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Title:
Relationships between substance use, mental health problems, and involvement in school-based extracurricular activities among high school students
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Language:
English
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Malval, Kristelle
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University of South Florida
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Tampa, Fla
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Subjects / Keywords:
Substance use
Depression
Anxiety
School involvement
Dissertations, Academic -- Psychological & Social Foundations -- Masters -- USF   ( lcsh )
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non-fiction   ( marcgt )

Notes

Abstract:
ABSTRACT: Substance use during adolescence is associated with numerous undesirable short term and long term consequences. This study examined rates of substance use, as well as rates of elevated anxiety and depressive symptomalogy, among 138 students attending a predominantly Hispanic, low-SES high school. The current study also examined the complex relationships between adolescent substance use, mental health problems, and involvement in school-based extracurricular activities, among this ethnically diverse sample. Results included that a significant proportion of adolescents in the sample fell in the "at-risk" category for a clinical diagnosis of depression and/or anxiety disorder. Further, those students who reported smoking cigarettes and using marijuana were more likely to endorse feelings/thoughts related to school avoidance. Results also indicated that the more adolescents reported being involved in prosocial/academically oriented school-based extracurricular activities and/or special interest clubs, the less likely they were to report smoking cigarettes. Finally, involvement in athletics protected students with social anxiety from using cigarettes. Implications of these findings for future research as well as practice are also discussed.
Thesis:
Thesis (EDS)--University of South Florida, 2010.
Bibliography:
Includes bibliographical references.
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Mode of access: World Wide Web.
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System requirements: World Wide Web browser and PDF reader.
Statement of Responsibility:
by Kristelle Malval.
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Title from PDF of title page.
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Document formatted into pages; contains X pages.

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ABSTRACT: Substance use during adolescence is associated with numerous undesirable short term and long term consequences. This study examined rates of substance use, as well as rates of elevated anxiety and depressive symptomalogy, among 138 students attending a predominantly Hispanic, low-SES high school. The current study also examined the complex relationships between adolescent substance use, mental health problems, and involvement in school-based extracurricular activities, among this ethnically diverse sample. Results included that a significant proportion of adolescents in the sample fell in the "at-risk" category for a clinical diagnosis of depression and/or anxiety disorder. Further, those students who reported smoking cigarettes and using marijuana were more likely to endorse feelings/thoughts related to school avoidance. Results also indicated that the more adolescents reported being involved in prosocial/academically oriented school-based extracurricular activities and/or special interest clubs, the less likely they were to report smoking cigarettes. Finally, involvement in athletics protected students with social anxiety from using cigarettes. Implications of these findings for future research as well as practice are also discussed.
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Relationships B etween Substance Use, Mental Health Problems, and Involvement in School Ba sed Extracurricular Activities A mong High School Students b y Kristelle Malval A thesis submitted in partial fulfillment of the requirements for the degr ee of Educational Specialist Department of Psychological and Social Foundation College of Education University of South Florida Major Professor: Shannon M. Suldo, Ph.D. Rance Harbor, Ph.D. Robert Dedrick, Ph.D. Date of Approval: July 1 st 2010 Keyw ords: substance use, depression, anxiety, school involvement, adolescence, high school Copyright 2010 Kristelle Malval

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ii Acknowledgments It is a pleasure for me to thank all those who made this thesis project possible. First and foremost, I woul d like to offer my deepest and sincerest gratitude to my major professor, Dr. Shannon M. Suldo, who supported me throughout my thesis project with her never ending supervision, constructive feedback, guidance, patience, and words of encouragement. Her pass ion for her work and her dedication to all students are truly inspiring. I would also like to thank Dr. Rance Harbor for giving me the opportunity to participate in his research project from the early stages and for allowing me to add a piece to this proje ct. This opportunity has allowed me to conduct research on a topic of interest. I also gratefully acknowledge Dr. Robert Dedrick for his expertise, continued support, and assistance throughout my thesis project. Without my committee, I would not have been able to accomplish this project. Finally, I would like to offer my regards and blessings to my husband and parents for their unconditional love and support. They were always there for me during the completion of this project and throughout my studies at th e University of South Florida. Thanks for always believing in me and for all the sacrifices you have made along the way. For that, I am forever grateful.

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i Table of Contents Table of Contents i List of Tables i v Abstract v Chapter One : Introduction Statement of the Problem 1 Definition of Key Terms 4 Substance Use 4 Depression 4 Anxiety 5 Involvement in School Based Extracurricular Activities 5 Purpose of the Current Study 6 Research Questions 7 Limitations 8 Contributions t o the Literature 8 Chapter Two: Review of the Literature Overview of Substance Use 10 Prevalence of Substance Use in Adolescence 1 3 Relationship Between Substance Use & Demographic Characteristics Socio Economic Status Race/Ethnicity Gende r 13 1 4 15 16 Mental Health Problems during Adolescence 18 Overview of Depression 19 Prevalence of Depression during Adolescence 20 Overview of Anxiety Disorders 22 Generalized Anxiety Disorder 24 Social A nxiety 25 School Refusal/Avoidan ce 26 Links between Mental Health and Substance Use among Adolescents 2 7 Educational Functioning and School Services 32 Links between Mental Health Problems and Academic Achievement 3 3 Li nks between Substance Use and Academic Achievement 3 7

