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Relations of self-efficacy to symptoms of depression and anxiety in adolescents with learning disabilities Mercer, Kay Louise 2004

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RELATIONS OF SELF-EFFICACY TO S Y M P T O M S O F DEPRESSION A N D A N X I E T Y I N A D O L E S C E N T S W I T H L E A R N I N G DISABILTIES by K A Y LOUISE M E R C E R B.A., University of Queensland, 1975 B.Ed., University of Alberta, 1979 M . A . , University of British Columbia, 1985  A THESIS S U B M I T T E D I N P A R T I A L F U L F I L M E N T O F T H E REQUIREMENTS FOR T H E DEGREE OF DOCTOR OF PHILOSOPHY in T H E F A C U L T Y O F G R A D U A T E STUDIES .• . ••  . ScWco* ;/ Psychology.  .•• >  We accept this thesis as conforming to the required standard  T H E U N I V E R S I T Y O F BRITISH C O L U M B I A July 2004 © K a y Louise Mercer, 2004  11  Abstract This study examined relationships between self-efficacy and symptoms of depression and anxiety i n a sample of adolescents (n = 83), aged 13 to 17 years of age, who were receiving special education support on the basis of their school-based identification as students w i t h learning disabilities. This study also examined these relationships w i t h i n two subsets of the sample, those participants who met "traditional" aptitude-achievement learning disability identification criteria and those who could be classified as having reading disabilities. The participants, w h o were all volunteers, completed measures assessing their academic skills (Wide Range Achievement Test - 3rd Edition and the Gray Silent Reading Tests), their perceptions of self-efficacy (Academic, Reading, Social, and Emotional Self-Efficacy Questionnaires) and social support (Social Support Questionnaire), and their experience of life events (Life Events Questionnaire) and symptoms of depression (Reynolds Adolescent Depression Scale - 2nd Edition) and anxiety (Multidimensional Anxiety Scale for Children). A s expected, emotional and social self-efficacy were strong predictors of symptoms of both depression and anxiety. Contrary to expectations, however, neither academic nor reading self-efficacy was a strong predictor of these symptoms. Also contrary to expectations, females d i d not report higher symptom levels than males, and participants who experienced particular difficulties i n the highly salient area of reading did not report higher symptom levels and lower self-efficacy than other participants in the sample. The most depressed and anxious participants were slightly older, perceived themselves to be less efficacious emotionally, were less satisfied w i t h the social support available to them, and reported experiencing more negative life events than participants  Ill  who reported the lowest levels of depression and anxiety. For these adolescents, who were receiving in-school academic support, social-emotional factors were more strongly associated w i t h their experience of symptomatology than were academic factors. The prevalence of clinically significant symptoms of depression w i t h i n this sample (6%) was considerably lower than previous estimates for adolescents from the general population and for adolescents with learning disabilities. In contrast, the prevalence of clinically significant symptoms of anxiety (10.8%) and comorbid depression and anxiety (3.6%) was consistent with previous estimates for adolescents from the general population. Implications of these findings and directions for future research are discussed.  iv  Table of Contents Abstract  ii  Table of Contents  iv  List of Tables  viii  List of Figures  xi  Acknowledgement  xii  Chapter i  INTRODUCTION A.  Self-Efficacy: Effects on Academic and Social Functioning  2  B.  Self-Efficacy: Effects on Affective Functioning  4  C.  Self-Efficacy and Cognitive Models of Depression  5  D.  The Contribution of Self-Efficacy to Depression and Anxiety  7  E.  Adolescents w i t h Learning Disabilities  8  F.  Rationale for the Study  10  G. Chapter 2  1  Summary of Research Questions  11  LITERATURE REVIEW  14  A.  14  B.  Adolescent Depression 1. Conceptualizing and Defining Depression  15  2. Measuring Depression  20  3. Prevalence of Depression  24  4. A g e and Gender Effects  29  5. Negative Outcomes Associated w i t h Depression  31  6. Conclusions regarding Adolescent Depression ...  32  Adolescent Anxiety  33  1. Conceptualizing and Defining Anxiety  33  2. Measuring Anxiety  36  3. Prevalence of Anxiety  38  4. A g e and Gender Effects  4  1  V  Chapter 2 (cont.)  5. Negative Outcomes Associated w i t h Anxiety  42  6. Conclusions regarding Adolescent Anxiety  43  C.  Comorbidity of Depression and Anxiety  D.  Depression and Anxiety i n Adolescents w i t h Learning Disabilities  43  45  1. Defining and Identifying Learning and Reading Disabilities  46  2. Research: Learning Disabilities and Depression ..  52  3. Research: Learning Disabilities and Anxiety  58  4. Conclusions: Depression and Anxiety i n Adolescents w i t h Learning Disabilities E.  The Self-Efficacy M o d e l of Depression  E  Research on Self-Efficacy and Depression and Anxiety  G.  Chapter 3  61 61  64  1. Social Self-Efficacy  65  2. Academic Self-Efficacy  67  3. Emotional Self-Efficacy  67  The Role of Life Events and Social Support  68  1. Life Events  68  2. Social Support  69  H.  Rationale for the Study  71  I.  Summary of Research Questions and Hypotheses ....  74  METHOD  76  A.  Design  7  B.  Participants  77  C.  Learning Disabilities and Reading Disabilities  80  D.  Measures  85  6  1. Demographic Information  85  2. Cognitive Ability  88  3. Academic Skills  9°  vi  Chapter 3 (cont.)  Chapter 4  4. Perceptions of Self-Efficacy  92  5. Social Support and Life Events  94  6. Symptoms of Depression and Anxiety  96  E.  Procedure  100  F.  Data Analysis  102  1. Preliminary Analyses  103  2. Primary Analyses  104  RESULTS  107  A . Preliminary Analyses  108  B. Primary Analyses  118  1. Prevalence and Severity of Depression and Anxiety  118  2. The Role of Self-Efficacy i n Predicting Depression and Anxiety  123  3. Social Support  129  4. Life Events  131  5. Gender  134  6. Reading Disabilities  136  7. Factors Associated w i t h the Experience of Depression and Anxiety  Chapter 5  144  C. Summary of Findings  147  DISCUSSION  152  Prevalence and Severity of Depression and Anxiety  154  The Relationship of Self-Efficacy to Depression and Anxiety  157  Social Support and Life Events  160  Reading Disabilities  *6i  Strengths and Limitations of the Study  162  Implications for Future Research  166  Conclusions  1  68  vii 170  References  194  Appendix A  Recruitment Summary  . . ,. „ Appendix B  Students w i t h Learning Disabilities: B C Ministry of „, ° Education  195  Appendix C  " A l l About M e " Demographic Questionnaire (DQ)  198  Appendix D  Academic Self-Efficacy Questionnaire (A-SEQ)  200  Appendix E  Reading Self-Efficacy Questionnaire (R-SEQ)  203  Appendix F  Social Self-Efficacy Questionnaire (S-SEQ)  205  Appendix G  Emotional Self-Efficacy Questionnaire (E-SEQ)  208  Appendix H  "Who I Can Count O n " Social Support Questionnaire (SSQ)..  211  Appendix I  Life Events Questionnaire (LEQ)  213  Appendix J  Letter of Invitation to Students  220  Appendix K  Parent Consent Form  221  Appendix L  Student Assent Form  223  r  r  3  viii List of Tables Table 1  Summary of Relevant Characteristics of Self-Report Measures  23  Table 2  Point-Prevalence Rates of Self-Reported Symptoms of Depression i n Nonreferred Adolescents Presented by Measure  26  M e a n Total Depression Scores Reported by Studies that Utilized the R A D S and the RADS-2  28  Point-Prevalence Rates of Self-Reported Symptoms of Anxiety i n Nonreferred Adolescents Presented by Measure  40  M e a n Total Anxiety Scores Reported by Studies that Utilized the MASC .  41  Summary of Studies Examining Depression i n Students w i t h Learning Disabilities  54  Summary of Methods Used to Specify the Aptitude-Achievement Discrepancy of Participants with Learning Disabilities  58  Summary of Studies Examining Anxiety i n Students w i t h Learning Disabilities  60  Foci of Studies Examining the Relationship of Self-Efficacy to Depression and Anxiety  65  Correlation between Depression and Self-Efficacy i n Studies of Children and Adolescents  66  Table 11  Summary of Age and Gender Characteristics of Sample  77  Table 12  Summary of Criteria for Total Sample and Disability Subsets  82  Table 13  Examples of Items from the Blue Form of the Wide Range Achievement  Table 3  Table 4  Table 5  Table 6  Table 7  Table 8  Table 9  Table 10  Test - 3rd Edition (WRAT-3)  9*  ix Table 14  Reliability of the Self-Efficacy Questionnaires  Table 15 Means, Standard Deviations, Ranges, Skewness, Kurtosis, and Results of Shapiro-Wilk Tests of Normality for Measured Variables Table 16  108  109  Skewness, Kurtosis, and Results of Shapiro-Wilk Tests of Normality for Transformed Variables  111  Table 17  Correlations between Variables  113  Table 18  Descriptive Statistics (Mean Scores, Standard Deviations and Ranges) of A l l Measures for Males and Females  114  Descriptive Statistics (Mean Scores, Standard Deviations, and Ranges) of A l l Measures for Total Sample and Disability Subgroups  116  Table 20  Number of Years Since Most Recent Psychoeducational Assessment  117  Table 21  Prevalence and Severity of Clinically Significant Symptoms of Depression Reported by G L D , T R A D - L D and R D Participants  120  Means (and Standard Deviations) for Total Depression Scores (Raw Scores and T-Scores) for G L D , T R A D - L D and R D Participants  120  Prevalence and Severity of Symptoms of Anxiety Reported by G L D , T R A D - L D , and R D Participants  122  Means (and Standard Deviations) for Total Anxiety Scores (Raw Scores and T-Scores) for G L D , T R A D - L D and R D Participants  122  Regression Analysis Summary for Social/Emotional Self-Efficacy Predicting Depression  126  Table 19  Table 22  Table 23  Table 24  Table 25  Table 26  Table 27  Regression Analysis Summary for Social/Emotional Self-Efficacy Predicting Anxiety Regression Analysis Summary for Social/Emotional Self-Efficacy Predicting Depression and Anxiety as a Composite  1 2  7  128  X  Table 28  Table 29  Table 30  Table 31  Table 32  Table 33  Table 34  Table 35  Table 36  Table 37  Table 38  Comparison of Participants Reporting H i g h and L o w Levels of Social Support from Family and from Friends  130  Comparison of Participants Reporting H i g h and L o w Levels of Life Events  133  Intercorrelations for Depression, Anxiety, Self-Efficacy and Social Support as a Function of Gender  135  Comparison of Participants with L o w and N o r m a l Word Reading Skills on Depression, Anxiety, and Self-Efficacy  138  Comparison of Verbal A b i l i t y / W o r d Reading Discrepant Readers w i t h A l l Other G L D Participants on Depression, Anxiety, and Self-Efficacy ...  139  Comparison of Reading Comprehension/Word Reading Discrepant Readers w i t h A l l Other G L D Participants on Depression, Anxiety, and SelfrEfficacy  140  Comparison of Discrepant Readers (RD-DIS) w i t h A l l Remaining G L D Participants  142  Comparison of Discrepant Readers (RD-DIS) w i t h Remaining Male G L D Participants  144  Comparison of Participants Reporting the Highest and Lowest Levels of Depression/Anxiety on Measured Variables  146  Comparison of Participants Reporting the Highest and Lowest Levels of Depression/Anxiety on Demographic Variables  148  Correlations between Depression and Self-Efficacy i n Present and Previous Studies  *57  xi List of Figures Figure 1  D S M - I V Criteria for Major Depressive Disorder ( M D D )  17  Figure 2  DSM-TV Criteria for Dysthymic Disorder (DD)  18  Figure 3  DSM-rV Criteria for Generalized Anxiety Disorder (GAD)  35  Figure 4  Data Collection Sheet  86  Figure 5  Data Collection Procedures  101  Figure 6  Summary of Most Recent Psychoeducational Assessment by Grade ...  118  Xll  Acknowledgement This dissertation could not have been completed without the generous support and encouragement of many individuals. I am grateful for: 4 The financial support of the Social Sciences and Humanities Research Council of Canada 4 The material support provided by Multi-Health Systems, Pro-Ed, Psychological Assessment Resources, and Wide Range, Inc. 4 The generosity and inspiring example of my colleagues from the Asante Centre for Fetal A l c o h o l Syndrome, Dr. K w a d w o Ohene Asante, Dr. Julianne Conry, Pam Munro, A u d r e y Salahub and Carol Woodworth 4 The encouragement and assistance of my colleagues from School District #42 (Maple Ridge - Pitt Meadows) especially Sharon Belec, Jenny Berg, Rosemary Braovac, Dr. Randy Cranston, Dr. Rick Erickson, Arnie Funk, Cheryl Harrington, Donna Heikkila, Irene Ives, Sharon Malone, Laurie Meston, Cynthia Murphy, Michelle Schmidt, M i k e Suddaby, Katie Sullivan, and Debbie Walsh 4  The generosity of m y colleagues i n the field i n facilitating m y study i n their schools  4 The willingness of so many students and their families to assist me i n my work, especially the Yep family, Rick and Judy and their oft-tested sons Byron and Brendan, whose friendship, help, and humour across these many years is deeply appreciated 4 The comradeship of m y fellow graduate students Laurie A i k m a n , Maria Arvanitakis, Stacey Bablitz, Farah Bhimani, Faye Karvat, D o n Kerr, Kelly Lemon, Karen Ott-Vandekamp, Natalie Rocke-Henderson, Veronica Smith, and especially Tanya McCreith who has cheerfully assisted me i n countless academic and nonacademic ways as we completed our journeys 4 The mentoring and support so generously extended to me by current and former members of the Departments of Educational and Counselling Psychology and Special Education (ECPS) and Language and Literacy Education (LLED), especially Dr. Jim Anderson, Dr. Nancy Carlman, Dr. Sydney Craig, Dr. M a r i o n Crowhurst, M s . Gail Gudmundson, Dr. Lee Gunderson, Dr. Shelley H y m e l , Dr. Janet Jamieson, Dr. L i z Jordan, M s . Lynda McDicken, Dr. Bill McKee, Dr. Leslie Perry, Dr. Marion Porath, M s . Antoinette Tse, and M s . Barbara Zurek  Xlll  The generous consideration and invaluable feedback provided by the members of my examining committee, Dr. Ruth Ervin, Dr. Nancy Heath and Dr. Jon Shapiro The superb guidance, unstinting support, and enthusiastic encouragement provided by m y research committee members, Dr. Kadriye Ercikan and Dr. Nancy Perry The gracious support, unflagging energy and optimism, thoughtful direction, and infinite patience of m y research supervisor, Dr. Deborah Butler, whose skills, deep knowledge, and passion for teaching and research are truly inspiring The generosity, complete understanding, and unwavering support of m y dear friend Anne M a u c h The rich opportunities, encouragement, and abundant support (both visible and invisible) provided so selflessly and generously by m y parents, Dr. Douglas and Rosemary Mercer, whose life-long zeal for learning has been infectious The love, total support, patience, and example of m y partner Robert Bringhurst, a true scholar, who steadfastly believed that I could and w o u l d achieve m y goals  Chapter I INTRODUCTION Depression is a serious mental health problem that appears to be increasing w i t h successive generations (Klerman, 1993; Ryan et al., 1992). Results of recent epidemiological studies suggest that between 10% and 24% of adolescents have experienced a depressive disorder (Hankin, Abramson, Silva, McGee, & Angell, 1998; Lewinsohn, Hops, Roberts, Seeley, & Andrews, 1993; Reynolds, 1994b), and that as many as 60-70% of these youth are likely to suffer from a recurrence of their disorder during their young adult years (Kovacs, Feinberg, Crouse-Novak, Paulauskas, & Finkelstein, 1984; Weissman et al., 1999). Of particular concern to parents, educators and medical professionals are adolescents with learning disabilities. A l t h o u g h empirical evidence is equivocal, many believe that these adolescents are at particular risk for developing negative affective outcomes, especially depression (Bender, Rosenkrans, & Crane, 1999; Gorman, 1999; Wright-Strawderman, Lindsey, Navarette, & Flippo, 1996). Clearly, this is a concern that warrants further investigation. A recent and informative approach to the study of negative affective functioning is the self-efficacy model of depression (Bandura, Pastorelli, Barbaranelli, & Caprara, 1999). This model, w h i c h is based upon the self-efficacy component of social cognitive theory (Bandura, 1997), posits that a sense of personal inefficacy (e.g., i n relation to social and academic self-efficacy) plays both a direct and a mediating role (e.g., through social behaviour and achievement) i n the development of anxiety and depression (Bandura et al., 1999). The present study extended the w o r k of Bandura and his associates by applying the self-efficacy model of depression to study potential links  between self-efficacy and anxiety and depression iri adolescents w i t h learning disabilities, especially those w i t h significant difficulties i n reading. Self-Efficacy: Effects on Academic and Social Functioning A s they enter and make their way through secondary school, adolescents are faced w i t h significant changes i n almost every domain of their lives - physical, social, emotional, and academic. Contrary to the perceptions of many within the general public, most adolescents handle these changes and make the transition to adulthood without developing significant problems (Offer & Schonert-Reichl, 1992). But Bandura and his associates contend that the success w i t h which adolescents manage these changes and challenges is influenced to a large degree by their perceptions of selfefficacy (Bandura et al., 1999); that is, their beliefs i n their "capabilities to perform i n ways that give them some control over events that affect their lives" (Bandura, 1999, p. 181). Within social cognitive theory, Bandura (1997) has described a central role for selfefficacy, stating that it is these beliefs that activate the cognitive, motivational, and affective processes that determine h o w knowledge and skills are translated into action. Although central i n the regulation of all types of performance, self-efficacy is described as "particularized judgments of capability" (Bandura, 1997, p. 42) that can be differentiated across tasks, contexts and domains of functioning. Thus, an individual could report strong perceptions of self-efficacy i n one particular area of performance (e.g., "I'm confident that I can translate this text into French") but perceptions of inefficacy i n another (e.g., "I don't think I'll be able to solve this equation").  3  Within the context of academic functioning, a growing body of research attests to the important contributions of self-efficacy to achievement, both directly and through a network of sociocognitive influences such as prosocial behaviour and social support (Bandura, 1997; Bandura et al., 1999; Pajares, 2002; Schunk & Pajares, 2002). To explain, in comparison w i t h students w h o doubt their academic capabilities, those w i t h strong perceptions of academic self-efficacy participate i n learning tasks more readily, work more diligently, demonstrate greater persistence i n the face of difficulties, and evidence levels of achievement higher than might be expected o n the basis of their skills alone (Linnenbrink & Pintrich, 2003; Pajares & Miller, 1994; Schunk & Zimmerman, 1997). Further, students w i t h strong perceptions of academic self-efficacy tend to demonstrate prosocial behaviour; for example, associating w i t h peers w i t h similar academic aspirations and avoiding problem behaviours that could negatively impact their academic success (Bandura, Barbaranelli, Caprara, & Pastorelli, 1996). Students w i t h strong perceptions of academic self-efficacy also tend to have a satisfying social support network, feeling accepted by peers and comfortable i n seeking academic assistance from knowledgeable classmates and adults. A s a result, these students tend to experience a school environment that is conducive to learning and academic success (Caprara, Barbaranelli, Pastorelli, Bandura, & Zimbardo, 2000; Schunk, 1995). Within the context of social functioning, research indicates that a strong sense of social self-efficacy both fosters and results from the formation of positive social relationships (Bandura et al., 1996). Compared w i t h individuals w i t h a l o w sense of selfefficacy, those w i t h strong perceptions of social self-efficacy form and maintain satisfying family and peer relationships, enjoy higher rates of peer acceptance and support, and participate more readily in social and recreational activities, which serve  4  to enhance and reinforce their perceptions of social self-efficacy (Bandura, 1997; Bandura et a l , 1996). Not surprisingly, experiences of success i n a particular area of functioning strengthen perceptions of self-efficacy (Schunk & Zimmerman, 1997). Furthermore, additional experiences of success serve to reinforce perceptions of self-efficacy, which then take on powerful self-confirming properties that are resistant to change (Maddux & Lewis, 1995). In contrast, experiences of failure weaken perceptions of self-efficacy (Schunk & Zimmerman, 1997). Individuals w h o experience persistent failure, especially in domains that are important to them, develop lowered perceptions of self-efficacy. Their beliefs that they have little capability to influence conditions i n order to attain desired outcomes, i n turn, have a negative impact on their affective functioning (Bandura, 1993; Bandura et al., 1999; M a d d u x & Meier, 1995). Self-Efficacy: Effects on Affective Functioning Bandura (1997) described three important pathways through w h i c h l o w selfefficacy can result i n the development of negative affective outcomes, especially symptoms of anxiety and depression. The first pathway is through perceptions of inefficacy to reach highly valued standards i n important cognitive activities (e.g. academic success). A l o w sense of academic self-efficacy may produce feelings of apprehension and despondency, even to the level of developing symptoms of anxiety and depression (Bandura, 1997; Bandura et al., 1999). The second pathway is through a low sense of social self-efficacy. Such beliefs can impede the development of supportive social relationships. Without social supports, individuals are more prone to experiencing stress and to developing symptoms of anxiety and depression, especially in social situations (Bandura, 1997; Bandura et al., 1999; M u r i s , 2001). The third pathway  5  is through perceptions of l o w self-efficacy for controlling negative thoughts. While most individuals experience periods of worry and despondency i n response to losses and setbacks at various times i n their lives, many are able to regain their sense of well-being within a reasonable amount of time. Those individuals w h o are not able to rebound quickly because they are engaging in recurrent negative rumination are likely to develop lowered perceptions of their self-efficacy to control their thoughts and their lives. This leads to the development of symptoms of anxiety and depression (Bandura, 1997; Bandura et al., 1999). Self-Efficacy and Cognitive Models of Depression Although Bandura's (1997) self-efficacy model of depression is generally consistent w i t h cognitive models of depression, there are two important differences between the models. First, the models differ i n conceptualizations of an individual's role i n adapting to circumstance. Second, the models differ i n specifications of the self construct that is negatively affected by depression. To elaborate, i n both Bandura's self-efficacy model and cognitive models of depression such as the helplessness/hopelessness model (Abramson, Seligman, & Teasdale, 1978; Abramson, Metalsky, & Alloy, 1989) and Beck's cognitive model (Beck, 1976), individuals are judged to be cognitively vulnerable (i.e. to possess diatheses or predispositions) when they are k n o w n to hold a pessimistic attribution style or dysfunctional attitudes about themselves and their environment. W h e n such individuals encounter a negative life event (i.e., a stressor) such as school failure, they are at risk for making negative inferences that w i l l lead them to develop feelings of hopelessness and depression.  These individuals may be protected from developing such negative affective outcomes, however, by factors such as social support. Within cognitive models of depression, a factor such as social support is described as a protective factor which serves to inhibit the individual's reaction to stress and to protect their sense of selfesteem (Metalsky, Joiner, Hardin, & Abramson, 1993). In contrast, within the selfefficacy model of depression, such a factor is seen not just as a buffer (stress protection), but as an enabling factor (an opportunity for agency) w h i c h can serve i n a proactive manner to facilitate the individual's adaptation to the stressor. Bandura contends that individuals w h o proactively recruit social support are both protected and enabled, and as a result, are likely to develop positive beliefs i n their efficacy to exercise control over the stressful events or circumstances that are affecting their lives. Bandura has described self-efficacy beliefs as the foundation of human agency (Bandura, 1997) and has stated that: "Unless people believe that they can produce desired results by their actions, they have little incentive to act or to persevere i n the face of difficulties" (Bandura, 1999, p. 181). Interestingly, exploratory research (Bong & Clark, 1999; Pajares & Miller, 1994) has indicated that self-efficacy has greater explanatory power and predictive capability for achievement outcomes and behaviour than either self-esteem, w h i c h Harter (1999) defines as an individual's global feelings of self-worth, or self-concept, defined by Harter (1999) as domain specific self-evaluations. These preliminary findings suggest further research is needed on the relationship between students' beliefs about their capabilities (self-efficacy) and their affective functioning. Accordingly, this topic was addressed i n the present study.  7  The Contribution of Self-Efficacy to Depression and Anxiety To date, empirical research on the contribution of perceived self-efficacy to anxiety and depression has largely focused on adults (Bandura, 1997; M u r i s , 2002). Nonetheless, there is a small but growing corpus of studies concerned w i t h the functioning of children and adolescents. Bandura and his associates (Bandura et a l , 1999) tested the contribution of perceived self-efficacy to depression i n a longitudinal study w i t h a large sample of children. They found that academic and social self-efficacy contributed to concurrent and subsequent depression, both directly and through other influences such as academic achievement and behaviour. Two studies, which focused upon the functioning of adolescents (Ehrenberg, Cox, & Koopman, 1991; M u r i s , Schmidt, Lambrichs, & Meesters, 2001), also found that academic and social self-efficacy were negatively correlated w i t h depression. Finally, a study of adolescents that focused on the contribution of social self-efficacy alone yielded complementary findings (McFarlane, Bellissimo, & N o r m a n , 1995; McFarlane, Bellissimo, N o r m a n , & Lange, 1994)O f particular interest, however, is a recent study completed by M u r i s (2002) who examined the contribution of social and academic self-efficacy to symptoms of anxiety as well as depression i n an adolescent sample. The focus on both symptoms is important for theoretical and practical reasons. First, the self-efficacy model of depression espoused b y Bandura (Bandura et al., 1999) specifies that both symptoms could be expected. Second, whether defined as symptoms or disorders, these distressing affective outcomes are highly comorbid (Kovacs & Sherrill, 2001; Poznanski & Mokros, 1994; Rohde, Lewinsohn, & Seeley, 1991). Interestingly, Muris's findings suggest that academic self-efficacy plays a more important role i n the development of  8  depressive symptoms while social self-efficacy is more salient to symptoms of anxiety. While the need for more research was acknowledged by the author, this finding has important implications for both diagnosis and intervention. For these reasons, selfreported symptoms of both anxiety and depression were assessed i n the present study. Adolescents w i t h Learning Disabilities In view of the robust findings concerning the contributions of self-efficacy to anxiety and depression i n adolescents from the general population, one cannot help but be concerned about adolescents who face failure on a daily basis. Students w i t h learning disabilities typically experience chronic (and often pervasive) academic failure across their years of schooling and beyond. In addition, many of these students also experience difficulties i n establishing and maintaining satisfying social relationships (Bryan, 1997; Kavale & Forness, 1996; Swanson & Malone, 1992). A s a consequence, low perceptions of self-efficacy and high rates of depression and anxiety, perhaps even to the level of clinical significance, could be expected i n this population. Indeed, many i n the field hold the opinion that students w i t h learning disabilities are at greater risk than their normally achieving peers for developing social-emotional difficulties, especially depression (Bender et a l , 1999; Bender & Wall, 1994; Gorman, 1999; Huntingdon & Bender, 1993; Weinberg & Emslie, 1988; Wright-Strawderman et al., 1996). Empirical studies, however, are few. Furthermore, the studies are diverse in focus (ranging from middle childhood to late adolescence across both school and clinic settings), varied i n methodology including specification of what constitutes a learning disability, and inconsistent i n their inclusion of additional variables k n o w n to act as risk or protective factors (e.g., level of social support and experience of life events) i n the development of negative affective outcomes. It is not surprising, therefore, that the  9  studies have yielded equivocal findings w i t h regard to the prevalence and severity of depression i n this heterogeneous population. Clearly, additional research is required in order to clarify whether particular risks are faced by students w i t h learning disabilities. In their call for the simultaneous study of educational and mental health issues, Roeser, Eccles, and Strobel (1998) asked a compelling question: " W h y (do) particular problems.... and particular manifestations of emotional distress.... co-occur i n some children?" (p. 153). They proposed that several different processes may be operating at the individual level to produce co-occurring problems and recommended that researchers focus on patterns of resources (e.g., cognitive, attentional, emotional and self-regulatory) that appear to be associated w i t h "more or less successful patterns of academic and social behavior across development" (p. 155). This study heeded their call, not only by focusing on both academic and mental health issues, but also by focusing on patterns of behaviour within a particular group (that is, adolescents w i t h learning disabilities, especially those w i t h particular difficulties reading) rather than between groups (normally achieving adolescents and adolescents w i t h learning disabilities) to search for answers regarding the widely-held view that students w i t h learning disabilities are especially vulnerable to psychological distress. A within-group approach was also advocated by L a Greca and Stone (1990). Following their study of academic achievement and interpersonal functioning among students w i t h and without learning disabilities, these researchers noted that comparison group research failed to account for the heterogeneity of students w i t h learning disabilities and likely masked important variability within this population.  10  Rationale for the Study The present study was designed to clarify the prevalence and severity of depression i n adolescents w i t h learning disabilities, not by comparing these students with their normally achieving peers (between-group differences), but by examining within-group and individual-level differences as advocated b y L a Greca and Stone (1990) and Roeser et al. (1998). In particular, the present multi-faceted study has focused upon the links between self-efficacy and depression and anxiety and extended previous work w i t h children and adolescents (Bandura et al., 1999; Ehrenberg et al., 1991; Muris, 2002; M u r i s et al., 2001) to a special population; namely, adolescent students w i t h learning disabilities, especially those experiencing significant difficulties i n the highly salient area of reading. The study investigated h o w depression might be linked to self-efficacy, both directly and indirectly, along the three specific pathways (academic, social and emotional self-efficacy) posited by Bandura (1997). The study also incorporated two important additional variables (level of social support and experience of life events) k n o w n to act as risk or protective factors i n the development of depression (Compas, Slavin, Wagner, & Vannatta, 1986; Klocek, Oliver, & Ross, 1997; Sarason, Shearin, Pierce, & Sarason, 1987; Wills & Shinar, 2000). Further, on the basis of well-documented high rates of comorbidity as w e l l as Bandura's contention that a negative affective outcome of anxiety could be expected i n addition to depression i n individuals w i t h low selfefficacy (Bandura, 1997; Bandura et a l , 1999), the study included a consideration of symptoms of anxiety. Finally, i n response to calls for criterial task specificity in selfefficacy research (Bandura, 1986; Pajares, 1996), the present study also focused upon  reading (and reading self-efficacy), a specific and salient academic skill that poses a significant challenge to many students with learning disabilities (Bender, 1995).  Summary of Research Questions  1. What is the prevalence and severity of self-reported symptoms of anxiety and depressi  in adolescents with learning disabilities, especially those with reading disabilities? prevalence and severity in this sample of students w i t h learning disabilities (especially those w i t h significant difficulties in reading) higher than current estimates for the general adolescent population? A n d is the rate of comorbid anxiety and depression also higher? 2. Can symptoms of anxiety and depression in adolescents with learning disabilities,  especially those with reading disabilities, be predicted on the basis of their perceptio self-efficacy? That is, are lowered perceptions of academic, reading, social and emotional self-efficacy associated with higher levels of anxiety, depression, and comorbidity of these symptoms? Further, are there particular patterns of relationships among these factors; for example, are lowered perceptions of social and emotional self-efficacy more closely associated w i t h high levels of anxiety? A n d are lowered perceptions of academic and reading self-efficacy more closely associated w i t h higher levels of depression?  3. Wfhat is the role of social support in predicting symptoms of anxiety and depression? Does level of social support appear to be acting both as a buffer and in concert with the development of greater social self-efficacy? That is, do students reporting higher levels of social support, from both family and friends, experience higher levels of self-efficacy (particularly social and emotional) and  12  lower levels of anxiety and depression? F i n a l l y does social support from friends play a more efficacious role than social support from family i n this sample?  4. What is the role of life events in predicting symptoms of anxiety and depression ? Doe experience of life events construed to be negative play a more salient role than self-efficacy and social support i n predicting anxiety and depression? O r does the effect of experiencing negative life events appear to be additive? What role does the experience of life events construed to be positive play? 5. What is the role of gender in predicting symptoms of anxiety and depression? Do females report lower levels of self-efficacy and higher levels of anxiety and depression than males? 6. What role does severity of reading disability play? A m o n g students identified as having learning disabilities, are those w i t h the weakest w o r d reading skills reporting lower levels of self-efficacy and higher levels of anxious and depressive symptoms than students with stronger w o r d reading skills? A n d , are students w i t h significant "discrepancies" (between w o r d reading skills and presumed cognitive abilities and/or reading comprehension abilities) reporting lower levels of self-efficacy and higher levels of symptoms of anxiety and depression than students without such discrepancies? 7. Finally, are there particular factors associated with the experience of anxiety and depression in adolescents with learning disabilities? W h e n all of the relevant factors are considered (social support, life events, w o r d recognition and reading comprehension skills, and self-efficacy across domains), what factors distinguish students w i t h high levels of symptomatology from those without such  difficulties? A n d , are there particular demographic factors (e.g., having an J school job and being involved i n extracurricular activities) that distinguish students w i t h high symptom levels from those without such difficulties?  14 Chapter 2 LITERATURE REVIEW This study was designed to clarify the prevalence and severity of psychological distress (specifically symptoms of depression and anxiety) i n adolescents w i t h learning disabilities and to explore the role of perceived self-efficacy as a factor associated with the experience of these internalizing difficulties. The study was situated within a social cognitive theoretical framework (Bandura, 1986) and drew upon the work of researchers from a number of disciplines; namely, education, psychology, and developmental psychopathology. In this chapter, relevant research from these disciplines is reviewed within six major sections. The first two sections review current knowledge concerning the experience of depression and anxiety by adolescents. In the third section, research on adolescents with learning disabilities is reviewed, especially w i t h regard to the experience of depression and anxiety i n this population as w e l l as to various methods of defining and identifying learning disabilities. The fourth section reviews and expands upon a sociocognitive model of depression and the self-efficacy model proposed by Bandura and associates (Bandura et al., 1999), while the fifth section reviews literature pertaining to the role of two additional factors implicated i n the experience of depression and anxiety; namely, availability of social support and experience of stressful life events. The chapter concludes w i t h a reiteration of the rationale for the study and a summary of the research questions and hypotheses. Adolescent Depression Depression is a serious mental health problem among adolescents (Lewinsohn, Rohde, & Seeley, 1998; Poznanski & Mokros, 1994; Reynolds & Johnston, 1994; Smith &  15  Weissman, 1992). Results of epidemiological studies indicate that although the general incidence of psychopathology increases only moderately during adolescence, the prevalence of depression increases significantly, especially among females (Hankin et a l , 1998; Lewinsohn, Hops, Roberts, Seeley, & Andrews, 1993). D u r i n g adolescence between 10 and 24% of adolescents w i l l experience a depressive disorder (Hankin et al., 1998; Lewinsohn, H o p s et al., 1993; Reynolds, 1994b) and as many as 60 to 70% of these youth are likely to suffer a recurrence of their disorder during their young adult years (Birmaher, Ryan, Williamson, Brent, Kaufman, et al., 1996; H a n k i n et al., 1998; Kovacs et al., 1984; Parker & Roy, 2001; Weissman et al., 1999). These numbers are alarming, made even more so by evidence that these figures are likely to rise i n coming years (Klerman, 1993; Ryan et al., 1992; Kessler & Waters, 1998; Lewinsohn, Rohde, Seeley, & Fischer, *993)Conceptualizing and Defining Depression Before discussing "depression" further, however, it is important to understand what is meant by this term, both i n the literature and i n this study. In both, the depression under consideration is "unipolar" depression and not the relatively rare "bipolar" or manic depression. The latter has a mean age at onset i n the early 20s and affects only 0.4 to 1.6% of the population (American Psychiatric Association (APA), 1994)While a degree of sadness or unhappiness is widely regarded as a normal human experience, significant a n d / o r continuing experience of depressed mood and other symptoms of depression which affect multiple areas of personal functioning is not. Yet the same term, depression, can be used to describe momentary feelings of depression, a  i6  prevailing mood, a syndrome (a constellation of co-occurring symptoms), a diagnosable disorder, and a disease (Nurcombe, 1994). To assist psychiatrists and other mental health professionals i n diagnosing type and severity of depression, a number of diagnostic systems have been developed and refined, primarily since the 1970s (Reynolds & Johnston, 1994). A t present, the most widely used system i n N o r t h America is the fourth edition of the Diagnostic and Statistical Manual of Mental Disorders, the D S M - I V ( A P A , 1994). In Europe, the International Classification of Diseases - Mental and Behavioural Disorders, the ICD-10 (World Health Organization ( W H O ) , 1992) is more commonly used. The D S M - I V and the ICD-10 are both criterion-referenced categorical systems. Within the D S M - I V classificatory system, the depressive disorders most frequently experienced by adolescents are Major Depressive Disorder (MDD) and Dysthymia (DD) (Cicchetti & Toth, 1998; Lewinsohn, Rohde, & Seeley, 1998; Merrell, 1999; Reynolds, 1994b). To be diagnosed w i t h M D D , an adolescent must have experienced one or more discrete major depressive episodes; that is, periods of at least two weeks during which significant depressed mood or loss of interest in customary activities is evident. These episodes must be accompanied by at least four additional symptoms of depression (e.g., increase or decrease i n appetite, increase or decrease i n weight, fatigue or loss of energy, feelings of worthlessness, diminished ability to concentrate, irritability, or recurrent suicidal ideation a n d / o r a suicidal attempt). The D S M - I V criteria for M D D are presented i n Figure 1. The experience of M D D is associated w i t h high mortality, with up to 15% of individuals committing suicide ( A P A , 1994).  17 Figure 1. D S M - I V Criteria for Major Depressive Disorder ( M D D ) A.  Five (or more of the following symptoms have been present during the same two-week period and represent a change from previous functioning; at least one of the symptoms is either (1) depressed mood or (2) loss of interest or pleasure. (1) Depressed mood most of the day, nearly every day, as indicated by either subjective report (e.g., feels sad or empty) or observation made by others (e.g. appears tearful). Note: In children and adolescents, can be irritable mood. (2) Markedly dmunished interest or pleasure in all, or almost all, activities most of the day, nearly every day (as indicated by either subjective account or observation made by others). (3) Significant weight loss when not dieting or weight gain (e.g., a change of more than 5% of body weight in a month), or decrease or increase in appetite nearly every day. Note: In children, consider failure to make expected weight gains. (4) Insomnia or hypersomnia nearly every day. (5) Psychomotor agitation or retardation nearly every day (observable by others, not merely subjective feelings of restlessness or being slowed down). (6) Fatigue or loss of energy nearly every day. (7) Feelings of worthlessness or excessive or inappropriate guilt (which may be delusional) nearly every day (not merely self-reproach or guilt about being sick). (8) Diminished ability to think or concentrate, or indecisiveness, nearly every day (either by subjective account or as observed by others). (9) Recurrent thought of death (not just fear of dying), recurrent suicidal ideation without a specific plan, or a suicide attempt or a specific plan for committing suicide.  B.  The symptoms do not meet criteria for a Mixed Episode (i.e. Manic Episode & Major Depressive Episode).  C.  The symptoms cause clinically significant distress or impairment in social, occupational, or other important areas of functioning.  D.  The symptoms are not due to the direct physiological effects of a substance (e.g., a drug of abuse, a medication) or a general medical condition (e.g., hypothyroidism).  E.  The symptoms are not better accounted for by Bereavement, i.e., after the loss of a loved one, the symptoms persist for longer than 2 months or are characterized by marked functional impairment, morbid preoccupation with worthlessness, suicidal ideation, psychotic symptoms, or psychomotor retardation.  ( A P A , 1994, p. 327) In contrast, D D is a less severe form of depression, but one that is nonetheless extremely debilitating, and a risk factor for the development of M D D . D D is characterized by the experience of at least one year (two years for adults) of chronic  i8  depressed mood, w h i c h is accompanied by additional symptoms such as feelings of inadequacy, generalized loss of interest or pleasure, social withdrawal, feelings of guilt or evidence of brooding, irritability or excessive anger, a n d / o r decreased activity. The D S M - I V criteria for D D are presented i n the Figure 2. Approximately 10% of individuals w h o have been diagnosed with D D w i l l develop M D D within a year ( A P A , 1994). Figure 2. D S M - I V Criteria for Dysthymic Disorder (DD) A.  Depressed mood for most of the day, for more days than not, as indicated either by subjective account or observation by others, for at least 2 years. Note: In children and adolescents, mood can be irritable and duration must be at least 1 year.  B.  Presence, while depressed, of two (or more) of the following: (1) poor appetite or overeating (2) insomnia or hypersomnia (3) low energy or fatigue (4) low self-esteem (5) poor concentration or difficulty making decisions (6) feelings of hopelessness  C.  During the 2-year period (1 year for children and adolescents) of the disturbance, the person has never been without the symptoms in Criteria A and B for more than 2 months at a time.  D.  No major Depressive Episode has been present during the 2 years of the disturbance (1 year for children and adolescents); i.e., the disturbance is not better accounted for by chronic Major Depressive Disorder, or Major Depressive Disorder, In Partial Remission.  E.  There has never been a Manic Episode, a Mixed Episode, or a Hypomanic Episode, and criteria have never been met for Cyclothymic Disorder.  F.  The disturbance does not occur exclusively during the course of a chronic Psychotic Disorder, such as Schizophrenia or Delusional Disorder.  G.  The symptoms are not due to the direct physiological effects of a substance (e.g., a drug of abuse, a medication) or a general medical condition (e.g., hypothyroidism).  H.  The symptoms cause clinically significant distress or impairment in social, occupational, or other important areas of functioning.  ( A P A , 1994, p. 349)  19 Not all researchers and clinicians, however, believe that the categorical approach to depression best captures the complexity of this heterogeneous condition which likely involves multiple etiological pathways (Gotlib, Kurtzman, & Blehar, 1997). M a n y regard unipolar depression as complex biopsychosocial phenomena, resulting from transactions among psychological (e.g., cognitive, affective, sociocognitive and socioemotional), social (e.g., interpersonal, familial, and cultural) and biological components (e.g., genetic and neurobiological), w h i c h can vary across a spectrum of severity from depressive symptoms to depressive disorders, (Cicchetti, Rogosch, & Toth, 1997; Daleiden, Vasey, & Brown, 1999; Lewinsohn, Solomon, Seeley, & Zeiss, 2000; Petersen et al., 1993). Accordingly, these professionals advocate viewing the condition as a multidimensional condition, which exists along a continuum (Compas, Ey, & Grant, 1993; Essau, Petermann, & Reynolds, 1999), an approach that can better account for individual differences (especially i n relation to cognitive development, age and gender) and provide greater assistance i n developing interventions or treatment (Cicchetti & Toth, 1998; Zahn-Waxler, Klimes-Dougan, & Slattery, 2000). Further support for considering depression as falling upon a continuum comes from findings that adolescents w i t h "subthreshold depression" (i.e. w i t h elevated scores on self-reports but who do not meet the diagnostic criteria for disorders) closely resemble adolescents w i t h M D D and D D except w i t h regard to suicidal ideation (Lewinsohn, Rohde, & Seeley, 1998). These adolescents also demonstrate problematic functioning including marked psychosocial difficulties and an elevated risk for future psychopathology (Birmaher, Ryan, Williamson, Brent, Kaufman et al., 1996; Gotlib, Lewinsohn, & Seeley, 1995; Luby, Todd, & Geller, 1996). In other words, the experience  20  of " m i l d " or "moderate" depressive symptoms is not necessarily a benign condition and these adolescents warrant additional attention. Given the wide support for depression as a multidimensional condition which can vary along a continuum of severity, the present study has adopted this approach to the study of depression. A s a result, this study is primarily concerned w i t h the experience of symptoms of depression (depressive symptomatology as a continuous variable) rather than w i t h diagnosed depressive disorders (diagnosis as grouping variable) and, as shown i n the following section, this approach had a critical influence on the choice of a depression measure. Measuring Depression Adolescent depression is typically assessed by of one or more of three general methods - clinical interviews, reports from parents/teachers/peers, and self-reports. In clinical settings, where the focus is upon making a diagnosis and providing treatment, the psychologist or psychiatrist may well use self-reports and reports by others, but the primary tool is the clinical interview, which is often guided by a structured interview schedule tied to one of the diagnostic systems. A widely used structured interview schedule for diagnosing depression i n children and adolescents is the Schedule for Affective Disorders and Schizophrenia in School-Age Children (Kiddie-SADS) (Puig-Antich & Chambers, 1978). In educational and community settings, where the focus is upon identifying students who are at-risk and i n need of further assessment and assistance, self-reports as well as reports from parents, teachers, a n d / o r peers are important tools. In these settings, teachers and counselors use the reports to evaluate symptom depth and severity and communicate their findings to clinicians.  21  Standardized self-reports and reports by others are based on the premise that human characteristics are normally distributed and that psychopathology occurs at the extreme end of the continuum of individual differences (Cicchetti & Rogosch, 1999). For this reason, most report instruments provide continuous scores (T-scores) as well as a clinical "cut point" to demarcate abnormal from normal levels of functioning. Two widely-used standardized reports for teachers and parents are forms of the Child Behavior Checklist (CBCL) (Achenbach & Edelbrock, 1983), and for classmates, the Peer Nomination Inventory of Depression (PNID) (Lefkowitz & Tesiny, 1980). Although reports by significant others i n an adolescent's life have a number of strengths, including ecological validity, the ability to d r a w on the rater's historical knowledge of the adolescent, and the ability to provide data on relatively infrequent behaviours (Clarizio, 1994), such reports may not account for some important aspects of the adolescent's condition. This is because depression is an internalizing condition largely comprised of symptoms that cannot be readily observed. Cognitive symptoms such as feelings of guilt or hopelessness and somatic symptoms such as insomnia and stomach aches are largely subjective to the adolescent and may not be noticed by others in the adolescent's immediate environment. A s a result, reports of others (parents, caregivers, teachers, and peers) are often discrepant w i t h self-reports, w i t h parents i n particular underestimating the internalizing symptoms of their children (Kazdin, 1994). To illustrate, M u r i s , Meesters, and Spinder (2003) obtained correlations i n the 0.33 to 0.51 range for adolescent- and parent-reported symptoms of depression and anxiety while Cole et al. (2002) obtained a correlation of 0.50 i n their investigation of child/adolescent- and parent-reported symptoms of depression. A s a consequence, self-  22  reports are regarded a critical component i n the assessment of depressive symptoms (Hankin & Abramson, 1999; K a z d i n , 1994; Reynolds, 1994a). Self-reports such as the Children's Depression Inventory (CDI) (Kovacs, 1991), the Beck Depression Inventory (BDI-II) (Beck, Steer, & Brown, 1996) and the Reynolds Adolescent Depression Scale (RADS-2) (Reynolds, 2002), allow an investigator or clinician to directly assess adolescents' perceptions of their symptoms and condition and the results generally correlate w e l l w i t h clinical interview measures of depression. Reynolds (2002) obtained a correlation coefficient of .82 between the RADS-2 and a widely-used clinical interview measure, the Hamilton Depression Rating Scale (HDRS) (Hamilton, 1967), indicating good criterion-related validity for the latest edition of his self-report instrument. This finding supports the importance of utilizing self-reports as a critical step i n identifying adolescents who are experiencing clinically significant levels of depressive symptomatology. It should be noted, however, that results from various self-report measures are difficult to compare even though estimates of convergent validity between instruments typically lie within the moderate range (e.g., Reynolds (1994a) reported correlations i n the .70 to .75 range between the Reynolds Adolescent Depression Scale (RADS) (Reynolds, 1987) and the Children's Depression Inventory (CDI) (Kovacs, 1991) while Skorikov and Vandervoort (2003) obtained a correlation coefficient of .75 between assessments of their sample using the Center for Epidemiologic Studies - Depression Scale (CES-D) (Radloff, 1977) and the Beck Depression Inventory (BDI) (Beck, W a r d , Mendelson, Mock, & Erbaugh, 1961). A s shown in Table 1, self-report measures of depression suitable for use with adolescents vary across a number of important dimensions which could  23 Table i . Summary of Relevant Characteristics of Self-Report Measures Age Range  Internal Consistency  Test-Retest Reliability  Period  Rdg. Level  7-17  .86  .63  Past 2 weeks  "low"  n.r.  .75  .51  Past week  n.r.  BDI (Beck et al., 1961) BDI-11 (Beck et al., 1996)  13-80  .86  .60 - .83  Past week  "low"  13-80  .93  .93  Past 2 weeks  "low"  RADS (Reynolds, 1987) RADS-2 (Reynolds, 2002)  13-18  .94  .86  Present  Grade 3  11-20  .93  .85  Present  Grade 3  Measure CDI (Kovacs, 1992) CES-D (Radloff, 1977)  A  B  c  Notes: CDI = Children's Depression Inventory (Kovacs, 1991); CES-D = Center for Epidemiological Studies - Depression Scale (Radloff, 1977); BDI = Beck Depression Inventory (Beck et al., 1961); BDIII = Beck Depression Inventory (2nd ed.) (Beck et al., 1996); RADS = Reynolds Depression Inventory (Reynolds, 1987); RADS-2 = Reynolds Depression Inventory (2nd ed.) (Reynolds, 2002); n.r. = not reported; "low" = CDI manual notes a "low" reading level (Berndt, Schwartz & Kaiser (1983) estimated a reading level of Grade 3 to 5); "low" = BDI manual notes a "low" reading level (Conoley (1992) estimated a Grade 5 reading level); "low" =BDI-II manual notes a "low" reading level (M. Decaire, a technical representative of the test's publisher, estimated a Grade 5 reading level (personal communication, March 17, 2004)). A  B  c  potentially affect results. First, the age range of an instrument (child-adolescent or adolescent-adult) is likely to affect the appropriateness of items for adolescents because clinical manifestations of depression vary by age (e.g., adults are more likely to endorse depressed mood while adolescents are more likely to endorse irritability). Second, the time period assessed (present to two weeks) is likely to affect results and thus prevalence rates. Third, and very importantly, the reading level of an instrument is likely to affect an individual's comprehension and ability to respond accurately. Given these factors as well as the focus of the present study on adolescents, many of w h o m have particular difficulties i n reading, the RADS-2 was selected for use. A review of the  24 characteristics of widely-used self-report measures i n Table 1 reveals that the R A D S - 2 has strong reliability (both internal consistency and test-retest) i n concert w i t h a reading level appropriate for the participants i n the present study. Prevalence of Depression Gaining clarity on the prevalence of depression within the adolescent population is a challenge. Prevalence rates vary considerably across studies depending on factors such as: (a) characteristics of the sample, including age, gender and whether the participants have been referred to a clinic or sampled from the community at large (i.e., a non-referred sample) (Poznanski & Mokros, 1994; Reynolds & Johnston, 1994), (b) the time period i n w h i c h depressive symptoms might have occurred (e.g., at a single point i n time ("point prevalence"), or at any time during the past month, the last twelve months, or a lifetime); and (c) the method/measure employed to assess depression, especially i n relation to the use of recommended clinical cut-off scores for identifying clinically significant levels of depressive symptomatology. W i t h regard to prevalence estimates for diagnosed adolescent depressive disorders ( M D D and DD), two large prospective longitudinal epidemiological studies of non-referred children and adolescents within their communities have provided valuable information. The D u n e d i n Multidisciplinary Health and Development Study (Silva & M c C a n n , 1996) followed the development of a cohort of 1,037 children from their birth i n the maternity hospital in Dunedin, N e w Zealand between A p r i l 1972 and March 1973 until 1994. The children were re-evaluated at 3 years of age, and subsequently re-evaluated every two years until the age 15, w i t h a summative evaluation at the age of 21 years ( N of 992). Results from this study, which aggregated  25 M D D and D D , indicated that within the previous 12 months, 0.5 to 2.8% of 13 year olds (students and non-students) had received a diagnosis of depression, w i t h prevalence rates climbing steadily w i t h age to 1.6 to 3.2% for 15-year olds and 16.5 to 17.0% for 18year olds (Hankin et al., 1998). The second study, the Oregon Adolescent Depression Project (Lewinsohn, Rohde, & Seeley, 1998) followed the development of approximately 1,500 high school students i n western Oregon. Results from this study indicated a point prevalence rate of 2.6 to 3.2% for M D D and 0.1 to 0.5% for D D . Lifetime prevalence rates were considerably higher w i t h 18.5 to 24% of adolescents having experienced an episode of M D D and 3.0 to 3.2% having experienced D D (Lewinsohn, Hops, Roberts, Seeley, & Andrews, 1993). Intuitively, one might expect that prevalence rates for D D w o u l d be higher than those for M D D but this is not the case, due to the diagnostic convention that individuals w h o develop M D D subsequent to D D receive a diagnosis of M D D while those w h o develop D D during an episode of M D D continue to be diagnosed w i t h M D D (Goodman, Schwab-Stone, Lahey, Shaffer, & Jensen, 2000). W i t h regard to the experience of depressive symptoms, epidemiological data have been generated primarily by cross-sectional studies that utilized self-report measures. Given the focus of the present study upon depressive symptomatology i n adolescents, these studies are of special interest. A s shown i n Table 2, however, point prevalence rates for clinically significant levels of depressive symptoms varied widely across these large scale studies of non-referred adolescents, from 4% (Millikan, Wamboldt, & Bihun, 2002) to 23.6% (Steinhausen & Metzke, 2000), estimates somewhat extended from the 8 to 18% range cited by Reynolds (1994b).  26 Table 2. Point-Prevalence Rates of Self-Reported Symptoms of Depression i n Nonreferred Adolescents Presented by Measure  Study  Measure  Prevalence  N  Age  Tartnenbaum & Forehand (1992)  150  11-15  Stark, Kaslow, & Laurent (1993)  720  9-14  Dubois, Felner, Bartels, & Silverman (1995)  435  9-16  (> cut-off 14) (S cut-off 19)  21.4% 10.1%  Millikan, Wamboldt, & Bihun (2002)  201  12-19  CDI  4%  Dierker et al. (2001)  632  14-15 (est.)  CES-D  12%  Steinhausen & Metzke (2000)  567  12-17  Ehrenberg & Cox (1990)  400  13-19  Gladstone & Koenig (1994)  325  13-18  Maag & Reid (1994)  126 (NLD)  12-18  648  16-19  Reynolds & Mazza (1998)  89  11-15  Auger (2004)  356  12-14 (est.)  Boyd et al. (2000)  (> cut-off 1.5 SD)  CDI (> cut-off 19)  CDI  McFarlane et al. (1994)  Dalley et al. (1992)  CDI  105 (NLD)  1,299  17 (M) 11-18  CES-D (> cut-off 16)  BDI (> cut-off 17)  BDI (> cut-off 24)  BDI (> cut off 20)  IDD RADS (> cut-off 77)  RADS (> cut-off 70)  RADS (> cut-off 77)  RADS (> cut-off 77)  8% 5.6%  23.6% 10.9% 4.9% 10% 10.9% 18% 17.4% 7.7% 14.2%  Note: CDI = Children's Depression Inventory (Kovacs, 1991); CES-D = Center for Epidemiologic Studies - Depression Scale (Radloff, 1977); BDI = Beck Depression Inventory (Beck, Ward, Mendelson, Mock, & Erbaugh, 1961); BDI-II = Beck Depression Inventory (2nd ed.) (Beck, Steer, & Brown, 1996); IDD = Inventory to Diagnose Depression (Zimmerman & Coryell, 1987); RADS = Reynolds Adolescent Depression Scale (Reynolds, 1987); RADS-2 = Reynolds Adolescent Depression Scale (2nd ed.) (Reynolds, 2002)  27 The variation i n prevalence rates of depressive symptoms across these studies is likely due to a number of important factors including: the age range of the samples (particularly early adolescence versus late adolescence as w i l l be discussed shortly); variations i n the symptoms assessed as well as the specification of cut-off points (severity) resulting i n the instruments having varied discriminant validities; and as shown previously i n Table 1, variations i n the reliabilities of the instruments (e.g. testretest reliability of .51 for the CES-D, .85 for the R A D S - 2 and .93 for the BDI-II) and i n the reading level of the instruments. A s a consequence, it w i l l be necessary to compare the results of the present study w i t h those of studies that have comparable samples and have used instruments w i t h "excellent" or "good" psychometric properties (Myers & Winters, 2002a). To this end, mean depression scores (T-scores) reported by studies that utilized the R A D S were also examined and noted for comparison w i t h findings from the present study. M e a n scores from these studies, for the total group as well as for females and males (with significant differences i n mean scores noted), are presented i n Table 3. Despite the variability i n prevalence estimates for depressive symptoms and depressive disorders, it is clear that a significant number of adolescents i n the general community are experiencing depression. Of further concern are indications that the problem of depression among adolescents is worsening. Depression is appearing at greater rates among adolescents and at younger ages than i n the past (Birmaher, Ryan, Williamson, Brent, & Kaufman, 1996; Lewinsohn, Hops, et al., 1993; Stark, Laurent, Livingston, Boswell, & Swearer, 1999). U n t i l recently, evidence of increasing rates of depression w i t h succeeding generations ("age cohort effect" or A C E ) was largely  28 Table 3. Mean Total Depression Scores Reported by Studies that Utilized the R A D S and the RADS-2 N  Age  Total M (SD)  Females M(SD)  Males M(SD)  Reynolds & Mazza (1998)  89  11-15  62.09 (15.03)  63.49 (n.r.)  60.03 (n.r.)  Boyd & Gullone (1997)  783  11-15  62.30 (14.33)  63.00 (14.58)  58.53 (14.02)  3,300  11-20  59.66 (14.89)  61.81 (15.23)  57.50 (14.22)  Auger (2004)  356  12-14  54.79 (14.57)  n.r.  n.r.  Schonert-Reichl (1994)  61  Baron & Campbell (1993)  153  14-16  Dalley et al. (1992)  105  17 (M) 58.81 (n.r.)  Studies  Reynolds (2002)  12-14 15-17  n.r. 55.09 (16.18)  Sig. Diff X  n.r.  n.r.  59.06 (8.32)  58.75 (18.57)  63.21 (14.25)  61.75 (13.63)  58.13 (17.64)  49.66 (11.45)  /  n.r.  n.r.  X  X  Note: All of the studies except for Reynolds (2002) used the RADS.  confined to adult samples (Klerman, 1993; Petersen et al., 1993), but studies have been conducted n o w w i t h children and adolescents which confirm an increase i n depression within these populations as w e l l (Ryan et a l , 1992). To illustrate, Lewinsohn and his associates (Lewinsohn, Rohde, Seeley, & Fischer, 1993) analyzed retrospective and cross-sectional data from four studies which had examined past and current diagnoses of depression. These researchers found support for A C E i n adolescents w i t h 7.2% from a later cohort (1972 to 1974) experiencing M D D i n comparison w i t h 4.5% from an earlier cohort (1968 to 1971). Although no definitive causes for the increase ("secular increase") i n depression have yet been identified, it has been suggested that the cohort effect i n youth may well be due to their exposure to increasingly more challenging environments (e.g., greater violence, abuse and family dysfunction) as well as to decreasingly available supports  29 (e.g., long-term, stable friendships and family relationships) (Birmaher, Ryan, & Williamson, 1996). Age and Gender Effects A consistent finding from prospective studies of depression i n children and adolescents has been that the severity of symptoms and prevalence of disorders increases dramatically w i t h age, with the lowest rates among preschoolers and the highest rates among adolescents, especially those w h o have reached puberty (Poznanski & Mokros, 1994). In a randomly selected community sample of adolescents, Lewinsohn and associates found that the average age of onset of M D D is 15 years of age (Lewinsohn, Clarke, Seeley, & Rohde, 1994; Lewinsohn, Hops, et al., 1993; Lewinsohn, Rohde, & Seeley, 1998). In a prospective study of depressed mood, H a n k i n and associates achieved complementary results. These researchers noted that depressed mood increased from 2.7% to 16.8% across the period from 15 to 18 years of age (Hankin et al., 1998). While there is a substantial increase i n overall rate of depression across the adolescent period, there are also significant gender differences. After the age of 13, and particularly between the ages of 15 and 18 years, adolescent females experience significantly more depressive symptoms and depressive disorders than males, such that they are twice as likely to be affected by depression as males of the same age ( A P A , 1994; Ge, Lorenz, Conger, Elder, & Simons, 1994; Nolen-Hoeksema & Girgus, 1994). H a n k i n et al. (1998) noted that depression increased from 4% to 23% among females and from 1% to 11% for males across the age span from 15 to 18 years. This 2:1 ratio continues for prevalence of M D D among adults (Fleming & Offord, 1990; Lewinsohn, Clarke, et al., 1994).  30 Although reasons for the widening gap between females and males during adolescence are not yet entirely clear (Hankin & Abramson, 2001; Nolen-Hoeksema, 1994), empirical evidence suggests that multiple interacting factors and processes contribute to the development of gender differences i n depression. One factor that has received empirical support is the pressure of gender-typed societal expectations; that is, a greater emphasis on active problem-solving and instrumental competence for males in comparison w i t h a greater emphasis on relying on others and minimizing assertive self-expression for females, which places the latter at greater risk for developing feelings of hopelessness and depression (Gjerde, 1995; Gjerde, Block, & Block, 1988). Another empirically supported factor is response style. Females tend to respond to distress w i t h rumination and self-focus, which predisposes them to internalizing difficulties, while males tend to respond to distress w i t h action, w h i c h predisposes them to substance abuse and externalizing difficulties (Nolen-Hoeksema, 1994; NolenHoeksema & Girgus, 1994). Finally, the greater interpersonal affiliative need of females, w h i c h places them at greater risk than males when faced w i t h negative events w i t h interpersonal consequences (e.g., an argument w i t h a friend) (Cyranowski, Frank, Young, & Shear, 2000), has been implicated i n gender differences i n depression i n adolescents. Given the factors attributed to gender differences i n prevalence of depression, it is not surprising that adolescent females and males tend to report different symptoms of psychosocial stress and to express their feelings i n different ways. For example, while females are generally more concerned with self-adequacy, personal appearance (particularly weight), social relationships, and academic success, and are more likely to express their disturbance i n somatic complaints, introspection and sometimes body-  3i  image distortion (Campbell, Byrne, & Baron, 1992), males are generally more concerned with their physical abilities and substance abuse issues and are more likely to express their disturbance i n irritability, acting-out, and physical aggression (Gjerde et al., 1988; Offer & Schonert-Reichl, 1992). Negative Outcomes Associated w i t h Depression Depression, whether experienced as symptoms or as a diagnosed mood disorder, is regarded w i t h serious concern due not only to the affected adolescent's immediate experience of intense misery and distress, but also to the associated short and long-term negative outcomes for the adolescent, his or her family members, and the community at large. In the short-term, affected adolescents may experience impaired daily functioning (including academic functioning) and significant disruptions i n their relationships w i t h family, friends, and the important adults i n their lives (e.g., teachers and employers) (Birmaher, Ryan, Williamson, Brent, Kaufman, et al., 1996; Gotlib et al., 1995; NolenHoeksema, 1994; Vitaro & Pelletier, 1995), which may undermine affected adolescents' ability to achieve their goals, including the grades necessary to enter post-secondary education (Nolen-Hoeksema, 1994). In addition, the experience of depression has been linked w i t h increased risk for engaging in self-harming behaviours including suicidal ideation and suicide completion (Luby et al., 1996; Reynolds, 1994b; Reynolds & M a z z a , 1994)In the long-term, the experience of depression during childhood or adolescence is associated w i t h increased risk for serious mental health problems i n adulthood (Hankin & Abramson, 2001; Reynolds, 1994b) including further m o o d disorders (Parker & Roy, 2001), anxiety disorders (Harrington & Dubicka, 2001), and substance abuse (Birmaher,  32 Ryan, Williamson, Brent, Kaufman, et al., 1996), all of w h i c h may contribute to family, social, and employment dysfunction (Thorpe et al., 2001). In turn, these associated outcomes place considerable burden on the community i n terms of loss of productivity and increased health care costs (Cicchetti & Toth, 1998; Gotlib, et al., 1997). Indeed, the W o r l d Health Organization's 1990 Global Burden of Disease study revealed that unipolar major depression was the second major source of disease burden i n "established market economies" (National Institute of Mental Health ( N I M H ) , 2001). Finally, adolescent depression is of serious concern because research has demonstrated that the condition is often unrecognized and undertreated. Parents and teachers are often not aware of an adolescent's condition due to the internalized nature of depression as w e l l as the fact that many adolescents, especially males, express their depression through irritability and anger, which may be misconstrued and not recognized as indicators of depression (Reynolds, 1990b; Reynolds & Johnston, 1994). With regard to treatment, studies indicate that the majority of distressed adolescents do not receive therapeutic help (Kowalenko et al., 2002; Reynolds & Johnston, 1994; Whitaker et al., 1990). Conclusions Regarding Adolescent Depression Depression is a serious and growing mental health concern. Prospective community studies have yielded compelling evidence that adolescence, particularly between the years of 15 to 18, is a critical time for increased vulnerability to depressive symptoms and disorders, especially for females (Hankin & Abramson, 2001). Epidemiological studies indicate that at any point i n time (i.e. "point prevalence"), approximately 3 % of adolescents are likely to be experiencing depression severe  33  enough to warrant a diagnosis of M D D or D D while over the course of their adolescent years (i.e. "life-time prevalence"), between 10 and 24% are likely to receive a diagnosis of M D D or D D (Lewinsohn, Hops, et al., 1993). In addition to immediate concerns about affected adolescents' distress and risk for self-harm are concerns about their long term development, including the risk for recurrence of their difficulties as well as the development of other mental disorders. Finally, the experience of depression, which impacts interpersonal and daily functioning as well as academic performance, may well curtail affected adolescents' development and negatively affect their life trajectories. Adolescent Anxiety Anxiety has only recently been recognized as a prevalent and highly-impairing condition among children and adolescents. A s a consequence, the research base is relatively sparse, especially i n comparison w i t h the well-researched area of child and adolescent depression (Manassis, 2000). Nonetheless, it is n o w widely recognized that anxiety is the most prevalent form of psychopathology among children and adolescents (Malcarne & Hansdottir, 2001) and a condition that can have significant deleterious effects upon affected adolescents' normative development (Woodward & Fergusson, 2001). Conceptualizing and Defining Anxiety Anxiety is an internalizing condition that typically involves subjective feelings (e.g., discomfort, dread, and numbness), behaviours (e.g., avoidance and social withdrawal), and physiological responses (e.g., sweating, nausea, and breathing difficulties) (Merrell, 1999). Unlike depression, however, where all of the disorders apply to the entire developmental range, there is one anxiety disorder (separation  34  anxiety disorder) that is unique to children and adolescents. The other anxiety disorders as defined i n D S M - I V (Panic Disorder Without Agoraphobia, Panic Disorder W i t h Agoraphobia, Agoraphobia Without History of Panic Disorder, Specific Phobia, Social Phobia, Obsessive-Compulsive Disorder, Posttraumatic Stress Disorder, Acute Stress Disorder, Generalized Anxiety Disorder, Anxiety Disorder Due to a General Medical Condition, Substance-Induced Anxiety Disorder, and Anxiety Disorder N o t Otherwise Specified,) apply to children and adolescents as well as to adults ( A P A , 1994). While children and adolescents are most commonly diagnosed w i t h Generalized Anxiety Disorder, Separation Anxiety Disorder, and Specific Phobia, during their early teen years adolescents tend to develop vulnerabilities w h i c h may lead to diagnoses of disorders which are commonly found i n adults; namely, the Panic Disorders, Agoraphobia and Social Phobia (Bernstein, Borchardt, & Perwien, 1996). Although this study is primarily concerned w i t h the experience of symptoms of anxiety rather than with anxiety disorders, reference w i l l be made to these disorders, particularly Generalized Anxiety Disorder, which is the most commonly diagnosed disorder among adolescents (Merrell, 1999) when referring to prevalence estimates. The D S M - I V criteria for G A D are presented i n Figure 3 . Although anxiety has many aspects in common w i t h depression - namely, substantial prevalence during adolescence, multiple causation, heterogeneity, and existence along a continuum of increasing severity and complexity from symptoms to diagnosed disorders - anxiety has traditionally been investigated quite separately. This is largely due to independent initial theories, systems of classification i n the various editions of the Diagnostic and Statistical Manuals of Mental Disorders, and bodies of  35  Figure 3. D S M - I V Criteria for Generalized Anxiety Disorder ( G A D ) A.  Excessive anxiety and worry (apprehensive expectation), occurring more days than not for at least 6 months, about a number of events or activities (such as work or school performance).  B.  The person finds it difficult to control the worry.  C.  The anxiety and worry are associated with three (or more) of the following six symptoms (with at least some symptoms present for more days than not for the past 6 months). Note: Only one item is required in children. (1) restlessness or feeling keyed up and on edge (2) being easily fatigued (3) difficulty concentrating or mind going blank (4) irritability (5) muscle tension (6) sleep disturbance (difficulty falling or staying asleep, or restless unsatisfying sleep)  D.  The focus of the anxiety and worry is not confined to features of an Axis 1 disorder, e.g., the anxiety or worry is not about having a Panic Attack (as in Panic Disorder), being embarrassed in public (as in Social Phobia), being contaminated (as in ObsessiveCompulsive Disorder), being away from home or close relatives (as in Separation Anxiety Disorder), gaining weight (as in Anorexia Nervosa), having multiple physical complaints (as in Somatization Disorder), or having a serious illness (as in Hypochondriasis), and the anxiety and worry do not occur exclusively during Posttraumatic Stress Disorder.  E.  The anxiety, worry, or physical symptoms cause clinically significant distress or impairment in social, occupational, or other important areas of functioning.  F.  The disturbance is not due to the direct physiological effects of a substance (e.g., a drug of abuse, a medication) or a general medical condition (e.g., hyperthyroidism) and does not occur exclusively during a Mood Disorder, a Psychotic Disorder, or a Pervasive Developmental Disorder.  ( A P A , 1994, pp. 435-436) research (Alloy, Kelly, Mineka, & Clements, 1990; Zahn-Waxier et al., 2000). A review of articles listed i n the P s y c I N F O database for the past 10 years (1993-2003) revealed that to some extent, this research trend continues. While 705 articles were classified with adolescence and depression as key concepts and 321 articles w i t h adolescence and anxiety as key concepts, only 106 articles addressed anxiety and depression i n adolescence.  36  There is an increasing move, however, particularly among developmental psychopathologists, to examine these two internalizing difficulties i n concert. This move is due to a growing recognition of the considerable overlap i n affected individuals' symptoms, family histories, responses to treatment, and etiology (i.e., presumed causation) (Alloy et al., 1990) as well as to findings that indicate the presence of important differences among children and adolescents w h o experience only depression, only anxiety, or comorbid depression and anxiety (Brady & Kendall, 1992). Accordingly, the present study w i l l examine whether there are indeed important differences among groups of adolescents w i t h learning (and reading) disabilities who report clinically significant symptoms of anxiety, depression, or both i n relation to their academic achievement, perceptions of self-efficacy and social support, and their experience of life events. Measuring Anxiety Consistent w i t h assessment methods for depression, adolescent anxiety is typically measured by one or more of three general methods - clinical interviews, reports from parents, teachers or peers, and/or self-reports. In clinical settings, where the focus is upon making a diagnosis and providing treatment, the psychiatrist or psychologist may well use self-reports and reports by others close to the patient, but the primary tool is the clinical interview. A s in the case of depression, structured interview schedules are often utilized. The Diagnostic Interview Schedule for Children (DISC) (Costello, Edelbrock, Kalas, & Dulcan, 1984) and the Diagnostic Interview for Children and Adolescents - Revised (DICA-R) (Reich, Leacock, & Shanfield, 1994) are widely used i n diagnosing anxiety disorders.  37  In schools and community settings, where the focus is u p o n identifying students who are i n need of clinical attention, self-reports as well as reports from parents, teachers and mentors, a n d / o r peers are important tools. However, as discussed i n regard to depression, many aspects of internalizing disorders are not readily detectable, even to those w h o k n o w the affected individual well. For this reason, the use of a selfreport measure is extremely valuable when examining an adolescent's experience and symptoms of anxiety. The most widely-used self-report measure is the Revised Children's Manifest Anxiety Scale ( R C M A S ) (Reynolds & Richmond, 1985) w h i c h can be used w i t h young people from 6 to 17 years of age. Although normative data for the R C M A S was obtained from a large sample (almost 5,000 children and adolescents across the United States) and the psychometric properties of the instrument have been rated as acceptable (Merrell, 1994; Schniering, H u d s o n , & Rapee, 2000), there are a number of concerns about this measure including the comparatively l o w reliability (internal consistency and test-retest) of the subscales (Merrell, 1994,1999) as well as the weak discriminant validity of the overall scale (Hodges, 1990; Myers & Winters, 2002b). Further to the latter, the R C M A S has been criticized for its symptom overlap w i t h measures of depression (Brady & Kendall, 1992; Hodges, 1990; Perrin & Last, 1992; Stark, Kaslow, & Laurent, 1993), which limits its ability to adequately identify individuals w i t h clinically significant levels of anxiety (Dierker et al., 2001). To illustrate, Hodges (1990) reported a correlation of .70 between the R C M A S and the Children's Depression Inventory (CDI) but only a correlation of .50 between the R C M A S and another measure of anxiety widelyused with children, the State-Trait Anxiety Inventory for Children (STAIC) (Spielberger, 1973). The difference between these two sets of correlations was statistically significant.  38  A more recent measure that is receiving considerable support from the field (Manassis, 2000; Myers & Winters, 2002b) is the Multidimensional Anxiety Scale for Children (MASC) (March, 1997). The M A S C , which w i l l be utilized i n the present study, has received excellent reviews for its clear specification of the construct of anxiety, for its good reliability (e.g., M a r c h (1997) reported internal reliability coefficients of .88 for females and .89 for males and a 3-month test-retest reliability of .93), and for its ability to measure anxiety separately from depression (Dierker et al., 2001; Myers & Winters, 2002b), the latter being of particular importance i n the present study. Prevalence of Anxiety Similar to the case for depression, it is a challenge to gain clarity on prevalence rates of anxiety within the adolescent population. In addition to sharing the confounding factors outlined for depression; namely, definition (symptoms or disorders), measures (reliability and validity as well as approach - categorical or dimensional), prevalence time period, and sample (especially w i t h regard to age and gender), findings from epidemiological studies of anxiety are difficult to compare and interpret because of a lack of standardization i n the reporting of results (Waddell, Offord, Shepherd, H u a , & M c E w a n , 2002) as well as constant revisions to the Diagnostic and Statistical Manual of Mental Disorders (DSM) i n terms of specified disorders as well as their diagnostic criteria (Costello & A n g o l d , 1999; Malcarne & Hansdottir, 2001). A n example pertinent to adolescents is the elimination of Over Anxious Disorder (OAD) described i n DSM-III and DSM-III-R. Adolescents w h o w o u l d have met the diagnostic criteria for O A D under these editions of the D S M are most likely (but not necessarily) to be diagnosed w i t h Generalized Anxiety Disorder (GAD) under the DSM-Pv system 7  39  (Merrell, 1999). Despite these challenges, however, recent studies indicate that anxiety is a highly prevalent form of psychopathology among adolescents and one that warrants attention. Costello and A n g o l d (1995) reviewed studies conducted between 1987 and 1995 and noted that point prevalence rates for anxiety disorders among adolescents ranged from 5.7% to 17.7% for any disorder. A n even higher rate was obtained by W o o d w a r d and Fergusson (2001) w h o found that 29.9% of their sample of adolescents aged from 14 to 16 years (from the D u n e d i n Multidisciplinary Health and Development Study) met the criteria for at least one anxiety disorder (with 11% meeting the criteria for Generalized Anxiety Disorder (GAD). A recent study completed b y Dierker et al. (2001) yielded an even higher estimate (of 20%) for G A D , among 632 9th-grade students enrolled i n 5 U.S. high schools. In contrast, Waddell et al. (2002) estimated a lower prevalence rate. These researchers reviewed extant epidemiological studies (identified by means of Medline) and selected 6 studies that met their criteria of utilization of rigorous design, representative community samples comparable w i t h Canadian children and adolescents, standardized assessment protocols measuring both symptoms and impairment, and reports from multiple informants. O n the basis of these studies (the Ontario C h i l d Health Study, the N I M H Methods for the Epidemiology of C h i l d and Adolescent Mental Disorders, the Great Smoky Mountains Study, the Virginia T w i n Study of Adolescent Behavioral Development, the Quebec C h i l d Mental Health Survey, and the British C h i l d Mental Health Survey), Waddell et al. estimated that a prevalence rate of 6.4% for any anxiety disorder among children and adolescents.  4° W i t h regard to symptoms of anxiety, many studies report mean symptom levels (often mean raw scores) rather than prevalence rates based on T-scores. A s a consequence, comparative prevalence data is scarce. Nonetheless, a recent review of studies reporting prevalence rates for clinically significant levels of symptomatology indicated that point prevalence estimates ranged from approximately 5% to 25% (mean 11.7%), a similar range to that reported for anxiety disorders (see review by Boyd, Kostanski, Gullone, Ollendick, & Shek, 2000). In their o w n study of 1,299 adolescents (aged 11 to 18 years) enrolled i n several schools i n Australia, Boyd et al. (2000) obtained a point prevalence rate of 13.2%. This result and those of additional comparable studies of self-reported symptomatology i n nonreferred adolescents are presented i n Table 4.  Table 4. Point-Prevalence Rates of Self-Reported Symptoms of Anxiety i n Nonreferred Adolescents Presented by Measure N  Age  1,299  11 - 1 8  Tannenbaum & Forehand (1992)  150  11 - 1 5  Stark, Kaslow, & Laurent (1993)  720  9--14  Casper, Belanoff, & Offer (1996)  497  16 - 1 8  HSCL (ANX)  8%  Millikan, Wamboldt, & Bihun (2002)  201  12 - 1 9  MASC  7%  Boyd et al. (2000)  Measure RCMAS (> cut-off 60T)  Prevalence 13.2%  RCMAS  9%  (cut-off 1.5 SD)  RCMAS (> cut-off 60T)  8.6%  Note: RCMAS = Revised Children's Manifest Anxiety Scale (Reynolds & Richmond, 1985); HSCL (ANX) = Hopkins Symptom Checklist (Anxiety Scale) (Derogatis et al., 1974); MASC = Multidimensional Anxiety Scale for Children (March, 1997) A s shown, the point-prevalence rates for clinically significant symptoms of anxiety ranged from 7% to 13.2% ( M = 9.16%) across these studies. For the purpose of comparing the results of the present study with previous findings, studies that utilized  4i  the M A S C and reported mean scores were also examined. The mean score results of these studies are presented i n Table 5. Table 5. Mean Total Anxiety Scores Reported by Studies that Utilized the M A S C N  Age  Muris et al. (2002)  521  12--18  Millikan et al. (2002)  201  12--19  229  Studies  Dierker et al. (2001)  Total M(SD)  Females  Males  M(SD)  M(SD)  43.2 (17.7)  32.0 (18.3)  n.r.  39.7 (14.8)  31.8(11.9)  13--15  n.r.  35.4 (16.70)  29.7 (15.52)  155  13--15  n.r.  36.4 (14.54)  32.5 (12.86)  248  13--15  n.r.  40.3 (16.15)  29.8 (13.55)  38.0 (18.8)  Sig. Diff  </  Note: Mean scores are Total scores (raw scores) and not mean T-scores; The sample utilized by Dierker et al. (2001) was composed of 9th grade students from 3 different geographic locations and mean scores were reported separately for each site.  