorial team has been hand-picked from every corner of the world. Their multi-ethnicity adds dynamic inputs to the discussions which result in innovative outcomes. These outcomes are then further discussed with the researchers and contributors who give their valuable feedback and opinion regarding the same. The feedback is then collaborated with the researches and they are edited in a comprehensive manner to aid the understanding of the subject. Apart from the editorial board, the designing team has also invested a significant amount of their time in understanding the subject and creating the most relevant covers. They scrutinized every image to scout for the most suitable representation of the subject and create an appropriate cover for the book. The publishing team has been involved in this book since its early stages. They were actively engaged in every process, be it collecting the data, connecting with the contributors or procuring relevant information. The team has been an ardent support to the editorial, designing and production team. Their endless efforts to recruit the best for this project, has resulted in the accomplishment of this book. They are a veteran in the field of academics and their pool of knowledge is as vast as their experience in printing. Their expertise and guidance has proved useful at every step. Their uncompromising quality standards have made this book an exceptional effort. Their encouragement from time to time has been an inspiration for everyone. The publisher and the editorial board hope that this book will prove to be a valuable piece of knowledge for researchers, students, practitioners and scholars across the globe.
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List of Contributors Robert M. Gordon Independent Practice, Allentown, USA Ronald W. Stoffey Psychology Department, Kutztown University, Kutztown, USA Bethany L. Perkins Department of Education and Human Services, Lehigh University, Bethlehem, USA Takeharu Seno Institute for Advanced Study, Kyushu University, Fukuoka, Japan Faculty of Design, Kyushu University, Fukuoka, Japan Research Center for Applied Perceptual Science, Kyushu University, Fukuoka, Japan George H. Van Doorn School of Applied Media and Social Sciences, Monash University, Melbourne, Australia Mandana Shirazi Education Development Center, Medical Education Department, Tehran University of Medical Sciences, Tehran, Iran, Departments of LIME and Clinical Science and Education, Södersjukhuset, Karolinska Institutet, Stockholm, Sweden Sagar V. Parikh University of Toronto, Toronto, Canada Ideh Dadgaran Medical-Surgical Nursing Department, Langroud Nursing and Midwifery School, Guilan University of Medical Sciences (GUMS), Rasht, Iran Research in Medical Education, Education Development Center (EDC), Guilan University of Medical Sciences (GUMS), Rasht, Iran Charlotte Silén Center for Medical Education, Department of Learning, Informatics, Medical Management and Ethics (LIME), Karolinska Institutet, Stockholm, Sweden Haitham Taha The Cognitive Lab for Reading and Learning-Sakhnin College for Teachers’ Education, Sakhnin, Israel Safra Brain Research Center for Learning Disabilities-Haifa University, Haifa, Israel Karen Hussar and Jared Horvath Fisher College, Boston, USA Andrea Gaggioli, Luca Morganti, Maurizio Mondoni and Alessandro Antonietti Università Cattolica del Sacro Cuore, Milano, Italy Wen Wen Advanced Research Centers, Keio University, Tokyo, Japan Hideaki Kawabata Department of Psychology, Faculty of Letters, Keio University, Tokyo, Japan Sarah Terrien Université de Reims Champagne-Ardenne, Laboratoire Cognition, Santé, Socialisation C2S EA 6291, Reims, France Service de Psychiatrie des Adultes, Hôpital Robert Debré, CHU de Reims, Reims, France Pôle d’Imagerie Médicale, Hôpital Maison-Blanche, CHU de Reims, Reims, France
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205
Fabien Gierski Université de Reims Champagne-Ardenne, Laboratoire Cognition, Santé, Socialisation C2S EA 6291, Reims, France Service de Psychiatrie des Adultes, Hôpital Robert Debré, CHU de Reims, Reims, France Pôle d’Imagerie Médicale, Hôpital Maison-Blanche, CHU de Reims, Reims, France Stéphanie Caillies and Véronique Baltazart Université de Reims Champagne-Ardenne, Laboratoire Cognition, Santé, Socialisation C2S EA 6291, Reims, France Christophe Portefaix and Laurent Pierot Pôle d’Imagerie Médicale, Hôpital Maison-Blanche, CHU de Reims, Reims, France Chrystel Besche-Richard Université de Reims Champagne-Ardenne, Laboratoire Cognition, Santé, Socialisation C2S EA 6291, Reims, France Institut Universitaire