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ii Outcomes 39 Conclusion s 44 Purpose of the Current Study 46 Chapter Three: Method Overview of the Settings 49 Selection of Parti cipants 50 Procedures 5 2 Measures 5 5 Demographic Questionnaire 5 5 Teen Alcohol and Drug Use Scale 5 5 Center for Epidemiological Studies Depression Scale 5 6 Screen for Child Anxiety Related Disorders 5 8 Participation in School Related Activities Q uestionnaire 6 1 Variables 6 3 Independent 6 3 Dependent 6 4 Moderators 6 4 Overview of Analyses Descriptive Analyses 6 4 6 4 Correlational Analyses 6 6 Logistic Regression Analyses 6 7 Chapter Four: Results Overview 6 9 Treatment of the Data 6 9 Descriptive Analyses 7 0 Correlational Analyses 7 7 Predictive Analyses 7 9 Chapter Five: Discussion Study Summary 8 8 Findings Regarding Frequency of Substance Use 8 9 Findings Regarding Depressive Symptomalogy among High School Students 9 1 Findings Regarding Anxiety Symptomalogy among High School Students 9 2 Notable Findings Regarding Interrelationships between Variables 9 6 Implications for School Psychologists and other Professionals 1 0 1 Limitations of the Current Study 1 0 5 Internal Validity 1 0 6 Ecological Validity 1 0 6 Population Validity 1 0 6 Directions for Future Research 1 0 9 Final Thoughts 1 1 0

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iii References 1 1 1 Appendices 1 2 5 Appendix A: Parent Consent Form 1 2 6 Appendix B: Student Assent Form 12 8 Appendix C: Demograp hic Information Questionnaire 1 3 0 Appendix D: Teen Alcohol and Drug Use Scale 1 3 1 Appendix E: Center for Epidemiological Studies Depression Scale 1 3 2 Appendix F: Screen for Child Anxiety Related Disorders Re lated Activities Questionnaire Appendix H: Logistic Regression Analyses : Interaction Effects Yielded for Substance Use, Mental Health Problems, and Involvement in School Based Extracurricular Activities Appendix I: Logistic Regression Analyses: Main Effec ts Yielded for Substance Use, Mental Health Problems, and Involvement in School Based 1 3 3 1 3 4 1 3 5 1 4 1

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iv List of Tables Table 1. Descriptive Statistics for Sample (n = 138) and School Population (n = 1780) 5 2 Table 2. Frequency of Substance Use on a Continuum 7 1 Table 3. Frequency of Substance Use in its Dichotomous Form 7 2 Table 4. Frequency of Depressive Symptomalogy W ithin the Complete Range of Scores 7 3 Table 5. Frequency of Anxiety Symptomalogy Within the Complete Range of Scores 7 5 Table 6. Frequency of Anxiety and Depressive Symptomalogy According to Cut Point Scores 7 7 Table 7. Correlat ion between Mental Health Symptomalogy and Substance Use 7 8 Table 8. Correlation between Participation in School Based Extracurricular Activitie s and Substance Use 7 9 Table 9. Intercorrelations between Substance Clusters o n TADUS, School I nvolvement Clusters, SCARED, and CES D scores 8 1

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v Relationships between Substance Use, Mental Health Problems, and Involvement in School Based Extracurricular Activities among High School S tudents Kristelle Malval ABSTRACT Substance use during adolescence is associated with numerous undesirable short term and long term consequence s This study examined rates of substance use as well as rates of elevated anxiety and depressive symptomalogy among 1 3 8 students attending a p redominantly Hispanic, low SES high school T he current study also examine d the complex relationship s between adolescent substance use, mental health problems, and involvement in school based extracurricular activities, among this ethnically diverse sample Results included that a significant proportion of adolescents in the sample fell in Further, those students who reported smoking cigarettes and using marijuana were m ore likely to endorse feelings/thoughts related to school avoidance. R esults also indicated that the more adolescents reported being involved in prosocial/academically oriented school based extracurricular activities and/or special interest clubs, the less likely they were to report smoking cigarettes. Finally, involvement in athletics protected students with social anxiety from using cigarettes. Implications of these findings for future research as well as practice are also discussed.

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1 Chapter One Introduction Statement of the Problem Substance use during the high school years is of particular concern because it has been linked to numerous negative outcomes including poor ac ademic functioning and educ ational attainment (Diego Field, & Sanders, 2003; Eng berg & Morral, 2006; King Iacono, & McGue, 2006), physical health (The National Survey on Drug Use and Health, 2008), socio emotional functioning (The National Survey on Drug Use and Health, 2008), and later dependency to substances (Diego, et al. 2003; Johnston, ). A National Institute on Drug Abuse report indicated that about three quarters of students (72%) have consumed alcohol before twelfth grade and approximately half of youth in the United States (46%) have tried cigarettes before the en d of high school (Johnston et al., 2007). S ubstance use generally starts during early adolescence (Diego et al., 2003; Kandel, Yamagushi, & Chen, 1992; The National Survey on Drug Use and Health, 2008). Moreover, various factors have also been found to influence not only substance use but also the choice of substance ; these as socio economic status (SES; Amaro et al., 2001; Bettes et al., 1990; Johnston et al., 2007; Luthar et al., 2005; Parker et al., 2000; Piko, 2006; Wagner et al., 2007; Wallace et al., 2003).