Age and Gender Effects In contrast to depression, there has been relatively little theoretical and empirical work concerning age and gender differences i n anxiety. Nonetheless, available research suggests that by 6 years of age, twice as many females as males have experienced an anxiety disorder and that this 2:1 ratio (similar to that for depression) continues into adolescence (Gullone, K i n g , & Ollendick, 2001; Kovacs & Devlin, 1998; Lewinsohn, Gotlib, Lewinsohn, Seeley, & A l l e n , 1998). Certainly i n their study of 9th grade students, Dierker et al. (2001) found that 24% of the females and 12% of the males met the criteria for a diagnosis of Generalized Anxiety Disorder (GAD). W i t h regard to symptoms of anxiety, Boyd et al., (2000) found that significantly more females (17.5%) reported clinically significant levels of symptomatology than males (8.5%). Concerning differences i n the prevalence of anxiety across the developmental period, Costello and A n g o l d (1995) noted i n their review of epidemiological studies that  42 anxiety disorders as a group appear to increase only slightly w i t h age, and that the effect cannot be detected i n any specific disorder. In support of this finding, Boyd et al. (2000) found no significant differences i n levels of symptoms of anxiety across the developmental period (11 to 18 years) of their participants. The lack of increase in anxiety w i t h age during adolescence contrasts markedly w i t h depression, i n which there are substantial increases i n prevalence of both symptomatology and disorders, especially during the late adolescent period. Negative Outcomes Associated w i t h Anxiety Anxiety i n adolescents, both as significant symptomatology and as diagnosed disorders, is regarded w i t h concern for three reasons. First, the experience of anxiety can be extremely debilitating, curtailing an adolescent's normative development especially w i t h regard to the establishment of stable social relationships and the achievement of academic goals (Woodward & Fergusson, 2001). Second, anxiety often precedes depression and is viewed as conferring additional risk for the development of depression and additional psychopathologies including further difficulties w i t h anxiety (Costello, Mustillo, Erkanli, Keeler, & A n g o l d , 2003; H a n k i n & Abramson, 2001; Malcarne & Hansdottir, 2001; Zahn-Waxier et al., 2000). Third, as w i l l be discussed further, anxiety is highly comorbid w i t h depression (Axelson & Birmaher, 2001; Brady & Kendall, 1992) and this particular comorbidity confers risk for increased severity and duration of depressive symptoms as well as increased risk for substance abuse, suicidality, and an array of significant psychosocial problems (Birmaher, Ryan, Williamson, Brent, Kaufman, et al., 1996; W o o d w a r d & Fergusson, 2001).  43  Conclusions Regarding Adolescent Anxiety Anxiety is the most prevalent form of psychopathology among adolescents (Malcarne & Hansdottir, 2001) w i t h point prevalence rates generally falling within the 5 to 25% range for symptomatology (Boyd et al., 2000) and within the 6 to 18% range for disorders (Costello & A n g o l d , 1995), although a recent study established a prevalence rate of almost 30% for anxiety disorders among a large cohort of nonreferred youth (Woodward & Fergusson, 2001). For many adolescents, the experience of anxiety can be extremely debilitating, curtailing their psychosocial and academic development. Of additional concern is the finding that anxiety appears to confer risk for the subsequent development of further difficulties w i t h anxiety and the development of other psychopathologies including depression. Accordingly, adolescent anxiety is a condition of considerable concern to professionals and parents. Comorbidity of Depression and Anxiety A robust finding across a range of studies, which have examined both clinic and nonreferred samples, is the considerable rate of comorbidity of depression and anxiety (Brady & Kendall, 1992; H a n k i n & Abramson, 1999; Kovacs, Gatsonis, Paulauskas, & Richards, 1989; Malcarne & Hansdottir, 2001; N e w m a n et al., 1996). For example, it has been estimated that as many as 25 to 50% of depressed adolescents w i l l receive an additional diagnosis of an anxiety disorder and 10 to 15% of anxious adolescents w i l l receive an additional diagnosis of depression (Axelson & Birmaher, 2001). O f further concern is that these estimates may well underestimate the rates (and the effects on functioning) of comorbidity given that few studies have accounted for high levels of subclinical symptomatology (Zahn-Waxier et al., 2000).  44  Comorbidity of anxiety and depression has received considerable attention because individuals w i t h this dual diagnosis appear to experience more severe symptoms, longer episodes, greater functional impairment, and a greater risk for a recurrence of their difficulties than individuals w i t h a single diagnosis (Brady & Kendall, 1992; Essau, 2003; H a n k i n et al., 1998; Strauss, Last, Hersen, & K a z d i n , 1988). But there are also questions about the comorbidity of depression and anxiety. There has been considerable debate as to whether depression and anxiety are separate but overlapping constructs or a single construct (Angold, Costello, & Erkanli, 1999; Schniering et al., 2000; Stark et al., 1993). In part, the confusion surrounding the two disorders and their comorbidity may result from overlapping diagnostic criteria (Anderson & McGee, 1994; Essau, 2003). To illustrate, depression and anxiety share symptoms of irritability, restlessness, difficulties w i t h concentration, sleep disturbance and fatigue. Nonetheless, empirical studies suggest that the two conditions are distinguishable when appropriate measures are utilized (March, 1997; Schniering et al., 2000), that there are significant differences between children and adolescents within the three diagnostic groups (anxiety, depression, concurrent anxiety and depression), and that these differences have important implications for treatment (Angold et al., 1999; Brady & Kendall, 1992). A s a result of these differences, the present study has utilized a measure of anxiety (the M A S C ) that, as noted earlier, has been shown to discriminate well between symptoms of anxiety and depression (Dierker et al., 2001; Myers & Winters, 2002b). This study examines the prevalence of comorbidity i n a sample of adolescents with learning (and reading) disabilities, as well as differences among students reporting high levels of anxiety, or depression, or both anxiety and depression.  45  Depression and A n x i e t y i n Adolescents w i t h Learning Disabilities Students w i t h learning disabilities have typically experienced years of chronic stress as a result of their learning difficulties. In addition, many of these students have also experienced problems i n establishing and maintaining satisfying relationships w i t h their peers (Bryan, 1997; Kavale & Forness, 1996). N o t surprisingly, therefore, many i n the field are of the opinion that these students are at greater risk than their normally achieving peers for developing social-emotional difficulties, especially depression (Bender, Rosenkrans, & Crane, 1999; Bender & W a l l , 1994; Gorman, 1999; Huntingdon & Bender, 1993; Learning Disabilities Association of America ( L D A ) , 1999,2004; Weinberg & Emslie, 1988; Wright-Strawderman, Lindsey, Navarette, & Flippo, 1996). Indeed, positing a relationship between learning difficulties (especially i n reading) and social-emotional distress has a long history (Gates, 1937,1941) and remains encapsulated i n both the ICD-10 and the D S M - I V . The ICD-10 lists l o w self-esteem, emotional problems and peer relationship difficulties as features commonly associated with reading disabilities while the D S M - I V indicates the possibility of elevated rates of depression. Nonetheless, empirical research has not uniformly supported these views. But before reviewing the bodies of studies w h i c h have examined the prevalence and severity of depression and anxiety i n students w i t h learning disabilities, it is important to unravel what is meant by the terms, learning disabilities and reading disabilities, both i n the literature and in the present study. It is important because even after 40 years, the field continues to search for consensus on definitions and methods of identification. N o t surprisingly therefore, inconsistencies abound i n the literature. A n d  46  as w i l l be shown, these inconsistencies threaten the interpretability and utility of findings (Durrant, 1994). Defining and Identifying Learning and Reading Disabilities The term learning disabilities was first introduced i n 1963 at a conference of concerned parents and educators who sought to describe and access assistance for youngsters who appeared to be intelligent but who were not achieving to the level that might be expected given their general aptitude for learning (Lerner, 2000; Torgesen, 1995; Wong, 1996). From that day (when the first Learning Disabilities association was voted into existence) until the present, there has been continuing and often heated debate as to what is exactly meant by the term (Aaron, 1991; Durant, 1994; Fletcher & Foorman, 1994; Siegel, 1989; Stanovich, 1999; Torgesen, 1995; Vellutino, Scanlon, & Lyon, 2000) and how individuals w i t h learning disabilities should most appropriately be identified (Proctor & Prevatt, 2003; Speece & Shekitka, 2002). To a large extent, difficulties i n defining learning disabilities stem from the highly varied nature of the disorder. Since being recognized as a diagnosable condition, learning disabilities have been regarded as heterogeneous i n origin (stemming from genetic a n d / o r neurobiological dysfunctions), heterogeneous i n effect (resulting i n impairments i n one or more of the cognitive processes such as language processing, memory and attention, visual-spatial reasoning, and executive functioning), and heterogeneous i n outcome (affecting the acquisition and utilization of one or more of a range of skills including oral language, reading, spelling and written language, mathematics, organizational skills, and social skills) (Learning Disabilities Association of Canada, 1981,2002; Lerner, 2000; National Joint Committee on Learning Disabilities (NJCLD), 1997; L y o n , 1996). W i t h i n this broad definition, an individual w i t h significant  47 difficulties i n the area of reading w o u l d be regarded as having a reading disability. Given the highly varied nature of learning disabilities (and reading disabilities) as well as the number and needs of the different stakeholders involved (parents and advocates, educators, psychologists, researchers, school officials and bureaucrats), it is not surprising that consensus has not yet been reached on the most appropriate (and acceptable) methods for defining the conditions and identifying affected individuals (Torgesen, 1995). Nonetheless, two broad approaches to identification can be seen within the literature; namely the "aptitude-achievement discrepancy approach" and the "functional skills assessment approach." In essence, the aptitude-achievement discrepancy approach focuses on the seemingly unexpected failure of students with learning (and reading) disabilities, and specifies that these individuals should present with significant discrepancies between their measured aptitude for learning and their academic achievement i n order to be classified as having a learning disability. This approach is encapsulated i n the Individuals w i t h Disabilities A c t (IDEA) of 1990 (and the amendments of 1997) w h i c h form the basis for state definitions and practice i n schools i n the U.S. (Lerner, 2000) as well as the definitions of both learning disorders and reading disorders i n the D S M - I V ( A P A , 1994). The D S M - I V states that a Learning Disorder can be diagnosed when an "individual's achievement on individually administered, standardized tests i n reading, mathematics, or written expression is substantially below that expected for age, schooling and level of intelligence" ( A P A , 1994, p. 46). "Substantially below" is defined as a discrepancy of more than two standard deviations between achievement and IQ, although the manual notes that a smaller discrepancy (between one and two standard  4  8  deviations) may be utilized when it is believed that an individual's performance on the measure of cognitive ability may have been compromised by "an associated disorder i n cognitive processing, a comorbid mental disorder or general medical condition, or the individual's ethnic or cultural background" ( A P A , 1994, p. 47). In the case of participants w i t h learning disabilities, many i n the field believe that the processing difficulties faced b y these students (e.g., expressive language, attention, and memory) warrant a reduced discrepancy, of 1.5 standard deviations, between aptitude and achievement. Indeed, i n the United States, 79% of the states utilizing a standard score discrepancy model defined a significant discrepancy as a difference of 1 to 1.5 standard deviations (Frankenberger & Fronzaglio, 1991). W i t h regard to a Reading Disorder, the D S M - I V states that an essential feature is reading achievement ("reading accuracy, speed or comprehension as measured by individually administered standardized tests") that falls "substantially below that expected given the individual's chronological age, measured intelligence, and ageappropriate education" ( A P A , 1994, p. 48). In the case of a reading disorder, however, the magnitude of the requisite discrepancy is not specified. Although the discrepancy approach has a long history of use and has been lauded by some for its apparent objectivity (Shaw, Cullen, M c G u i r e , & Brinckerhoff, 1995), it has been increasingly criticized for its over-reliance on IQ testing (Siegel 1989,1999; Stanovich, 1991a, 1999), for its highly varied implementation (use of different IQ tests/scores and discrepancy formulae (e.g., standard score difference or regression)) resulting i n nonequivalent eligibility decisions (Fletcher et al., 1998; Kaufman & Kaufman, 2001; Shaw et al., 1995), and for its lack of a utility i n diagnosing reading  49  disabilities and informing instruction (Fletcher et a l 1998; Torgesen & Wagner, 1998; v  Vellutino et al., 2000). A s a result, there has been a move towards a greater emphasis on the assessment of individuals' skills and functioning including intra-individual discrepancies. This approach to the identification of learning disabilities, w h i c h is named here as the "functional skills assessment approach," has long been touted by researchers such as Siegel and Stanovich, who along with others (Torgesen & Wagner, 1998; Vellutino et al., 2000) have stressed the critical importance of assessing core phonological abilities i n the case of reading disabilities. The functional skills approach is now receiving greater support within the field and is reflected i n other current definitions; for example, the definitions of the N J C L D (1997) and more recently, of the ten organizations participating i n the Learning Disabilities Round table (U.S. Department of Education, 2002). A functional skills approach is also evident i n the current B C Ministry of Education (2002) criteria for classification of students w i t h learning disabilities i n that a specific discrepancy is no longer specified (formerly a 2 standard deviation discrepancy was required) and a much greater emphasis is now placed on multiple sources of assessment data (standard testing, curriculum-based assessment, observation, and information from parents) to examine and track a student's development i n specific areas of skill deficit. A s part of the press for a functional skills approach, Stanovich (1999) has stated that the term, learning disabilities, is a confusing umbrella term and he advocated for the separate consideration and labeling of domain-specific disabilities (e.g., reading disability or an arithmetic disability). In their research, Siegel and her associates (Barwick & Siegel, 1996; McBride & Siegel, 1997; Morrison & Siegel, 1991) have  5° operationalized this call by defining individuals w i t h reading disabilities as those whose w o r d reading skills (on the reading subtest of the Wide Range Achievement Test) fall at or below the 25th percentile (a level that is equivalent to a standard score of 90). Those w i t h w o r d reading skills at or above the 30th percentile were classified as normally achieving. Although the functional skills approach is receiving considerable positive attention, it is not without criticism. Some have argued that this approach is overly inclusive (a problem for funding and service delivery (Fletcher et al., 1998; Wong, 1989)) and that it fails to differentiate individuals of average and above intelligence with specific and unexpected learning difficulties from individuals w i t h l o w intelligence and commensurate low achievement, a cornerstone of learning disabilities as a special education category (Kaufman & Kaufman, 2001). Interestingly, throughout all of the controversies, this is one facet of the original conception of learning disabilities that remains constant. That is, the majority of researchers w i t h i n the field continue to agree that individuals w i t h learning disabilities are of average or above average intelligence and present w i t h significant difficulties i n particular areas of academic achievement (Kaufman & Kaufman, 2001). A s a result, therefore, it is not surprising that the most have continued to use the aptitudeachievement discrepancy model to select or to describe the participants with learning disabilities i n their studies (Stanovich, 1991b). In the present study, both discrepancy and functional skills approaches were utilized in classifying the participants as having learning or reading disabilities. There were several important reasons for adopting multiple approaches to classifying the students w i t h i n the sample. First, by adopting the traditional aptitude-achievement  51 discrepancy approach, including students w i t h processing and performance problems across a range of academic skills, the results of the present study could be more readily compared w i t h previous research on adolescents w i t h "learning disabilities" as often defined i n the literature. Second, by restricting attention to a subgroup of students with reading disabilities, albeit defined i n three different ways, it was possible to more closely examine the skills and social-emotional functioning of individuals who face significant challenges i n a specific skill area that is crucial for success i n school and beyond. Focusing attention on just students with reading challenges also reduced the heterogeneity of the sample under study (as recommended b y Durrant, 1994). The subgroup of participants with reading disabilities was identified three times, using three different criteria. First, the subgroup was formed on the basis of the operational definition instituted by Siegel and her associates (Barwick & Siegel, 1996; McBride & Siegel, 1997; Morrison & Siegel, 1991); namely, by selecting all those students w h o scored at or below a standard score of 90 (25th percentile) on the reading subtest of the WRAT-3. This functional skills assessment approach allowed for a comparison of this study's findings w i t h those of Siegel and others w h o have used this method for identifying students w i t h reading disabilities. Second, the subgroup was reformed on the basis of the discrepancy (1.3 standard score points between verbal ability and w o r d reading skills) used by the B.C. Ministry of Education to identify those students who were eligible for being provided w i t h a reader during their provincial examinations. Finally, the reading disability group was reidentified on the basis of a different type of discrepancy, that between students' comprehension levels and w o r d reading  52 skills. This group was formed in response to my observations as a teacher and researcher that students w h o are severely challenged by w o r d reading deficits, but are able to make good use of context clues and their knowledge of the w o r l d and language to comprehend text, are deeply frustrated by their difficulties (especially their slow reading speed). It seemed that these students i n particular might be at considerable risk for developing negative affective outcomes. Although the reading disability subgroup could have been formed by considering a discrepancy i n the opposite direction (i.e., strong w o r d reading skills but weak reading comprehension skills), students with this profile had not been observed to have notable social-emotional difficulties, and thus were not of specific interest i n the present study. Nonetheless, it is acknowledged that these students could be frustrated by their reading difficulties as well. Consequently, an examination of their self-perceptions may be warranted i n future investigations. By categorizing the participants i n these four ways - one w a y identifying students w i t h general learning disabilities and three ways identifying students w i t h reading disabilities - there was a degree of overlapping membership, but it was possible to investigate more closely relationships among students' academic functioning, their perceptions of self-efficacy, and their experience of depression and anxiety. Details of the identification strategies are discussed more completely i n Chapter 3. Research: Learning Disabilities and Depression A s noted earlier, despite the considerable body of literature attesting to the greater vulnerability of students w i t h learning disabilities for developing social-emotional difficulties (especially depression), empirical research has not uniformly supported these views. A summary of studies that have examined self-reported symptoms of depression i n children and adolescents enrolled i n regular schools a n d / o r learning  53  disability programs is presented in Table 6. A s shown, results from these studies are inconsistent. While seven studies reported that there was a significant difference between students w i t h learning disabilities and students without disabilities (or with norms), nine studies reported no such difference w i t h regard to the experience of depressive symptoms. A number of reasons are proposed for the equivocal nature of findings regarding the prevalence and severity of depression i n students (particularly adolescents) with learning disabilities. The first reason concerns the measures used to assess symptoms of depression. Recall from the earlier discussion regarding the measurement of depression that, self-report instruments range i n the time period assessed (e.g. " n o w " by the R A D S but the "past two weeks" by the CDI), i n their reliability (e.g., test-retest reliability of .63 for the C D I , .86 for the R A D S , and .93 for the BDI-II), and i n their convergent validity (e.g., Reynolds (1987) reported a correlation coefficient of .70 between the R A D S and CDI). A s a consequence, results from studies utilizing different measures cannot be compared w i t h complete confidence. Second, even within a set of studies that have utilized the same measure (e.g., the CDI), some researchers (Rodriguez & Routh, 1989; Short, 1992) have not stated what clinical cut-off point was utilized, while others (Heath, 1992; Palladino et a l , 2000; WrightStrawderman & Watson, 1992) have used cut-off points (e.g., 12 & 13) which are recommended for use w i t h clinic-referred samples, and are considerably lower than the cut-off point of 19 recommended by Kovacs (1991) to identify individuals w i t h clinically significant symptomatology within a general population such as school students. This difficulty w i t h comparability can be seen i n an examination of the prevalence figures.  54  Table 6. Summary of Studies Examining Depression i n Students w i t h Learning Disabilities  Maag & R e i d (1994) Maag & Behrens (1989a) Howard & Tryon (2002) Maag, Behrens, & DiGangi (1992) Goldstein, P a u l , &  Sanfilippo-Cohn (1985) Wright-Strawderman & Watson (1992) Rodriguez & Routh (1989) Stevenson & Romney  95 (69 M , 26 F ) 126 (69 M , 5 7 F ) L D : 321 (219 M , 1 0 2 F ) N L D : n.a. L D : 52 (28 M , 24 F ) N L D : (norm) L D :  Hall & Haws (1989) Heath & R o s s (2000)  S h o r t (1992)  L D : 2 3 6 (164 M , 72 F )  342 (253 M , 89 L D : 85 (67 M , 18 F ) N L D : (norm) N L D :  LD:50 N L D : L D : N L D L D :  50  (1999)  -18  14 (13 M , 1 F ) 14 (13 M , 1 F ) 66 (35 M , 31 F ) : 69 (33 M , 36 F ) 85 (51 M , 34 F ) : 696 (348 M , 348 F  N L D L D : N L D  L D : 4 8 (35 M , 13 F )  N L D : 75 ( 3 6 M , 3 9 F )  )  97 n.r.  N L D :  n.r.  L D :  n.a.  N L D :  n.r.  n.r.  11  -14  11  -14  6--19 14 -19  n.r. LD:104 101  LD:94 101  LD:97 N L D :  104  LD:98 N L D :  104  n.r. LD:99 N L D :  ACHdis<15ss  IQru.  8--13  N L D :  IQ "average"  ACHdisS75%  101  N L D :  ACHdis<2Qss  ACH-2grds  n.r.  -14  IQ 90-110  BDI (cut-off 20) BDI-S (cut-off 16) BDI-II (cut-off 20) BDI-S (cut-off 16) CDI (cut-off 19) CDI (cut-off 13) CDI (cut-off n.r.) CDI  IQ85-115  8--13  -13  Measure  ACHdis<50%  LD:96  L D :  L D Criteria  IQru.  14 -17  11 - 1 2  (M&Fn.r.)  L D :  LD:80  10  )  IQM  13 -16  10  ( M & F n . r . )  (54 M , 46 F ) : 104 (54 M , 50 F 31 ( M & F n . r . )  NLD:30  L D :  (M&Fn.r.)  100  Marcheschi (2000)  Navarette  12  8-- 1 1  (norm)  N L D :  & P e a r s o n (1995)  -19  5 -8  N L D : (norm) L D : 31 ( M & F n . r . ) N L D : 31 ( M & F n . r . ) L D : 103 (85 M , 18 F )  L D :  Newcomer, Barenbaum,  F )  L D : 5 3 ( 3 7 M , 16 F )  Palladino, Poli, Masi, &  Heath (1992)  12  N L D :  N L D :  (1984)  Age  Sample  Author(s)  n.r.  IQ>85 A C H : dis 23 ss nr.  IQ>80 ACHdis2yrs  IQru. ACHdis<40%  IQ>85 A C H dis 18 ss IQ>80 A C H dis 12 ss IQru. ACHdis<15sd  IQ>85 ACH<7%ile  IQru. ACH<lSDRdg  IQru. ACHdis<15SD  (cut-off 19)  CDI (cut-off 19)  CDI (cut-off 19)  CDI (cut-off n.r.)  CDI (cut-off 13)  CDI (cut-off 12)  DAYS RADS (cut-off 77)  DEPM  DEP % L D :  10.5% 10%  N L D : L D :  20.9%  n.a. 32%  N L D : L D :  N O R M :  n.r.  N L D :  LD:26% N O R M :  N O R M :  N L D :  n.r.  14%  L D :  N O R M :  N L D : L D :  2%  17% 9%  N L D : L D : N L D : L D :  N L D :  n.r. n.r.  43% 0%  N L D :  42% 32%  L D :  n.r.  L D :  N L D : L D : N L D :  n.r. 10%  17%  M =F  ^(est)  M =F  L D :  14.88  •  M =F  L D :  22.21  x  M<F  N L D : 25.40 L D :  13.78  L D :  11.43  L D :  10.6  8.5  N L D :  M =F  •  M =F  x  n.r.  M =F  L D :  11.09  x  L D :  13.34  •/  M =F  x  F L D > F N L D  x  n.r.  •  n.r.  x  M =F  10%  24%  L D :  x  15.45 n.a.  10%  n.r.  L D :  Gender  N L D :  L D :  10%  36%  L D :  SgDif  n.r.  N L D :  n.r.  n.r.  L D :  n.r.  L D :  LD:8.09Hll.47F  NU>.934M,7.92F L D :  9.0  N L D : L D : N L D : L D : N L D :  6.4 11.79  6.93 11.97 8.75  LD:100 N L D : L D : N L D :  x  102 n.r. n.r.  x  M<F M =F  Comments students  with LDs i n  special c l a s s p l a c e m e n t  with LDs receiving SPED support students AfricanAmerican only; low IQ students from school and corrections facility students i n separate LD program (not at school) students with LDs i n special c l a s s placement students i n LD c l a s s placement; (44 M , 18 F ) students i n LD c l a s s students  placement s t u d e n t s i n LD c l a s s  placement; (52 M , 48 F ) students with LDs i n regular c l a s s placement students w i t h LDs i n  SPED class (53% M , 47% F ) s t u d e n t s w i t h LDs f r o m  medical c l i n i c  students with LDs i n regular class p l a c e m e n t students  with LDs i n  special class p l a c e m e n t students from p u b l i c  school; LD IQ 86-115  s t u d e n t s w i t h LDs i n L D : 64.00 LD:24% RADS L D : n.r. IQru. Dalley, Bolocofsky, L D : 42 (27 M , 15 F ) • M =F 17 (M) special c l a s s placement N L D : 58.81 (cut-off 77) N L D : 8 % A C H n r . N L D : n . r . N L D : 105 ( 3 9 M , 6 6 F ) Alcorn, & Baker (1992) Note: Studies are arranged by depression measure and by age of the participants; BDI = Beck Depression Inventory (Beck et al., 1961); BDI-S = BDI - Short  Form (Beck & Beck, 1972); BDI-II = BDI - 2nd ed. (Beck et al., 1996); CDI = Children's Depression Inventory (Kovacs, 1983,1991); DAYS = Depression and Anxiety in Youth Scale (Newcomer, Barenbaum, & Bryant, 1994); RADS = Reynolds Adolescent Depression Scale (Reynolds, 1987); ss = standard scores  55  To illustrate, when examining the prevalence of clinically significant symptoms of depression i n a grade 4-10 sample by means of the C D I , Dubois, Felner, Bartels, and Silverman (1995) found that a cut-off score of 19 yielded a prevalence rate of 10.1% whereas a cut-off score of 14 yielded a much higher rate, of 21.4% (see Table 2). N o t surprisingly, therefore, estimates within the present corpus of studies for clinically significant levels of depressive symptomatology range widely, from 10 to 43% among students w i t h learning disabilities and from o to 32% for students without disabilities. Fortunately, many studies have reported mean symptom levels for groups. This practice facilitates comparisons among studies that have utilized the same measure. A n examination of studies w h i c h utilized the C D I reveals that mean depression levels for students w i t h learning disabilities range from 8.09 to 13.34 while means for students without disabilities range from 6.40 to 9.34. Third, equivocal results may also stem from the nature of the samples studied. Apart from the two large scale studies conducted by M a a g and his associates (Maag & Behrens, 1989a; M a a g , Behrens, & DiGangi, 1992), the samples of students w i t h learning disabilities are relatively small (ranging from 14 to 103, M of 61). In addition, the samples often contain considerably lower numbers of females (a bane of researchers i n the area of learning disabilities), and span a wide range of ages (5 to 19 years), w i t h one study i n particular including students from several developmental periods. To illustrate, Newcomer, Barenbaum, and Pearson (1995) examined 85 students w i t h learning disabilities, and their ages ranged from 6 to 19 years. Given that two robust findings from depression research have been that prevalence is low amongst children but increases dramatically w i t h age, particularly after age 15, and  56  that during adolescence females are twice as likely to suffer from depression as males of the same age, it is unfortunate that the corpus of studies does not include more adolescent samples, especially samples w i t h equal representation of females and males. Note, however, that although two of the studies w h i c h examined older adolescents d i d report significant gender differences i n favour of females (Maag et al., 1992; Newcomer et al., 1995) a gender difference was not as widespread a finding as might have been expected. Finally, and most importantly, equivocal results likely stem from a lack of consistency across studies w i t h regards to the identification of students w i t h learning disabilities. A s can be seen i n Table 6, not all of the studies i n this particular body of research have specified the cognitive abilities of the students w i t h learning disabilities. A l t h o u g h 9 studies reported mean IQ scores (all but one of which fall within the average range), only 7 studies stated the specific criteria utilized in identifying participants w i t h learning disabilities. A n d w i t h i n these 7 studies, the specified lower limit of cognitive ability varies from a standard score of 80 (Short, 1992; Stevenson & Romney, 1984) through 85 (Heath, 1992; Heath & Ross, 2000; M a a g et al., 1992; Wright-Strawderman & Watson, 1992) to 90 (Maag & Reid, 1994). Of further concern w i t h regards to comparability of findings is that within the 7 studies that d i d provide information about cognitive ability, 2 studies utilized truncated samples. M a a g and his associates (Maag & Reid, 1994; M a a g et al., 1992) specified an upper limit standard score of 115 for their participants w i t h learning disabilities. A l l of these factors, a lack of information and varied criteria, make it difficult to compare and interpret findings from the body of studies w i t h confidence.  57  Comparison and interpretation of findings is further compromised by the varied methods of operationalizing the aptitude-achievement discrepancy. Across the body of 16 studies, only 3 studies utilized a comparable method of specifying the aptitude-achievement discrepancy. Navarette (1999) and Palladino et al. (2000) specified a discrepancy of 1.5 standard deviations or more between cognitive ability and achievement while Wright-Strawderman and Watson (1992) specified a 23 standard score difference, a method that w o u l d produce essentially an equivalent outcome. Other methods of specifying the discrepancy are summarized i n Table 7 . Again, the highly varied nature of methods used to construct and/or describe the samples of students w i t h learning disabilities makes comparing results and interpreting findings from this body of studies very difficult. To conclude, although there is a considerable body of literature attesting to the greater vulnerability of students w i t h learning disabilities to depression, empirical research is limited and the findings are equivocal. G i v e n the great variability across the body of extant research studies i n terms of depression measures, adherence to clinical cut-off points, reporting of data (prevalence and mean scores) and samples examined (size, age, gender, and requirements for students to be identified as having learning disabilities), it is not surprising that results are highly varied and difficult to interpret. But if a conclusion must be drawn, it is done so more confidently from the subset of studies (N = 10) w h i c h utilized a common measure and reported mean depression levels. Unfortunately for the purposes of this study, that measure is the CDI, which has been used i n these studies to examine depression only i n children and  58  0  Table 7. Summary of Methods Used to Specify the Aptitude-Achievement Discrepancy of Participants w i t h Learning Disabilities Method SD  SS  > 1 (Reading) Newcomer etal. (1995) >12  2 grades Maag et al. (1992) Dalley et al. (1992)  Rodriguez & Routh(1989)  >7% Heath (1992)  Gr./Yrs.  Navarette (1999) >15 Maag & Behrens (1989a) >40% Hall & Haws (1989) 2 years Stevenson & Romney (1984)  Short (1992) %Diff.  > 1.5  Studies > 1.5 Palladino et al. (2000) >18 Heath & Ross (2000) >50% Howard & Tryon(2002)  >20 >23 Maag & Reid Wright-Strawderman & (1994) Watson (1992) £75% Goldstein et al. (1985)  N.R.  Note: SD = Standard Deviations; SS = Standard Scores; N.R. = Not Reported. young adolescents. These studies report mean depression scores from 8.09 to 13.34 = 11.26) for students w i t h learning disabilities and from 6.40 to 9.34 (M- 7.97) for students without disabilities). Based on these results, it is apparent that children and young adolescents w i t h and without learning disabilities report mean levels of depressive symptoms that are not greatly dissimilar. This conclusion suggests that a closer study of students with learning disabilities, particularly w i t h regard to factors known to be associated w i t h the development and maintenance of depressive symptoms is warranted. Research: Learning Disabilities and Anxiety M a n y of the factors that made comparing and interpreting results from the studies of depression among students with and without learning disabilities difficult  59  are evident i n the literature on anxiety, including a lack of consistency in measures and data reported as w e l l as comparability of samples examined, especially with regard to the identification of learning disabilities (note that Fisher, Allen, and Kose (1996) specified a lower limit standard score of 75 for cognitive ability, a figure well below the average range). Nonetheless, conclusions can be d r a w n somewhat more readily w i t h regard to the experience of anxiety. A s shown i n Table 8, although 2 studies found no significant difference, the majority of studies ( N = 5) reported a significant difference between students w i t h learning disabilities and those without disabilities w i t h regard to self-reported symptoms of anxiety. A n d i n one further study, a significant difference was reported between students without disabilities (NLD) and students w i t h learning disabilities who were receiving part-time special education support, but not between N L D students and students w h o were receiving full-time special education (i.e., enrolled i n special education programs). Note, however, that all of the studies approached anxiety as a continuous phenomenon and thus cut-off scores and prevalence rates were not reported. A s was the case for depression, however, additional clarity can be achieved by examining subsets of studies that utilized identical measures and reported mean anxiety scores (mean raw scores rather than mean T-scores as reported by Rodriguez and Routh (1989)). It can be ascertained that students w i t h learning disabilities generally reported higher levels of symptoms of anxiety than d i d their nondisabled peers, although once again, the overall difference is not large. To illustrate, the 3 studies that utilized the STAIC reported mean anxiety scores from 32.7 to 45.5 ( M = 40.3) for students w i t h learning disabilities and from 32.6 to 40.9 ( M = 37.2) for  6o  Table 8. Summary of Studies Examining Anxiety i n Students w i t h Learning Disabilities Sample  Author(s) Margalit & Zak (1984) Newcomer, Barenbaum, & Pearson (1995) Rodriguez & Routh (1989) Paget & Reynolds (1984)  L D :  N L D :  100 (68 M , 32 F 113 (80 M , 38  ) F )  L D : 8 5 (5lM,34F)  696 (348 M , 348 F L D : 31 N L D : 31 L D : 106 (73 M , 33 F ) N L D : (norm)  N L D :  )  IQM  6-13  n.r.  6-19  n.r.  8-13  n.r.  nr.  6-17  n.r.  "Public Law 94-142"  10-12  n.r.  9-11  n.r.  L D ( F T ) : 1 5 (15M,OF)  (15M,0F) N L D : 30 (30 M , 0 F ) L D : 4 5 (45M,0F)  Stein & Hoover (1989)  LD(FT):15  Fisher, Allen, & Kose (1996)  N L D : 4 5 (45M,OF)  Short (1992) Margalit & Shulman (1986)  L D :  31 30 20 (20 M , 0 F ) : 20 (20 M , 0 F  11-12  N L D : L D :  N L D  )  LD Criteria IQ 80-120 A C H : ru. IQru.  Age  11-13  LD:94 N L D :  101  n.r.  ACH<lSDRdg  IQ: "average" A C H nr.  ANX Measure CAS (cut-off n.r.) DAYS RCMAS (cut-off n.r.) RCMAS (cut-off n.r.) RCMAS  STAIC IQ>75 A O C dis 2 years (cut-off n.r.) IQ>80 STAIC A C H dis 12 ss (cut-off n.r.) STAIC IQ "average" (cut-off n.r.) A C H ru.  ANXM  ANX % L D :  n.r. n.r. n.r. : n.r. n.r. : n.r.  N L D : L D :  N L D L D :  N L D L D :  N L D :  n.r. n.r. N L D : n.r. L D : n.r. N L D : n.r. L D : n.r. N L D : n.r. L D : n.r. N L D : n.r.  L D  (FT):  L D  ( F T ) :  8.41 5.78 L D : 100.6 N L D : 98.4 L D : 51.8 N L D : 46.2 L D : 17.8 N L D : 14.7 L D ( F T ) : 13.7 L D ( P T ) : 14.7 N L D : 10.2 L D : 42.8 N L D : 38.0 L D : 32.7 N L D : 32.6 L D : 45.45 N L D : 40.93  Sig. Diff.  L D :  Gender n.r.  N L D :  X  M<F  V  n.r.  •  n.r.  • x  n.a  •  n.a  X  n.r. n.a  Comments Students with LDs in special class placement students with LDs in special class placement students with LDs in SPED class; (44 M , 18 F ) Students with LDs in special class placement sig. diff. only between NLD and LD students receiving part-time SPED Students with LDs in special class placement students with LDs in special class placement Students with LDs in special school  Note: Studies are arranged by anxiety measure and approximately by the age of the participants; CAS = Child Anxiety Scale (Gillis, 1980); DAYS = Depression and Anxiety in Youth Scale (Newcomer, Barenbaum, & Bryant, 1994); RCMAS = Revised Children's Manifest Anxiety Scale (Reynolds & Richmond, 1985); STAIC = State-Trait Anxiety Inventory for Children (Spielberger, 1973); ss = standard score points  6i  students without disabilities. Similarly, the 2 studies that used the R C M A S reported mean anxiety scores from 13.7 to 17.8 ( M = 15.4) for students w i t h learning disabilities and from 10.2 to 14.7 ( M = 12.5) for students without disabilities. Conclusions: Depression and Anxiety i n Adolescents w i t h Learning Disabilities A review of studies which have examined depression and anxiety i n adolescents with learning disabilities, comparing prevalence a n d / o r severity of symptoms w i t h norms or w i t h the symptoms reported by students without disabilities reveals highly equivocal results, especially for depression. Prevalence rates for depressive symptoms ranged from o to 32% for students without disabilities and from 10 to 43% for students with learning disabilities. Inconsistencies across studies w i t h regard to measures utilized (and clinical cut-off scores), data reported (prevalence rates and mean severity), and samples examined (age ranges, gender representation, and identification of learning disability characteristics) have likely been the cause for the confusing picture. Nonetheless, an examination of subsets of studies that have utilized the same measures and reported mean raw scores indicates that students w i t h learning disabilities generally report higher levels of depressive and anxious symptomatology than their peers without disabilities. The differences, however, are not large suggesting that further research is warranted, particularly within samples of students w i t h learning disabilities given that this group is i n itself highly varied. The Self-Efficacy Model of Depression A n informative approach to the study of negative affective functioning is the selfefficacy model of depression (Bandura et al., 1999). This model, w h i c h is based on the self-efficacy component of social cognitive theory (Bandura, 1994), posits that a sense of personal inefficacy to cope w i t h potential threats and to achieve success i n domains of  62  importance to an individual can play both a direct and a mediating role i n the development of negative affective functioning. While the self-efficacy model of depression is generally consistent w i t h cognitive vulnerability models of depression (e.g. Beck's (1987) "cognitive model," Abramson, Metalsky, and A l l o y ' s (1989) "hopelessness model," and H a n k i n & Abramson's (2001) "general, elaborated cognitive vulnerability-transactional stress model of depression"), there are two important differences. First, the self-efficacy model emphasizes the role of the individual as an "active shaper" (or agent) and not just as a "passive reactor" to his or her circumstances and environment (Maddux, 1995, p. 4). Second, rather than emphasizing the direct but passive role of self-esteem (i.e., a global judgment of self) i n the development and maintenance of depression (Robinson, Garber, & Hilsman, 1995), the self-efficacy model emphasizes the direct and mediating role of self-efficacy, domain specific judgments of self-capabilities. Bandura (1997) has proscribed a central role to self-efficacy, stating that perceptions of self-efficacy activate cognitive, motivational, and affective processes and determine h o w knowledge and skills are translated into action. The critical differences between the two approaches to depression, cognitive vulnerability and socio-cognitive, are well illustrated i n a consideration of the role of social support and negative life events, both factors robustly associated w i t h depression (Compas, Ey, & Grant, 1994; Ge, Lorenz, Conger, Elder, & Simons, 1994; Klocek, Oliver, & Ross, 1997; Parker & Roy, 2001). While cognitive vulnerability models of depression generally describe social support as a protective factor that serves to inhibit an individual's reaction to stress, failure, and other negative life events (thus protecting self-esteem), the self-efficacy model describes social support as an enabling factor (an  63  opportunity for agency) which can serve i n a proactive manner to facilitate the individual's adaptation to these stressors. Further discussion of the important roles of social support and life events follows. While self-efficacy has been shown to play a critical role i n affective functioning, a growing body of research attests to its important role i n academic functioning as well, both directly and through sociocognitive influences such as social support and prosocial behaviour (Bandura, 1997; Bandura, Pastorelli, Barbaranelli, & Caprara, 1999; Pajares, 2002; Schunk & Pajares, 2002). A s described i n the introduction to this study, students w i t h a strong sense of academic self-efficacy are more likely than their less self-efficacious peers to engage i n challenging learning activities, to persist when tasks become difficult, and to be resilient i n the face of setbacks and failure (Bandura, 1993; Schunk, 1995). N o t surprisingly, academic success serves to reinforce academic selfefficacy. Students w i t h a strong sense of academic self-efficacy also tend to demonstrate prosocial behaviours and to develop positive and supportive social networks, thus experiencing a school environment that is conducive to learning and academic success (Bandura et a l , 1996; Caprara et al., 2000; Schunk, 1995). Similarly, students w i t h a strong sense of social self-efficacy are more likely to form and maintain positive friendships, to be accepted by their peers, and to behave appropriately at school than their peers with a weaker sense of social self-efficacy. Again, success i n this domain serves to reinforce perceptions of self-efficacy. Students with a strong sense of social self-efficacy also tend to be more academically successful than their less socially-efficacious peers. Social self-efficacy and social competence have been shown to be positively related to school adjustment and achievement and  6  4  negatively related to dropping out of school (Bandura, 1997; Bandura et al., 1996; H y m e l , Comfort, Schonert-Reichl, & McDougall, 1996). While considerable research has focused on the importance of self-efficacy to academic and social functioning i n children and adolescents, less attention has been paid to affective functioning. To date, empirical research on the contribution of perceived self-efficacy to affective functioning has focused largely on adults (Bandura, 1997; Muris, 2002). Nonetheless, there is a small but growing corpus of studies that have examined the contribution of self-efficacy to affective functioning, specifically depression and anxiety, i n children and adolescents. Research on Self-Efficacy and Depression and Anxiety Bandura (1986) described three important pathways through w h i c h l o w selfefficacy can result i n depression and anxiety. The first pathway is through perceptions of inefficacy to reach highly valued standards i n important cognitive activities (e.g. academic success). Bandura and his associates (Bandura, 1997; Bandura et al., 1999) noted that a l o w sense of academic self-efficacy can produce feelings of apprehension and despondency, even to the level of developing symptoms of anxiety and depression. The second pathway is through a low sense of social self-efficacy. L o w social selfefficacy can impede the development of supportive social relationships, without which individuals are more prone to experiencing stress and to developing symptoms of anxiety and depression, especially i n social situations (Bandura, 1997; Bandura et al., 1999; M u r i s , 2001). The third pathway is through perceptions of l o w emotional self-efficacy; that is, perceptions of control over negative thinking. While most individuals experience periods of worry and despondency at various times, many are able to regain their sense  65  of well-being after a short period of adjustment. Those individuals w h o are not able rebound quickly tend to develop lowered perceptions of their self-efficacy to control their thoughts and their lives. This leads to the development of symptoms of anxiety and depression (Bandura, 1997; Bandura et al., 1999). Studies that have investigated the relationship between self-efficacy and depression (and more recently anxiety) i n children and adolescents have varied i n their focus upon these three pathways or domains of self-efficacy (see Table 9). A review of these studies follows. Table 9. Foci of Studies Examining the Relationship of Self-Efficacy to Depression and Anxiety Study  Age Group  S-SE  A-SE  E-SE  R-SE  DEP A N X  McFarlane et al. (1994,1995)  17.1 yrs (M)  Y  Ehrenberg et al. (1991)  14 - 1 8 yrs  Y  Y  Y  Bandura et al. (1999)  11.5 yrs (M)  Y  Y  Y  Muris et al. (2001)  13 - 1 9 yrs  Y  Y  Y  Y  Muris (2002)  12 - 1 9 yrs  Y  Y  Y  Y  Y  Present Study  13 - 1 7 yrs  Y  Y  Y  Y  Y  Y  Y  Note: S-SE = Social Self-Efficacy; A-SE = Academic Self-Efficacy; E-SE = Emotional Self-Efficacy; R-SE = Reading Self-Efficacy; DEP = Depression; A N X = Anxiety Social Self-Efficacy A s shown, all of the studies (including the present study) have examined social self-efficacy i n relationship to depression. A n d despite the use of different self-report measures, Bandura's (1986) assertion of a negative relationship between social selfefficacy and depression has received consistent support (Bandura et al., 1999; Ehrenberg, Cox, & Koopman, 1991; McFarlane, Bellissimo, N o r m a n , & Lange, 1994;  66 McFarlane, Bellissimo, & N o r m a n , 1995; Muris, 2002). Correlation coefficients obtained in the studies ranged from -0.22 to -0.37 (see Table 10).  