de France, Paris, France Shoko Yamane Faculty of Economics, Kinki University, Osaka, Japan Taiki Takahashi Department of Behavioral Science, Center for Experimental Research in Social Sciences, Hokkaido University, Hokkaido, Japan Akiko Kamesaka School of Business Administration, Aoyama Gakuin University, Tokyo, Japan Yoshiro Tsutsui Graduate School of Economics, Osaka University, Osaka, Japan Fumio Ohtake Institute of Social and Economic Research, Osaka University, Osaka, Japan Tzu-Fen Chang and Esther E. Onaga Department of Human Development and Family Studies, Michigan State University, East Lansing, USA Eun-Jin Han Department of Social Welfare, Seoul Women’s University, Seoul, South Korea M. Brent Donnellan Department of Psychology, Michigan State University, East Lansing, USA Bill Thornton Department of Psychology, University of Southern Maine, Portland, USA Richard M. Ryckman and Joel A. Gold Department of Psychology, University of Maine, Orono, USA Laura Marcos-Arribas Social and Human Sciences Faculty, Comillas Pontifical University, Madrid, Spain Justino Jiménez Almonacid and Alberto Marcos Dolado Neurology Department, Hospital Clínico San Carlos, Madrid, Spain Lily Halsted Queens University of Charlotte, Charlotte, USA Yota Xanthacou, Thomas Babalis and Nektarios A. Stavrou University of Athens, Athens, Greece Eddy J. Davelaar Department of Psychological Sciences, Birkbeck, University of London, London, UK
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List of Contributors
Patrizio Tressoldi Dipartimento di Psicologia Generale, Università di Padova, Padova, Italy Gizelle L. Gilbert Phoenix Day School for the Deaf, Phoenix, USA Candace Myers, M. Diane Clark, Shelley Williams and Angela McCaskill Gallaudet University, Washington DC, USA Peter Horvath and Vanessa McColl Department of Psychology, Acadia University, Wolfville, Canada M. Diane Clark, Song Hoa Choi and Thomas E. Allen Gallaudet University, Washington DC, USA Sharon Baker Mary K. Chapman Center, University of Tulsa, Tulsa, USA Satomi Hara College of Arts and Sciences, The University of Tokyo, Tokyo, Japan ERATO, Okanoya Emotional Information Project, Japan Science Technology Agency, Saitama, Japan Kentaro Katahira Center for Evolutionary Cognitive Sciences, The University of Tokyo, Tokyo, Japan Emotional Information Joint Research Laboratory, RIKEN Brain Science Institute, Saitama, Japan Kazuo Okanoya ERATO, Okanoya Emotional Information Project, Japan Science Technology Agency, Saitama, Japan Center for Evolutionary Cognitive Sciences, The University of Tokyo, Tokyo, Japan Emotional Information Joint Research Laboratory, RIKEN Brain Science Institute, Saitama, Japan Graduate School of Arts and Sciences, The University of Tokyo, Tokyo, Japan Rita de Cássia Coutinho Vieira Fornasari, Tais Ferreira De Lima and Sylvia Maria Ciasca Department of Neurology, Research Laboratory of Learning and Attention Disorders (DISAPRE), School of Medical Sciences, State University of Campinas (UNICAMP) Campinas, São Paulo, Brazil Izumi Uehara Department of Psychology, Ochanomizu University, Tokyo, Japan Tianmei Zhou School of Educational Science, Neijiang Normal University, Neijiang, China Jiewei Chen School of Foreign Languages, Neijiang Normal University, Neijiang, China Li Luo School of Geography & Resources Science, Neijiang Normal University, Neijiang, China Jalal Younesi and Akram Alsadat Mirafzal University of Social Welfare and Rehabilitation Sciences, Tehran, Iran Tatjana Alexander Department of Rehabilitation Psychology, Albrecht-Ludwigs-University of Freiburg, Freiburg, Germany Rainer Oesterreich Department of Quantitative Methods, University of Technology, Berlin, Germany Masayo Uji Department of Bioethics, Kumamoto University Graduate School of Life Sciences, Kumamoto, Japan
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Yukihiro Takagishi Department of Human Psychology, Kansai University of International Studies, Miki, Japan Keiichiro Adachi Department of Psychology, Kobe Shoin Women’s University, Kobe, Japan Toshinori Kitamura Kitamura Mental Health Institute Tokyo, Akasaka, Japan Silvana B. Gaino Health Sciences Center, Federal University of Bahia’s Reconcavo, Santo Antonio de Jesus, Brazil Francisco Baptista Assumpção Jr. and Gerson Silva Santos Neto Institute of Psychology, University of Sao Paulo, São Paulo, Brazil Victor Galvao Universidade Federal do Reconcavo da Bahia, Cruz das Almas, Brazil Keetam D. F. Alkahtani Department of Special Education, College of Education, King Saud University, Riyadh, KSA
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