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2 Mental health problems, more specifically depression and anxie ty, are also of concern during adolescence. Depression and anxiety are two of the most common and prevalent internalizing disorders during adolescence (Albano et al., 2003; Costello et al., 2005; Huberty, 2008; Rushton et al., 2002). Current estimates sug gest that as many as 15 20% of children and youth have depressive or anxiety problems that warrant direct intervention (Huberty, 2008). Prevalence rates of depression and depressive symptomalogy among children and adolescents range widely, from 1% to 18% ( Costello, Egger, & Angold, 2005). Prevalence rates of anxiety among youth have also been found to be significant ranging from 2% to 33% (Costello, Egger, & Angold, 2005). The current study focuses on generalized anxiety disorder (GAD) and social anxiety i n particular, as they are among the most prevalent anxiety disorders during adolescence (Costello, Egger, & Angold, 2005). Although not a diagnosable anxiety disorder, school refusal/avoidance is also a focus of the current study as it has been found to be a symptom in multiple anxiety disorders and is associated with risky behaviors such as school failure and subst ance use (Kearney, 2008; Mattis & Ollendick, 2003). Such em otional and academic functioning ( Evans, Van Velsor, & Schumacher, 2002 ; McCarthy, Downes, & Sherman, 2008). As with substance use during adolescence, prevalence rate s of depression and anxiety as well as the severity and expression of the symptoms are a lso influenced by demographic characteristics such as gender, age, ethnic/racial background, and SES ( Angold et al., 1999; Cooley, 2004; Costello et al., 2006; Lewinsohn et al., 1998; Manassis et al., 2004; Roberts et al., 1997; Rushton et al., 2002; The N ational Survey on Drug Use and Health, 2008 ).

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3 Links bet ween substance use (e.g., tobacco alcohol, marijuana) and internalizing disorders such as depression and anxiety have been found in severa l studies (Comeau, Stewart, & Loba, 2001 ; Diego et al., 2003 ; King et al. 2004; Kaplow, Curran, Angold, & Costello, 2001; Poulin, Hand, Boudreau, & Santor, 2005; Vogel, Hurford, Smith, & Cole, 2003 ). However the relationship between substance use and internalizing disorders, such as depression and anxiety, is not fully understood as the direction of the re lationship is not certain (Grant, Stinson, Dawson, Chou, Dufour, Compton, Pickering, & Kaplan, 2004). Regardless preventative efforts are warranted as youth with internalizing disorders and/or substance use probl ems have been found to experience academic difficulties (Albano et al., 2003; Aloise Young & Chavez, 2002; Bhatia et al., 2007; Engberg & Morral, 2006; Evans et al., 2002; Farmer, 2002; Kessler et al., 1995; Van Ameringen et al., 2003). P rotective factor s such as involvement in school based extracurricular activities, which are characterized by structure and supervision while at the same time allowing youth to socialize and express th eir identity, positively impact educational outcomes and reduce the likeli hood of substance use during adolescence (Bohnert et al., 2007; Darling, 2005; Eccles et al., 1999; Fredricks et al., 2 006; Peck et al., 2008). To date the relationship s between involvement in school base d extracurricular activities, their menta l health problems, and their substance use has not been extensively studied. In the one published study that has included these variables in the same project, Darling (2005) examined links between adolescent participation in school based extracurricular ac tivity, substance use, depression, and attitudes towards school. She found that extracurricular activity involvement predicted less tobacco and illicit drug use, but was

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4 not related to depression nor alcohol use in the primarily Caucasian sample. Althoug h Darling established activity involvement as a buffer against the adverse effect of stressful life events, this author (nor authors of any other published study) did not conceptualize or test school involvement as a possible moderator in the relationships between depression and substance use or between anxiety and substance use. Such research with depression (or anxiety) as the predictor and substance use as the outcome is needed in order to determine if activity involvement serves as a protective factor, especially among students particularly at risk, such as students from low SES backgrounds. It is imperative for school psychologists to identify factors, such as activity involvement, that would potentially help prevent or alleviate substance use during hi gh school, particularly among students with symptoms of mental health problems. S chool psychologists and other school based mental health providers have the opportunity to participate in preventative efforts as they are in the schools and can provide servi ces on a consistent basis. Definition of Key Terms Substance u se This study focuses on adolescents, for whom it is illegal to consume subst ances (e.g., alcohol and cigarettes ) that are not unla wful for adults. Substance use in this study includes several illicit su bstances (i.e., alcohol, cigarettes and marijuana). In the majority of studies substances are often categorized into distinct groups. This study also examine d substance use by categori zing substances into three type s: Alcohol, Cigarettes and M arijuana Depression In the current study, prevalence rates of depressive symptomalogy are discussed as well as level of risk for actual diagnoses of depression. Depressive symptomalogy is different from Major Depressive Episode and presents depression on a