Table 10. Correlation between Depression and Self-Efficacy i n Studies of C h i l d r e n and Adolescents Study  DEP Measure  SE Measure  McFarlane et al. (1994,1995)  IDD  ASSES  Ehrenberg et al. (1991)  BDI  SES  Bandura et al. (1999)  CDI  MSPSE  Muris et al. (2001)  CDI  MSPSE  n.r.  n.r.  n.r.  -0.30**  Muris (2002)  CDI  SEQ-C  -0.37*  -0.41*  -0.57*  -0.57*  S-SE  A-SE  E-SE  TOT-SE  -0.22** -0.28  -0.60**  -0.68**  -0.30**  -0.43**  n.r.  Note: S-SE = Social Self-Efficacy; A-SE = Academic Self-Efficacy; E-SE = Emotional Self-Efficacy; TOT-SE = Total Self-Efficacy; IDD (Inventory to Diagnose Depression (Zimmerman & Coryell, 1987); ASSES = Adolescent Social Self-Efficacy Scale (Connolly, 1989); BDI = Beck Depression Inventory (Beck et al., 1961); SES = Self-Efficacy Scale (Sherer et al., 1982); CDI = Children's Depression Inventory (Kovacs, 1983,1991); MSPSE = Multidimensional Scales of Perceived SelfEfficacy (Bandura, 1990), SEQ-C = Self-Efficacy Questionnaire (Muris, 2001). *p_<.05, **p_<.oi Although Bandura (1986) also specified anxiety as a likely negative affective outcome of perceptions of personal inefficacy, especially i n the case of perceived inefficacy to deal w i t h a threat or imminent failure, only one of the studies examined the relationship between social self-efficacy and anxiety. U s i n g the State-Trait Anxiety Inventory for Children (STAIC) (Spielberger, 1973) and the Screen for Child Anxiety Related Emotional Disorders (SCARED) (Birmaher, et al., 1999), M u r i s (2002) obtained correlations of -0.44 and -0.38 between social self-efficacy and trait anxiety/neuroticism (STAIC) and generalized anxiety (SCARED) respectively, again providing support for the self-efficacy model proposed by Bandura (1986).  67" Academic Self-Efficacy Given that achieving an education is a major factor i n the lives of children and adolescents, it is not surprising that academic self-efficacy was the focus of all but one of the studies under review. A s shown i n Table 10, a negative relationship between depression and academic self-efficacy has been a uniform finding, w i t h correlations coefficients ranging from -0.41 to -0.60. M u r i s (2002) also examined the relationship of academic self-efficacy to anxiety and obtained correlation coefficients of-0.31 for trait anxiety/neuroticism (STAIC) and 0.28 for generalized anxiety (SCARED), providing further support for Bandura's model (Bandura, 1986). Emotional Self-Efficacy Although Bandura and his associates (1999) d i d not examine emotional selfefficacy (or anxiety) i n their study of children, Bandura and his associates (Bandura, 1986; Bandura et al., 1999) had specified emotional self-efficacy as one of the three pathways to the development of negative affect. M u r i s (2002) examined this domain of self-efficacy i n relationship to both symptoms of affective dysfunction. A s predicted, M u r i s found evidence of a strong negative relationship between emotional self-efficacy and depression, r - -0.57, p < .05, and between emotional self-efficacy and anxiety, r = 0.70, p < .05 and r = -0.68, p < .05, for trait anxiety/neuroticism and generalized anxiety respectively. Table 10 provides correlations between depression and total self-efficacy. These coefficients are provided only as additional confirmation of the consistency of findings across studies despite the use of various measures. A s discussed i n Chapter One, self-  68 efficacy is a multidimensional domain-specific construct, i n m u c h the same manner as self-concept (Bandura, 1997; Pajares, 1996). The Role of Life Events and Social Support in Depression and Anxiety Two factors that have been strongly associated w i t h depression and anxiety are individuals' perceptions of social support and their experience of stressful life events. These factors have not typically been investigated i n studies of depression among adolescents w i t h learning disabilities and indeed, of the preceding studies, only that conducted by McFarlane and his associates (McFarlane et al., 1994; McFarlane et al., 1995) accounted for participants' perceptions of social support and experience of life events i n an examination of the relationship between self-efficacy and depression. From a socio-cognitive point of view, however, accounting for all potentially important social, cognitive and environmental factors is crucial. A s a consequence, the contribution of life events and social support were examined i n the present study. Life Events Prospective empirical studies have yielded considerable support for the contribution of stressful life events to the development and maintenance of depression in adolescents (Compas, Grant, & Ey, 1994; Ge et al., 1994; Goodyer, 2001; Lewinsohn, Roberts, et al., 1994; Petersen et a l , 1993). However the relationship between experience of stressful life events and depression is not necessarily simple, w i t h correlation estimates ranging from .22 to .47 (Robinson et al., 1995). T w o reasons proposed for the variability i n the relationship are the diversity of individuals' interpretations of events and the diversity i n individuals' subsequent responses (Angold & Costello, 2001; Garber & Flynn, 2001; Goodyer, 1999).  69  Additional reasons for variability i n findings include "additivity," "reciprocity" and gender. A d d i t i v i t y refers to the finding that individuals w h o face two or more concurrent stressful life events are more likely to develop symptoms of depression than those who face only one stressful life event (Goodyer, 1999). Reciprocity refers to the finding that depressed individuals are responsible, i n part, for some of the stressful life events that they experience. For example, it has been documented that depressed individuals w h o are socially withdrawn experience social rejection (causing them more stress), which i n turn exacerbates and maintains the original depressive symptoms (including social withdrawal) (Goodyer, 1999; H a m m e n , 1991) resulting i n long-term social difficulties (e.g., establishing relationships within the peer group) (Ingram, Scott, & Siegle, 1999). W i t h regard to gender, female adolescents appear to react more negatively than males to stressful events of both a social nature and an environmental nature (Compas, 1987; Ge et a l , 1994). Accordingly, it was deemed important i n this study to not only gather information about the number and source of stressful events i n the lives of the participants, but also attempt to evaluate the valence (positive to negative) of each event for each individual (Sarason, Sarason, & Pierce, 1990) and to examine gender differences. Social Support A review of the important theoretical perspectives on social support research (i.e., the stress and coping perspective, the social constructivist perspective, and the relationship perspective) is beyond the scope of this literature review. However, it is important to note that the present study has adopted a socio-cognitive view of social support (Sarason, Pierce, & Sarason, 1990), consistent w i t h this study's socio-cognitive perspective on depression, anxiety, and life events. A socio-cognitive approach to social  7° support is based on the premise that consensus on what constitutes supportive behaviours by others is virtually impossible given the range of individual differences i n need for social contacts and i n the meanings attributed to those contacts. What is important, therefore, is to focus on an individual's personal belief about the social support that is available to them. Accordingly, perceived rather than received social support is measured i n the present study. While there is substantial empirical evidence that social support is a significant variable i n the prediction of depression (Klocek et al., 1997), social support is also important because of its interaction with stressful life events i n the development of psychological distress. Perceived social support has been shown to reduce the effects of stressful life events including the development of symptoms of depression (Compas, Slavin, Wagner, & Vannatta, 1986; Klocek, Oliver, & Ross, 1997; Malecki & Demaray, 2002; Wills & Shinar, 2000) and anxiety (Sarason, Sarason, & Pierce, 1990; Sarason, Sarason, Shearin, & Pierce, 1987). A m o n g adolescents, those w h o perceive themselves as receiving l o w levels of parental support (Lewinsohn, Roberts, et al., 1994; McFarlane et al., 1995) and l o w levels of peer support (Shirk, V a n H o r n , & Leber, 1997), report higher levels of depressive symptoms than their peers w h o report a greater sense of interpersonal connectedness w i t h family and friends (Wills & Cleary, 1996). A n d i n regard to adolescent females i n particular, maternal warmth and support has been shown to have a significant effect i n protecting these young w o m e n from the effects of adverse events during adolescence (Ge et al., 1994). Although numerous measures of social support have been developed, one of the most useful and widely-used measures of perceived social support is the Social Support Questionnaire (SSQ) (Sarason, Levine, Basham, & Sarason, 1983), w h i c h asks  7  1  respondents to record the availability of social supports as well as their satisfaction w i t h these various types of support (e.g., family, friends and others i n social network). A s discussed i n Chapter 3, an adapted short version of the SSQ w i l l be utilized i n the present study. Rationale for the Study Depression is a serious mental health problem and one that appears to be increasing w i t h successive generations (Klerman, 1993; Ryan et al., 1992). Epidemiological studies indicate that perhaps as many as 24% of adolescents w i l l experience a depressive disorder or significant symptoms of depression during their teen years (Lewinsohn, Hops, et al., 1993; Steinhausen & Metzke, 2000) and that 60 to 70% of these adolescents w i l l suffer a recurrence of their difficulties during their young adult years (Kovacs et al., 1984; Weissman et al., 1999). G i v e n the considerable distress and functional impairment suffered b y adolescents w i t h depression, these estimates are alarming. Of further concern is the finding that between 25 and 50% of adolescents diagnosed w i t h depression are likely to receive an additional diagnosis of an anxiety disorder (Axelson & Birmaher, 2001). Adolescents w i t h a dual diagnosis are likely to experience more severe symptoms, longer episodes, greater functional impairment, and a greater risk for substance abuse, suicidality and a recurrence of their difficulties than their peers w h o have been diagnosed w i t h depression alone (Birmaher et al., 1996; Brady & Kendall, 1992; H a n k i n et al., 1998; Strauss et al., 1988; Woodward & Fergusson, 2001). One group of adolescents who are thought to be at particular risk for experiencing psychosocial distress including significant symptoms of depression and anxiety are  72  those w i t h learning disabilities. Students with learning disabilities typically experience chronic and pervasive academic failure across their years of schooling. In addition, many of these students experience difficulties i n establishing and maintaining satisfying social relationships (Bryan, 1997; Kavale & Forness, 1996). G i v e n that these two areas are of critical importance during the adolescent developmental period, it is not surprising that many i n the field of education believe that students w i t h learning disabilities are at greater risk than their normally achieving peers for developing serious social-emotional difficulties (Bender et al., 1999; Bender & Wall, 1994; Gorman, 1999; Huntingdon & Bender, 1993; Weinberg & Emslie, 1988; Wright-Strawderman et al., 1996). Empirical studies of the prevalence and severity of depression among adolescents with learning disabilities, however, are few and findings are equivocal. Additional research is needed to clarify whether students w i t h learning disabilities do indeed face particular risks for depression. Further, additional research is needed to elucidate factors, beyond the genetic and biological (Hankin & Abramson, 2001) that may be contributing to the experience of depression and anxiety i n this population. The present study w i l l contribute to our understanding of depression and anxiety i n adolescents w i t h learning disabilities, not only by clarifying the prevalence and severity of depressive and anxious symptomatology i n a group of adolescents with learning disabilities (including those w i t h significant problems i n reading), but also by examining links w i t h self-efficacy. In his self-efficacy model of depression, Bandura (1997) posited that depression and anxiety develop i n individuals w h o feel inefficacious; that is, individuals who perceive themselves to lack the ability to control events and conditions that affect their  73  lives and, therefore, to be unable to attain desired outcomes. A l t h o u g h empirical research on the contribution of perceived self-efficacy to depression and anxiety to date has largely focused on adults (Bandura, 1997; Muris, 2002), a small but growing corpus of studies has yielded robust findings for children and adolescents. The present study w i l l extend this work w i t h normally achieving children and adolescents (Bandura et al., 1999; Ehrenberg et al., 1991; McFarlane et al., 1994,1995; Muris, 2002; M u r i s et al., 2001) i n three important ways. First, the study w i l l address links between self-efficacy and depression and anxiety i n adolescents w i t h learning disabilities, especially those w h o are experiencing significant difficulties i n the highly salient area of reading. Second, the study w i l l examine all three specific pathways academic, social and emotional self-efficacy - posited by Bandura and his associates (Bandura, 1997; Bandura et al., 1999); to date, only academic and social self-efficacy have been examined. Third, given this study's particular focus on students w i t h reading disabilities as well as calls for criterial task specificity i n self-efficacy research (Bandura, 1986; Pajares, 1996), the present study w i l l also examine links between self-efficacy for reading and symptoms of anxiety and depression. Finally, the present study w i l l also include consideration of two important variables (life events and social support), which are k n o w n to act as risk and protective factors i n the development of depression (Compas et al., 1986; Klocek et al., 1997; Sarason, Shearin, et al., 1987; Wills & Shinar, 2000) and anxiety (Sarason, Pierce et al., 1990; Sarason, Sarason, Shearin, & Pierce, 1987) but to date, have largely been ignored i n research on these conditions i n students w i t h learning disabilities.  74  Summary of Research Questions and Hypotheses Question 1. What is the prevalence and severity of anxiety and depression i n adolescents w i t h learning disabilities, especially those w i t h reading disabilities? Hypothesis 1.1 The prevalence and severity of clinically significant symptoms of anxiety, depression and comorbid anxiety and depression i n adolescents with learning disabilities w i l l be higher than is typically found w i t h i n the normal population. Question 2. C a n anxiety and depression i n adolescents w i t h learning disabilities be predicted on the basis of their perceptions of self-efficacy? Hypothesis 2.1 L o w perceptions of self-efficacy w i l l be associated w i t h high levels of depression, anxiety, and comorbid symptoms of depression and anxiety. Hypothesis 2.2 L o w perceptions of social and emotional self-efficacy w i l l be most strongly associated w i t h high levels of anxiety. Hypothesis 2.3 L o w perceptions of academic and reading self-efficacy w i l l be most strongly associated w i t h high levels of depression. Question 3. What is the role of social support i n predicting anxiety and depression? Hypothesis 3.1 Students reporting the highest levels of support (family and friends) w i l l report high levels of social and emotional self-efficacy and low levels of anxiety and depression. Question 4. What is the role of life events in predicting anxiety and depression? Hypothesis 4.1 Students reporting the highest levels of negative life events w i l l report l o w levels of social support (particularly from family), l o w levels of social and emotional self-efficacy, and high levels of anxiety and depression.  Question 5. What is the role of gender i n predicting anxiety and depression? Hypothesis 5.1 Females w i l l report lower levels of self-efficacy (across all domains) and higher levels of anxiety and depression than males. Question 6. What role does severity of reading disability play? Hypothesis 6.1 A m o n g students with learning disabilities, those w i t h low w o r d reading skills (at or below the 25th percentile) w i l l report lower levels of selfefficacy (especially academic and reading self-efficacy) and higher levels of anxiety and depression than students w i t h stronger w o r d reading skills (at or above the 30th percentile). Hypothesis 6.2 A m o n g students with learning disabilities, those w i t h significant discrepancies (1.3 standard deviations or more) between their verbal ability and their w o r d reading skills and between their reading comprehension abilities and their w o r d reading skills, w i l l report lower levels of self-efficacy (especially academic and reading self-efficacy) and higher levels of anxiety and depression than students without such discrepancies. Question 7. A r e there particular factors associated w i t h the experience of depression and anxiety that distinguish adolescents with learning disabilities w h o report high levels of symptomatology from those who report l o w levels of symptomatology? Hypothesis 7.1 There w i l l be significant differences between students who report high symptom levels of depression, anxiety, and comorbid depression and anxiety and those w h o report l o w levels of symptomatology on the basis of their self-efficacy, social support, experience of life events, and achievement i n reading.  76  Chapter 3 METHOD The present multifaceted study extended previous w o r k examining the links between self-efficacy and negative affective outcomes i n children and adolescents (Bandura, Pastorelli, Barbaranelli, & Caprara, 1999; Ehrenberg, C o x , & Koopman, 1991; McFarlane, Bellissimo, & N o r m a n , 1995; McFarlane, Bellissimo, N o r m a n , & Lange, 1994; Muris, 2002; M u r i s , Schmidt, Lambrichs, & Meesters, 2001) by examining functioning within a special population; namely, adolescent students w i t h learning disabilities, especially those experiencing significant difficulties i n the highly salient area of reading. Design A within-subjects correlational design was utilized to develop an understanding of the complex relationships among the variables under study. Social-cognitive theory and the extant research base i n education, educational psychology, and psychopathology indicates that all four of the conditions of interest (namely, learning disabilities, reading disabilities, depression and anxiety), are heterogeneous i n nature and likely due to complex interactions among predisposing and maintaining factors rather than to any singular causes. A s noted i n the review of literature, depression and anxiety are complex, often comorbid conditions that are not yet w e l l understood, especially i n adolescents (Angold et al., 1999; Reynolds, 1994b; Schniering et al., 1996). Similarly, research regarding the defining characteristics and causes of learning disabilities, particularly as expressed in reading, continues w i t h no clear resolution to date (Aaron, 1991; Durrant, 1994; Fletcher & Foorman, 1994; Siegel, 1989; Speece & Shekitka, 2002; Stanovich, 1999; Vellutino, Scanlon, & Lyon, 2000). G i v e n this heterogeneity and complexity, a within-subjects correlational design was deemed the  77 most suitable for developing an understanding of the many factors involved i n the participants' functioning. Participants The 83 participants i n this study, 24 females and 59 males, were drawn from thirteen schools across four school districts. The students, from Grades 8 to 11, ranged in age from 13 to 17 years w i t h a mean age of 14.42 years (SD - 1.16). The mean age of the females was 14.38 years (SD = 1.10) and the mean age of the males was 14.44 years (SD= 1.19). Table 11. Summary of A g e and Gender Characteristics of Sample Age 13 14 15 16 17 Total  Total Sample 22 22 26 8 5 83 (100%)  Females 7 5 8  Males 15 17 18 4  0 24 (28.9%)  4  5 59 (71.1%)  Although the original intent of the study had been to create a pool of volunteers and to select 120 participants at random from this pool such that there were equal numbers of females and males, there were insufficient numbers of volunteers to follow this procedure. (Note: a power analysis was conducted to determine the necessary sample size and it was determined that i n order to achieve a power level of .80 and detect an effect size i n the small to medium range (.35), a sample size of 120 was needed to reject null hypotheses at alpha levels of .05 (Hair, Anderson, Tatham, & Black, 1998, p. 13)). To obtain the 83 participants i n this study, 9 school districts and 26 schools were approached (see recruitment summary i n A p p e n d i x A ) . Due to such pressures as school  7»  closures, staff layoffs, inexperienced staff i n Special Education positions, staff stress, and concurrent participation of staff i n other research studies, 3 school districts and 11 schools declined to host the present study. Two additional school districts agreed to facilitate the study but permission came from only one school i n each district, and both notifications arrived too late for data collection to proceed. A total of 355 eligible students from 14 schools were invited to participate i n the study by their Special Education teachers. Across these schools, 93 students volunteered (i.e., the consent rate for the present study was 26.2%). Of these students, 83 (89.2%) participated i n the study. The loss of 10 cases (10.8%) was a result of four students being absent while the researcher was conducting assessments within the school district, one student not having a scheduled support block or nonacademic block i n w h i c h to participate, two students not having psychoeducational assessment reports i n their files, and three students declining to participate after all due to course conflicts (namely, a scheduled demonstration i n woodworking, the beginning of a new project i n auto mechanics, and a field trip). O f note, three students completed their assessments during the lunch hour a n d / o r after school so that they could participate i n the study but not miss receiving support during their Special Education block. A l l of the participants were enrolled i n British Columbia public schools located either i n the Lower M a i n l a n d or on Vancouver Island. The schools ranged from urban to rural i n character, and all serviced a diverse range of students i n terms of socioeconomic status and ethnicity/cultural background. The majority of the participating students (n = 66,79.5%) identified themselves as White/Caucasian while 9 students (10.8%) identified themselves as Asian, 5 students (6.0%) as Aboriginal Canadians, and 3 students (3.6%) as Black. With regard to the primary language spoken  79 in their homes, 76 students (91.6%) spoke English while 7 students (8.4%) spoke other languages (primarily Cantonese but also French, Polish, and Somalian). The majority of students (n = 79,95.2%) were born i n Canada. With regard to their family situations, 47 students (56.6%) lived w i t h their biological parents, 20 students (24.1%) w i t h a single biological parent, 13 students (15.7%) with a biological parent and a stepparent/partner, and 3 students (3.6%) i n other situations (e.g., w i t h relatives or i n a foster home). With respect to the educational attainments of their parents, 7 students (8.4%) d i d not k n o w the level reached by their mothers and 8 students (9.6%) d i d not know the level reached by their fathers. A m o n g the remaining students, 7 mother (8.4%) and 11 fathers (13.3%) reportedly d i d not complete high school, 37 mothers and 37 fathers (44.6% respectively) graduated from high school, 23 mothers (27.7%) and 20 fathers (24.1%) graduated from college (2 to 4 year programs), 7 mothers (8.4%) and 4 fathers (4.8%) graduated from university with a bachelor's degree, and 2 mothers (2.4%) and 3 fathers (3.6%) graduated w i t h an advanced degree. In accordance w i t h previous research on learning disabilities, any students who had been diagnosed w i t h a significant sensory deficit (i.e. students identified as meeting B.C. Ministry of Education criteria for classification as a Student with a Visual a Student who is Deaf, or a Student with a Hearing Impairment),  Impairment,  or w h o had been identified  as having significant behavioural difficulties (i.e. students w h o had been identified as meeting Ministry criteria for classification as a Student requiring Intensive Behaviour Interventions), a n d / o r whose English language facility had been judged by their ESL or Special Education teachers to be insufficient for them to participate meaningfully i n the  8o study w o u l d have been excluded from the sample. N o n e of the participants met these exclusionary criteria, however, and all of the volunteers were included i n the study. Learning Disabilities and Reading Disabilities A l l of the study participants had been identified as Students with Learning Disabilities by school district staff on the basis of psychoeducational assessments conducted either by district school psychologists or by private psychologists and reviewed by district staff. In British Columbia, students are classified as learning disabled according to criteria established by the Ministry of Education. These criteria, which are based upon the Canadian Learning Disabilities Association's definition of Learning Disabilities (released i n January 2002), are presented i n A p p e n d i x B. To be identified as having a learning disability, students must demonstrate "at least average abilities essential for thinking a n d / o r reasoning," manifest a "significant weakness i n one or more cognitive processes (e.g., memory, attention, language) relative to overall intellectual functioning, as measured by norm-referenced assessment instruments, which directly impact their performance," and present w i t h "persistent difficulties" in the acquisition of academic skills (e.g., reading, writing, a n d / o r numeracy). During the period between Grades 4 and 12, students "may demonstrate a significant discrepancy (note: degree unspecified) between estimated learning potential and academic achievement as measured by norm-referenced achievement instruments" (BC Ministry of Education, 1995/2002, pp. E 11-15). While the majority of study participants ( N = 75,90.4%) had been administered the Wechsler Intelligence Scale for Children - 3rd Edition (WISC-III) (Wechsler, 1991) during their most recent psychoeducational assessment, 9.6% ( N = 8) had completed the  8i  Stanford Binet Intelligence Scale - 4th Edition (SB-IV) (Thorndike, Hagen, & Sattler, 1986). The students' Full Scale (WISC-III) and Test Composite (SB-IV) scores were utilized to describe the students' cognitive abilities. A l t h o u g h the WISC-III and the SB-IV are based on somewhat different conceptual frameworks, correlations between WISC-III Full Scale scores and SB-IV Test Composite are generally strong i n the range of .81 to .82 (Carvajal et al., 1993; Lavin, 1996; Rust & Lindstrom, 1996). O f particular relevance to this study, Prewett and Matavich (1994) obtained a correlation of .81 (p< .01) with a sample of 72 children w i t h academic difficulties. For the purposes of the present study, therefore, both WISC-III Full Scale scores and SB-IV Test Composite scores were accepted as valid estimates of the students' general cognitive ability. While the primary goal of the present study was to focus u p o n students with learning disabilities, a secondary focus was upon students w i t h learning disabilities who were experiencing particular difficulties i n the area of reading. To this end, the participating students completed a number of academic measures i n order to ascertain subsets of students w h o might be identified as reading disabled. The students were administered the Reading (vocabulary or w o r d recognition), Spelling and Arithmetic subtests of the Wide Range Achievement Test -yd  Edition (WRAT-3) (Wilkinson, 1993)  and the Gray Silent Reading Tests (GSRT) (Wiederholt & Blalock, 2000). The students' results on the W R A T - 3 and the GSRT, as well as their results on the WISC-III or SB-IV, were utilized i n several different ways (using both discrepancy and functional skills assessment methods) to identify those w i t h significant difficulties i n reading because consensus has not been reached within the field as to what constitutes a reading disability. A s discussed in the review of literature, defining learning and  82  reading disabilities has been the source of considerable debate since the 1960s and agreement about the most appropriate methods for identifying individuals w i t h learning and reading disabilities has been elusive (Fletcher at al., 1998; Proctor & Prevatt, 2003; Speece & Shekitka, 2002; Siegel, 1999; Stanovich, 1999). Nonetheless, most in the field agree that individuals w i t h learning disabilities are of average or above intelligence and present w i t h significant difficulties i n particular areas of academic achievement (Kaufman & Kaufman, 2001). Table 12 summarizes the different groupings of students developed to facilitate the data analyses. Table 12. Summary of Criteria for Total Sample and Disability Subsets Group General Learning Disabilities Traditional Learning Disabilities Reading Disabilities: Low Word Reading Reading Disabilities: Verbal/Word Reading Reading Disabilities: Comprehension/Word 7?  /"I IT"* CT  Label  Criteria  GLD  All participants; all previously identified by school district staff as meeting BC Ministry of Education criteria for classification as Students with Learning Disabilities  TRAD-LD  R  R D  ^  ^  _v/W*  Cognitive ability within the average range or better (> a standard score of 80 with 1.5 SD or more discrepancy between cognitive ability and achievement in one or more academic skill areas)  WRAT-3 Reading (word reading) score < a standard score of 90  1.3 SD or more discrepancy between Verbal Ability (WISC-III VIQ score) and WRAT-3 Reading (word reading) score  RD-C/W  1.3 SD or more discrepancy between Reading Comprehension skills (GSRT score) and WRAT-3 Reading (word reading) score  In the first instance, analyses were conducted upon the data yielded by all of the participants, all of w h o m had been identified by school district staff as meeting B C Ministry of Education criteria for classification as Students with Learning Disabilities.  83  Thus, for the purposes of this study, all students were classified as having General Learning Disabilities (GLD). U p o n reviewing the participants' cognitive ability scores and their results on the academic measures, however, it became clear that many students (N - 46) d i d not meet "traditional criteria" for learning disabilities; that is, the students' cognitive ability d i d not fall within the average range or better (at or above a standard score of 80) a n d / o r they d i d not present w i t h a discrepancy of at least 1.5 standard deviations between cognitive ability and achievement i n one or more academic skill areas. A s a consequence, a subgroup of participants was formed w h o d i d meet the traditional criteria. These students, classified by means of the "aptitude discrepancy approach," were labeled as having Traditional Learning Disabilities ( T R A D - L D ) . The creation of this subgroup allowed for the results of the present study to be compared more readily w i t h results from other studies of this heterogeneous population. However, it should be noted that i n the present study a conservative lower bound of the average range for cognitive ability (i.e., equal to or greater than a standard score of 80 rather than 85) as recommended by Siegel and her associates (Morrison & Siegel, 1991; Siegel & Heaven, 1986) was used because more than 60% of the students' psychoeducational assessments had been completed more than 3 years prior to this study, raising concerns about the current validity of their cognitive ability estimates. A further subgroup of participants was then created to allow for an examination of the experience of participants w i t h significant difficulties i n reading. A s described i n Chapter 2, the subgroup of participants with reading disabilities was formed i n three different ways. First, participants were classified as reading disabled on the basis of the  8  4  research-driven definition (a "functional skills assessment approach") proposed by Siegel and her associates (Barwick & Siegel, 1996; Morrison & Siegel, 1991; Siegel & Heaven, 1986) and accepted as the standard by many i n the field (Fletcher et a l , 1994). That is, all of the participants whose scores on the reading (word recognition) subtest on the WRAT-3 fell at or below the 25th percentile (i.e., a standard score of 90) were classified as having Reading Disabilities: Low Word Reading (RD-LW) and analyses were conducted utilizing this subset of the sample. Second, the subgroup was reformed on the basis of a field-driven discrepancybased definition utilized by the B.C. Ministry of Education to determine which students with special needs (in particular, those classified as having learning disabilities) should be allowed a reader for provincial examinations. U s i n g this method, students who presented w i t h a 1.3 standard deviation discrepancy (i.e. 20 standard score points) between their verbal ability (WISC-III Verbal Scale score) and their reading decoding skills (WRAT-3 Reading subtest score) were classified as having Reading Disabilities: Verbal/Word ( R D - V / W ) . Finally, participants were reidentified as reading disabled on the basis of discrepancy-based definition proposed by this researcher as a result of field observations; namely, that students who are severely challenged by w o r d reading deficits (possibly as a result of phonological processing difficulties), but who are able to make good use of context clues and their knowledge of the w o r l d and language to comprehend text, are deeply frustrated by their difficulties, especially their slow reading speed. Accordingly, students presenting w i t h a significant discrepancy (1.3 standard deviations or 20 standard score points) between their reading comprehension  85  skills and their w o r d recognition skills were identified as having Reading Disabilities: Comprehension/Word ( R D - C / W ) . Measures In addition to collecting demographic information about the participants and their families and obtaining the cognitive ability scores of the participants from their confidential school files, four broad categories of measures were used i n this study; namely, academic skills, perceptions of self-efficacy (academic, reading, social and emotional), self-reports of social support and experience of life events, and self-reports of symptoms of anxiety and depression. The data collection sheet (Figure 4) provides a useful visual overview of the measures and the scores to be utilized i n the analyses. Demographic Information The demographic questionnaire, All About Me (see A p p e n d i x C) was constructed by this researcher to obtain information about the participants' age, gender, ethnicity/ cultural background, language background, employment activity, extra-curricular involvement, and family background (composition as well the educational level of the parents or guardians). This information was sought i n accordance w i t h the guidelines for descriptive variables set out by the Council for Learning Disabilities (CLD) Research Committee (Smith et al., 1984). Students were asked about their involvement i n extracurricular activities as well as their after-school employment because it has been suggested that involvement i n structured voluntary activities (such as sports or the arts) as well as after-school employment can act as important mediating variables in their psychosocial development (Holmbeck & Shapera, 1999; Larson, 2000).  86  Figure 4. Data Collection Sheet.  Grade:  Age:  Gender:  School:  SD#:  Participant #  DEMOGRAPHIC INFORMATION Ethnicity  Language  Place of Birth  _ 1 . White  1 . English  1 . Canada  _  2 . Other  _  2 . Asian  _ 2 . Other  3. Native  Description:  Yrs in Canada  1.  Bio  (2)  1 . < High School  1 . < High School  2.  Bio  (1)  2 . High School  2 . High School  3. College (2-4 yrs)  3. College (2-4 yrs)  4. Bachelor Degree  4. Bachelor Degree  5. Graduate Degree  5. Graduate Degree  3. Bio+  5. No. of Sibs  _ 5. Other  Unpaid Job  Extra-Curric (School)  Paid Job l.Yes  l.Yes 2.  Mother's Education  _ 4. Other  _4. Black  No  2.  Description:  Father's Education  Family  _  No  1.  _ 2 .  Yes  1.  Yes  No  2.  No  Description:  Description:  Extra-Curric - Community  Description:  COGNITIVE ABILITY Age:  Date:  Grade:  b). SB-IV  a). WISC-III Scales  Years Since Administration:  Standard Scores  Indices  Standard Scores  Area/Composite  Verbal Scale  Verbal Comprehension  Verbal Reasoning  Performance Scale  Perceptual Organization  Abstract/Visual Reasoning  Full Scale  Freedom from Distractibility  Quantitative Reasoning  Processing Speed  Short-Term Memory Test Composite  Verbal Subtests  Scaled Scores  Performance Subtests  Information  Picture Completion  Similarities  Coding  Arithmetic  Picture Arrangement  Vocabulary  Block Design  Comprehension  Object Assembly  (Digit Span)  (Symbol Search) (Mazes)  Scaled Scores  Scaled Scores  87  Figure 4. Data Collection Sheet (cont.)  DISABILITY CATEGORY  ACADEMIC SKILLS Subtests/Tests  Standard Scores  Descriptor  Category  N.A.  WRAT-3 Reading  GLD  All Students  WRAT-3 Spelling  LD-TRAD  Cog - any Acad = > 15 SD  WRAT-3 Arithmetic  RD-LW  Word < 90 standard score  GSRT Rdg. Comprehension  RD-V/W  WBCVIQ - Word=>20  RD-C/W  Comp- Word=>20  ANXIETY  DEPRESSION Subscales/Scale  Calculation  T-Scores  Subscales/Scale  Dysphoric Mood  Physical Symptoms  Anhedonia  Harm Avoidance  Negative Self-Evaluation  Social Anxiety  Somatic Complaints  MASC Total  Depression Total  Anxiety Disorder Index  T-Scores  SELF EFFICACY QUESTIONNAIRES Questionnaires  Scores  Academic Self-Efficacy Reading Self-Efficacy Social Self-Efficacy Emotional Self-Efficacy Total Self-Efficacy  SOCIAL SUPPORT QUESTIONNAIRE Scales  Scores  LIFE EVENTS QUESTIONNAIRE Scales  Social Support - Family  Positive Events  Social Support - Friends  Neutral Events  Social Support - Total  Negative Events  Satisfaction with Support  Scores  Result  88  Cognitive Ability A s already described, information regarding the cognitive ability of the participants was obtained from the students' confidential school files. Students' results on the Wechsler Intelligence Scale for Children (3rd Edition) (WISC-III) (Wechsler, 1991) or the Stanford-Binet Intelligence Scale (4th Edition) (SB-TV) (Thorndike, Hagen, & Sattler, 1986) were recorded on the prepared data collection sheets identified only by code numbers and not by the students' names (see Figure 4). The WISC-III is a widely-used individually administered instrument for assessing the cognitive ability of individuals aged from 6 to 16 years of age. The WISC-ILI consists of thirteen subtests w h i c h measure different facets of intellectual functioning. A student's performance on these subtests is summarized i n three composite scores, the Verbal, Performance, and Full Scale IQ scores. The WISC-III has excellent psychometric properties. The average reliability coefficients for the composite scores are .95 (Verbal Scale), .91 (Performance Scale) and .96 (Full Scale) (Wechsler, 1991). The SB-TV, w h i c h is used less widely than the WISC-III i n British Columbia schools, is also an individually administered instrument for assessing cognitive ability. The SB-TV can be used w i t h individuals from 2 to 23 years of age. The scale consists of fifteen subtests, although not all subtests are used across all ages. A n individual's performance on the relevant subtests is summarized i n four area scores (Verbal Reasoning, Abstract/Visual Reasoning, Quantitative Reasoning, and Short-Term Memory) and a Composite score. The SB-TV has excellent psychometric properties w i t h reliability coefficients for the composite score across the different age groups falling within the .95 to .99 range (Thorndike, Hagen, & Sattler, 1986).  8  9  For the purposes of this study, only the Full Scale (FSIQ) WISC-III score, the Verbal Scale (VIQ) WISC-HI score, and the SB-IV Test Composite score were utilized. The FSIQ and SB-IV Composite scores allowed for the calculation of discrepancies between participants' aptitude and achievement, currently the most widely-used method within the research literature for identifying students w i t h learning disabilities. V I Q scores, available for the majority of participants, allowed for the identification of students w i t h particular difficulties i n the area of reading who, under current B.C. Ministry of Education criteria, w o u l d qualify for a reader for provincial examinations. Participants' Performance Scale (PIQ) scores from the WISC-III were not utilized i n the present study. Similarly, participants' WISC-III and SB-IV subtest scores were not utilized i n the study. Nonetheless, these scores were noted on the protocol sheets in order to allow for the calculation of scale or area standard scores i n cases where a student's psychoeducational assessment report noted subtest scores but only standard score ranges, percentile scores, or descriptors (e.g., "average") for the scales (WISC-III) or areas (SB-IV). Finally, it should be noted that the SB-IV's Verbal Reasoning area score was not utilized i n any of the analyses related to reading disability, because the abilities measured by this group of subtests are quite different from the abilities measured by the subtests of the WISC-III's Verbal Scale. To explain, the WISC-III Verbal Scale includes measures of verbal abilities (Vocabulary, Comprehension, Similarities), general knowledge (Information) and arithmetic/ working memory (Arithmetic) while the SB-IV Verbal Reasoning area is restricted entirely to measures of verbal abilities (Vocabulary, Comprehension, Absurdities, and Verbal Relations). Given the small number of students who had been administered the SB-IV and the fact that only one student presented w i t h  9°  a large discrepancy between his Verbal Reasoning area score and his w o r d reading abilities, this situation (and loss of one case for analysis) was not regarded as problematic. Academic Skills Information about students' current academic skills, particularly i n the area of reading, was obtained by means of the Reading (word list), Spelling and Arithmetic subtests of the Wide Range Achievement Test -yd  Edition (WRATV3) (Wilkinson, 1993)  and the Gray Silent Reading Tests (GSRT) (Wiederholt & Blalock, 2000). The WRAT-3 is a widely-used screening instrument w i t h a long history of use (more than 60 years across its various editions) i n schools, clinics, and research studies. The test is designed for use w i t h individuals from 5 to 74 years of age and takes approximately 15-30 minutes to administer. O n the reading subtest, w h i c h is administered individually, the participants were asked to read words of increasing difficulty until a ceiling was reached; namely, ten consecutive errors. O n the spelling subtest, the students were asked to spell words of increasing difficulty, also until a ceiling of ten consecutive errors was reached. O n the arithmetic subtest, the students were asked to complete as many of the problems that they could within a 15 minute time period. The majority of students were accustomed to using a calculator, so they found this subtest quite challenging. Examples of items from the Blue Form are presented i n Table 13. The Blue Form of the WRAT-3 was used i n the present study because the reliability coefficients for 13-17 year olds on this form, Reading, r = .90 to .92 ( M = .91),  9i  Spelling, r = .91 to .93, ( M = .92), and Arithmetic, r = .85 to .89, ( M = .88) (Wilkinson, 1993), were equal to or stronger than the coefficients for the Tan Form. Table 13. Examples of Items from the Blue Form of the Wide Range Achievement Test - 3rd Edition (WRAT-3). Reading  Item Nos.  