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5 continuum. Even when a clinical diagnosis is not met, high scores on self report measures of depression may indicate impaired functioning and a greater likelihood of developing later mental health disorders. Adolescents experiencing sub syndromal depr essive symptoms can benefit from early preventative efforts as these symptoms still warrant treatment. Anxiety This study also discuss es rate s of anxiety sympt omalogy among adolescents and specifically look ed at G eneralized A nxiety D isorder (GAD) social anxiety and school refusal/avoidance. Symptoms were also conceptualized on a continuum in addition to level of risk for actual clinical diagnoses. Higher scores on self report measures of anxiety may be indicative of the presence o f a later development of clinically diagnosed anxiety disorders. Involvement in school based extracurricular activities. Numerous studies have based extracurricular activities (Bohnert & Garber, 2007; Darling, 2005; Eccles & Barber 1999; Fredricks & Eccles, 2006; Peck, Roeser, Zarett, & Eccles, 2008). Such involvement has been identified by Darling (2005) as providing for adolescents, a highly structured environment in which they can not only express their identity but also develop a strong social network while being supervised by adults and monitored for delinquent behaviors. I n the current study, school involvement is defined as participation in different types of school based extra curricular activities such as athletics (e.g., ba sketball, gymnastics), performing arts (e.g., music, dance), academics (e.g., language, academic clubs), and social clubs/hobbies (e.g. hobby clubs, social clubs). Such activities should be differentiated from unsupervised activities or after school activ ities not affiliated with the schools (e.g., community sports team)

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6 Purpose of the Current Study This study examine d the rate of substance use among adolescents (9 th to 12 th grade) in a predominan tly low SES high school, attended by primarily Hispanic students, in the s tate of Florida. Furthermore, the percentage of adolescents in the sample who experienc ed elevated anxiety and depressive symptomalogy was also examined Given that the use of substances and the presence of mental problems have been fou nd to be common during ad olescence the current study expand s on the aforementioned research by providing prevalence rates of substance use as well as anxiety and depression symptomalogy in a low SES and prima rily Hispanic student sample Thi s study also s pecifically examined the relationship(s) between substance use anxi ety, and depressive symptomalogy. This study also contribute s to the current literature by determin ing the extent to which involvement in school based extracurricular activities (e.g., ath letics, performing arts, and special interests clubs) serves as a protective factor against substance use for adolescents who are experiencing anxiety and/or depressive symptomalogy. In other words, the current study attempted to determine if school involv ement operates as a moderator in the relationship between mental health problems and substance use such that involvement in school related activities buffers studen ts experiencing mental health problems from abusing substances. Very few studies have exami ned the relationships between mental health problems and substance use among adolescents while also looking at engagement in school based extracurricular ac tivities. The current study looked at the dynamics between all these variables, while taking into co demographic characteristics (e.g., gender, age, ethnic/racial background, SES)

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7 Identifying specific aspects of school involvement that serve as protective factor s against substance use assists school psychologists in the developmen t and implementation of effective prevention programs. R e s e a r c h Q u e s t i o n s In sum, the research questions examined in the following study include : 1. Among students attending a predominantly low SES high school, what is the rate of adolescent substance use with respect to the f ollowing substances: a. Alcohol (e.g. liquor, beer, and wine) b. Cigarettes c. Marijuana? 2. Among students attending a predominantly low SES high school, what is the percentage of students who have/are experiencing clinical levels of the following mental health prob lems: a. Depression b. Anxiety i. General Anxiety Disorder ii. Social Anxiety Disorder iii. Significant school a voidance ? 3. What are the relationships between substance use and mental health problems such as anxiety disorders and depression among high school students? 4. Is sch ool involvement a moderator in the relationship between mental health problems and substance use such that high levels of school involvement protect students who experience mental health problems from abusing substances?

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8 Limitations The current st udy analyzed an archival dataset that includes data from 10.3% of eligible students at the participating high school. Due to the convenience sampling method used to obtain the data, as well as the requi rement for active parent consent and active student as sent to participate, the students who did participate in the study could differ significantly from students whose parents declined participation. In the current study, the participants were from a predominantly low SES high school and predominantly Hispani c. As a result, the findings of the study might not generalize to a higher SES high school or to other ethnic groups. Furthermore, the sample size for this study is fairly small (139 participants). The small sample size limit s stat istical power, as well as representative of the overall population. Another limitation is that all the information in the archival dataset came from report Additiona l rater biases might occur due to normal mood changes that youth experience during adolescence. Also the assessment instrument students used to report current depressive symptomalogy involves moods in only the past two weeks and not past levels of symptom alogy which might also limit the results of this study. Regarding school involvement, this study does not provide in depth information about every possible extracurricular activity in which students were involved; instead, information is available regardin categories of activities (e.g., performing arts). Contributions to the Literature The current study add s to the literature on substance use anxiety and depressive

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9 symptomalogy as well as student involvement in scho ol based extracurricular activities by comprehensively examining the interrelationships among all four variables. A greater understanding of the relationship between mental health problems and substance use as well as the relationship between school invo lvement in extracurricular activities and substance use adds to the literature by providing more det ailed information on these topics specific to students attending a predominantly low SES high school with a significant Hispanic student population Findin gs relevant to involvement in particular school related activities as a buffer against substance use is crucial to the development of effective school based preventive programs for yout h who are at risk for engaging in substance use. Preventing substance i s essential due to the many deleterious effects of term and long term educational outcomes.