Arithmetic  Spelling  #1  in  and  1+ 1=?  #10  size  circle  7x6 =?  #20  triumph  quantity  1/3 + 1/3 = ?  #30  heresy  conscience  6.23 x 12.7 = ?  #40  assuage  vicissitude  f (x) = 3X + x - 7. Find f (-2) 2  The Gray Silent Reading Tests (GSRT) (Wiederholt & Blalock, 2000) comprise a recently published instrument designed as an adjunct to the widely-used Gray Oral Reading Tests - 4th Edition (GORT-4) (Wiederholt & Bryant, 2001). The GSRT was designed to assess the silent reading comprehension ability of individuals from 7 to 25 years of age. The tests consist of parallel forms (A & B) each of w h i c h contains 13 developmentally sequenced reading passages. The tests take approximately 15 to 20 minutes for most individuals to complete. After reading a passage, the examinee is required to answer five multiple-choice comprehension questions and to mark the answer for each question (one of four given choices) on an answer sheet. Starting points are suggested by age, although an individual must achieve a basal level of o errors on their lowest passage and a ceiling level of 3 or more errors on a higher-level passage for the testing to be discontinued. A n individual's performance yields age and grade equivalents, percentiles and a standard score, the silent reading quotient (SRQ). The latter was utilized i n this study. With regard to psychometric properties, normative data  92  for the GSRT were gathered from 1400 individuals proportionately represented from across 32 states of the United States of America. Form A of the GSRT was used i n the present study. The internal reliability coefficient of this form is 0.95 (Wiederholt & Blalock, 2000). Perceptions of Self-Efficacy Data on students' perceptions of self-efficacy was obtained by means of four questionnaires - the Academic Self-Efficacy Questionnaire (A-SEQ) (see A p p e n d i x D), the Reading Self-Efficacy Questionnaire (R-SEQ) (see A p p e n d i x E), the Social Self-Efficacy Questionnaire (S-SEQ) (see A p p e n d i x F), and the Emotional Self-Efficacy Questionnaire (ESEQ) (see A p p e n d i x G). In all four questionnaires, the participants were asked to respond to questions ("How well can you...") by circling a number on a seven point Likert-type scale (1 " N o t Well at A l l " to 7 "Very Well") to elicit their perceptions of their capabilities across the four domains. The questionnaires were developed on the basis of previous research (Bandura, 1990,2001; Bandura, Pastorelli, Barbaranelli, & Caprara, 1999; M u r i s , 2001,2002). Bandura and his associates (Bandura et al., 1999) used 37 items of Bandura's original 57item Children's Self-Efficacy Scale (Bandura, 1990) to examine self-efficacy pathways to depression i n children. The abbreviated scale loaded onto three factors, Academic SelfEfficacy (ASE, 19 items), Social Self-Efficacy (SSE, 13 items) and Self-Regulatory Self-Efficacy (SRSE, 5 items). This scale was deemed unsuitable for the purposes of the present study, however, because neither it nor the original 57-item measure included a measure of emotional self-efficacy (although Bandura et al. (1999) had emphasized the importance of emotional self-efficacy i n their conceptual model) and the Social Self-Efficacy and  93  Academic Self-Efficacy subscales were judged to include many items irrelevant to the present study (e.g., Social: " H o w well can y o u do regular physical activities?" and Academic: " H o w well can y o u learn biology?") or insufficiently detailed items to tap the domain of particular interest (e.g., Academic: " H o w well can y o u learn reading and writing language skills?"). Heeding the call by Bandura et al. (1999) to broaden the study of self-efficacy to include an examination of affect regulation, M u r i s (2001) built u p o n the work of Bandura and his associates to develop the Self-Efficacy Questionnaire for Children (SEQC), a 24-item scale w h i c h he tested w i t h 330 adolescents. After exploratory factor analyses, Muris's reduced the scale to 21-items w h i c h loaded satisfactorily on three factors; namely, Academic Self-Efficacy (ASE, 7 items), Social Self-Efficacy (SSE, 7 items), and Emotional Self-Efficacy (ESE, 7 items). Although the internal consistency estimates for the SEQ-C were strong and the items valid for the present study, this researcher wished to alter some of the wording to reflect Canadian vocabulary, to add several new items to the scales, to use a 7-point rather than a 5-point Likert-type response scale (as recommended b y Bandura, 2001), and to develop a measure of reading self-efficacy to assess participants' perceptions i n this salient academic area. A s a consequence, this researcher used Muris's S E Q - C (Muris, 2001) as a base, referred back to Bandura's original items (Bandura 1990), and consulted Bandura's guide for constructing self-efficacy scales (Bandura, 2001) to develop the Academic SelfEfficacy Questionnaire (A-SEQ), the Social Self-Efficacy (S-SEQ), and the Emotional SelfEfficacy (E-SEQ). Appendices D , F and G show the process of adaptation and development of items. The Reading Self-Efficacy Questionnaire (R-SEQ) is an entirely new scale developed by this researcher to assess participants' perceived capability i n the  94 domain of reading; specifically, to read and to comprehend materials read for pleasure and for purposes required by their teachers. The items were designed to measure the skills widely thought to be essential for effective and efficient reading; namely, word recognition skills, knowledge of word meanings, silent reading comprehension skills of both narrative and expository texts, and long-term memory skills. Graduate study i n reading education and years of experience as a special education teacher and school psychologist informed the development of items for this questionnaire. Social Support and Life Events Data on students' perceptions of the social support available to them as well as their recent experience of life events was obtained by means of two instruments that have been used i n previous related research. Social Support. A widely used measure for assessing perceptions of social support is the Social Support Questionnaire (SSQ) developed by Sarason, Levine, Basham, and Sarason (1983). The SSQ, which yields scores for the total number of supportive persons in an individual's life ( N scores) as well as the individual's satisfaction w i t h that support (S scores), consists of 27 questions (e.g., " W h o m can y o u really count on to listen to y o u when y o u need to talk?"). In response, an individual is required to list all of the people that they can count on, by writing their initials and relationship (e.g., T.N. brother) and then indicating on a Likert-type scale (1-6) their overall satisfaction with the support that they feel is available to them. The SSQ has acceptable reliability and validity and has been used i n previous research including studies examining the relationship between self-efficacy and depression i n adolescents (e.g., McFarlane, Bellissimo, & N o r m a n , 1995). Sarason et al.  95  (1983) reported internal reliability coefficients of .97 for Size of Social Support ( N scores) and .94 for Satisfaction with Social Support (S scores). However, given the number of measures to be administered i n the present study as well as the concerns of school staff, parents and students regarding the detrimental effect of significant interruptions to instructional time, it was decided that the brief version of the SSQ should be utilized i n the present study. The SSQ-6 was obtained from Barbara Sarason i n M a r c h 2003. For the purposes of this study, the SSQ-6's Likert-type Satisfaction rating scale was reformatted so that responses corresponded i n direction and valence (e.g., left end - negative to right end positive) to other measures i n the present study; namely, the four self-efficacy questionnaires (A-SEQ, R-SEQ, S-SEQ, & E-SEQ), the Life Events Questionnaire (LEQ), the Multidimensional Anxiety Scale for Children ( M A S C ) , and the Reynolds Adolescent Depression Scale - 2nd Edition (RADS-2). Such consistency has been found to be important w i t h individuals who are struggling with learning disabilities, particularly i n the area of reading. In addition, the measure was given the title, Who I Can Count On (see Appendix H ) to assist the participants i n identifying the measure as they progressed through the packet of measures utilized i n this study. The reliability and validity of the SSQ-6 has been established across a number of studies; for example, .90 to .93 by A l l e n and Stoltenberg (1995), .91 to .95 by Klocek, Oliver, and Ross (1997), and .90 to .93 by Sarason, Sarason, Shearin, and Pierce (1987). Life Events. Students' experience of life events (and their rating of them as negative, neutral or positive) was measured by means of a revision and extension of the Life Events Questionnaire (LEQ). The L E Q was developed by Newcomb, H u b a and  9  6  Bentler (1981) specifically for the assessment of adolescents' perceptions of stress. Although the L E Q has been used i n related research (Gladstone & Koenig, 1994; McFarlane, Bellissimo, & N o r m a n , 1995; McFarlane, Bellissimo, N o r m a n , & Lange, 1994), it should be noted that the reliability coefficients of the seven scales comprising the L E Q are not strong. N o overall reliability coefficient was reported but KR-20 coefficients ranging from .37 to .58 were reported for the scales (Newcomb et al., 1981). In defence of their measure, however, Newcomb et al. noted that many of the events experienced by adolescents may be independent. A s a consequence, an expectation for high inter-correlations was likely unrealistic. Given this reasoned defence and the use of the L E Q i n related research, it was decided that a revised and extended version of this adolescent-specific instrument w o u l d be utilized i n the present study. The L E Q was revised by altering the wording of items to enhance comprehension for students w i t h reading disabilities and it was extended by including four additional items (related to drug and alcohol abuse as well as to physical and verbal assault) which are widely regarded as current concerns for many adolescents. The process of revising and extending the L E Q is presented i n Appendix I. Symptoms of Depression and Anxiety Information regarding students' symptoms of affective distress was obtained by means of two widely-used standardized self-report measures, the second edition of the Reynolds Adolescent Depression Scale - 2nd Edition (RADS-2) (Reynolds, 2002), which was designed specifically for use w i t h adolescents, and the Multidimensional Anxiety Scale for  97 Children ( M A S C ) (March, 1997), which facilitates self-reporting of symptoms of anxiety by both adolescents and children. Although many studies have utilized the cut-off scores (either "clinical" or "researcher-specified") from self-report measures of depression and anxiety to categorize participants into two groups (those w i t h and without significant levels of symptomatology), the present study analyzed symptoms as both categorical and continuous variables. The former approach allowed for a comparison of results with those from previous studies that adopted a categorical approach (and reported prevalence estimates) while the latter approach allowed for a more fine-grained analysis of the relationships among all the variables of interest (which, w i t h the exception of gender, are continuous in nature), thus m i n i m i z i n g the potential for an attenuation of findings (Gjerde, Block, & Block, 1988). Depression. The presence and severity of depressive symptoms experienced by participants was measured b y means of the RADS-2, a widely-used 30 item self-report scale designed to measure depressive symptomatology i n adolescents aged from 13 to 18 years of age. The measure, written at a third grade reading level, takes approximately five minutes to administer and yields a Total Depression score as well as scores for four scales: Dysphoric Mood, Anhedonia (i.e., inability to feel pleasure i n activities normally pleasurable)/Negative Affect, Negative Self-Evaluation and Somatic Complaints. The participants were required to rate themselves on each of the thirty items using a four-point Likert-type response format ("Almost Never," " H a r d l y Ever," "Sometimes" and "Most of the Time"). Some examples of items from the scale are as follows:  98  #19.1 feel that I am bad (Negative Self-Evaluation) #14.1 feel like having fun w i t h other students (Anhedonia/Negative Affect) #21.1 feel sorry for myself (Dysphoric Mood) #24.1 have trouble sleeping (Somatic Complaints). Before leaving each school, identification of students experiencing clinically significant levels of depression was made by two methods; namely, checking for total depression scores above the empirically derived clinical cut-off score (a raw score of 76 which corresponds to a T-score of 61) as well checking for students w h o had indicated high levels of symptomatology on any of the six critical items. School staff were alerted immediately of students who presented with significantly elevated scores on the critical items or the total scale so that appropriate follow-up measures could be instituted. The R A D S - 2 was standardized w i t h approximately 9,000 adolescents from the United States (8 states) and Canada (the province of British Columbia). The internal consistency reliability coefficient for the total score (Depression Total) was .93 with reliability coefficients for the four scales ranging from .80 to .87 (median .86) (Reynolds, 2002). Anxiety: The presence and severity of symptoms of anxiety experienced by participants was measured by means of the M A S C , a 39-item self-report measure designed to measure symptoms of anxiety i n children and adolescents (8 to 19 years of age). The M A S C , written at a fourth grade reading level, takes approximately 10 minutes for students to complete and yields scores for four basic scales (Physical Symptoms, Harm Avoidance, Social Anxiety, and Separation/Panic). The measure also yields scores for a total scale (Total MASC) and two major indices (Anxiety Disorder Index and  99 Inconsistency Index). The Anxiety Disorder Index is designed to identify individuals who w o u l d likely benefit from a referral for a more detailed clinical assessment while the Inconsistency Index is designed to identify random or careless responding by participants. The participants were required to rate the frequency w i t h w h i c h they experienced particular symptoms on a four-point scale (o = never; 1 = rarely; 2 = sometimes; and 3 = often). Some examples of items from the scale are as follows: #10. I'm afraid that other kids w i l l make fun of me. (Social Anxiety) #19.1 avoid going to places without m y family. (Separation/Panic) #25.1 stay away from things that upset me. (Harm Avoidance) #37.1 feel restless and on edge. (Physical Symptoms) Before leaving each school, students experiencing clinically significant levels of anxiety were identified by checking for Total MASC scores and Anxiety Disorders Index scores above the clinical cut-off score (T-score above 65). A g a i n , school staff were alerted immediately of students w h o presented w i t h significantly elevated scores so that appropriate follow-up measures could be taken as required. The M A S C was standardized w i t h approximately 2,700 children and adolescents from the United States, stratified according to census data. The mean internal consistency reliability coefficients for students from 12 to 19 years of age were .89 (.88 for females and .89 for males) for the Total MASC score, .63 for the Anxiety Index score, .85 for the Physical Symptoms scale, .68 for the Harm Avoidance scale, .85 for the Social Anxiety scale, and .67 for the Separation/Panic scale (March, 1997). For the purposes of the present study, the most reliable and informative scores were utilized; namely, Total MASC score and the scores for Physical Symptoms and Social Anxiety.  lOO  Procedure The students were invited to participate i n the study by their Special Education support teachers (see Letter of Invitation to Students i n A p p e n d i x J). In British Columbia, where the Ministry of Education has mandated an inclusionary model i n all public schools, students w i t h learning disabilities are generally enrolled i n regular classes w i t h curriculum adaptations or modifications as required. The participants were all receiving Special Education support either within the subject classrooms where they were experiencing the greatest difficulties (e.g., English or Social Studies) a n d / o r within specified blocks of time i n special education resource centres (e.g., Student Development Centres, Resource Rooms or Learning Assistance Centres). The students w h o volunteered to participate i n the study obtained their parents' informed written consent (see Parent Consent Form i n A p p e n d i x K ) and gave their o w n informed written assent (see Student Assent Form i n A p p e n d i x L) before taking part i n the study. The study procedures are outlined i n Figure 5. The students completed the measures listed there (academic tests and questionnaires) either individually or i n small groups (depending on their particular individual timetables), over a period of two sessions in w h i c h they normally received blocks of Special Education Support or Learning Assistance. During the first assessment session, participants were reminded about the general purpose of the study and invited to give their informed assent. Once it was clear that the students understood their role and rights as participants, they were asked to begin completing the measures as directed. Given the significant reading difficulties of the majority of participants, this researcher read aloud all of the measures, except the  101 Figure 5. Data Collection Procedures Phases  Activities  Preparation  Permission obtained from UBC Behavioural Research Ethics Board Permission obtained from Superintendents of School Districts Permission obtained from Principals of Secondary Schools Consent to facilitate study obtained from Special Education Teachers Students invited to participate by their Special Education Teachers Signed Parent Consent Forms returned by students Files of students with permission reviewed for cognitive ability data Special Education teachers consulted re. possible exclusionary factors  Session #1 (50 mins)  Procedures and confidentiality reviewed with students Students give Written Assent to participate in study " A l l About Me" Demographic Questionnaire (DQ) WRAT-3 Spelling subtest WRAT-3 Arithmetic subtest Academic Self-Efficacy Questionnaire (A-SEQ) Life Events Questionnaire (LEQ) "Who I Can Count On" Social Support Questionnaire (SSQ) Social Self-Efficacy Questionnaire (S-SEQ) Assessment Time - Subtotal  4 mins. 2 mins. 5 mins. 8 mins. 10 mins. 3 mins. 5 mins. 5 mins. 3 ™i 45 mins.  Gray Silent Reading Tests (GSRT) WRAT-3 Reading subtest Reading* Self-Efficacy Questionnaire (R-SEQ) Reynolds Adolescent Depression Scale - 2nd Ed. (RADS-2) Multidimensional Anxiety Scale for Children (MASC) Emotional Self-Efficacy Questionnaire (E-SEQ) Assessment Time - Subtotal  13 mins. 3 mins. 3 mins. 5 rrtins. 8 mins. 3 mins. 35 mins.  Assessment Time - Total  80 mins.  Session #2 (50 mins)  Time  ns  WRAT-3 Reading (word reading) subtest and the Gray Silent Reading Tests (GSRT), noting that this w o u l d save the participants time and effort. M a n y of the students expressed their approval of this strategy and none of the students declined the assistance. In the first assessment session, the participants began b y completing the demographic questionnaire, All about Me. Students then worked o n the WRAT-3 Spelling  102  and Arithmetic subtests before completing the Academic Self-Efficacy Questionnaire (ASEQ). Finally, the students were asked to complete three brief measures in sequence; the Life Events Questionnaire (LEQ), the Social Support Questionnaire (SSQ) Who I Can Count On, and the Social Self-efficacy Questionnaire (S-SEQ). During the second assessment period, the students were asked to complete two academic measures, the Gray Silent Reading Tests (GSRT) and the WRAT-3 Reading (word reading) subtest, followed by a related self-efficacy measure, the Reading Self-Efficacy Questionnaire (R-SEQ). The WRAT-3 Reading subtest was administered individually in an adjacent empty room when more than one student was taking part in the second assessment session. Upon completion of the R-SEQ, the students were asked to complete two self-report scales in counter-balanced order to preclude sequence effects; the Reynolds Adolescent Depression Scale - 2nd Edition (RADS-2) and the Multidimensional Anxiety Scale for Children (MASC). Finally, the students were asked to complete the Emotional Self-Efficacy Questionnaire (E-SEQ). Again, many of the measures were read aloud to the students by the examiner (R-SEQ, RADS-2, MASC & E-SEQ). The students were then thanked for their participation and invited to share (in the small group or privately) any questions or concerns that they might have had about their participation in the study. Data Analysis The data were subjected to two broad classes of analyses; namely, preliminary analyses to assess the veracity of the data and evaluate statistical assumptions and primary analyses to answer the seven research questions posed by this study.  Preliminary Analyses The participants' responses on all of the measures were scored, summarized on the individual Data Collection Sheets (see Figure 4) and entered into an SPSS 11.0 data file (SPSS Inc., 2003). Scores on the data sheets were in the form of standard scores for the cognitive and academic measures (WISC-III, SB-IV, WRAT-3 & GSRT), T-scores for the measures of anxiety and depression (RADS-2 & MASC), and raw scores for the measures of self-efficacy (A-SEQ, R-SEQ, S-SEQ, & E-SEQ), social support (SSQ), and experience of life events (LEQ). The data file was inspected visually and statistically (SPSS Frequencies) for input errors and missing data. The data were then assessed both graphically (by constructing stem and leaf diagrams, histograms, boxplots, normal probability plots, and scatter plots) and statistically (by calculating skewness and kurtosis estimates, by conducting Shapiro-Wilk tests, and by constructing a correlation matrix) to ascertain the presence of outliers and to assess for normalcy of distribution and collinearity between variables. The data were also assessed for accuracy by conducting an inter-rater reliability analysis. A random sample of 10 participants (i.e. 12% of the total sample) was selected by means of the SPSS Selection function and complete sets of protocols for these 10 participants were scored independently by a qualified and trained graduate student researcher. The overall inter-rater reliability yielded by this process was 97.3% with agreement for individual measures as follows: 100% for Depression (RADS-2), 98% for Anxiety (MASC), 100% for Self-Efficacy (A-SEQ, R-SEQ, S-SEQ & E-SEQ), 95% for Social  104  Support (SSQ), 100% for Life Events (LEQ), 90% for Reading (WRAT-3 word reading), 90% for Reading Comprehension (GSRT), 90% for Spelling (WRAT-3) and 90% for Arithmetic (WRAT-3). Finally, as discussed earlier in this chapter, the reliability (internal consistency) of the self-efficacy questionnaires was calculated. It should be noted that although selfefficacy is widely regarded as a multidimensional construct, in the same manner as the closely-related construct of self-concept (Bandura, 1997; Bong & Clark, 1999; Bong & Skaalvik, 2003; Byrne, 1996; Harter, 1999; Pajares, 1996), an overall reliability estimate (Total Self-Efficacy) was calculated to allow for a comparison of the reliability of the present measures with previous measures (Bandura et al., 1999; Muris, 2001,2002). The internal consistency of the four questionnaires and the total scale was satisfactory with coefficients falling within the .80 to .93 range (see Table 14). Primary Analyses To answer the seven research questions posed in the present study, various analytic methodologies (descriptive statistics, analysis of variance, and regression analysis) were employed. With regard to the first question concerning the prevalence and severity of anxiety and depression in adolescents with learning disabilities, the percentage of participants (GLD and TRAD-LD) falling within the clinically significant ranges of symptomatology were calculated and compared with previous studies. In addition, the mean levels of anxiety were calculated for comparison with previous studies that had utilized the MASC and reported these sample statistics. To answer the second question as to whether anxiety and depression could be predicted on the basis of perceptions of self-efficacy, three sets of regression analyses  105 were conducted (i.e., for depression, for anxiety, and for a composite of depression and anxiety). The analyses were all conducted separately for males and for females because an analysis of variance had revealed significant gender differences on a number of important predictor variables. Unfortunately, conducting analyses separately by gender resulted in small sample sizes. This, in combination with collinearity among three of the self-efficacy variables, precluded a full assessment of the contribution of all four domains of self-efficacy. Accordingly, the second question could only be answered by conducting simple regression analyses. The next two questions, (questions 3 and 4) concerning the role of social support and life events were examined by means of analyses of variance and descriptive statistics. An examination of the contribution of these factors to the predictive relationship between self-efficacy on the one hand and experience of depressive and anxious symptoms on the other by means of regression analyses (as originally planned) was precluded by collinearity among variables as well as small sample sizes (as described above), which resulted in only simple regression analyses being possible. The fifth question regarding the role of gender was examined by means of analyses of variance and descriptive analyses to further examine differences in levels of symptomatology, self-efficacy, social support and experience of life events between the two groups. The sixth question, which addressed the role of type and severity of reading disability in the experience of depression and anxiety, was answered by conducting an analysis of variance for each of the three hypotheses. In the first analysis, participants with low word reading skills (RD-LW) were compared with all other participants from the general sample (GLD) who presented with "normal" (average or better) word  io6  reading skills. In the second, participants with word reading skills that were discrepant from their measured verbal ability (RD-V/W) were compared with participants from the general sample (GLD) without such a discrepancy. Finally, in the third analysis, participants with word reading skills that were discrepant from their reading comprehension abilities (RD-C/W) were compared with participants from the general sample (GLD) without such a discrepancy. To address the seventh question, analyses of variance were conducted to examine differences between students reporting high and low levels of co-occurring depressive and anxious symptomatology. These analyses identified specific factors that reliably distinguished between the two groups. In addition, demographic information (ethnicity, cultural and language background, employment, involvement in extracurricular activities, parental education, and family composition) was also considered.  107 Chapter 4 RESULTS The present study was designed to extend previous research that examined the links between self-efficacy and negative affective outcomes in children and adolescents (Bandura et al., 1999; Ehrenberg et al., 1991; McFarlane et al., 1995; McFarlane et al., 1994; Muris, 2002; Muris et al., 2001) by focusing upon a population commonly thought to be at particular risk for developing symptoms of anxiety and depression; namely, adolescent students with learning disabilities. This study also examined a subset of the sample, specifically those adolescents experiencing significant difficulties in the highly salient area of reading, and included an examination of two factors known to act as risk or protective factors in the development of depression; namely, social support and experience of negative life events. The results of the present study are presented in three sections. The first section (preliminary analyses) reports on the reliability of the self-efficacy questionnaires developed for use in this study, the accuracy of the data, an evaluation of statistical assumptions, and descriptive statistics concerning the sample. The second section (primary analyses) describes the results of the analyses that addressed the seven research questions guiding this study; namely, questions concerning: (a) the prevalence and severity of anxiety and depression in adolescents with learning disabilities, (b) the prediction of anxiety and depression in adolescents with learning disabilities on the basis of their perceptions of self-efficacy, and the roles of (c) social support, (d) life events, (e) gender, (f) reading disability, and (g) patterns of factors in the experience of anxiety and depression by adolescents with learning disabilities. The third and concluding section of this chapter provides an overall summary of the findings.  io8 Preliminary Analyses In this section, findings are provided concerning the reliability of the self-efficacy questionnaires, data accuracy, results of the evaluation of statistical assumptions, and characteristics of the sample. The reliability of the self-efficacy questionnaires were calculated by means of SPSS Reliability Analysis. The analyses yielded acceptable Cronbach's a coefficients in the range of .80 to .93 (see Table 14) comparable with results reported in previous research (Bandura et al., 1996; Bandura et al., 1999; Muris, 2002; Muris et al, 2001). Recall from Chapter 3 that the academic, social and emotional self-efficacy measures used in this study were adaptations of the measures used by Bandura, Muris, and their associates while the reading self-efficacy measure was developed specifically for the present study.  Table 14. Reliability of Self-Efficacy Questionnaires N  Age  A-SE  R-SE  S-SE  E-SE  T-SE  Bandura et al. (1996)  279  11-14 yrs  .87  -  .75  -  -  Muris (2001)  330  14-17 yrs  .88  -  .85  .86  .88  Muris (2002)  596  12-19 yrs  .84  -  .82  .86  .90  Present Study  83  13-17 yrs  .84  .91  .80  .87  .93  Study  Note: Coefficients are Cronbach's a except for Bandura et al. (1996,1999) who reported squared multiple correlations of factor scores; A-SE = Academic Self-Efficacy; R-SE = Reading Self-Efficacy; S-SE = Social Self-Efficacy; E-SE = Emotional Self-Efficacy; T-SE = Total Self-Efficacy  With regard to statistical assumptions, each variable was tested for normalcy of distribution graphically (by constructing stem and leaf diagrams, histograms, and normal probability plots) and statistically (by calculating statistics for skewness and kurtosis and conducting Shapiro-Wilk tests). Table 15 summarizes the latter in addition  109 Table 15. Means, Standard Deviations, Ranges, Skewness, Kurtosis, and Results of Shapiro-Wilk Tests of Normality for Measured Variables  Variables  M  SD  Range  Skewness  Kurtosis  Shapiro-Wilk  Sig.  46.22 51.29  8.81 10.73  33-75 27-80  .99 .15  1.05 -.32  .93** .99  .000 .954  42.46 47.20 51.14 48.28  9.89 10.28 8.67 9.47  22-66 16-67  .27 - .50 -.78 -.42  -.29 .42 1.02 .51  .98 .98 .96* .98  .359 .189 .013 .172  Social (Family) Social (Friends) Satisfaction  2.02  1.14  1.05 .77 -.81  1.53 -.11 -.47  .000  1.08 .68  0-6 0-4.17 3-6  .94**  1.48 5.17  .93** .93**  .000 .000  10. 11. 12.  Positive Life Events Neutral Life Events Negative Life Events  4.48 2.30 2.67  2.44 2.12 2.69  0-9 0-13 0-11  .20 2.24 1.34  -.61 7.63 1.28  .96** .79** .84**  .008 .000 .000  13. 14.  Cognitive Ability Verbal Ability  95.14 92.28  12.53 15.61  67 -125 54 -125  .25 .06  -.30 -.40  .99 .99  .548 .669  15.  Word Reading Reading Comprehension  87.31  12.46 16.83  51-118  .01 .01 .44  .37 -.58  .98 .97*  .317  55 -123 61-113  .97  45 -112  -.20  .061 .783  1.  Depression  2.  Anxiety  3. 4.  Academic SE Reading SE  5. 6.  Social SE Emotional SE  7. 8. 9.  16. 17. 18.  Spelling  82.31 83.59  Arithmetic  80.36  12.56 12.62  23-68 22-69  -.29 .32  .99  .034  Note. N = 83 except for Verbal Ability (WISC-III VIQ) where N = 74; SE = Self-Efficacy. *p <  .05. **p < .01.  to presenting means, standard deviations, and ranges for each variable, and demonstrates that a number of variables were not normally distributed. Accordingly, remedies were applied. Before discussing the transformations of the problematic variables, however, the contribution of outliers should be noted. Outliers were identified using boxplots and stem and leaf diagrams. It was clear that the presence of a number of outliers was affecting the distribution of several variables. Accordingly, the data file and the scoring protocol of each outlying case were examined to ensure that the observations were not due to procedural errors. No errors  no  were detected and an examination and a consideration of the cases (participants) suggested that all but two of the outlying observations should be retained. On the social support questionnaire, two participants had not followed the directions to name (by providing initials) those specific friends on whom they could depend. Instead, the students had noted that they had many friends (18-20), but had not provided their friends' initials. It was decided that these were indeed "extraordinary events" (Hair, Anderson, Tatham, & Black, 1998, p. 64) that should not be represented in sample. The observations were deleted and replaced by substituting the mean (M = 1.48) of all other cases on this particular subscale. The statistics for social support from friends and total social support in Table 15 reflect the imputation. With regard to the remaining outliers, there was no reason to believe that these observations were not representative of the general population of adolescents with learning disabilities to which the results of this study will generalize. By retaining these observations, however, it was difficult to achieve normal distributions on all variables despite instituting transformations. Transformations to achieve more normal distributions for depression, social selfefficacy, social support (from family, from friends and satisfaction with support), experience of life events (positive, neutral, and negative), and reading comprehension were not uniformly successful (see Table 16). In the case of depression, a log transformation did rectify the distribution and this transformed variable was used in all subsequent analyses. Interestingly, a non-normal distribution for depression is not unusual. As discussed in the review of literature, selfreports of depressive symptoms are based on the premise psychopathology occurs at the extreme end of a continuum of individual differences with regard to human  Table 16. Skewness, Kurtosis, and Results of Shapiro-Wilk Tests of Normality for Transformed Variables Skewness  Kurtosis  Shapiro-Wilk  Sig.  .52  -.10  .97  .053  Square  -.19  -.00  .99  .761  Social (Family)  Square Root  -.11  1.00  .98  .305  Social (Friends)  Square Root  -.16  -.37  .98  .141  Satisfaction  Cube  -.21  -.82  .95**  .002  Positive Life Events  +3, Square Root  -.17  -.49  .96*  .015  Neutral Life Events  +3, Log of Log  .14  .02  .94**  .001  Negative Life Events  +3, Log of Log  .12  -.87  .93**  .000  Variables  Transformation  Depression  Log  Social SE  Note. N = 83; SE = Self-Efficacy  *p < .05. **p < .01. characteristics (Cicchetti & Rogosch, 1999). As a result, a lack of normalcy in the distribution of self-reported symptoms of depression can be expected. Certainly, such a pattern of distribution has been described by others conducting research in this area (Millikan et al., 2002; Muris, 2001) and similar transformations were applied. With regard to remedying the distribution of the remaining variables, success was attained for social self-efficacy by means of squaring the scores and for social support (by both family and friends) by applying a square root transformation. These transformed variables were used in all subsequent analyses. Only a measure of success was achieved for satisfaction with social support (cubing scores) and for life events (positive, neutral, and negative) (by adding 3 to each score to overcome zero scores, thus enabling log transformations to be conducted). No transformations were found that remedied the distribution of reading comprehension,  112  so the original untransformed variable was used in subsequent analyses. Given the lack of normalcy in distribution of these last five variables, all analyses involving these variables were interpreted with caution and descriptive statistics were employed to further explore relationships among variables. The next step of the preliminary analyses involved constructing a correlation matrix (see Table 17) to ensure that any collinearity, especially between the variables to be utilized in the regression analyses, fell within acceptable limits. With regard to these variables, there was a problematically high correlation (i.e., > .60) between social support from family and total social support (r = .72, p < .01). Because total social support is comprised of two subscales, social support from family and social support from friends, only the subscales are included in the analyses. There were also moderate but potentially problematic correlations between emotional self-efficacy and two other domains of self-efficacy; namely, reading (r = .62, p < .01) and social self-efficacy (r = .60, p < .01). Given the theoretical distinction and utility of these different domains of self-efficacy, it was desirable that these variables be utilized in subsequent analyses. However, the collinearity among these predictors precluded interpretation of multiple regression coefficients in the regression analyses (Rosenthal & Rosnow, 1991). As a result, reading self-efficacy was excluded from the regression analyses while social and emotional self-efficacy were aggregated. A n examination of the statistical assumptions for this composite revealed a non-normal distribution. A transformation (by squaring) rectified the distribution and yielded acceptable skewness (-.10), kurtosis (.15) and Shapiro-Wilk statistic (.99, p = .67).  ii3  Table 17. Correlations between Variables VARS  DEP  DEP  —  ANX  ASE  RSE  SSE  ESE  SFM  ANX  .46**  ASE  -25*  -.05  RSE  -.11  -.07  .44**  SSE  -.35**  -.24*  .55**  .44**  ESE  -.39**  -.25*  .41**  .62**  .60**  SFM  -.28**  -.03  .20  .15  .21  .07  .18  -.13  -.01  SFR  STO  SAT  POS  NEU  NEG  AGE  GEN  COG  VIQ  R-W  R-C  SPL  — — — — — —  SFR  .02  -.15  -.05  -.05  STO  -.39**  -.19  -.10  .13  .32**  .06  .72**  .41**  SAT  -.31**  -20  .33**  28**  .48**  .41**  .18  -.07  .15  PCS  -.18  .05  .24*  -.01  .34**  .16  .08  .19  21  .34**  —  NEU  .23*  -.11  -.03  -.02  .00  -.16  -.14  .19  -.11  .01  -.03  .03  -.12  .11  .05  .14  .00  .31**  -.05  — — —  —  NEG  .23*  .32**  -.10  .04  AGE  25*  .04  -.03  .02  -.05  -.02  -.20  .12  -.16  -.21  -.11  -.10  .06  GEN  -.07  -.02  -.15  .11  -.14  24*  -.20  -.26*  -29**  -.15  -20  .06  -.12  .03  COG  -.24*  -.11  .05  .40**  .37**  .47**  -.05  .11  .08  -.00  .12  -.06  .05  .05  .34**  —  VIQ  -26*  -.11  -.03  .41**  .32**  .40**  -.07  .08  .07  -.06  .04  -.06  .05  .06  .35**  .90**  —  -.10  .01  .09  .20  .13  .05  .31**  .34**  —  .14  .23*  .41**  .48**  .40**  —  — — —  R-W  .16  .05  -.06  .37**  -.03  -.08  .05  .20  .06  R-C  .08  -.06  -.02  .37**  .14  .18  .01  .06  -.02  -.07  -.16  .08  -.03  SPL  .19  .18  -.09  .22*  -.22*  -.13  .10  -.14  .11  -.16  -.06  .11  .31**  .02  -.06  .03  .02  .76**  20  —  .15  .32**  .02  .20  -.02  -.06  -.02  -.07  .09  .11  .11  -.10  .17  .24*  .09  .25*  .27*  .25*  ART  -.03  ART  -.07  —  Note. N = 83; Includes transformed variables; VARS = Variables; DEP = Depression; A N X = Anxiety, ASE = Academic Self-Efficacy; RSE = Reading SelfEfficacy; SSE = Social Self-Efficacy; ESE = Emotional Self-Efficacy; SFM = Social Support from Family; SFR = Social Support from Friends; STO = Total Social Support; SAT = Satisfaction with Social Support; POS = Positive Life Events; N E U = Neutral Life Events; N E G = Negative Life Events; A G E = Age of participants; G E N = Gender; C O G = Cognitive Ability; VIQ = Verbal Ability (WISC-III VIQ scores); R-W = WRAT-3 Reading; R-C = GSRT Reading Comprehension; SPL = WRAT-3 Spelling; ART = WRAT-3 Arithmetic. *p< .05. **p< .01.  n  4  A final step in the preliminary analyses involved determining whether there were gender differences on all of the main variables (see Table 18). Analyses of variance revealed no significant differences between males and females on depression or anxiety  Table 18. Descriptive Statistics (Mean Scores, Standard Deviations and Ranges) of all Measures for Females and Males Measures  Females (n = 24) M (SD)  Range  Males (n = 59) M (SD)  ANOVA Range  F ( l , 81)  V  Age  14.38(1.10)  13- -16  14.44(1.19)  13- -17  .05  .817  Cognitive Ability  88.54 (10.50)  67- 113  97.83(12.37)  7 1 - 125  10.46**  .002  Verbal Ability  83.91 (12.69)  54- 107  95.75 (15.48)  63- 125  10.05**  .002  Word Reading  86.25 (10.02)  72- 113  87.71 (13.39)  5 1 - 118  .24  .623  Reading Comp.  76.21 (16.58)  55- 121  84.73 (16.39)  55- 123  4.64*  .034  Spelling  84.75 (11.00)  64- 112  83.08 (13.12)  6 1 - 111  .29  .595  Arithmetic  77.04(14.88)  45- 102  81.68(11.37)  57- 112  2.38  .127  Depression  47.08 (9.03)  35- -68  45.86(8.78)  33- -75  .36  .554  Anxiety  51.54(13.07)  33- -80  51.19 (9.74)  27--70  .02  .892  Academic SE  44.79 (9.71)  29- -66  41.51 (9.88)  22- -64  1.90  .172  Reading SE  44.29 (11.37)  16- -62  48.39 (9.65)  25- -67  2.77  .100  Social SE  53.58 (8.04)  34- -67  50.15 (8.79)  23--68  2.91  .092  Emotional SE  44.96 (8.28)  22- -62  49.63 (9.66)  23- -69  4.31*  .041  Social Sup. (Family)  2.27 (.84)  1.16--4.50  1.91 (1.23)  0.00- -6.00  3.23  .076  Social Sup. (Friends)  1.92 (1.14)  .17- -4.17  1.30 (1.02)  0.00 -4.00  5.94*  .017  Satisfaction (Soc. Sup.)  5.35 (.45)  4.50 -6.00  5.09 (.74)  3.00 -6.00  1.79  .185  Positive Life Events  5.21 (2.28)  1--9  4.19(2.46)  0--9  3.27  .074  Neutral Life Events  2.13 (1.78)  0- -6  2.37(2.25)  0- 13  .29  .594  Negative Life Events  3.29 (3.29)  0-  2.42 (5.70)  0- 10  1.13  .292  1  11  Note: Verbal Ability = VIQ scores for the 75 participants whose most recent psychoeducational assessment utilized the WISC-III. •p<.05.**p<.01.  "5  However, there were significant differences found on emotional self- efficacy (F (i, 81) = 4.31, p < -05), social support from friends (F (1,81) = 5.94, p < .05), cognitive ability (F (1, 81) = 10.46, p < .01), verbal ability (F (1,72) = 10.05, P < - )/ 01  a n  d reading comprehension  (F (1,81) = 4.64, p < .05). Accordingly, regression analyses were run separately for males and females in this study and the differences in the patterns yielded by the two groups are discussed below. Before turning to the primary analyses, it will be useful to examine descriptive statistics for the disability subgroups (see Table 19). Recall from Chapter 3 that all participants in the study had been identified by school district personnel as having learning disabilities. In this study, these students are considered as having "General Learning Disabilities" (GLD) (N = 83). However, because many of these students did not meet a more restrictive definition for identifying learning disabilities, a subgroup of students based on more "traditional" criteria was created. This subset of the total sample, "Traditional Learning Disabilities" (TRAD-LD), included students with cognitive ability scores within the average range or better (a standard score of 80 or higher), and a discrepancy of 1.5 or more standard deviations between their cognitive ability and achievement in one or more academic skill areas (n = 41). Another subset of students, those with reading disabilities, was also formed. As described in detail in Chapter 3 and summarized in Table 12, the reading disabilities subgroup was formed in three ways: the first, "Reading Disabilities: Low Word Reading" (RD-LW) included students whose word reading scores fell below a standard score of 90 (n = 56); the second, "Reading Disabilities: Verbal/Word Reading" (RDV/W) V / W ) included students demonstrating a 1.3 or more standard deviation  n6  Table 19. Descriptive Statistics (Mean Scores, Standard Deviations and Ranges) of all Measures for Total Sample (GLD) and Disability Subgroups ( T R A D - L D and RD)  Age Cognitive Ability Verbal Ability  1  Word Reading Reading Comp. Spelling Arithmetic Depression Anxiety Academic SE Reading SE Social SE Emotional SE Social Sup. (Family) Social Sup. (Friends) Satisfaction (Soc. Sup.) Positive Life Events Neutral Life Events Negative Life Events  GLD  TRAD-LD  RD-LW  RD-V/W  RD-CAV  (N = 83) MSD  (n = 41) MSD  (n = 56) MSD  (n = 17) MSD  (n = 6) MSD  14.42 (1.16) 13-17 95.14 (12.53) 67-125 92.28 (15.61)  14.56 (1.14) 13-17 101.12 (11.40) 80 -123 99.19 (14.0)  14.23 (1.16) 13-17 93.29 (11.88) 67-120 90.08 (14.89)  14.12 (1.05) 13-17 103.53 (9.66) 84 -122 105.00 (11.81)  15.00 (1.27) 14-17 102.17 (7.14) 88 -107 97.67 (12.53)  54 -125 87.31 (12.46) 51-118 82.31 (16.83) 55 -123 83.59 (12.56)  66 -125 84.49 (13.94) 51 -118 80.32 (19.43) 55-110 79.93 (12.52)  54 -122 80.73 (8.29) 51-89 79.73 (15.57) 55 -109 78.41 (9.24)  85 -122 77.94 (10.03) 62-92 83.12 (16.84)  61 -113 80.36 (12.62)  61 -112 76.73 (14.09) 45 -112 43.88 (6.23)  61 -102 79.25 (13.46) 45 -112 45.23 (8.14)  61-86 79.59 (10.68) 57-97 42.82 (7.03)  34-58 50.15 (10.78)  33-68 50.59 (11.31)  34-59 48.71 (10.02)  84 -118 73.50 (10.06) 62-86 99.00 (9.82) 84 -109 71.50 (8.69) 61-84 80.83 (19.10) 57-112 44.33 (5.24) 37-50 55.00 (6.99)  27-80 42.46 (9.89)  32-73 43.59 (8.85)  27-80 42.34 (9.50)  22-66 47.20 (10.28) 16-67 51.14 (8.67)  26-62 48.46 (11.11) 25-67 53.05 (7.90)  22-66 44.64 (9.86) 16-67 51.55 (8.50)  32-68 44.29 (9.33) 31-62 48.35 (11.59) 25-67 52.94 (8.04)  23-68 48.28 (9.47)  37-68 51.34 (8.37)  23-68 48.13 (9.62)  37-68 54.76 (8.49)  38-62 50.83 (9.91) 40-67 55.83 (5.19) 50-64 58.50 (8.09)  22-69 2.01 (1.13)  34-69 1.93 (1.09)  22-69 2.01 (1.20)  37-69 1.70 (.96)  51-69 1.36 (.59)  .00 - 6.00 1.48 (1.08) .00-4.17 5.16 (.68) 3.00-6.00 4.48 (2.44)  .00-5.00 1.43 (1.15)  .00-4.00 1.16 (.89)  .83-2.17 .50 (.28)  .17-4.17 5.26 (.58)  .00 - 6.00 1.37 (1.05) .00-4.17 5.23 (.61)  3.83 - 6.00 4.51 (2.55)  3.38 - 6.00 4.45 (2.46)  .17-1.00 5.31 (.75) 4.00-6.00 4.17 (2.31)  0-9 2.30 (2.12)  0-9 2.15 (1.80)  0-9 2.18 (1.82)  .17-3.00 5.31 (.57) 4.17-6.00 4.76 (2.66) 0-9 2.65 (1.84)  0-13 2.67 (2.69)  0-8 2.22 (2.10)  0-8 2.63 (2.87)  0-8 1.65 (1.46)  0-3 1.00 (1.09)  0-11  0-8  0-11  0-4  0-3  45 -112 46.22 (8.81) 33-75 51.29 (10.73)  55 -105 73.35 (8.54)  47-66 47.33 (9.54)  1-8 1.33 (1.03)  Note: Verbal Ability = VIQ scores (n = 75); GLD = General Learning Disabilities; TRAD-LD = Traditional Learning Disabilities; RD-LW = Reading Disabilities: Low Word Reading; RD-V/W Reading Disabilities: Verbal/Word Reading; RD-CAV = Reading Disabilities: Reading Comprehension/Word Reading. >p<.05. **p<.01.  n  7  discrepancy between verbal ability and word reading skills (n = 17), and finally, "Reading Disabilities: Comprehension/Word" (RD-C/W) included students demonstrating a 1.3 or more standard deviation discrepancy between reading comprehension skills and word reading skills (n = 6). It is important to note that membership in these reading groups overlapped to some degree. Accordingly, analyses were conducted only by comparing students within a specific disability group with students remaining in the total sample (GLD) and not by comparing students across the disability groups. The groups were not independent because a given student might be classified as reading disabled on the basis of meeting one, two or all three sets of criteria. Nonetheless, it is interesting to note that students classified as RD-LW had the lowest mean cognitive ability, verbal ability and reading comprehension skills. In contrast, the students classified as R D - V / W and R D - C / W had the highest means for cognitive ability but the lowest mean scores for word reading and spelling skills. Of further interest, mean arithmetic scores were low across all groups (standard scores of 76.73 to 80.83), but lowest was yielded by students classified as having "traditional" learning disabilities (TRAD-LD). It is important to note that over 60% of the participants completed their most recent psychoeducational assessments more than 3 years ago (see Table 20).  Table 20. Number of Years since Most Recent Psychoeducational Assessment  Years  0  1  2  3  4  5  6  7  8  9  10  n  2  13  10  8  12  9  12  7  8  1  1  %  2.4  15.7  12.0  9.6  14.5  10.8  14.5  8.4  9.6  1.2  1.2  Cum. %  2.4  18.1  30.1  39.8  54.2  65.1  79.5  88.0  97.6  98.8  100  n8  Although 10.8% of the students completed their last psychoeducational assessment after entering the secondary grades (grades 8 to 12), 42.1% completed their assessment during their intermediate years (grades 4 to 7) and 47.1% completed their most recent assessment during their primary years (grades 1 to 3) (see Figure 6). The lack of recency i n psychoeducational assessment data (specifically, cognitive and verbal ability scores) places a limitation upon the present study.  Figure 6. Summary of Most Recent Psychoeducational Assessments by Grade 20  10  ! 4 . -z  fl'.  c  n  1  0  1  j  •  2  3  Grade Tested  Primary Analyses In this section, findings are provided from the analyses conducted to address the seven research questions guiding this study. Prevalence and Severity of Depression and Anxiety The first question posed i n this study concerned the prevalence and severity of anxiety and depression i n adolescents w i t h learning disabilities i n comparison w i t h their normally achieving peers. O n the basis of findings from previous research, it was  ii9  hypothesized that the prevalence and severity of clinically significant symptoms of depression, anxiety and comorbid depression and anxiety would be higher in this sample of adolescents with learning disabilities than is typically found within the normal adolescent population. Recall from Chapter 3 that the participants were asked to complete two selfreport measures, the Reynolds Adolescent Depression Scale - 2nd Edition (RADS-2) and the Multidimensional Anxiety Scale for Children (MASC), both of which asked the students to rate themselves on 4-point Likert scales. Depression. A frequency analysis of data yielded by the RADS-2 indicated that 6% of the entire sample of participants (GLD) obtained scores at or above the clinical cutoff of a T-score of 61. With regard to severity of depression, 2.4% of the participants rated themselves within the severe range, 2.4% within the moderate range, and 1.2% within the mild range for clinically significant symptomatology. To facilitate comparisons with findings from previous research, prevalence, severity, and mean total depression scores (T-scores and raw scores) were also calculated. Further, all of these statistics were calculated for the subsamples of participants identified as having traditional learning disabilities (TRAD-LD) and reading disabilities (RD) (see Tables 21 and 22). None of the participants in the TRAD-LD subsample reported clinically significant levels of depressive symptoms. These findings indicate that as a total group, the participants reported considerably lower rates of prevalence for clinically significant symptoms and lower mean levels of depressive symptomatology than has generally been reported in the  120  literature for both learning disabled and normally achieving adolescents, with the subsets of TRAD-LD and RD participants reporting even lower levels than the overall sample (GLD).  Table 21. Prevalence and Severity of Clinically Significant Symptoms of Depression Reported by GLD, TRAD-LD and RD Participants Group  n (%)  Moderate n(%)  Severe n (%)  Total n(%)  Mild  N/n  GLD  83  1 (1.20%)  2 (2.40%)  2 (2.40%)  5 (6.00%)  TRAD-LD  41  0 (0.00%)  0 (0.00%)  0 (0.00%)  0 (0.00%)  RD-LW  56  0 (0.00%)  2 (3.57%)  0 (0.00%)  2 (3.57%)  RD-V/W  17  0 (0.00%)  0 (0.00%)  0 (0.00%)  0 (0.00%)  RD-C/W  6  0 (0.00%)  0 (0.00%)  0 (0.00%)  0 (0.00%)  Note: Mild = T-scores 61 to 64; Moderate = T-scores 65 to 69; Severe = T-scores at or above 70; GLD = General Learning Disabilities; TRAD-LD = Traditional Learning Disabilities; RD-LW = Reading Disabilities: Low Word Reading; RD-V/W = Reading Disabilities: Verbal/Word Reading; RD-C/W = Reading Disabilities: Reading Comprehension/Word Reading.  Table 22. Means (and Standard Deviations) for Total Depression (Raw Scores and T-Scores) for G L D . T R A D - L D and R D Participants T-Scores  N/n  Raw Scores M (SD)  GLD  83  53.92 (13.02)  46.22 (8.81)  TRAD-LD  41  50.44 (9.19)  43.88 (6.23)  RD-LW  56  52.45 (11.99)  45.23 (8.14)  RD-V/W  17  48.82 (10.43)  42.82 (7.03)  RD-C/W  6  51.00  44.33 (5.24)  Group  (7.64)  M  (SD)  Note: GLD = General Learning Disabilities; TRAD-LD = Traditional Learning Disabilities; RD-LW = Reading Disabilities: Low Word Reading; RD-V/W = Reading Disabilities: Verbal/Word Reading; RD-C/W = Reading Disabilities: Reading Comprehension/Word Reading.  121  Anxiety. A frequency analysis of data yielded by the M A S C indicated that 10.8% of the entire sample of participants (GLD) obtained scores at or above the clinical cutoff of a T-score of 66. With regard to severity, 3.6% of the participants rated themselves within the severe range ("Very Much Above") and 7.2% within the moderate range ("Much Above") for clinically significant symptomatology. The MASC also allows for the classification of subclinical symptoms. A further 9.6% (n = 8) of the participants obtained scores within the mild range ("Above Average"). To facilitate comparisons with findings from previous research, prevalence, severity, and mean total anxiety scores (T-scores and raw scores) were also calculated. Again, as for depression, these results were also calculated for the subsamples of participants identified as having traditional learning disabilities (TRAD-LD) and reading disabilities (RD) (see Tables 23 and 24). The results were also calculated for females and males (despite there being no significant difference between the groups) to facilitate comparison with results from previous studies that had utilized the MASC (see Table 5). The mean total anxiety scores (raw scores) for females was 46.58 (SD = 18.89) and 38.80 (SD = 14.18) for males (F (1,81) = .397, p < .05). These findings indicate that the prevalence of clinically significant symptoms of anxiety within the total group (GLD) and the "traditional" subgroup (TRAD-LD) are generally comparable with prevalence rates reported for adolescents from the general adolescent population (Note: to date, prevalence rates have not been reported by previous studies examining the functioning of adolescents with learning disabilities). With regard to mean severity of symptomatology, the levels reported in the present study are only somewhat higher than has been reported for adolescents from the general population, with the magnitude of difference similar to that reported by studies  122  which have utilized other anxiety measures to compare levels of anxiety in adolescents with and without learning disabilities (Note: to date, no studies have used the MASC to examine anxiety in adolescents with learning disabilities).  Table 23. Prevalence and Severity of Symptoms of Anxiety Reported by GLD, TRAD-LD and RD Participants  Group  N/n  Subclinical Above Average  Clinical Much Above Average  Clinical Very Much Above Average  Clinical Total  n(%)  n(%)  n(%)  n(%)  GLD  83  8 (9.6 %)  6  (7.20 %)  3 (3.60 %)  9 (10.80 %)  TRAD-LD  41  3 (7.31 %)  3  (7.31 %)  1 (2.44 %)  4  RD-LW  56  3 (5.36 %)  4  (7.14 %)  3 (5.36 %)  7 (12.50 %)  RD-V/W  17  0 (0.00 %)  2 (11.76%)  0 (0.00 %)  2 (11.76 %)  RD-C/W  6  0 (0.00 %)  1 (16.66%)  0 (0.00 %)  1 (16.66 %)  (9.75 %)  Note: Clinically Significant = scores at or above a T-score of 66; Very Much Above = T-scores at or above 71; Much Above = T-scores from 66 to 70; Above = T-scores from 61 to 65; GLD = General Learning Disabilities; TRAD-LD = Traditional Learning Disabilities; RD-LW = Reading Disabilities: Low Word Reading; RD-V/W = Reading Disabilities: Verbal/Word Reading; RD-C/W = Reading Disabilities: Reading Comprehension/Word Reading.  Table 24. Means (Standard Deviations) of Total Anxiety for GLD, TRAD-LD and RD Participants G r o u  P  N  /  n  Raw Scores M (SD)  T-Scores M (SD)  GLD  83  41.05 (15.97)  51.29 (10.73)  TRAD-LD  41  39.10 (15.87)  50.15 (10.78)  RD-LW  56  40.43 (17.15)  50.59 (11.31)  RD-V/W  17  34.82 (14.34)  48.71 (10.02)  RD-C/W  6  44.17  55.00 (6.99)  (9.70)  Note: GLD = General Learning Disabilities; TRAD-LD = Traditional Learning Disabilities; RD-LW = Reading Disabilities: Low Word Reading; RD-V/W = Reading Disabilities: Verbal/Word Reading; RD-C/W = Reading Disabilities: Reading Comprehension/Word Reading.  123  Comorbidity. As expected, there was a positive relationship between depression and anxiety (r = .46, p < .01). A frequency analysis of the data from the RADS-2 and the MASC identified 3.6% (n = 3) of the GLD participants within the clinically significant range for both depression and anxiety. None of the participants identified with clinically significant comorbid symptoms met the criteria for classification as students with "traditional" learning disabilities (TRAD-LD), but two of the students met the criteria for low word reading disabilities (RD-LW). Given that prior research indicates that 25 to 50% of depressed adolescents will receive an additional diagnosis of an anxiety disorder and 10 to 15% of anxious adolescents will receive an additional diagnosis of depression (Axelson & Birmaher, 2001), it could be expected that between one and three adolescents within the total sample (GLD) would fall within the comorbid category while between zero and one adolescent within the TRAD-LD category would do the same. As a consequence, the present findings with regards to comorbidity (namely, three GLD adolescents and no TRAD-LD students) are consistent with rates indicated in the literature. The Role of Self-Efficacy in Predicting Depression and Anxiety The second research question posed in this study focused on whether anxiety and depression in adolescents with learning disabilities could be predicted on the basis of perceptions of self-efficacy. It was hypothesized that low perceptions of self-efficacy would be associated with high levels of anxiety, depression, and comorbid anxiety and depression, with academic and reading self-efficacy in particular being most strongly associated with depression and social and emotional self-efficacy being most strongly associated with anxiety.  124 Recall from Chapter 3 that the participants were asked to complete four selfefficacy measures, the Academic Self-Efficacy Questionnaire (A-SEQ), the Reading SelfEfficacy Questionnaire (R-SEQ), the Social Self-Efficacy Questionnaire (S-SEQ), and the Emotional Self-Efficacy Questionnaire (E-SEQ). An examination of intercorrelations among the variables of interest (see Table 17) revealed expected significant negative relationships between depression and academic (r - -.25, p < .05), social (r - -.35, p < .01), and emotional (r = -.39, p < .01) self-efficacy and between anxiety and social (r = -.24, p < .05), and emotional (r = -.25, p < .05) selfefficacy. Contrary to predictions, reading self-efficacy was not significantly correlated with either depression or anxiety and academic self-efficacy was not significantly correlated with anxiety. As anticipated, however, significant positive correlations were found between reading self-efficacy and all of the academic variables: word reading (r = •37/ V < - )' reading comprehension (r = .37, p < .01), spelling (r = .22, p < .05), and 01  arithmetic (r = .32, p < .01). But such relationships were not evident for academic selfefficacy. Unexpectedly, academic self-efficacy was negatively related to spelling (r = -.22, p < .05). As expected, there were also significant positive correlations among all of the domains of self-efficacy; for example, academic self-efficacy with reading (r = .44, p < .01), social (r = .55, p < .01), and emotional (r = .41, p < .01) self-efficacy, reading selfefficacy with social (r = .44, p < .01) and emotional (r = .62, p < .01) self-efficacy, and social self-efficacy with emotional self-efficacy (r = .60, p < .01). To determine the predictive relationship of self-efficacy to self-reported symptoms of depression and anxiety, regression analyses were conducted. Unfortunately, the original intent to examine the predictive power of all four domains of self-efficacy (as  125 well as the possible additional contribution of social support and life events) was thwarted. As discussed in the section on preliminary analyses, it was necessary to perform the analyses separately for males and females because of significant differences between these groups on predictor variables. And due to collinearity between emotional self-efficacy and reading self-efficacy (r = .62, p <.oi) and social self-efficacy (r = .60, p <.oi), it was necessary to exclude reading self-efficacy from the analyses and aggregate social and emotional self-efficacy into a composite variable. Three separate sets of regression analyses were conducted to predict depression, anxiety, and comorbid depression and anxiety, respectively. In each set of analyses, academic self-efficacy and social /emotional self-efficacy were entered as the only predictors. As noted above, these analyses were performed separately for males and for females, for both the total sample (GLD) and for the subset of the sample classified as having "traditional" learning disabilities (TRAD-LD). Given the small female subgroup sizes (GLD n = 24 & TRAD-LD n = 9), however, a less stringent alpha level, of 10 percent (p < .10), was accepted for these analyses so that the possibility of correctly detecting significant differences (i.e., the power of the analyses) was increased. Depression. As expected, social/emotional self-efficacy was a significant predictor of depression in the total sample (GLD) (R = .19, F (2,80) = 9.64, p <.oi). This finding 2  was statistically reliable for males and females (see Table 25). Within the smaller TRADLD sample, social/emotional self-efficacy was a significant predictor of depression in females but not in males. Contrary to expectations, academic self-efficacy did not add to the prediction of depression in any of these analyses.  126 Table 25. Regression Analysis Summary for Social /Emotional Self-Efficacy Predicting Depression t  V  -.40  -2.02  .056*  SSE/ESE  -.46  -3.87  .000***  9  SSE/ESE  -.64  -2.19  .065*  32  SSE/ESE  -.10  -.56  .583  Group  N  Predictor  GLD Females R = 0.16, F (1, 22) = 4.07, p >.05  24  SSE/ESE  GLD Males R = 0.21, F (1, 57) = 14.95, p <.01  59  TRAD-LD Females R = 0.41, F (1, 7) = 4.79, p >.05 TRAD-LD Males R = 0.01, F (1, 30) = 0.31, p >.05  2  2  2  2  Note: G L D = General Learning Disabilities; TRAD-LD = Traditional Learning Disabilities; SSE/ESE = Social and Emotional Self-Efficacy Composite *p<.10. **p< .05.***p <.01. Anxiety. The regression analyses for anxiety revealed that social/emotional selfefficacy was a significant predictor of anxiety depression when considering the entire sample (GLD) (R = .10, F (2,80) = 4.21, p <.Q5), but not for the subset of students 2  classified by more traditional criteria (TRAD-LD). Separate analyses by gender revealed that social/emotional self-efficacy was a significant predictor for females with general learning disabilities and in the expected direction for females with traditional learning disabilities. Although social/emotional self-efficacy was not a significant predictor of anxiety for males from either the total sample (GLD) or the traditional learning disabilities (TRAD-LD) subsample, a trend in the expected direction was evident for GLD males (see Table 26). Again, as was the case for depression, academic self-efficacy was not predictive of students' self-reported anxiety.  127 Table 26. Regression Analysis Summary for Social/Emotional Self-Efficacy Predicting Anxiety Group GLD Females R = 0.24, F (1, 22) = 6.81,  p  >.05  GLD Males R = 0.35, F (1, 57) = 2.08,  p  >.05  2  2  TRAD-LD Females R = 0.30, F (1, 7) = 3.06, 2  p  TRAD-LD Males R = 0.00, F (1, 30) = 0.05, 2  >.05 p  >.05  N  Predictor  J8  t  V  24  SSE/ESE  -.49  -2.61  .016*  59  SSE/ESE  -.19  -1.44  .154  9  SSE/ESE  -.55  -1.75  .124  32  SSE/ESE  .04  .22  .827  Note: GLD = General Learning Disabilities; TRAD-LD = Traditional Learning Disabilities; SSE/ESE = Social and Emotional Self-Efficacy Composite *p<.05. **p<.01. Depression and Anxiety. Additional regression analyses were conducted to examine the relative contribution of social/emotional self-efficacy to co-occurring symptoms of depression and anxiety. There were several reasons for examining depression and anxiety aggregated as a composite continuous variable. First, the selfefficacy model of depression (Bandura et al., 1999) posits that both depression and anxiety are likely negative affective outcomes for individuals with a low sense of personal self-efficacy. Second, as discussed in Chapter 2, the disorders are highly comorbid. Third, the experience of subclinical symptomatology is not a benign condition (Lewinsohn, Rohde, & Seeley, 1998). The composite variable, depression/anxiety, was constructed (by dividing the sum of each individual's T-scores by 2) and evaluated for statistical assumptions. The non-normal distribution of the composite was rectified by means of a log transformation which yielded acceptable skewness (-.23), kurtosis (1.14) and ShapiroWilk statistic (.99, p = .59).  128  The regression analyses revealed that, as expected, social/emotional self-efficacy was a significant predictor of comorbid depression/anxiety when considering the entire sample (GLD) (R = .17, F (2,80) = 7.97, p <.oi). However, contrary to prediction, 2  social/emotional self-efficacy was not a significant predictor of depression in the total subset of students classified with traditional learning disabilities (TRAD-LD). Separate analyses by gender revealed that social/emotional self-efficacy was a significant predictor of co-occurring symptoms of depression and anxiety for females and males with general learning disabilities and for females (but not males) with traditional learning disabilities (see Table 27). Again, contrary to expectations, academic selfefficacy did not add to the prediction of depression in any of these analyses. Table 27. Regression Analysis Summary for Social/Emotional Self-Efficacy Predicting Anxiety and Depression as a Composite  JL  N  Predictor  24  SSE/ESE  -.51  -2.78  59  SSE/ESE  .36  -2.87  .006**  TRAD-LD Females R = 0.46, F (1, 7) = 6.06, p >.05  9  SSE/ESE  -.68  -2.46  .043*  TRAD-LD Males R = 0.00, F (1, 30) = 0.00, p >.05  32  SSE/ESE  .00  -.01  .993  Group GLD Females  .011*  R = 0.26, F (1, 22) = 7.73, p <.05 2  GLD Males R = 0.13, F (1, 57) = 8.22, p <01 2  2  2  Note: GLD = General Learning Disabilities; TRAD-LD = Traditional Learning Disabilities; SSE/ESE = Social and Emotional Self-Efficacy Composite *p<.05.**p<.01.  129 Social Support The third question posed in this study concerned the role of social support in the relationship between self-efficacy and depression and anxiety. Recall from Chapter 3 that the participants were asked to complete the Social Support Questionnaire (SSQ) which assessed their perceptions of available support from family and friends as well as their satisfaction with this support. On the basis of previous research, it was hypothesized that students reporting high levels of support (family and friends) would report high levels of social and emotional self-efficacy and low levels of anxiety and depression. Consistent with this expectation, social support from families and satisfaction with social support were negatively correlated with depression (r = -.28, p < .01 & r - -.31, p < .01 respectively) (see Table 17). However, similar associations were not found for anxiety, and social support from friends was not significantly correlated with either depression or anxiety. Positive relationships were found between students' satisfaction with the social support they receive, and with their perceptions of self-efficacy, including academic (r = .33, p < .01) reading (r = .28, p < .01) social (r - .48, p < .01) and emotional (r = .41, p < .01) selfefficacy. However, contrary to expectations, social support from family and social support from friends were not related to self-efficacy. These findings suggest complex relationships among social support, emotional well-being, and personal self-efficacy. To examine these relationships further, separate analyses of variance for social support from family and for social support from friends were conducted with subsets of participants who reported the highest and the lowest scores on each of these variables. The "high support" and "low support" groups for each variable were constructing by  130 ranking the observations for that variable and selecting the 21 participants (i.e., 25% of the total sample) with the highest scores and the 21 participants with the lowest scores. Social Support from Family. Analyses of variance revealed significant differences between the high and low groups for depression (F (1, 40) = 13.12, p < .01), with students in the low support group reporting a significantly higher mean level of depressive symptoms (M = 48.71) and significantly lower levels of social self-efficacy (M = 49.14) than students in the high support group (means of 41.29 and 54.86 respectively). Contrary to expectations, however, there were no significant differences between the groups with regard to symptoms of anxiety and perceptions of emotional self-efficacy. In addition, there were no significant differences with respect to satisfaction with social support (see Table 28). Table 28. Comparison of Participants Reporting High and Low Levels of Social Support from Family and from Friends High M(SD)  Low M(SD)  ANOVA F (1, 40)  Depression  41.29 (4.99)  48.71 (7.96)  13.12**  .001  Anxiety  50.62 (11.02)  50.81 (12.77)  .00  •959  Social SE  54.86 (6.51)  49.14 (10.96)  4.22*  .047  Emotional SE  50.24 (8.23)  49.95 (11.43)  1.14  .292  Support Satisfaction 5-45 (-38)  5.04 (1.0)  3.20  .081  Depression  4743 (9-93)  45.76 (8.67)  •34  .566  Anxiety  50.57 (9.25)  53.14 (11.21)  .66  .422  Social SE  51.76 (10.00)  51.10 (9.27)  .05  .824  Emotional SE  45.71 (8.17)  52.19 (11.31)  4.52*  .040  5.28 (.77)  1.17  .286  Support Variable Family  Friends  Support Satisfaction 5.05 (.60) Note: SE = Self-Efficacy *p<.05.**p<.01.  V  131 Social Support from Friends. There were no significant differences between students with high perceptions of social support from friends and those with low perceptions on depression, anxiety, and social self-efficacy (see Table 28). There was a significant difference for emotional self-efficacy (F (1,40) = 4.52, p < .05), but contrary to expectations, the students reporting the highest levels of support recorded lower levels of emotional self-efficacy than those who reported the lowest levels of support from friends. Again, there were no significant differences between the high and low friend support groups for satisfaction with social support. Life Events The fourth question concerned the role of life events in the relationship between self-efficacy and depression and anxiety. Recall from Chapter 3 that the students were asked to complete the Life Events Questionnaire (LEQ). On the basis of previous research, it was hypothesized that students who reported the highest levels of negative life events would report low levels of social support (particularly from family), low levels of social and emotional self-efficacy, and high levels of anxiety and depression while students who reported the highest levels of positive life events would report high levels of social support (from family and friends), high levels of social and emotional self-efficacy and low levels of anxiety and depression. An examination of correlations among these variables revealed significant positive correlations between negative life events and both depression (r = .23, p < .05) and anxiety (r = .32, p < .01) as expected. Positive life events were not related to depression or anxiety, but were significantly correlated with satisfaction with social support (r = .34, p < .01), academic self-efficacy (r = .324, p < .05) and social self-efficacy  132 (r = .34, p < .01) suggesting links among these variables. Neutral life events were significantly correlated with only one variable, depression (r = .23, p < .05). These findings were explored further (in the same manner as for social support) by comparing subsets of participants reporting "high" and "low" levels of positive, neutral, and negative life events respectively (see Table 29). Again, each group consisted of 21 participants comprising 25% of the total sample. Negative Life Events. As expected, students reporting the highest levels of negative life events reported significantly higher levels of depression (M = 49.05) than students reporting the lowest levels of negative life events (M = 43.95) (F (1,40) = 4.31, p < .05). Contrary to expectations, however, these students did not report significantly higher anxiety or significantly lower levels of social and emotional self-efficacy. Positive Life Events. The students reporting the highest levels of positive life events did report significantly higher levels of social self-efficacy (M = 53.67) (F (1,40) = 13.47, p < .01) and satisfaction with social support (M = 5.48) (F (1,40) = 9.02, p < .01) than those who experienced low levels of positive life events (means of 44.29 and 4.80 respectively), but contrary to expectations, there were no significant differences between these groups for depression, anxiety, or emotional self-efficacy. Neutral Life Events: Despite the significant correlation between depression and neutral life events, there were no differences between the group reporting high levels and the group reporting low levels of neutral life events. This unexpected finding was explored further by comparing participants who scored above the mean and those who scored below the mean for neutral life events. Again, there were no differences between the groups. These unexpected results may well be an artifact of the lack of normalcy in  i 3 3  the distribution of neutral life events despite every attempt to rectify this challenge to assumptions by means of a transformation (see Table 16).  Table 29. Comparison of Participants Reporting High and Low Levels of Life Events Life Events  Variable  Positive  Neutral  Negative  High  Low  ANOVA F(l, 40)  V  M(SD)  M(SD)  Depression  45.24 (9.36)  48.67 (10.48)  1.35  .252  Anxiety  50.81 (10.52)  49.76 (11.23)  .10  .757  Social SE  53.67 (7.46)  44.29 (9.42)  13.47**  .001  Emotional SE  48.48 (9.85)  43.81 (10.28)  2.25  .141  Sup. Family  1.84  (1.00)  1.82  (1.21)  .09  .764  Sup. Friends  1.75  (1.10)  1.25  (1.15)  3.50  .069  Sup. Satisfaction  5.48 (0.43)  4.80  (0.89)  9.02**  .005  Depression  49.05 (10.17)  43.95 (8.90)  3.32  .076  Anxiety  49.19 (12.22)  51.38 (12.60)  .33  .570  Social SE  50.62 (9.94)  53.24 (7.04)  .76  .390  Emotional SE  47.19 (9.02)  50.10 (10.12)  .96  .332  Sup. Family  1.72 (1.00)  2.13 (1.18)  1.56  .219  Sup. Friends  1.50 (0.92)  1.08  (0.96)  3.00  .091  Sup. Satisfaction  5.25 (0.59)  5.31  (0.74)  .23  .631  Depression  49.90 (10.76)  44.10 (4.98)  4.31*  .044  Anxiety  55.19 (12.60)  48.52 (11.34)  3.25  .079  Social SE  52.05 (9.65)  52.52 (7.99)  .01  .934  Emotional SE  45.05 (11.34)  50.10  (7.09)  2.99  .091  Sup. Family  1.89 (1.05)  1.81  (1.25)  .21  .649  Sup. Friends  1.73 (1.18)  1.23  (1.00)  1.82  .185  Sup. Satisfaction  5.16 (0.71)  5.18  (0.82)  .06  .801  Note: SE = Self-Efficacy *p<.05. **p<.01.  134 Gender The role of gender was explored by means of analyses of variance (see Table 18). Contrary to expectations, males and females did not differ significantly in their reports of depression and anxiety. Nor did they differ with respect to mean levels of academic, reading and social self-efficacy. There was a difference, however, for emotional selfefficacy with females reporting significantly lower perceptions in this domain (M = 44.96) than males (M = 49.63) (F (1,81) = 4.31, p <.ofj. In contrast, females reported significantly higher perceptions of support from friends (M = 1.92) than males (M = 1.30) (F (1,81) = 5.94, p <.05). To examine gender effects further, correlations were also calculated with gender as a dichotomous variable (female coded as o, male as 1). Patterns were consistent with the findings from the group comparisons, revealing a significant positive relationship between gender and emotional self-efficacy(r = .24, p < .05) and a significant negative relationship with support from friends (r = -.26, p < .05). Again, significant relationships were not found for depression, anxiety or for the other forms of personal self-efficacy. Given that the experience of depression and anxiety by males and females has been shown to be different, especially during the adolescent period, intercorrelations among the variables of interest were also calculated as a function of gender (see Table 30). For both males and females, there was an expected positive relationship between depression and anxiety as well as an expected negative relationship between depression and social self-efficacy (r = -.32, p <.05 for males and r = -.49, p <.05 for females), but no other significant relationships with depression were evident for females. In contrast, for males, there were also significant negative relationships between depression and  135 Table 30. Intercorrelations for Depression, Anxiety, Self-Efficacy (Academic, Reading, Social & Emotional) and Social Support (Family, Friends, & Satisfaction) as a Function of Gender Variables ffi  Depression Total  Depression —  Total Anxiety Total  .47*  Academic  Anxiety Total  .46**  —  .18  .10  Reading Self-Eff.  .05  -.34  Social Self-Eff.  -.49*  Emotional Self-Eff.  Academic Self-Eff.  Reading Self-Eft  Social Self-Eft  Emotional Self-Eft  Support Family  Support Friends  Support Satisfaction  -.43**  -.05  -.33*  -.55**  -.30*  .06  -.44**  .12  -.12  -.27*  -.05  -.02  -.31*  -.13  .44**  .63**  .64**  .31*  -.15  .39**  .39  —  .57**  .46**  .21  -.16  .21  -.40  .25  .36  .74**  .19  -.03  .57**  -.29  -.54**  .30  .72**  .23  -.17  .59**  Support Family  -.35  .03  -.41*  -.21  —  -.05  .17  Support Friends  -.16  -.44*  .09  .16  .61**  .45*  -.15  —  -.06  .05  .04  .40  .16  .30  .03  -.29  Self-Eff.  Support Satisfaction  .06  —  —  .75** .16  —  -.09  —  Note. Intercorrelations for male participants (n = 59) are presented above the diagonal and intercorrelations for female participants (n = 24) are presented below the diagonal; Variables are transformed variables where applicable; Self-Eff. = Self-Efficacy *p<.05. **p<.01.  emotional self-efficacy (r = -.55, p <.oi), satisfaction with social support from family (r = -.44, p <.oi), academic self-efficacy (r = -.43, p <.oi), and support from family (r = -.30, p <.05). In the case of anxiety, males and females shared a significant negative relationship between anxiety and emotional self-efficacy, although it was stronger for females (r = .54,  p <.oi)  than for males  (r = -.27, p <.o<j). The only other significant relationships for  anxiety were with support from friends (r = -.44, p <.o^) for females and with support satisfaction (r = -.44, p <.oi) for males.  136 Given that males and females reported different patterns of intercorrelations for depression and for anxiety as well as the robust finding in the literature that depression is more prevalent among females than males, especially during older adolescence, it was entirely unexpected that there should be no difference between males and females with respect to mean levels of depression and anxiety. A significant positive relationship between age and depression (r = .25, p < .05), however, suggested that further examination of gender differences was warranted. Analyses of variance were conducted to determine whether an examination of age in concert with gender would reveal additional information concerning the relationships between gender and age on the one hand and depression, anxiety, and self-efficacy on the other. Four groups were constructed; namely, males 13-14 (n = 32), males 15-17 (n = 27), females 13-14 (n = 12) and females 15-17 (« = 12). Significant differences were not found for the groups for anxiety and self-efficacy (academic, reading, social and emotional). However, there was a significant difference for depression (F (3,79) = 3.46, p < .05). Post hoc analyses (with Bonferroni corrected alpha levels to maintain family-wise alpha at the .05 level) revealed that as a group, older males experienced more severe symptoms of depression (M = 49.48, SD = 7.04) than younger males (M = 42.81, SD = 9.37) and the difference was significant (p < .01). No significant differences were found between older and younger females or between males and females in either the younger or older groups. Reading Disabilities The sixth research question concerned the role of severity of reading disability in perceived self-efficacy and the experience of anxiety and depression. Recall from Chapter 3 that the participants completed the word reading subtest from the Wide Range  137 Achievement Test - 3rd Edition (WRAT-3) and the Gray Silent Reading Tests (GSRT). The students' scores from these measures as well as their cognitive and verbal ability results from their most recent psychoeducational assessment were used in the analyses addressing this research question. Several hypotheses were posed with regard to reading disabilities. First, adopting the functional skills assessment approach to the identification of reading disabilities and the operational definition utilized by Siegel and her associates (e.g., McBride & Siegel, 1997), it was hypothesized that within the sample of students with general learning disabilities, students with low word reading skills (at or below the 25th percentile) (RDLW, n = 25) would report lower levels of self-efficacy (especially academic and reading self-efficacy) and higher levels of anxiety and depression than students with stronger word reading skills (specifically at or above the 30th percentile) (n = 56). Note, only two students did not fall into one of the two categories, both having word reading skills at the 27th percentile. Only one component of this first hypothesis, was supported by the data (see Table 31). Students with low word reading abilities had lower perceptions of their reading self-efficacy (M = 44.64) than students with "normal" reading abilities (that is, at or above the 30th percentile) (M = 54.08) and the difference was significant (F (1, 79) = 18.13, v < .01). In addition to word reading skills, reading comprehension skills are critical during the secondary years. As a consequence, additional exploratory analyses of variance were conducted to ascertain whether within the sample of students with general learning disabilities, students with low reading comprehension skills (at or below the 25th percentile) (n = 56) would report lower levels of self-efficacy (especially  i8 3  Table 31. Comparison of Participants with Low Word Reading Skills and Normal Word Reading Skills on Depression, Anxiety and Self-Efficacy Low Word Reading n = 56 M(SD)  Normal Word Reading rc = 25 M(SD)  ANOVA F (1, 79)  Depression  45.23 (8.14)  46.96 (8.60)  .82  .368  Anxiety  50.59 (11.31)  52.08 (9.50)  .33  .567  Academic SE  42.34 (9.50)  44.00 (10.13)  .51  .478  Reading SE  44.64 (9.86)  54.08 (7.52)  18.13**  .000  Social SE  51.55 (8.50)  51.84 (7.32)  .00  .959  Emotional SE  48.13 (9.62)  49.72 (8.19)  .52  .474  Variable  V  Note: SE = Self-Efficacy; Low Word Reading = WRAT-3 Word Reading score < 25th percentile; Normal Word Reading = WRAT-3 Word Reading score > 30th percentile *p<.05.**p<.01. academic and reading self-efficacy) and higher levels of anxiety and depression than students with stronger reading comprehension skills (specifically at or above the 30th percentile) (n = 26). Only one student did not fall within one of these two categories. As was found in the comparison of students with "low" and "normal" word reading skills, the only significant difference between groups was on reading self-efficacy (F (1,80) = 4.52, p < .05). And, as might be expected, the mean reading self-efficacy of students with "low" reading comprehension skills was lower (M = 45.52, SD - 10.23) than that of students with "normal" reading comprehension skills (M = 50.62, SD = 9.82). Second, taking the aptitude-achievement discrepancy approach to reading disabilities utilized by the B.C. Ministry of Education to determine which students would be afforded a reader for provincial examinations, it was hypothesized that within the sample of students with general learning disabilities those who presented  139 with a significant discrepancy (of 1.3 standard deviations or more) between their verbal ability and their word reading skills (RD-V/W) would report lower levels of selfefficacy (especially academic and reading self-efficacy) and higher levels of depression and anxiety than students without such discrepancies within the total sample (GLD). This second hypothesis was not upheld (see Table 32). The only significant difference between these groups was on emotional self-efficacy (F (1, 81) = 8.20, p <.oi), and contrary to predictions, students with discrepancies between their verbal ability and their word reading skills had higher self-perceptions in this domain (M = 58.50) than students without such discrepancies (M = 47.48). Table 32. Comparison of Verbal Ability/Word Reading Discrepant Readers with All Other GLD Participants on Depression, Anxiety and Self-Efficacy Variable  RD-VAV Participants n = 17 M(SD)  Rem. GLD Participants n = 66 M(SD)  ANOVA F(l, 81)  Depression  42.82 (7.03)  47.09 (9.06)  3.43  .068  Anxiety  48.71 (10.02)  51.90 (10.88)  1.24  .268  Academic SE  44.29 (9.33)  41.98 (10.04)  .74  .394  Reading SE  48.35 (11.59)  46.91 (9.99)  .26  .609  Social SE  52.94 (8.04)  50.68 (8.83)  .92  .341  Emotional SE  54.76 (8.49)  46.61 (9.03)  11.29**  .001  Note: SE = Self-Efficacy; Rem. GLD = Participants remaining in the GLD sample. *p<.05.**p<.01. Finally, taking another aptitude-achievement discrepancy approach to reading disabilities (proposed by this researcher on the basis of observed distress in this population), it was hypothesized that within the sample of students with general learning disabilities those who presented with a significant discrepancy (of 1.3 standard  140 deviations or more) between their reading comprehension skills and their word reading skills (RD-C/W) would report lower levels of self-efficacy (especially academic and reading self-efficacy) and higher levels of anxiety and depression than students without such discrepancies within the total GLD sample. It was difficult to examine this hypothesis with confidence because the number of students in the R D - C / W category (n= 6) was too low to permit robust group-based comparisons. Nevertheless, results indicated that the hypothesis was not upheld (see Table 33). Again, the only significant difference between the R D - C / W group and the remaining GLD participants was on emotional self-efficacy (F (1,81) = 8.20, p <.oi), and again contrary to expectations, students with discrepant reading skills reading had higher self-perceptions in this domain (M = 58.50) than students without such discrepancies (M = 47.48). Table 33. Comparison of Reading Comprehension/Word Reading Discrepant Readers with All Other GLD Participants on Depression. Anxiety and Self-Efficacy RD-CAV Participants n=6 M(SD)  Rem. GLD Participants n = 77 M(SD)  Depression  44.33 (5.24)  46.36 (9.04)  .19  .668  Anxiety  55.00 (6.99)  51.00 (10.94)  .77  .382  Academic SE  47.33 (9.54)  42.08 (9.87)  1.58  .212  Reading SE  50.83 (9.91)  46.92 (10.31)  .80  .372  Social SE  55.83 (5.19)  50.78 (8.80)  1.89  .173  Emotional SE  58.50 (8.09)  47.48 (9.14)  8.20**  .005  Variable  ANOVA F (1, 81)  Note: SE = Self-Efficacy; Rem. GLD = Participants remaining in the GLD sample. *p<.05.**p<.01.  V  141 The finding that participants with discrepant reading abilities, both R D - V / W and RD-C/W, should report higher emotional self-efficacy than remaining participants in the total sample (GLD) was an unexpected finding. As a result, exploratory analyses were conducted to examine similarities and differences across a wider range of variables. Given that four of the six R D - C / W participants were also classified as RDV / W , the two groups were aggregated into a composite, RD-DIS (n - 19), for the purpose of these analyses. Analyses of variance comparing the composite group, RD-DIS, with all remaining GLD participants revealed a number of significant differences between the two groups (see Table 34). First, as expected, the groups differed significantly with respect to emotional self-efficacy, with RD-DIS participants reporting a higher mean score (M = 54.37, SD = 8.09) than the remaining GLD participants (M = 46.47, SD = 9.14). Although the groups were not significantly different with regards to mean levels of social selfefficacy, they did differ significantly on a composite of emotional and social self-efficacy with RD-DIS participants reporting a higher mean score (M = 53.53, SD = 7.41) than the remaining GLD participants (M = 48.58, SD = 8.30). Second, the two groups were significantly different with respect to their experience of negative life events. The RD-DIS group reported a lower incidence of negative life events (M = 1.53, SD = 1.43) than the remaining G L D participants (M = 3.02, SD = 2.88). Third, the two groups differed significantly with regards to aptitude for learning and skill development in word reading (although not reading comprehension) and spelling. As a group, the RD-DIS participants scored higher on general cognitive ability  142 Table 34. Comparison of Discrepant Readers (RD-DIS) with All Remaining G L D Participants Variables Age  RD-DIS Participants n = 19 (19 M, 0 F)  Rem. GLD Participants n = 64 (40 M, 24 F)  M (SD)  M (SD)  ANOVA F (1, 81)  V  14.21 (1.08)  14.48 (1.18)  0.82  .369  Cognitive Ability  103.58 (9.13)  92.64 (12.36)  12.77**  .001  Verbal Ability  103.29 (12.27)  89.05 (15.08)  12.67**  .001  Word Reading  78.42 (9.64)  89.95 (12.02)  14.65**  .000  Reading Comp.  85.42 (17.36)  81.39 (16.69)  0.84  .362  Spelling  73.63 (8.11)  86.55 (12.15)  18.88**  .000  Arithmetic  81.37 (12.51)  80.06 (12.74)  0.16  .695  Depression  43.16 (6.83)  47.13 (9.17)  3.07  .084  Dysphoria  41.53 (6.89)  44.59 (9.21)  1.80  .183  Anhedonia  48.21 (7.93)  50.95 (7.63)  1.86  .176  Neg. Self-Evaluation  44.95 (6.32)  48.31 (9.82)  1.98  .164  Somatic Complaints  43.68 (8.56)  46.97 (10.73)  1.49  .225  49.53 (9.77)  51.81 (11.01)  0.66  .418  Physical Symptoms  51.47 (10.07)  49.72  (8.02)  0.62  .433  Social Anxiety  52.00 (8.88)  55.73 (11.93)  1.59  .210  Depression & Anxiety  46.34 (6.60)  49.47 (8.74)  1.88  .174  Academic SE  43.84 (8.91)  42.05 (10.19)  0.48  .491  Reacting SE  48.05 (11.06)  46.95 (10.11)  0.17  .685  Social SE  52.68 (7.62)  50.69  0.69  .408  Emotional SE  54.37 (8.09)  46.47 (9.14)  11.50**  .001  Social & Emotional SE  53.53 (7.41)  48.58  (8.30)  6.04*  .016  Social Sup. (Family)  1.67 (0.93)  2.17  (1.18)  2.83  .097  Social Sup. (Friends)  1.11 (0.85)  1.59  (1.13)  1.96  .165  Satisfaction (Soc. Sup.)  5.23 (0.62)  5.15  (0.70)  0.15  .701  Positive Life Events  4.47 (2.67)  4.48  (2.39)  0.10  .920  Neutral Life Events  2.58 (1.77)  2.22  (2.21)  1.44  .234  Negative Life Events  1.53 (1.43)  3.02  (2.88)  4.39*  .039  1  Anxiety  (8.97)  Note: RD-DIS = Composite group of RD-VAV and RD-CAV readers; SE = Self-Efficacy; Rem. G L D = Participants remaining in the G L D sample; Verbal Ability = VIQ scores for the participants whose most recent psychoeducational assessment utilized the WISC-III (RD-DIS n = 17 & Rem G L D n = 58).  *p<.05. **p<.01.  143 and verbal ability (M = 103.58, SD = 9.13 and M = 103.29, SD = 12.27 respectively) than the remaining GLD participants (M = 92.64, SD = 12.36 and M = 89.05, SD = 15.08). In contrast, however, the RD-DIS group achieved lower mean scores on word reading and spelling (M = 78.42, SD = 9.64 and M = 73.63, SD = 8.11 respectively) than the remaining GLD participants (M = 89.95, SD = 12.02 and M = 86.55, SD = 12.15). Finally, the difference between the two groups on depression (F (1, 81) = 3.07, p < .08) was marked with the RD-DIS group reporting a lower mean depression (M = 43.16, SD = 6.83) than the remaining GLD participants (M = 47.13, SD = 9.17). It is important to note, however, that the RD-DIS group was comprised of males entirely whereas the comparison group, all other GLD participants, consisted of 40 males and 24 females. In order to assess whether gender was a significant factor in the apparent differences between the groups, another set of analyses of variance were conducted comparing the RD-DIS group (n = 19) with the males from the remnant GLD sample (n = 40). Apart from negative life events (on which the significance of the difference increased to an alpha level of .06), the pattern and direction of significant differences between the two groups remained constant with the RD-DIS group scoring higher on aptitude (cognitive and verbal ability) and emotional and social-emotional self-efficacy but lower on skill development in word reading and spelling than the remaining males in the GLD sample. And again, using less stringent criteria (p < .10), there was significant difference between the two groups on depression with a mean score of 43.16 (SD = 6.83) for RD-DIS males and a mean score of 47.15 (SD = 9.37) for the males remaining in the GLD group (see Table 35).  144 Table 35. Comparison of Discrepant Readers (RD-DIS) with Remaining Male G L D Participants RD-DIS Participants n = 19 (19 M)  Rem. Male G L D Participants n = 40(40M)  M (SD)  M (SD)  Cognitive Ability  103.58 (9.13)  95.10 (12.85)  6.65*  .013  Verbal Ability  1  103.29 (12.27)  92.19 (15.71)  6.57*  .013  Word Reading  78.42 (9.64)  92.18 (12.68)  17.49**  .000  Spelling  73.63 (8.11)  87.63 (12.80)  18.98**  .000  Depression  43.16 (6.83)  47.15 (9.37)  2.72  .104  Anxiety  49.53 (9.77)  51.98 (9.76)  0.81  .372  Depression & Anxiety  46.34 (6.60)  49.56 (8.24)  2.03  .160  Social SE  52.68 (7.62)  48.95 (9.14)  2.38  .128  Emotional SE  54.37 (8.09)  47.38 (9.61)  7.52**  .008  Social & Emotional SE  53.53 (7.41)  48.16 (8.75)  5.76*  .020  Negative Life Events  1.53 (1.43)  2.85 (2.64)  3.60  .063  Variables  ANOVA F (1, 57)  V  Note: RD-DIS = Composite group of RD-V/W and RD-C/W readers; SE = Self-Efficacy; Rem. G L D = Participants remaining in the G L D sample; Verbal Ability = VIQ scores for the participants whose most recent psychoeducational assessment utilized the WISC-III (RD-DIS n = 17 & Rem Male G L D n = 36).  *p<.05.**p<.01. Factors Associated with the Experience of Depression and Anxiety The seventh and final question of the study focused on ascertaining whether there were patterns of factors associated with the experience of anxiety and depression in adolescents with learning and reading disabilities. Specifically it was hypothesized that there would be significant differences between students who reported high levels of symptoms of both depression and anxiety and those who reported low levels of both symptoms with regards to perceptions of self-efficacy and social support, experience of life events, and reading achievement. To address this hypothesis, the participants were ranked as before (question 2) on the basis of their composite depression and anxiety  145 score. Again, the 21 highest scoring and the 21 lowest scoring participants were selected for study. These groups each comprised 25% of the total sample. Analyses of variance demonstrated that there were significant differences between these two groups on age (F (1,40) = 4.40, p < .05), emotional self-efficacy (F (1, 40) = 7.45, p < .01), satisfaction with perceived social support (F (1,40) = 4.57, p < .05), and experience of negative life events (F (1,40) = 6.65, p < .05). And, as would be expected given the manner in which the groups were constructed, there were also significant differences between the groups on depression (F (1,40) = 84.91, p < .01), the majority of the depression subscales, anxiety (F (1,40) = 144.89, p < .01), the two anxiety subscales (physical symptoms and social anxiety), and the composite of depression and anxiety (F (1,40) = 283.89, p < .01). A n examination of group means revealed that the most depressed /anxious participants were slightly older, perceived themselves to be less efficacious emotionally, were less satisfied with the social support available to them, and experienced more negative life events than the least depressed/anxious participants (see Table 36). An examination of the demographic information provided by the participants in the two groups revealed equal numbers of males and females and equal numbers of students describing themselves as White and Native Canadian, reporting their country of birth as Canada, and reporting involvement in extra-curricular activities at school. There were some differences between the two groups, however, on the remaining variables. For example, more of the students reporting the highest scores for depression and anxiety spoke languages other than English at home (namely, Cantonese, Polish, Somali), lived with two biological parents, had parents who did not complete high school, were not involved in extra-curricular activities in the community, and did not  146 Table 36. Comparison of Participants Reporting the Highest and Lowest Levels of Depression / Anxiety on Measured Variables High M (SD)  Low M(SD)  Depression/Anxiety  59.67 (6.03)  39.05 (2.33)  283.89**  .000  Depression  55.71 (8.59)  38.76 (3.97)  84.91**  .000  Dysphoric Mood  53.14 (8.39)  36.62 (4.27)  64.66**  .000  Anhedonia/Negative Affect  54.00 (8.49)  49.90 (7.33)  2.80  .102  Negative Self-Evaluation  56.67 (10.50)  41.48 (4.07)  38.22**  .000  Somatic Complaints  52.10 (7.67)  37.29 (5.47)  51.92**  .000  63.62 (7.47)  39.33 (5.45)  144.89**  .000  Physical Symptoms  57.86 (8.75)  43.19 (5.17)  43.73**  .000  Social Anxiety  66.48 (9.40)  43.38 (6.15)  88.82**  .000  Age  14.76 (1.18)  14.05 (1.02)  4.40*  .042  Cognitive Ability  90.71 (13.84)  94.86 (14.24)  .91  .345  Word Reading  88.33 (13.95)  83.52 (9.91)  1.67  .205  Reading Comprehension  81.57 (17.08)  80.33 (15.09)  .06  .805  Spelling  86.05 (13.80)  79.19 (9.37)  3.55  .067  Arithmetic  79.76 (13.21)  83.95 (13.17)  1.06  .309  Academic Self-Efficacy  41.57 (13.71)  43.62 (8.78)  .33  .567  Reading Self-Efficacy  46.81 (12.15)  46.33 (9.96)  .02  .890  Social Self-Efficacy  46.95 (10.68)  51.95 (7.61)  2.77  .104  Emotional Self-Efficacy  42.95 (12.09)  51.24 (6.88)  7.45**  .009  Social Support from Family  1.69 (.74)  2.38 (1.48)  1.70  .200  Social Support from Friends  1.34 (1.22)  1.57 (1.13)  .59  .449  Satisfaction (Soc. Sup.)  4.87 (.71)  5.30 (.55)  4.57*  .039  Positive Life Events  4.33 (2.18)  4.52 (2.58)  .02  .884  Neutral Life Events  2.38 (2.78)  2.29 (2.19)  .02  .903  Negative Life Events  3.81 (3.44)  1.62 (1.56)  6.65*  .014  Variable  Anxiety  Note: n = 21 in both the High and Low Anxiety/Depression groups. *p<.05.**p<.01.  ANOVA F (1, 40)  V  H7 have paid after-school jobs in comparison with the students who reported the lowest scores for depression and anxiety. But Chi-square analyses revealed that these differences were not statistically significant (see Table 37). Summary of Findings The present study extended previous research examining the links between selfefficacy on the one hand and depression and anxiety on the other by focusing on a population widely thought to be at particular risk for developing such symptomatology. The study also examined a subset of the sample, adolescents with particular difficulties in the high salient academic skill area of reading and included an examination of two factors known to act as risk or protective factors in the development of depression; namely, social support and experience of negative life events. Prevalence and Severity of Depression and Anxiety. Contrary to expectations, the prevalence and mean severity of symptoms of depression, anxiety and comorbid depression and anxiety of students with learning and reading disabilities were not higher than has been reported in the literature for normal adolescents. Further, the prevalence rate and mean severity of depression were considerably lower than has been reported in previous studies of students with learning disabilities. Also contrary to expectation, females did not report higher rates or more severe symptoms of either depression or anxiety than males. The Role of Self-Efficacy in Predicting Depression and Anxiety. As discussed, the planned examination of the predictive power of self-efficacy across all four domains (academic, reading, social and emotional) by means of regression analyses was thwarted by collinearity among variables and the small number of females within the  148  Table 37. Comparison of Participants Reporting the Highest and Lowest Levels of Depression and Anxiety on Demographic Variables Highest  Lowest  n = 21  n = 21  Male Female  15 6  15 6  0.00  1.000  White Asian Black Native  17 3 0 1  17 1 2 1  3.00  .392  First Language  English Other  18 3  20 1  1.11  .293  Country of Birth  Canada Other  20 1  20 1  0.00  1.00  Two Biological Parents  14  11  Guardian(s)  One Biological Parent Biological & Step-Parent Foster Parents/Other  3 3 1  5 5 0  2.36  .501  2  Number of Siblings  None One Two Three Four Five Seven  2 11 2 3 2 0 1  5.79  .448  Incomplete High School High School Graduate  3 11  11  College Graduate Undergraduate degree Graduate degree Unknown  3 2 0 2  4 2 2 1  3.48  .627  Incomplete High School  4  2  Father's  High School Graduate College Graduate  11 4  8 6  Education  Undergraduate degree  0  1  3.21  .668  Graduate degree  1  2  Unknown  1  2 0.47  .495  Variable  Categories  Gender  Ethnicity/ Cultural Heritage  Parent(s)/  Mother's Education  8 7 2 1 1 0  X  2  V  1  Involved  8  8  (School)  Not Involved  13  13  Extra-Curricular  Involved Not Involved  10 11  14 7  1.56  .212  Paid Job No Paid Job  5 16  7 14  0.47  .495  Extra-Curricular  (Community) After-School Employment  149 sample. Nonetheless, by examining the results of simple regression analyses in conjunction with a comparison of participants reporting high and low levels of symptomatology as well as correlations among the variables of interest, several conclusions could be drawn. Contrary to expectation, neither academic nor reading selfefficacy was a strong predictor of depression or anxiety in students with learning disabilities. In contrast, taken together, social and emotional self-efficacy were stronger predictors, particularly of depression in males and anxiety in females. Further, emotional self-efficacy reliably distinguished students reporting high levels of depression and anxiety from those reporting low levels of these symptoms. Social Support. It was expected that social support would appear to be acting as a buffer against the development of negative affective outcomes for students with learning disabilities. Although there was a significant negative relationship between depression and social support from family (and social support from family reliably distinguished between students reporting the highest and lowest levels of depression as well as of co-occurring depression and anxiety), there was no such relationship for social support from friends. Further, a paired-samples t-test indicated that there was a significant difference between social support from family and social support from friends (t (82) = 3.45, p < .01). Neither social support from family nor social support from friends was significantly associated with anxiety. Nonetheless, satisfaction with social support was a reliable distinguishing factor between students reporting the highest levels and the lowest levels of co-occurring symptoms of anxiety and depression. Life Events. It was expected that the experience of high levels of negative life events would be a risk factor for the development of negative affective outcomes for students with learning disabilities. Indeed, students who reported the highest incidence  150 of negative life events reported significantly higher mean levels of depression than those who experienced the lowest incidence of such events and this factor reliably distinguished between students reporting the highest and the lowest levels of cooccurring symptoms of anxiety and depression. Reading Disabilities. As might be expected, students with low word reading skills reported lower levels of reading self-efficacy than students with "normal" word reading skills within the GLD sample, but there was no difference in their reported experience of depression and anxiety. And contrary to expectations, students with significant discrepancies (between verbal ability and word reading skills and between comprehension abilities and word reading skills) did not report higher levels of anxiety or lower levels of self-efficacy (academic, reading, and social) than students in the GLD sample without such discrepancies. There were, however, significant differences in their perceptions of emotional self-efficacy with discrepant readers reporting higher mean levels of emotional self-efficacy than their non-discrepant peers. Further, using a less stringent alpha level (p < .10) which is acceptable given the small sample size of the reading discrepant group (RD-DIS n = 19), there was a significant difference in depressive symptoms with the discrepant readers reporting lower mean levels of symptomatology than their non-discrepant peers. Finally, the discrepant readers reported significantly fewer negative life events than students in the GLD sample without such discrepancies. Anxiety and Depression. The factors that reliably distinguished the subsample of students reporting the highest levels of depression and anxiety from the subsample of students reporting the lowest levels of these symptoms were age, emotional selfefficacy, satisfaction with social support and reported experience of negative life events.  i5i  Taken together, the results of the present study suggest that the prevalence and severity of clinically significant depression and anxiety among adolescents with learning disabilities and reading disabilities is not much different from the estimates of these symptoms within the general adolescent population. Further, the results indicate that the relationship between depression and anxiety on the one hand and self-efficacy on the other is stronger for the affective domain (social and emotional self-efficacy) than for the academic domain (academic and reading self-efficacy) among adolescents with learning disabilities. Similarly, social-emotional considerations (e.g., satisfaction with social support and experience of negative life events) are more strongly associated with these adolescents' symptoms of depression and anxiety than academic considerations (e.g., skill development in reading). Further discussion of these findings and their implications are presented in Chapter 5.  152 Chapter 5 DISCUSSION Depression is a serious health problem that increases dramatically in prevalence during adolescence (Hankin et al., 1998; Lewinsohn, Rohde, et al., 1993; Reynolds, 1994b). Adolescents with learning disabilities are of particular concern to parents, medical professionals, and educators for many believe that these students are at special risk for developing depression and anxiety (Bender et al., 1999; Gorman, 1999; WrightStrawderman et al., 1996). Empirical studies, however, are few and findings are equivocal. A recent and informative approach to the study of depression is the self-efficacy model of depression, based on the self-efficacy component of social cognitive theory (Bandura, 1994). The model, which posits that personal inefficacy (e.g., in social and academic domains) plays both a direct and a mediating role (e.g., through social behaviour and academic achievement) in the development of depression and anxiety, has received considerable support in studies of children and adolescents from the general school population (Bandura et al., 1999; Ehrenberg et al., 1991; McFarlane et al., 1994; McFarlane et al., 1995; Muris, 2002; Muris et al., 2001) The present study has extended the work of these researchers by focusing upon a specific adolescent population. By examining students with learning disabilities, especially those with particular difficulties in the highly salient area of reading, this study has been able to assess the utility of the self-efficacy model of depression with a sample from a special population and to supply information about the prevalence and severity of depression and anxiety within this particular sample. In addition, this study has expanded the self-efficacy model by including an examination of a specific  153 academic domain (reading) and by accounting for two factors (social support and life events) robustly associated with the development and maintenance of depression and anxiety. Participants in the study were 83 adolescents, aged 13 to 17 years of age enrolled in public schools in British Columbia. All of the participants were volunteers and all were currently receiving regularly scheduled periods of special education support on the basis of their school identification as students with learning disabilities. The participants completed measures which assessed their academic skills (including word reading and reading comprehension skills), their experience of symptoms of depression and anxiety, their perceptions of self-efficacy (academic, reading, social and emotional), their perceptions of social support (from family and friends) and their satisfaction with this support, as well as their experience of significant life events (construed to be positive, neutral or negative). Information concerning the participants' measured cognitive abilities was obtained (with informed written parental permission) from the students' confidential school files. The data yielded by these measures were analyzed (a) to evaluate the students in relationship to learning and reading disability criteria, (b) to calculate prevalence and severity of symptoms of depression and anxiety, (c) to examine the predictive role of self-efficacy to self-reported symptoms of depression and anxiety, (d) to evaluate the significance of social support and life events in students' experience, and (e) to ascertain which factors most clearly distinguished between students reporting high levels of depression and anxiety and those reporting low levels of symptomatology. Findings related to the research questions posed in this study are presented in the remaining portion of this chapter along with explanations for convergence and/or  154 divergence from the literature. The chapter concludes by providing an analysis of the strengths and limitations of the present study and presenting implications for future research. Prevalence and Severity of Depression and Anxiety Results of the present study indicated that for this particular sample of adolescents, the prevalence and mean severity of symptoms of depression was lower than has been reported generally for both normal adolescents and for adolescents with learning disabilities. Previous studies that utilized the RADS-2 to evaluate adolescents from the general population have obtained point-prevalence rates for clinically significant depressive symptoms within the 8 to 18% range with mean symptom severity within the 55 to 62 (T-score) range. Typically, mean scores for females in these studies been somewhat higher, in the range of 58 to 63. The present results, a pointprevalence rate of 6% (with 0% for adolescents with traditional learning disabilities) is considerably lower than previously reported. And with mean T-scores of 45 and 47, for males and females respectively, mean symptom levels also are lower and do not reflect the significant gender difference that is typically found during the adolescent period. With regard to the experience of anxiety, present results are largely comparable with previous findings. Previous studies that have utilized the MASC to evaluate adolescents from the general population have obtained prevalence rates in the 7 to 13% range with mean total scores (raw scores) in the range of 30 to 33 for males and 35 to 43 for females. While the present prevalence rate of 10.8% is within the range for normal adolescents, the obtained mean scores of 39 for males and 47 for females are somewhat higher. The magnitude of the difference, however, appears to be comparable to the  *55  differences reported in studies that have compared adolescents with and without learning disabilities on other measures of anxiety. A greater degree of specificity is unattainable because no studies of adolescents with learning disabilities that utilized the MASC were located. With regard to comorbidity of clinically significant symptoms of depression and anxiety, the present rate of 3.6% was consistent with previous research (Axelson & Birmaher, 2001). Despite concerns about methodological inconsistencies in the literature (as discussed at length in Chapter 2), the discrepancy in rates of prevalence and severity of depressive symptoms between the present study and previous studies of adolescents is marked. Why would anxiety rates be largely comparable but depression rates so much lower? A likely explanation is the nature of the sample under study. First, all of the participants in the present study were currently attending school. Given that a number of special education teachers had mentioned to this researcher that several students with identified learning disabilities were not attending school during the period of the study due to severe social-emotional difficulties, it is quite possible that the sample did not include students experiencing a full range of depressive symptomatology. Attenuation has been described as a common problem faced by researchers when examining psychopathology in a school-based sample (Offer & Schonert-Reichl, 1992). Second, all of the participants were receiving regularly scheduled periods of special education support. The receipt of such support entails parental permission and typically, the involvement of the parents and the student in regular Individual Education Plan (IEP) meetings. As a result, it is possible that many of these students were enjoying the protective benefit of complementary academic and social support  i 6 5  from their teachers and their parents (Christenson, 2004), a factor which might well have been acting to reduce potential stress (including that of academic failure) and to enhance the students' feelings of well-being. In contrast, students identified with learning disabilities who were not currently receiving support (and who were necessarily excluded from the study due to concerns about students missing time from academic classes) may have been feeling more vulnerable, may have been experiencing greater academic failure, and may have reported higher levels of depressive symptoms than their supported peers. Third, all of the students in the present study were volunteers who, along with their parents and teachers, knew that the study was examining social-emotional functioning including depression. It is conceivable that some students (of their own accord or at their parents' suggestion) may have chosen not to participate in the study because of their experiences with symptoms of depression. Again, this would have resulted in attenuation of the present sample. In contrast, the experience of symptoms of anxiety may be regarded as more normative, and students suffering from these symptoms may have been less uncomfortable about (or not discouraged from) participating in the study. Clearly, research with a more widely-representative sample of adolescents with learning disabilities is needed to clarify prevalence and severity of depressive symptoms in this population. With regard to gender, it is possible that the present study failed to detect expected differences between males and females in prevalence and severity of depression due to the small number of females in the study. Recruiting equal numbers of males and females with learning disabilities has been a continuing challenge for  157 researchers in the field (see Tables 6 and 8). Females have long been under-identified with learning disabilities (Lerner, 2000). The Relationship of Self-Efficacy to Depression and Anxiety As previously discussed, the planned examination of the predictive power of selfefficacy across all four domains of self-efficacy (academic, reading, social and emotional) by means of regression analyses was thwarted by collinearity among several of the predictor variables and by the small number of females within the sample. As noted by Hair et al. (1998, p. 164) only simple regression with a single independent variable is appropriate for small samples where there are 20 or fewer observations. In the present study, there were only 24 females in the total sample and 9 females within the subset of students classified with traditional learning disabilities. Nonetheless, an examination of the correlation coefficients between the variables under study reveals relationships that are consistent in direction with previous research (see Table 38) and consistent with the basic tenets of Bandura's self-efficacy model of depression and anxiety (Bandura, 1986; Bandura et al., 1999).  Table 38. Correlations between Depression and Self-Efficacy in Present and Previous Studies S-SE  A-SE  Age Group  N  McFarlane et al. (1994,1995)  17.1 yrs (M)  682  -0.22**  Ehrenberg et al. (1991)  14 -18 yrs  366  -0.28  -0.60**  Bandura et al. (1999)  11.5 yrs (M)  282  -0.30**  -0.43**  Muris (2002)  12 -19 yrs  596  -0.37*  -0.41*  Study  E-SE  R-SE  -0.57*  -0.39** -0.11 -0.25* -0.35** 83 13 -17 yrs Present Study Note: S-SE = Social Self-Efficacy; A-SE = Academic Self-Efficacy; E-SE = Emotional Self-Efficacy; R-SE = Reading Self-Efficacy. *p<.05, **p<.01  i 8 5  With further regard to correlations among the variables under study, results indicated important differences between males and females in the patterns of relationships among depression, anxiety, self-efficacy, social support, and satisfaction with social support (see Table 30). Although the males and females in this sample shared strong negative relationships between depression and social self-efficacy and between anxiety and emotional self-efficacy, they differed with regard to other factors related to psychological distress. For males, perceptions of self-efficacy in the academic domain, support of family, and satisfaction with available social support were salient. While these factors were not significant for females, social support from friends was of critical importance. Although additional research is required to fully explore these gender differences, the present findings suggest that interventions for male and female adolescents with learning disabilities may need to be differentiated. For example, males may well need targeted interventions that are designed to build not only their academic learning skills but their perceptions of academic competence as well while females may need explicit instruction and assistance in developing supportive social relationships. Finally, the relatively weak negative relationships between depression and both academic and reading self-efficacy are of great interest. With regard to academic selfefficacy, previous studies with children and adolescents from the general population (Ehrenberg et al., 1991; Bandura et al., 1999; Muris, 2002) have obtained stronger negative correlation coefficients (-0.41 to -0.60). While the present result (-0.25) may be a function of the considerably smaller sample size (see Table 38), two additional possibilities are offered for consideration. First, the participants may be over-estimating their academic skills and, as a result, they may have reported higher perceptions of their academic and reading self-  *59  efficacy than perhaps is warranted, thus weakening the negative relationship with symptoms of depression. Certainly, previous studies (e.g., Meltzer, Roditi, Houser, & Perlman, 1998; Stone & May, 2002) have found that in comparison with normally achieving adolescents, those with learning disabilities have overestimated their academic skills and abilities. Further to this, studies that have specifically examined "calibration," the degree of congruence between students' actual performance and their perceptions of self-efficacy in specific academic domains, have generally found that even though students with learning disabilities have lower skills than their normally achieving peers, they tend to report similar levels of self-efficacy (see review by Klassen, 2002). Of particular relevance to the present study is Pintrich, Anderman, and Klobucar's (1994) examination of calibration in regard to reading comprehension skills. In this study of grade 5 students, those with learning disabilities reported similar levels of self-efficacy (as well as intrinsic orientation and anxiety) to the normally achieving students despite significantly lower skills. A second possibility is that the present sample of adolescents had legitimate reasons to feel efficacious with regard to reading and meeting general academic requirements. Given that the majority of these students had likely been identified as having learning disabilities at an early age (recall that more than 47% of the students had completed a psychoeducational assessment during the primary grades and a further 42% during their intermediate years), and were currently being supported in their secondary years, it is possible that many of these students had in fact been afforded special education supports (and possibly considerable parental support) for much of their schooling. As a consequence, many of these students may well have been the recipients of additional instruction and practice, more manageable learning tasks,  i6o  more individualized feedback, more specific instruction in study skills, and adapted assignments and examinations. As a consequence, these students would likely be more motivated, more engaged in learning, and more confident in their abilities to be successful (i.e., efficacious) than their less well-supported peers. Such contextual factors (including emotional and social support) have been described as "enablers" of academic achievement (Christenson & Anderson, 2002; Di Perna, Volpe, & Elliott, 2002). Unfortunately, information concerning the students' past educational history as well as their current academic achievement (in the form of course grades) was not obtained. But the finding of lower than expected correlations between depression and self-efficacy in academic domains (general and reading) indicates that future investigations would be enriched by accounting for the possible influence of such contextual factors. Social Support and Life Events Although the present study found a significant negative relationship between depression and social support from family (and social support from family reliably distinguished between students reporting the highest and lowest levels of depression and co-occurring depression and anxiety), there was no such relationship for social support from friends. Further, level of social support from family was significantly greater than the level of social support from friends (t (82) = 3.45, p < .01). That the participants perceived themselves to have greater available support from family than from friends is consistent with the findings of Geisthardt and Munsch (1996). In their study of early adolescents with and without learning disabilities, these researchers found that although the two groups of students were alike in the number of family members and non-related adults named as social supports, students with learning  i6i  disabilities named significantly fewer friends as individuals that they thought they could access for academic and interpersonal support. In a similar vein, Sabornie (1994) and Margalit and Levin-Alyagon (1994) found that adolescents with learning disabilities reported that they were lonelier than their peers without learning disabilities. Additional research examining relationships among depression and anxiety, perceptions of social and emotional self-efficacy, and received as well as perceived support would provide important information about the role of social support in the experience of adolescents with learning disabilities. Consistent with previous research, the students who reported the highest levels of negative life events also reported higher mean levels of depression and anxiety (Compas et al., 1994). And as expected, these students also reported lower mean levels of emotional self-efficacy. But contrary to expectations and the findings of previous research (McFarlane et al., 1994; McFarlane et al., 1995) these students did not report lower social self-efficacy. On the basis of the results from his study with adolescents, Muris (2002) concluded that the relationship between social self-efficacy and depression was weak and carried predominantly by anxiety. Again, further examination of the relationships among these variables with a larger more representative sample of adolescents with learning disabilities, which also allowed for the evaluation of gender differences, would be fruitful. Reading Disabilities Unexpectedly, among the participants with learning disabilities, those with particular and significant difficulties in the highly salient area of reading (defined in three different ways) did not report higher levels of depression and anxiety than their fellow participants without such difficulties in reading. Although this result may have  l62 been different if the students with reading disabilities had been compared with students without any learning disabilities, it is possible (as discussed earlier) that these particular students, who were all actively receiving special education supports, were buffered from developing negative affective outcomes on the basis of their reading challenges. Of additional interest is the finding that students with "discrepant" profiles (significant discrepancies between verbal ability and word reading skills and between comprehension abilities and word reading skills) reported higher mean levels of emotional self-efficacy in comparison with other participants in the sample. Results of the analyses of variance indicated that although this particular group of students had significantly lower basic skills in word reading and spelling, their general aptitude for learning and their verbal learning ability were significantly stronger. Certainly, general intelligence and verbal ability (in conjunction with good self-efficacy) have been posited as strong factors in resilience (Bland, Sowa, & Callahan, 1994; Dole, 2000). Further investigation of the relationships among aptitude, achievement, self-efficacy, and symptoms of depression and anxiety with a larger, more representative sample of adolescents, with and without learning disabilities, would be informative. Strengths and Limitations of the Study Despite the obvious limitations imposed by the size and characteristics of the sample, the present study has a number of strengths. In addition, the study has made several important contributions to the literature. First, the study has provided additional support for the self-efficacy model of depression posited by Bandura and his associates (Bandura, 1986; Bandura et al., 1999) and extended the model to a new population, adolescents with learning disabilities. Recent literature searches of both the ERIC and PsycINFO databases failed to reveal the  163 existence of any other studies that have examined relationships between self-efficacy and either depression or anxiety in children or adolescents with learning disabilities. Thus, the present study is unique in extending the self-efficacy model of depression to this population. Second, the present study has built upon the work of a corpus of previous studies that utilized the self-efficacy model of depression as a theoretical framework to examine the experience of children and adolescents from the general population by: (a) examining anxiety concurrently with depression (Muris, 2002), by examining all three self-efficacy domains (Muris, 2002), and by incorporating an examination of two factors robustly associated with depression and anxiety; namely, social support and life events (McFarlane et al., 1994; McFarlane et al., 1995). Third, the present study has extended this body of work by considering relationships between depression and anxiety and a specific and highly salient academic domain, reading. A new measure, the Reading Self-Efficacy Questionnaire, designed to be specific to a criterial task as called for by Bandura (1986) and Pajares (1996), was developed for the purpose of this study. Fourth, the present study considered depression and anxiety concurrently. As discussed in the review of literature, relatively few studies have addressed both depression and anxiety despite evidence of considerable comorbidity. Indeed, within the learning disabilities literature, only three studies (Newcomer et al., 1995; Rodriguez & Routh, 1989; and Short, 1992) examined both depression and anxiety. In addition to examining depression and anxiety concurrently, the present study also considered both as categorical and as continuous variables. The first allowed for an estimation of the prevalence of clinically significant symptomatology within the present sample while the  164 latter facilitated an evaluation of the relationship of severity of symptoms with the other continuous variables under investigation. Finally by choosing a reliable measure of anxiety (the MASC), known to distinguish well between the symptoms of depression and anxiety, the present study was able to examine participants' self-reported symptoms in both areas with confidence. Despite the strengths and contributions of the present study, there are a number of limitations that are important to note. First, the study utilized a within-subjects correlational design to develop an understanding of the complex relationships among the variables under study. While the study yielded valuable information about the experience of a particular group of adolescents with learning and reading disabilities, the lack of a comparison group comprised of individuals from the general adolescent population precluded a consideration of similarities and dissimilarities between samples from these two populations. Further, the correlational nature of the data precluded the development of causal interpretations. Second, the participants were recruited by nonrandom means. The participants were all volunteers, who were currently attending school on a regular basis, and who had obtained their parents' permission to engage in the study. Due to ethical requirements, the participants and their parents were necessarily made fully aware that the study focused on depression and anxiety. As a result of all of these factors, the study may not have captured a full range of participants with regard to the experience of depression and anxiety and the participants in the study may not be representative of the general population of students with learning disabilities. These factors limit the generalizability of findings.  