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10 Chapter Two Review of the Literature The following literature review begins with a definition of substance use disorders as well as the prevalence of substance use during adolescence. The relationship s between demographic variables, namely socio economic status (SES), ethnicity, and gender, and adolescent substance use are also discussed. Next, two mental health p roblems, specifically adolescent depressive disorders and anxiety disorders, are defined. The prevalence of specific anxiety disorders (e.g., generalized anxiety, social anxiety, and significant school avoidance) is also reviewed in part to provide a ratio nale for how the specific anxiety disorders to be examined in the current study were selected as foci. Then, the links between mental health problems and substance use among high school students are presented. Finally, implications for school psychologists are discussed by presenting the relationships between mental health problems, substance use and academic achievement and explaining the role of school involvement in extracurricular activities as a potential Over view of Substance Use Substance use during adolescence is a major concern in the United States. Trends in substance use among youth have been examined via the Monitoring the Future Study (MFS) a large scale data collection effort that has been conducted a nnually since 1975. The MFS examines current prevalence rates of substance use among 8 th 10 th and 12 th grade students in the United States. In 2006, nearly 50, 000 students from over 403

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11 secondary schools nationwide participated in the MFS. According to the 2006 MFS results, approximately three quarters of students (72%) have consumed alcohol before twelfth grade, approximately half of American youth (46%) have tried cigarettes before the end of high school, and almost one quarter of twelfth grade student s (22%) are current substance use have also been examined by the Substance Abuse and Mental Health Services Administration (SAMHSA). SAMHSA sponsors an annual survey on substan ce use and health issues and approximately 67, 500 people are interviewed each year. In this annual report, a section is devoted to youth between the ages of 12 and 17 years. In the results from the 2007 National Survey on Drug Use and Health (NSDUH; 2008) the current rate of illicit (e.g. marijuana, ecstasy, cocaine, LSD, and prescription type drugs used nonmedically) drug use in the United States among youth is 9.5% which is nge drinking rates in 2007 were approximately 10%. Youth substance use has been a major problem in life such as socio emotional functioning, health, and academic performa nce (Diego, Field, & Sanders, 2003). Substance abuse disorders are defined by the Diagnostic and Statistical Manual IV (DSM IV TR, American Psychiatric Association, 2000) as: impai rment or distress, as manifested by three (or more) of the following, occurring within a twelve month period: (1) recurrent substance use resulting in a failure to fulfill major role obligations at work, school, or home (e.g., repeated

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12 absences or poor wor k performance related to substance use; substance related absences, suspensions, or expulsions from school; neglect of children or household), (2) recurrent substance use in situations in which it is physically hazardous (e.g., driving an automobile or ope rating a machine when impaired by substance use), (3) recurrent substance related legal problems (e.g., arrests for substance related disorderly conduct), and (4) continued substance use despite having persistent or recurrent social or interpersonal proble ms caused or exacerbated by the effects of the substance (e.g., arguments with spouse about consequences of intoxication, physical fights) ; (p.199). is used and is described as situations in which an individual is cu rrently using and/or has used substances in the past twelve months, but does not necessarily meet the criteria for a substance use disorder. Substance use is usually initiated in adolescence and typically begins with the use of substances such as alcohol and tobacco, then followed by marijuana and other illegal substances (Diego et al., 2003; Kandel, Yamagushi, & Chen, 1992; The National Survey on Drug Use and Health, 2008). A considerable number of adolescents who use substances also report some problems associated with the use of these substances such as going to school and playing sports while under the influence (Zoccolillo, Vitaro, & Tremblay, 1999). Zoccolillo et al. (1999) surveyed adolescents (879 boys and 929 girls) in Canada on problems related to their use of alcohol and illegal drugs and found that of illegal drug users, 94% of boys and 85% of girls reported at least one problem related to the use of drugs.