i6  5  Third, due to recruitment difficulties, the sample (N = 83) was considerably smaller than planned (N = 120) and there was unequal gender representation. As a consequence, the ability of the study to detect significant relationships among the variables of interest was compromised. Fourth, the data were primarily drawn from students' self-reports and such measures are open to socially desirable responding; that is, the students may have reported how they wanted to be viewed by the researcher or they may have reported how they wanted to view themselves. Nevertheless, previous studies have attested to the reliability of adolescents as informants of their depressive symptoms (Hankin & Abramson, 1999; Kazdin, 1994). Further, the importance of students' perceptions of themselves in their environment (e.g., sense of school belonging) have been shown to have powerful relations to motivation, academic achievement and a sense of well-being (Anderman, 2002; Roeser, Midgley, & Urdan, 1996). Fifth, many of the participants' most recent psychoeducational assessments, from which the cognitive ability data for the present study was obtained, were conducted more than 3 years prior to this study. As a result, the validity of this data is questioned and complete confidence cannot be placed in the classification of the participants into the subgroups, traditional learning disabilities and reading disabilities, for a number of the analyses. Finally, it should be noted that although the participants' academic skills were assessed for the purposes of the present study, information concerning the students' actual academic performance (e.g., most recent marks for courses) was not obtained. Nor was information obtained about the students' educational history (in terms of special education supports provided, adaptations required, and courses failed and /or  i66  grades repeated). As a consequence, it is not known whether the participants had actually experienced years of chronic difficulties and failures and were thus vulnerable to developing symptoms of depression and anxiety on these grounds. Despite these limitations, the present study has examined a particular group of adolescents with learning disabilities and obtained findings that contribute to the existing literature and suggest avenues for future research. Implications for Future Research Findings of the present study have a number of implications for future research. First, important limitations of this study need to be addressed in future investigations. Specifically, studies with larger, gender-balanced samples would allow for more robust assessments of the relationships among the variables of interest. Further, more widely representative samples of adolescents with learning (and reading) disabilities would strengthen estimates of prevalence and severity of symptoms of depression and anxiety and allow for greater generalization of findings. In particular, the risk of attentuation of sample needs to be addressed. Second, the addition of three comparison groups (students with learning disabilities who were not receiving direct special education support and students without learning disabilities, one group with average and above achievement and the other with below average achievement) would facilitate the development of better understandings about the role of special education support and the impact of having a learning disability. With regard to the latter, access to recent cognitive assessment data and the addition of academic performance data would strengthen investigations. Third, the finding of the present study with regard to higher symptoms levels among older students (in conjunction with robust findings in the literature of significant  167  increases in depression during later adolescence, particularly among females) indicates that an expansion of investigations to include cross-sectional data is important. Fourth, findings of the present study with regard to lower than expected negative relationships between symptoms of depression and anxiety and self-efficacy in the academic domains (general academic and reading) suggest that further investigation of students' skill levels and performance, their perceptions of competence, their perceptions of self-efficacy, and the congruence among all of these factors in specific academic areas (especially reading) in conjunction with continued focus on symptomatology would be a fruitful line of research and a valuable addition to the literature. Fifth, future investigations that are designed to account for the cumulative effect of both "risk" factors (e.g., negative life events and chronic academic failure) and "protective" factors including "enablers" (e.g., complementary support from parents and teachers, strong social-emotional support from family, targeted academic support especially study skill/strategy instruction) would likely yield important findings and contribute much to the literature. Finally, given the complex, interactional nature of depression and anxiety, the heterogeneity of learning disabilities, and the importance of students' perceptions of self and their environment to their academic and affective functioning, future investigations would be enriched by the collection of qualitative data. Two methodologies are suggested. First, studies of specific cases, including students experiencing high levels of depression, anxiety, and comorbidity and students experiencing low symptoms levels, would undoubtedly be fruitful especially with regard to information about how these students perceive their experience of a learning  i68  disability and/or academic challenges and what coping strategies they have developed. Additional data collection by means of semi-structured interviews with small focus groups (with appropriate attention to issues of confidentiality and ethical procedures) is suggested as a way of sampling information and gaining insights across individuals (Butler, 2002). This method would also allow for the collection of information across time, a factor emphasized by De Groot (2002), and one that could be important to investigations in the present line of research. This researcher has observed that certain times of the school year (e.g., school opening, examination periods, and the weeks leading up to school dances and graduation celebrations) can be especially stressful for some students with learning disabilities. Interestingly, upon completing assessment sessions in the present study, a number of students (individually and in small groups) spontaneously stayed to ask questions about the study and to offer observations. A common theme was the failure of the Social Support Questionnaire to include an accounting of the social support provided by pets. Given the opportunity, participants in future investigation would undoubtedly contribute much to developing a richer understanding of students' perceptions of self-efficacy and their experience of depression and anxiety. Conclusions Given the heterogeneous nature of learning disabilities as well as the complexity of factors associated with the development and maintenance of both depression and anxiety, it is a challenge (but a vitally important one) to determine which students, regardless of educational classification, are most at risk for developing negative affective outcomes. Apart from the considerable psychological distress experienced by young people suffering from symptoms of depression and anxiety, additional concern  169  needs to be directed towards the potential disruption of their learning. Studies of the relationship between emotion and cognition have shown that negative and anxious emotions can seriously disrupt higher order cognitive processes such as attention, memory and problem-solving (Blair, 2002; Goldstein & Dundon, 1987). As a consequence, ascertaining the pattern of cognitive, social-emotional, and environmental factors that point to affective and academic dysfunction is of critical importance. In the present study, the factors that reliably distinguished students reporting the highest levels of depression and anxiety from those reporting the lowest levels of these symptoms were age, emotional self-efficacy, satisfaction with social support and reported experience of negative life events. Results also indicated that the relationship between self-efficacy and depression and anxiety was stronger for the affective domain (social and emotional self-efficacy) than for the academic domain (academic and reading self-efficacy). Similarly, social-emotional considerations (e.g., satisfaction with social support and experience of negative life events) were more strongly associated with symptoms of depression and anxiety than academic considerations (e.g., skill development in reading). Perhaps the salience of the social-emotional domain over the academic domain is to be expected given that adolescence is a period when individuals often hold very strong social interaction goals (Csikszentmihalyi & Larson, 1984) and the task of negotiating the social environment is posited to be critical to self development and self differentiation (Harter, 1999). Cross-sectional research involving both qualitative and quantitative data with a more widely representative sample of adolescents would assist in developing a better understanding of the relative importance of these various factors including the role played by achievement and selfefficacy in specific academic domains.  170 References Aaron, R G. (1991). Can reading disabilities be diagnosed without using intelligence tests? Journal of Learning Disabilities, 24,178-186. Abramson, L. Y., Metalsky, G. I. & Alloy, L. B. (1989). Hopelessness depression: A theory-based subtype of depression. Psychological Review, 96, 358-372. 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Journal of Consulting and Clinical Psychology, 55,55-59.  193  Appendix A Recruitment Summary  School Districts  SUP  A  AO  ST  A-l  V  V  910  A-2 A-3  S V  S  1228 1043 1100 988 909 1262 1156 999 837  A-4 A-5 A-6 A-7 A-8 A-9 A-10 B-l B-2  B  C  C-l C-2 C-3 C-4 C-5  D E  V V  Pop.  •/  s S X X  —  X  —  X  —  V s  B-3 B-4 B-5  V  Total  Schools  X  s X  X  —  X  —  Permission Denied  Permission Granted  16 22 27  2  5 2 7  29 17 15  8 6 0  Tested  1  4 2 6 7 6  0 1 1 0 0  0  —  —  —  —  —  —  —  —  —  —  —  —  —  —  —  —  —  —  —  35 50  994 1096 1076  31 25  456 928 394 459  0 3 4 0 0  Not Tested  —  1298 1447  773  V V  Possible Participants  —  29 12  2 3 2 0 —  3 1  9 10 11 9 —  9 8  9 9 11 6  0 1 0 3 —  —  3 0  6 8  —  —  —  —  —  —  —  —  —  —  —  —  —  —  —  D-l  s  D-2  s  E-l  *s  —  1372  —  —  —  —  —  E-2  X  —  263  —  —  —  —  —  E-3 E-4  X  —  —  —  —  —  —  X  —  —  —  —  —  —  805  28  915  19  495 480  2 1  6 3  0  6 3  0  F  *s  —  —  —  —  —  —  —  —  —  G  X  —  —  —  —  —  —  —  —  —  H  X  —  —  —  —  —  —  —  —  —  X  —  —  —  I N =9  N = 26  —  N = 23,683  —  N = 355  —  N = 23  —  N = 93  —  N=10  —  N = 83  Note: SUP = Superintendent; A O = Administrative Officer (School Principal); ST = Special Education Support Teacher; * = permission granted too late for study to proceed 67% of school districts approached agreed to host the study 65% of the principals or administrative officers in the consenting school districts agreed to host the study 88% of the Special Education teachers approached by their principals agreed to facilitate the study 26.2% of possible students (i.e. identified with LDs) were granted parent permission to participate 6.5% of possible students were denied parent permission to participate 89.2% of students with permission were tested (case loss was 10.8%)  194  Appendix B Students w i t h Learning Disabilities: B C M i n i s t r y o f Education In August 2002, the BC Ministry of Education published a number of revisions to the Special Education Services' Manual of Policies, Procedures and Guidelines (BC Ministry of Education, 1995) including an entirely new section on "Students with Learning Disabilities." This section includes a new definition of learning disabilities, based on the definition released in January 2002 by the Canadian Learning Disabilities Association, as well as updated criteria for assessment/identification and recommendations for the support of students with learning disabilities. The Ministry's definition of learning disabilities and guidelines for assessment and identification (with emphasis added) are as follows: D e f i n i t i o n of Learning Disabilities Learning disabilities refers to a number of disorders that may affect the acquisition, organization, retention, understanding or use of verbal or nonverbal information. These disorders affect learning in individuals who otherwise demonstrate at least average abilities essential for thinking and/or reasoning. As such, learning disabilities are distinct from global intellectual disabilities. Learning disabilities resultfromimpairments in one or more processes related to perceiving, thinking, remembering or learning. These include, but are not limited to: language processing, phonological processing, visual spatial processing, processing speed, memory and attention, and executive functions (e.g. planning and decisionmaking). Learning disabilities range in severity and may interfere with the acquisition and use of one or more of the following: (a) Oral language (e.g., listening, speaking, understanding); (b) Reading (e.g., decoding, phonetic knowledge, word recognition, comprehension); (c) Written language (e.g., spelling and written expression); and (d) Mathematics (e.g., computation, problem solving) Learning disabilities may also involve difficulties with organizational skills, social perception, social interaction and perspective taking. Learning disabilities are life-long. The way in which they are expressed may vary over an individual's lifetime, depending on the interaction between the demands of the environment and the individual's strengths and needs. Learning disabilities are  195  suggested by unexpected academic under-achievement or achievement that is maintained only by unusually high levels of effort and support. Learning disabilities are due to genetic and/or neurological factors or injury that alters brain function in a manner that affects one or more processes related to learning. These disorders are not due primarily to hearing and/or vision problems, social-economic factors, cultural or linguistic differences, lack of motivation, inadequate or insufficient instruction, although these factors may further complicate the challenges faced by individuals with learning disabilities. Learning disabilities may co-exist with other disorders such as attentional, behavioural or emotional disorders, sensory impairments, or other medical conditions. Assessment and Identification of Learning Disabilities The Ministry presented revised guidelines for the process of assessment and identification of students with learning disabilities as follows: Students with learning disabilities often experience difficulties in the acquisition of basic academic skills and/or in school performance and are characterized by unexpected academic under-achievement or achievement that is maintained only by unusually high levels of effort and support. The severity of these academic difficulties is such that students demonstrate: (a) persistent difficulties in the acquisition of pre-academic skills such as recognition of letters and numbers in the early primary years: and/or (b) persistent difficulties in the acquisition of reading, writing and/or numeracy skills. Students with learning disabilities may demonstrate a significant discrepancy between estimated learning potential and academic achievement as measured by norm-referenced achievement instruments in Grades 4.-12. Students with learning disabilities demonstrate a significant weakness in one or more cognitive processes (e.g., perception, memory, attention, receptive or expressive language abilities, visual-spatial abilities) relative to overall intellectual functioning, as measured by norm-referenced assessment instruments, which directly impact their performance. The Ministry also noted that students should be identified through a process of "progressive assessment and systematic documentation" which integrates information from various sources and includes: (a) comprehensive assessment of learning needs and use of alternative instructional strategies by classroom teacher; (b) consultation with the parent and student, with possible screening to investigate whether there is a health basis for the learning difficulty; (c) collaboration with school-based personnel to develop additional assessment and intervention strategies;  196  (d) referral to the school based team for further assistance in implementing strategies or coordination of support services; and (e) possible referral for an extended assessment {psycho-educational assessment) to determine the presence, nature, severity and educational implications of a learning disability and provide additional information for planning. Finally, the Ministry noted that the assessment may be multidisciplinary, including information from other professionals involved with the student (e.g., a speech-language pathologist or an occupational therapist), and "should contribute to the process of planning and evaluating the student's education program" (BC Ministry of Education, 1995, 2002).  197 Appendix C Demographic Questionnaire - A l l About Me All About Me UBC StudyLearning About Teens Learning (DQ) School:  S.D.#  Participant No:  1.  Are you male or female? ( / one)  2.  What is your date of birth?  3.  How old are you today i n years?  4.  What grade are you in?  5.  How do you describe yourself i n terms of ethnic or cultural heritage? {/ one) White Latin  male (Day)  (Month)  Native Black  female (Year)  Asian Indo-Canadian  Other (Please describe)  ___  6.  What language(s) do your speak at home?  7.  Were you born i n Canada? {/ one)  (Yes)  . (No)  If not, how long have you lived i n Canada? 8.  years  Who do you usually live with? (Check the most applicable category) Two biological parents One biological parent One biological parent and one step-parent/partner Grandparents or other relatives Foster parents Other (Please describe briefly) How many other children or adolescents do you usually live with? Number of brothers/step-brothers Number of sisters/step-sisters Others (Please describe briefly)  D o y o u have a paid job?  (Yes)  or (No)  (Yes)  or (No)  H o w many hours a week do you work? Please briefly describe your paid job D o y o u have an u n p a i d job? H o w many hours a week do y o u work? Please briefly describe your unpaid job A r e y o u involved i n any extra-curricular activities at school? (e.g. drama club, jazz band, basketball etc.)  (Yes)  or (No)  Please describe:  A r e y o u involved i n any extra-curricular activities outside of school? (e.g. music lessons, dance, soccer etc.)  (Yes)  or (No)  _  Please describe:  What is the highest level of education reached b y your parents/guardians? Mother/Guardian/Other  Did not complete high school Completed high school Some time at college Completed a college education Some time at university Completed a Bachelor's degree at university Completed a Master's or other advanced degree at university Father/Guardian/Other  Did not complete high school Completed high school Some time at college Completed a college education Some time at university Completed a Bachelor's degree at university Completed a Master's or other advanced degree at university  199  Appendix D Academic Self-Efficacy Questionnaire (A-SEQ) As discussed in Chapter 3, the Academic Self-Efficacy Questionnaire (A-SEQ) was adapted from previous research (Bandura, 1990; Muris, 2001,2002). A summary of the item development process is presented here followed by the final measure. The meaning of the codes is as follows: B = Bandura with the additional letters representing the source scale (SE = SelfEfficacy, A = Academic, SRL = Self-Regulated Learning, & MOE = Meet Others' Expectations) M = Muris (with the number representing the item number in his scale) L M = Item utilized by this researcher 1.  B (SE-SRL) M(i )  How well can you concentrate on school subjects? How well can you pay attention during every class?  LM  How well can you pay attention during class?  B (SE-SRL) M LM  How well can you take notes during class instruction?  B (SE-A)  How well can you remember information presented in class and in textbooks?  M LM  (no equivalent or similar item) How well can you remember information presented in class?  B (SE-SRL) B (SE-SRL) M LM  How well can you plan your school work? How well can you organize your school work?  5-  B (SE-SRL) M LM  How well can you motivate yourself to do school work?  6.  B (SE-SRL)  How well can you study when there are other interesting things to do? How well can you study when there are other interesting things to do? How well can you study a chapter for a test?  3  2.  3-  4-  M( ) M( ) LM 4  7  (no equivalent or similar item) How well can you take notes during class instruction?  (no equivalent or similar item) How well can you plan and organize your schoolwork?  (no equivalent or similar item) How well can you motivate yourself to do school work?  How well can you study when there are other interesting things to do? (Note: Muris Item #7 seen as redundant)  200  7-  8.  9-  B (SE-SRL)  How well can you use the library to get information for class assignments?  M  (no equivalent or similar item)  LM  H o w well can you use the library to get information for class assignments?  B (SE-SRL) M(io)  How well can you finish your homework assignments by deadlines? How well do you succeed in finishing all your homework every day?  LM  H o w w e l l can y o u finish your homework assignments b y deadlines?  B  (no equivalent or similar item)  M(i6)  How well do you succeed in passing all subjects? (LM - reword item; evaluative)  M(22)  How well do you succeed in passing a test?  LM  H o w w e l l can y o u usually succeed i n passing your courses?  B (SE- MOE)  How well can you live up to what your parents expect of you? How well do you succeed in satisfying your parents with your schoolwork?  (LM - drop item; evaluative and redundant)  lO.  M(i ) LM 9  H o w w e l l can you usually live up to your parents' expectations of you with regard to your school work?  201  W H A T I T H I N K (frl) UBC Stiidy;- Learning About Teens Learning (A-SEQ) School:  S.D.#  Participant No: _  Directions: Circle the number on the scale that best tells what you think about yourself 1.  H o w w e l l can y o u pay attention during class? 6 Not well at ill  2.  Mot loo well  3 Not too well  2  6  5 Pretty well  7 Very well  3 4 N o t too well  5  6 Vcrv well  Pretty well  2  3 N o t loo well  4  6  5 Pretty well  7 Very well  2  3 Not too well  4  7 Very well  5 Preth i \  3 4 Not too well  5  Very well  Pretty well  3 4 Not too well  5  1 'retry well  •  •  i  l  l  Verv well  H o w w e l l can y o u usually succeed i n passing your courses? 1 2 Not well at all  10.  4  H o w w e l l can y o u finish your homework assignments b y deadlines? 1 2 Not well at .111  9-  3 Not too ".vll  H o w w e l l can y o u use the library to get information for class assignments? 1 2 Not well at all  8.  Very VM-II  H o w well can y o u study when there are other interesting things to do? 1 Not well at all  7-  6  5 Prettv well  H o w well can y o u motivate yourself to do school work? 1 Not well at all  6.  4  H o w w e l l can y o u plan and organize your schoolwork? 1 2 Not well at all  5-  II  H o w w e l l can y o u remember information presented i n class? 1 Not well at all  4-  Very  H o w well can y o u take notes during class instruction? 1 2 Not well at all  3-  Pretty well  3 N o t too well  4  5 Pretty well  6 Very well  H o w well can y o u live you usually up to your parents' expectations of you with regard to your school work? 1 2 Not well at all  3 N o t too well  4  5 Pretty well  Very well  202  Appendix E Reading Self-Efficacy Questionnaire (R-SEQ) As discussed in Chapter 3, the Reading Self-Efficacy Questionnaire (R-SEQ) was developed by this researcher for the present study. The final measure is presented here.  203 W H A T I T H I N K (#3) UBC Study - Learning About Teens Learning (R-SEQ) School:  S.D.#  Participant No:  Directions: Circle the number on the scale that best tells what you think about yourself l.  How well can you read the words that you encounter when you are reading? 1  2  2.  3  4  Not too well  Not well at all  6  5  Pretty well  Very well  7  How well can you figure out any difficult words that you encounter when you are reading? 2  Not well al all  3  4  Not too well  6  5  Pretty well  7 V\\  \  A  I'll  How well can you understand the meaning of words that you encounter in your reading? 1  2  Not well at all  3  4  Not too well  6  5  Pretty well  Very well  7  How well can you comprehend what you are reading when you read silently? 1  2  Not well al all  3 Not tOO VM'II  4  r>  5  Pretty well  Very well  7  How well can you remember what you have read when you have finished reading a long passage or a chapter from a novel? 1  2  6.  1  4  Not tOO -A I'll  Not well at all  6  5  Pretty well  Very well  7  How well can you complete comprehension questions after you have read a long passage or a chapter from a novel? 2  J  Not well at all  4  3  Not too well  6  Pretty well  Very well  7  How well can you succeed in reading when you are working on homework a assignments? 1  SUES!)  2  8.  I  2  6  5  Pretty well  l  Not too well  7  \ 'ery well  5  6  Pretty well  7  Very well  How well can you succeed in reading when you are reading for pleasure? (e.g., a mystery novel or a story in a magazine, etc.) 1  2  Not well at .ill  10.  4  How well can you succeed in reading when \ on are working on tests and exams? Not well at all  9.  3  Not too well  Nol well at all  3  4  5  Not too well  6  7  Pretty well  \ ( ry well  How well can you succeed in reading when you are reading for information? (e.g., rules for a game, a recipe, or instructions for constructing a model, etc.) 1 Not well at all  "  2  3  Not too well  4  ;  <5*  Prettyfwell  6  "*  Very well  7  204 Appendix F Social Self-Efficacy Questionnaire (S-SEQ) As discussed in Chapter 3, the Social Self-Efficacy Questionnaire (S-SEQ) was adapted from previous research (Bandura, 1990; Muris, 2001,2002). A summary of the item development process is presented here followed by the final measure. The meaning of the codes is as follows: B = Bandura with the additional letters representing the scale (SE = Self-Efficacy, S = Social, SA = Self-Assertive, & ESR = Enlisting Social Resources) M = Muris (with the number representing the item number in his scale) L M = Item utilized by this researcher 1.  LM  How well can you make and keep friends of the same gender? Opposite gender? How well can you become friends with other children? How well can you succeed in staying friends with other children? How well can you make friends with other teens?  LM  How well can you keep friendships with other teens?  B (SE-S)  How well can you carry on conversations with others? How well can you have a chat with an unfamiliar person? How well can you carry on conversations with people that you don't know very well?  B (SE-S)  M(6) M(20)  2.  3-  M(8) LM  4-  B (SE-S) M(n) LM  5-  B (SE-SA) M(2)  LM  6.  B (SE-SA) M(i ) 4  LM  How well can you work in a group? How well can you work in harmony with your classmates? How well can you work with your classmates i n groups during class time? How well can you express your opinions when other classmates disagree with you? How well can you express your opinions when other classmates disagree with you? How well can you express your opinions when your classmates disagree with you? How well can you deal with situations where others are annoying you or hurting your feelings? How well can you tell other children that they are doing something that you don't like?' How well can you deal with situations where others are annoying you or hurting your feelings?  205  LM  How well can you get adults/a friend to help you when you have social problems? How well can you tell a funny event to a group of children? ( L M - drop; question relevance) How well can you tell a friend that you don't feel well? ( M dropped) How well can you get an adult to help you when you have problems?  8.  LM  How well can you get a friend to help you when you have problems?  9-  B (SE-ESR)  How well can you resist peer pressure to do things in school that can get you into trouble? How well do you succeed in preventing quarrels with other children? ( M dropped) How well can you resist peer pressure to do things i n school that can get you into trouble?  7-  B (SE-ESR) M(i ) 7  M(i8)  M(23)  LM  10.  LM  How well can you resist peer pressure to do things i n the community that can get into trouble?  206 W H A T I T H I N K (#2) UBC Study - Learning About Teens Learning (S-SEQ) S.DJ  School:  Participant No:  Directions: Circle the number on the scale that best tells what y o u think about yourself 1.  How well can you make friends with other teens? 1  2  3  Not well at nil  2.  1  2  2  3  2  5  6  Pretty well  Pretty well  4  7  Very well  Very well  5  6  7  Pretty well  3  4  Not too well  Very well  5  6  Pretty, well  7  Very well  How well can you deal with situations where others are annoying you or hurting your feelings? 1  2  Not well at all  3  4  Not loo well  5  6  Pretty well  7  Very well  How well can you get an adult to help you when you have problems? 1  2  Not well at all  3  4  Noitoolvell  5  6  Pretty well  Very well  7  How well can you get a friend to help you when you have problems? 1  2  3  Notwell at all 9-  Very well  How well can you express your opinions when your classmates disagree with you? 1  8.  4  Not too well  Not well at all  7-  7  How well can you work with your classmates in groups during class time? 1  6.  3  Not too well  Not too well  Not well at all 5-  6  How well can you carry on conversations with people that you don't know very well? Not well at all  4-  5  Pretty well  How well can you keep friendships with other teens? ,No,t;wellatall  3-  4  Not too well  4  5  Not too well  6  Pretty well  7  Very well  H n w well ran you resist peer pressure to do things in school that can get you into trouble? •1  2  . . . . Notwell at all  3  4  Not too well  ...  5  6  Pretty well  .  7  *  Very well.  10. H o w well can you resist peer pressure to do things in the communitv that can get you into  trouble?  1  Not well at all  2  3  Not too well  4  5  Pretty well  6  7  Very well  207 Appendix G Emotional Self-Efficacy Questionnaire (E-SEQ) As discussed in Chapter 3, the Emotional Self-Efficacy Questionnaire (E-SEQ) was adapted from previous research (Bandura, 1990; Muris, 2001,2002). A summary of the item development process is presented here followed by the final measure. The meanings of the codes are as follows: B = Bandura with the additional letters representing the scale (e.g. SE = SelfEfficacy & SRE = Self-Regulatory Efficacy) M = Muris (with the number representing the item number in his scale) L M = Item utilized by this researcher 1.  LM  How well can you usually figure out your own emotions or feelings?  2.  LM  How well can you usually figure out the emotions or feelings of other people?  3-  M( )  How well do you succeed in becoming calm again when you are very scared? (reword; evaluative) How well can you calm yourself when you are feeling scared?  5  LM 4-  M(i ) 5  LM  5-  How well do you succeed in cheering yourself up when an unpleasant event has happened? (reword to more colloquial language) How well can you cheer yourself up when something bad has happened?  M( ) 3  LM 6.  How well can you prevent to become nervous? (reword; awkward) How well can you stop yourself from being overly nervous?  M( ) 9  LM 7-  M(2 ) 4  LM  How well can you give yourself a peptalk when you feel low? (reword to more colloquial language) How well can you cheer yourself up when you are feeling really low and down on yourself?  How well do you succeed in not worrying about things that might happen? (reword; evaluative) How well can you manage to stop worrying about things that might happen?  208 8.  9-  10.  M(2l)  H o w well do you succeed in suppressing unpleasant thoughts?  LM  (reword to more colloquial language) How well can you put recurring unpleasant thoughts out of your mind?  M(12)  H o w well can you control your feelings?  LM  How well can you keep i n charge of your emotions or feelings so that you don't feel overwhelmed by them?  B (SE-SRE)  H o w well can you control your temper?  LM  How well can you control your temper?  209  W H A T I T H I N K (^4) UBC Study - Learning About Teens Learning (E-SEQ) School:  S.D.#  :  Participant No:  Directions: Circle the number on the scale that best tells what you think about yourself 1.  How well can you usually figure out your own emotions or feelings? 2  Not well at all  2.  3  Nol Loo well  4  =5  6  Pretty well  7  Very well  How well can you usually figure out the emotions or feelings of other people? 1  2  3  Not well at all  Not too well  4 ''  5  Pretty well  6  Very well  7  How well can you calm yourself when you are feeling scared? 1  2  Not well at all  4.  Not too well  1  7  Very well  Very well  Pretty well  Very well  2  3  Not too well  4  5  Pretty well  6  Very well  7  How well can you manage to stop worrying about things that might happen? 1  2  Not too well  4  5  Pretty well  6  Very well  7  How well can you put recurring unpleasant thoughts out of your mind? 1  2  Not well at all 9-  Pretty well  Nut too well  Not well at all  8.  6  How well can you stop yourself from being overly nervous? Not well at all  7.  -  Pretty well  How well can you cheer yourself up when something bad has happened? Not well a I all  6.  4  How well can you cheer yourself up when you are feeling really low and down on yourself? Not well at all  5.  3  Not too well  3  Not too well  4  5  Pretty well  6  Very well  7  How well can you keep i n charge of your emotions or feelings so that you don't feel overwhelmed by them? 1  2  Nol well at all  3  Very well  Pretty well  Not too well  How well can you control your temper? 1  Not well at .ill  2  3  \\>l U"> well  4  5  Pretty .w 11  6  Very well  7  210 Appendix H Social Support Questionnaire Who I Can Count O n UBC Study - Learning About Teens Learning (SSQ) School:  S.D.#  Participant No:  Directions: The following twelve questions ask you about people i n your environment who provide you with help or support. Each question has two parts. In the first part of each question, list all the people you know, excluding yourself, whom you can count on for help or support in the manner described. Give the person's initials and their relationship to you (see example below). Do not list more than one person next to each of the letters beneath the questions. For the second part of each question, circle how satisfied you are with the overall support you have. If you have no support for a question, circle the words, "No one," but still rate your level of satisfaction. Do not list more than rune people per question. Please so your best to answer all of the questions as well as you can. Remember, all your responses will be kept in strictest confidence. Example: Who do you know whom you could trust with information that could get you into trouble? No one a). T.N. (brother) d). T.N. (father) g). b) . T.M. (friend) e). R.N. (mother) h). c) . R.S. (friend) f). i). How satisfied are you with the overall support you have? Fairly  Very \ Dis satisfied Satisfied  A Little  till  (.TV  1.  Dissatisfied  Dissatisfied  A I ittle  Fairly  Satisfied  Satisfied  Who can you really count on to be dependable when you need help? No one  a).  d).  g).  b) .  e).  h).  c) .  f).  i).  How satisfied are you with the overall support you have? Very Very Dissatisfied Satisfied  Fairly Dissatisfied  A Little Dissatisfied  IIP*  A Little  Fairly  Satisfied  Satisfied  211  2.  Who can you really count on to help you feel more relaxed when you are under pressure or feeling tense? No one a). d). g). b) . e). __ h). c) . f). i). How satisfied are you with the overall support you have? Very niw.il-i.snvd  Fairly A Little Dissatisfied  3  A Little Dissatisfied  4  5 Fairlv Satisfied  6 Vi iyjpjS^^ Satisfied  Satisfied  3.  Who accepts you totally, including both your worst and your best points? No one a). d). g). b) . e). h). c) . f). i). How satisfied are you with the overall support you have? Very Dissatisfied  1 1 1 ^ - ' S I l l l l Taii-ly A I ittle Dissatisfied  3  A I.iltle Dissatisfied  5  4  J11S3*•airlySatisfied  6 Very Satisfied  Satisfied  4.  Who can you really count on to care about you, regardless of what is happening to you? No one a). • d). g). b) . e). h). c) . f). i). How satisfied are you with the overall support you have? Very Dissatisfied  Fairly A 1 ittle Dissatisfied  3  A Little Dissatisfied  4  5 Fairly Satisfied  6 Very Satisfied  Satisfied  Who can you really count on to help you feel better when you are feeling generally down-in-the dumps? No one a). d). g). b) . e). h). c) . f). i). How satisfied are you with the overall support you have? Very Dissatisfied  lIlllKlisllB  A Little Fairly Dissat sfied  3  A 1 ittle Dissatisfied  4  5 Fairly Satisfied  6 Veiy  Satisfied  Satisfied  6.  Who can you count on to console you when you are very upset? No one a). d). g). _ b) . e). h). . c) .  f).  i). _  How satisfied are you with the overall support you have? Very Dissatisfied Satisfied  Fairly A Little Dissatisfied  3  A Little Dissatisfied  4  llBSjjijiifc  Fairly Sat sfied  6  Very  Satisfied  212  Appendix I Life Events Questionnaire The Life Events Questionnaire (LEQ) is a revision and extension of a measure developed by Newcomb, Huba and Bentler (1981). A summary of the item development process is presented here with the original items in italics and the revised items in bold type. The final measure follows. In the original measure, participants were required to rate ah items; "How I would feel if it happened." It was decided that this instruction was too abstract and the requirement unnecessarily time-consuming for participants. Further, the items (e.g. #1. Parents divorced) seemed rather terse descriptions of possible life events. Consequently, the questionnaire was revised in several ways to facilitate the participants' comprehension. First, the items were rewritten for presentation as simple sentences rather than isolated fragments. Second, the directions were rewritten so that participants would only have to rate those life events that they had experienced; "If it happened, how did you feel?" Third, some words were changed to reflect current language use; for example, "venereal disease" was changed to "sexually transmitted disease (STD)." Finally, the questionnaire was extended by adding five items that reflect current concerns of many adolescents; namely, losing weight (Item 34), verbal and physical aggression (Items 39 & 40) and abuse of alcohol and drugs (Item 41). An additional item concerning "falling out with best friend(s)" (Item 38) was also added to reflect peer relationship concerns, which are particularly salient for adolescent females.  213  A. 1. 1. 22. 20. 24. 22. 36. 31. 4337-  B. 2. 2. 6. 6. 8. 8. 40. 35-  C. 7714. 1320. 19. 27. 24. 3i28. 3732. 41. 36.  D. 331312. 1514. 18. 17-  FAMILY/PARENTS  (Parents divorced) My parents separated or divorced (Family had money problems) My family had money problems (Parents argued or fought) My parents argued or fought a lot (Parent remarried) One of my parents remarried (Parent abused alcohol) One of my parents abused alcohol and/or drugs ACCIDENT/ILLNESS  (Family accident or illness) Someone in my family had an accident or became seriously ill (Given medication by physician) I was prescribed medication by my doctor (Death in the family) One of my close friends or family members died (Serious accident or illness) One of my close friends had a serious accident or became seriously ill SEXUALITY  (Fell in love) I fell in love (Got or made pregnant) I got or made someone pregnant (Got or gave venereal disease) I got or gave someone a sexually-transmitted disease (STD) (Started dating regularly) I started dating regularly (Broke up with boy/girl-friend) I broke up with my boy-friend/girl-friend (Had a gay experience) I had a gay experience (Lost virginity) I lost my virginity AUTONOMY  (Found a new group of friends) I started hanging out with a new group of friends (Began a tirne-consuming hobby or sport) I got involved in a time-consuming hobby or sport (Decided about college) I made a decision about my career goals (Joined a club or group) I joined a club or special interest group  214  (Got own stereo or television) 21. I got my own stereo, television or computer (Took vacation without parents) 29. 26. I went on a trip without my parents 30. (Started driving) 27. I started driving (Started making own money) 3330. I started making my own money 23.  DEVIANCE  E.  44-  5519.  18.  (Got into trouble with the law) I got into trouble with the police or the law (Stole something valuable) I stole something valuable (Got into trouble at school) I got into trouble with the Principal or Vice-Principal RELOCATION  F.  12.  11. 1716. 32.  29. G. 9-  911.  10. 16.  1526.  23. 28.  2539-  33-  (Parent changed jobs) One of my parents changed jobs (Changed schools) I changed schools (Family moved) My family moved DISTRESS  (Face broke out in pimples) My face broke out (Started seeing a therapist) I started seeing a counselor, therapist or psychiatrist (Thought about suicide) I thought about suicide (Ran away from home) I ran away from home (Got poor grades in school) I got poor grades (Gained a lot of weight) I gained a lot of weight NEW ITEMS  3438. 3940. 41.  I lost a lot of weight I had a serious falling out with my best friend(s) I was verbally attacked by someone I was physically assaulted by someone I abused alcohol and/or drugs  215  Events in My Life UBC Study - Learning About Teens Learning (LEQ-41) School:  S.D.#  Participant No:  Directions: You are asked to do two things for each of the events listed below. First, check off whether or not the event has occurred in your life during the past 12 months. Second, if the event did happen over the past year, rate how it made you feel on the 5-point scale provided. No.  1.  2.  Did Happen  Did Not Happen  Life Events M y parents separated or divorced If it happened, how did you feel? 1 Very Unhappy  2 Unhappy  3 Neutral  4 Happy  5 Very Happy  2 Unhappy  3 Neutral  4 Happy  5 Very Happy  2 Unhappy  3 Neutral  4 Happy  5 Very Happy  4 Happy  5 Very Happy  4 Happy  5 Very Happy  4 Happy  5 Very Happy  I stole something valuable If it happened, how did you feel? 1 Very Unhappy  6.  5 Very Happy  I got into trouble with the police or the law If it happened, how did you feel? 1 Very Unhappy  5.  4 Happy  I started hanging out with a new group of friends If it happened, how did you feel? 1 Very Unhappy  4.  3 Neutral  Someone in my family had an accident or became seriously ill If it happened, how did you feel? 1 Very Unhappy  3.  2 Unhappy  2 Unhappy  3 Neutral  I was prescribed medication by my doctor If it happened, how did you feel? 1 Very Unhappy  7.  2 Unhappy  3 Neutral  I fell in love If it happened, how did you feel? 1 Very Unhappy  8.  2 Unhappy  3 Neutral  One of my close friends or family members died If it happened, how did you feel? 1 2 Very Unhappy  9.  Unhappy  3 Neutral  4 Happy  5 Very Happy  4 Happy  5 Very Happy  M y face broke out If it happened, how did you feel? 1 Very Unhappy  2 Unhappy  3 Neutral  2l6 No. 10.  Did Happen  Did Not Happen  Life Events I started seeing a counselor, therapist or psychiatrist If it happened, how did you feel? 1 Very Unhappy  11.  2 Unhappy  3 Neutral  4 Happy  5 Very Happy  4 Happy  5 Very Happy  One of my parents changed jobs If it happened, how did you feel? 1 Very Unhappy  12.  2 Unhappy  3 Neutral  I got involved in a time-consuming hobby or sport If it happened, how did you feel? 1 Very Unhappy  13.  2 Unhappy  3 Neutral  4 Happy  5 Very Happy  4 Happy  5 Very Happy  4 Happy  5 Very Happy  4 Happy  5 Very Happy  4 Happy  5 Very Happy  4 Happy  5 Very Happy  I got or made someone pregnant If it happened, how did you feel? 1 Very Unhappy  14.  3 Neutral  I made a decision about my career goals If it happened, how did you feel? 1 Very Unhappy  15.  2 Unhappy  2 Unhappy  3 Neutral  I thought about suicide If it happened, how did you feel? 1 Very Unhappy  16.  3 Neutral  2 Unhappy  3 Neutral  I got into trouble with the Principal or Vice-principal If it happened, how did you feel? 1 Very Unhappy  19.  2 Unhappy  I joined a club or special interest group If it happened, how did you feel? 1 Very Unhappy  18.  3 Neutral  I changed schools If it happened, how did you feel? 1 Very Unhappy  17.  2 Unhappy  2 Unhappy  3 Neutral  4 Happy  5 Very Happy  I got or gave someone a sexually-transmitted disease (STD) If it happened, how did you feel? 1 Very Unhappy  20.  2 Unhappy  3 Neutral  4 Happy  5 Very Happy  4 Happy  5 Very Happy  M y family had money problems If it happened, how did you feel? 1 Very Unhappy  2 Unhappy  3 Neutral  217  No. 21.  Did Happen  Did Not Happen  Life Events I got my own stereo, television or computer If it happened, how did you feel? 1 Very Unhappy  22.  3 Neutral  4 Happy  5 Very Happy  4 Happy  5 Very Happy  4 Happy  5 Very Happy  4 Happy  5 Very Happy  4 Happy  5 Very Happy  4 Happy  5 Very Happy  4 Happy  5 Very Happy  4 Happy  5 Very Happy  4 Happy  5 Very Happy  4 Happy  5 Very Happy  4 Happy  5 Very Happy  M y parents argued or fought a lot If it happened, how did you feel? 1 Very Unhappy  23.  2 Unhappy  2 Unhappy  3 Neutral  I ran away from home If it happened, how did you feel? 1 Very Unhappy  24.  2 Unhappy  3 Neutral  I started dating regularly If it happened, how did you feel? 1 Very Unhappy  25.  3 Neutral  I got poor grades If it happened, how did you feel? 1 Very Unhappy  26.  2 Unhappy  2 Unhappy  3 Neutral  I went on a trip without my parents If it happened, how did you feel? 1 Very Unhappy  27.  3 Neutral  I started driving If it happened, how did you feel? 1 Very Unhappy  28.  2 Unhappy  2 Unhappy  3 Neutral  I broke up with my boy-friend/girl-friend If it happened, how did you feel? 1 Very Unhappy  29.  2 Unhappy  3 Neutral  I started making my own money If it happened, how did you feel? 1 Very Unhappy  31.  3 Neutral  M y family moved If it happened, how did you feel? 1 Very Unhappy  30.  2 Unhappy  2 Unhappy  3 Neutral  One of my parents remarried If it happened, how did you feel? 1 Very Unhappy  2 Unhappy  3 Neutral  2l8 No. 32.  Did Happen  Did Not Happen  Life Events I had a gay experience If it happened, how did you feel? 1 Very Unhappy  33.  2 Unhappy  3 Neutral  4 Happy  5 Very Happy  2 Unhappy  3 Neutral  4 Happy  5 Very Happy  2 Unhappy  3 Neutral  4 Happy  5 Very Happy  4 Happy  5 Very Happy  4 Happy  5 Very Happy  I lost my virginity If it happened, how did you feel? 1 Very Unhappy  37.  5 Very Happy  One of my close friends had a serious accident or became seriously ill If it happened, how did you feel? 1 Very Unhappy  36.  4 Happy  I lost a lot of weight If it happened, how did you feel? 1 Very Unhappy  35.  3 Neutral  I gained a lot of weight If it happened, how did you feel? 1 Very Unhappy  34.  2 Unhappy  2 Unhappy  3 Neutral  One of my parents abused alcohol and/or drugs If it happened, how did you feel? 1 Very Unhappy  38.  3 Neutral  4 Happy  5 Very Happy  2 Unhappy  3 Neutral  4 Happy  5 Very Happy  4 Happy  5 Very Happy  4 Happy  5 Very Happy  I was physically assaulted by someone If it happened, how did you feel? 1 Very Unhappy  41.  2 Unhappy  I was verbally attacked by someone If it happened, how did you feel? 1 Very Unhappy  40.  3 Neutral  I had a serious falling out with my best friend(s) If it happened, how did you feel? 1 Very Unhappy  39.  2 Unhappy  2 Unhappy  3 Neutral  I abused alcohol and/or drugs If it happened, how did you feel? 1 Very Unhappy  2 Unhappy  3 Neutral  

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