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13 Prevalence of Substance Use in Adolescence According to the most recent MFS national s urvey of adolescent drug use, i n 2006, the annual prevalence rate of any alcohol use in grades 8, 10, and 12 was 31.8 % 56.3 % and 66.4% of respondents, respectively (Johnston et al., 2007). Alcohol scents and has been consumed by almost three quarters of students by the end of high school. In terms of tobacco use among high school students, almost half of young Americans (47%) have tried cigarettes by twelfth grade and 22% of twelve grade students ar e current smokers. As for eight grade students, 25% have tried cigarettes (Johnston et al., 2007). In 2006, the annual prevalence rate of any use of illicit drug in grades 8, 10, and 12 was 13.2 % 28.1 % and 35.9%, respectively. Even though there was a sli ght decline in the use of certain drugs in 2006, these declines were not found to be statistically significant, suggesting that the use of illicit drugs still merits concern (Johnston et al., 2007). A slight increase in the use of marijuana and heroin amon g twelve grade students was observed in 2006, as were increases in the use of inhalants and cocaine among tenth grade students, and the use of LSD and ecstasy among eight to twelve grade students (Johnston et al., 2007). Relationship between Substance Use and Demographic Characteristics It is important to consider demographic characteristics as well as differences between subgroups when examining the prevalence rate of substance use among high school students, as certain demographic variables are associated with the rate and choice of substance use. Key studies that examined the links between adolescent substance use economic status, gender, and ethnicity/race are reviewed next.

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14 Socio economic status (SES). In the MFS (2007), very small d ifferences were found between substance use among high school students and the average educational differences have been found between other measures of SES, such as family income, and adolescent substance use (Parker, Calhoun, & Weaver, 2000). However, it has been suggested that SES can increase the risk of adolescent substance use in cases of extreme poverty level and when behavior problems are noticeable (Hawkins, C atalano, & Miller, 1992; Mash & Barkley, 2003). It should also be noted that the relationship between adolescent substance use and SES can vary depending on the substance. An increase in the use of cocaine, because of the growth in the prevalence of crack cocaine, was associated with lower SES populations in the 1980s (Mash & Barkley, 2003). This trend is currently less noticeable but still illustrates how such demographic variables can i nfluence the use of particular substances among adolescents. Luthar and Ansary (2005) examined whether engaging in various problem behaviors, including substance use, would have an impact on academic school performance and whether these links would vary in relation to SES. They surveyed 488 tenth grade students from variou s communities in the North East. Among these students, 264 were from an affluent suburban high school (higher SES) and 224 were from an inner city school (lower SES). The schools were chosen to represent both ends of the SES continuum, based on family inco me and level of education. To measure substance Bachman, 1984). The researchers found that substance use, especially cigarette smoking, was higher among adolescents from the higher SES suburban school, and that substance

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15 use had a significant negative relation to academic grades only among the students in the higher SES school (Luthar & Ansary, 2005). Race/ethnicity. In the MFS, significant relationships were found betwee n eighth, tenth, and twelfth grade African American students, significantly lower rates of use of any illicit drugs, alcohol, and cigarettes are found when compared to Caucasian students, especially use of cigarettes. Hispanic students reported higher rates of crack, heroin, and methamphetamine use in grade twelve. I n general, their rates of substance use were higher than African American students but lower than Cauc asian students in twelfth grade. However, in eighth grade, Hispanic youth reported higher rates of drug use (e.g., crack, heroin) than African American and Caucasian students. Various explanations have tance use decrease s by twelfth grade, including that this trend may be due to the high school dropout rate of Hispanic students and/or due to the fact that other ethnic groups initiate substance use later in adolescence (Johnston et al., 2007). In the resu lts from the 2007 National Survey on Drug Use and Health (NSDUH; 2008), the rate of alcohol use in the past month for youth between the ages of 12 and 20 was lowest among Asian youth (16.8%), followed by African American youth (18.3%), Hispanic youth (24.7 %), American Indian and Alaska Native youth (28.3%), and highest among Caucasian youth (32%). combined data from 1996 to 2000 drawn from the MFS to conduct an investigation of ethnic di fferences in substance use among adolescent girls. The authors focused their attention on adolescents who responded that they used alcohol, tobacco, and/or a variety

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16 of illicit drugs (e.g., marijuana, cocaine, and stimulants) in their lifetime, in the las t thirty days, or on a daily basis. Wallace and colleagues (2003) found that substance use was particularly high among Native American adolescent girls, relatively lower among Caucasian, African American, and Hispanic girls, and was the lowest among Asia n girls. The authors also pointed out that this pattern was very similar to the one observed for boys. When looking at substance use and ethnic differences, it is also important to look at variations between subgroups of the same race, as well as potenti al differences in the type of substances with which adolescents experiment. Bettes, Dusenbury, Kerner, James Ortiz, and Botvin (1990) determined differences exist, in terms of tobacco and alcohol consumption, between two Hispanic groups (Dominican and Puer to Rican), Caucasian, and African American adolescents. The authors surveyed 2,125 seventh grade students in various New York City public and parochial schools. All participants were asked to report, on a 9 point scale, their rates of cigarette as well as alcohol consumption (1= never to 9=daily). No significant differences emerged between ethnic groups in terms of cigarette use However, Dominican students had the highest rate of alcohol consumption ( M = 1.81) when compared to Puerto Rican students ( M = 1. 65), Caucasian students ( M = 1.67) and African American students ( M = 1.58). Gender. Johnston et al. (2007) have also found gender differences in the use of substances during adolescence. In general, females report lower rates of illicit drug use and rep ort using fewer types of drugs than males. Males also have higher rates of heavy drinking, whereas differences in the use of cigarettes are less apparent (Johnston et al., 2007). It should be noted, however, that rates of substance use in relation to gende r varies

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17 according to age and grade level In younger grades, differences between genders are less apparent and become more noticeable by the end of high school, which may reflect a developmental phenomenon (Mash & Barkley, 2003). Wallace et al. (2003 ) found similar gender differences. Specifically, among eighth grade adolescents, the rate of substance use between males and females was comparable, however gender differences were noticeable among the twelfth grade participants. During twelfth grad e, mar ijuana and alcohol use were more prevalent among males than females. It should also be noted that within the past decade, the gender gap in substance use among twelve grade students has narrowed (Wallace et al., 2003). In regards to gender differences in the likelihood of developing chemical dependence, Wagner and Anthony (2007) found that males were more likely to develop dependence on marijuana and alcohol than females. However, there were no gender differences with respect to the risk of becoming cocai ne dependent. To arrive at these conclusions, the authors analyzed data from participants ages 15 to 44 years in the Natio nal Comorbidity Survey which was collected between 1990 and 1992. Data were gathered through structured interviews, using the Diagnost ic and Statistical Manual of Mental Disorders, Revised Third Edition criteria to assess drug dependence. In addition to differences in prevalence rates and substance dependence, reasons why people may choose to engage in substance use varies by gender. Fo r instance, females report using alcohol and cigarettes to reduce anxiety (Amaro, Blake, Schwartz, & Flinchbaugh, 2001). This issue is discussed in further detail when looking at the relationships between substance use and anxiety disorders. Motives for wh y adolescents engage in substance were also discussed by Piko (2006). A total of 634 middle and high

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18 school students between the ages of 11 and 19 years participated in this study with approximately equal number of males (50.6%) and females (49.4%). The st udents completed a questionnaire which included questions on smoking and drinking, social influences and social motives. The researcher found that males scored significantly higher than females on social motives for drinking. Adolescent boys were also more In sum, substance use generally starts during the early adolescent years and is partly associated with demographic characteristics. Adolescence is a time of transitions whether the y are physical, psychological, or social which can lead to various stressful life events (Maag & Irvin, 2005). Depression and anxi ety during adolescence are also challenges that warrant attention as they usually emerge during this developmental period. The following sections define depression and anxiety as well as discuss prevalence rates and the i mpact these mental health problems can have on youth. Mental Health Problems during Adolescence Depression and anxiety are two of the most common psychologica l problems that children and adolescents can experience (Huberty, 2008). Current estimates suggest that as many as 15 20% of children and youth have depressive or anxiety problems that warrant direct intervention. According to Huberty (2008), or chronic anxiety or depression during the formative years can result in problems that persist into (p.1473). Internalizing disorders such as depression and anxiety can have negative consequence s besides the immediate symptoms and impairment. Such internalizing disorders have been found to esteem, academic performance, social relationships,

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19 and substance use behavior, as well as elevate risk for developing m ore severe mental health problems and attempting or completing suicide (Merrell, 2008). Overview of Depression According to the Diagnostic and Statistical Manual of Mental Disorders IV (DSM IV TR, American Psychiatric Association, 2000) in order to rec eive a diagnosis of Major Depressive Episode: Five (or more) of the following symptoms have been present during the same 2 week period and represent a change from previous functioning; at least one of the symptoms is either (1) depressed mood or (2) loss o f interest or pleasure: (a) 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); (b) markedly diminished 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); (c) 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; (d) insomnia or hypersomnia nearly every day; (e) psychomotor agitation or retardation nearly every day (observable by others, not merely subjective feelings of restlessness or being slowed down); (f) fati gue or loss of energy nearly every day; (g) feelings of worthlessness or excessive or inappropriate guilt (which may be delusional) nearly every day (not merely self reproach or guilt about being sick); (h) diminished ability to think or concentrate, or in decisiveness, nearly every day (either by subjective account or as observed by others); and (i) recurrent thoughts

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20 of death (not just fear of dying), recurrent suicidal ideation without a specific plan, or a suicide attempt or a specific plan for committ ing suicide (p.356). For this study, the author will examine rates of depressive symptomalogy among high school students and not actual clinical rates of depression. Depressive symptomalogy conceptualizes depression on a continuum and is different from Ma jor Depressive Episode which requires a clinical diagnosis. It is also important to note that even if diagnostic criteria for depression are not met, sub syndromal depressive authors further explain that high self report scores may also indicate impaired functioning and the possibility of the later development of clinically diagnosed disorders. Yet, according to Evans, Van Velsor, and Schumacher (2002), depression may be one of the psychological disorders that is the most overlooked during adolescence. Underidentification and undertreatment are very common during childhood and adolescence (Bhatia & Bathia, 2007; Mufson & Pollack Dorta, 2003). Depressive symptoms have also been a ssociated with various risk factors (e.g., suicide, substance use, and decline in school performance) for youth and affect various aspects of life including peer relationships, family relationships, and educational experiences (Bhatia & Bhatia, 2007; Evans et al., 2002). Prevalence of Depression during Adolescence According to epidemiological studies, the prevalence of depressive symptomalogy and depression in children and adolescents ranges between 1.6% and 8.9% (Angold & Costello, 2001). In 2007, approxi mately 8% of the population between the ages of 12 and 17 experienced a Major Depressive Episode (MDE) and 5.5% of these

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21 youth experienced MDE with severe impairment in one or more of the following areas: chores at home, school, close relationship with f am ilies and their social life (r esults from the 2007 NSDUH, 2008). Depressed mood and individual symptoms of depression are even more common during adolescence (Rushton, Forcier, & Schectman, 2002). Rushton et al. (2002) analyzed the National Longitudinal St udy of Adolescent Health data set, collected from 13, 568 adolescents in grades seven through twelve. The Center for Epidemiologic Studies Depression (CES D: Radloff, 1977) scale was used as the primary measure of depressive symptomalogy. The authors foun d that approximately 30% of the adolescent sample reported depressive symptomalogy and almost 10% indicated moderate to severe depressive symptoms. In the National Comorbidity Survey, the lifetime prevalence of major depression among fifteen to eighteen ye ar olds was 14% with an additional 11% reporting minor depression (Kessle r, Avenevoli, & Merikangas, 2001; Kessler & Walters, 1998 ). Like substance use disorder, rates of depression among adolescents vary with gender, SES, and ethnicity/race. In terms of gender differences, higher rates of depressive diagnoses and symptoms are typically found among females (NSDUH, 2008; Rushton, Forcier, & Schectman, 2002; The National Survey on Drug Use and Health, 2008 ). In 2007, the rate of MDE was considerably higher a mong adolescent females (11.9%) than males (4.6%; NSDUH, 2008). Gender differences specifically emerge during the adolescent years. According to Angold, Costello, Erkanli, and Worthman (1999) depressive disorders are more than twice as common in girls as i n boys by the age of fourteen. The authors explain that these differences can partly be attributed to differences in coping styles and/or hormonal changes during puberty. A meta analysis that looked at

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22 26 studies of youth younger than age 18, found that t he overall prevalence estimates of depression based on model predictions averaged over studies were higher for adolescent girls (5.9%) than for adolescent boys (4.6% ; Costello, Erkanli, & Angold, 2006). Roberts, Roberts, and Chen (1997) examined gender and ethnocultural differences in the prevalence of adolescent depression. The authors surveyed 5,423 middle school students ranging from 10 to 17 years of age and measured depression using the DSM Scale for Depression through questionnaires. They found hig her rates of prevalence among girls with a female: male ratio of 1.4. In terms of ethnic differences, Mexican American girls reported significantly higher rates of major depression (Roberts et al., 1997). No significant interactions between ethnic group an d SES emerged. In sum, the prevalence of depressive symptomalogy and depression in youth between the ages of 5 to 17 years ranges between 1% and 18% (Costello, Egger, & Angold, 2005). Rates of depression vary according to gender, with females experiencing higher rates of depression and more severe symptoms. Even when youth do not meet diagnostic criteria for depression, depressive symptomatology can greatly impact an per formance). Other mental health conditions warranting attention during adolescence include anxiety disorders. Several anxiety disorders that are particularly salient during the adolescent years are discussed in the following sections. Overview of Anxiety Di sorders According to the National Mental Health Information Center (2003), a nxiety disorders are among the most common mental health problems to occur during childhood and adolescence, as about 13% of children and adolescents (ages 9 to 17) experience

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23 some type of anxiety disorder. In the United States, studies examining rates of anxiety disorders in youth estimated the prevalence to be between 10 and 20% (Albano, Chorpita, & Barlow, 2003; Costello & Angold, 1995). Notably, anxiety disorders are highly como rbid with other mental health conditions such as depression; additionally, the comorbidity among various anxiety disorders is particularly high for females (Bittner, Egger, Erkanli, Costello, Foley, & Angold, 2007; Lewinsohn, Zinbarg, Seeley, Lewinsohn, & Sack, 1997). Regarding demographic characteristics associated with anxiety disorders, anxiety disorders are more common in adolescent females than in males (Lewinsohn, Gotlib, Lewinsohn, Seeley, & Allen, 1998; Manassis, Avery, Butalia, & Mendlowitz, 2004). This difference is noticeable after puberty; boys and girls may be almost equally affected during early childhood (Manassis et al., 2004). A different conclusion was drawn by Lewinsohn and colleagues (1998). In this longitudinal study, data indicated that by the age of 6 years, twice as many girls as boys had experienced an anxiety disorder. Of note, little research has looked at childhood and adolescent anxiety disorders and the impact of culture, including the role of ethnicity or race. However, Cooley and constructs among multiethnic youth may influence the expression and severity of anxiety symptomatology as well as their choice According to the Diagnostic and Statistical Manual of Mental Disorders IV (DSM IV TR, American Psychiatric Association, 2000) children and adolescents can be diagnosed with any of ten anxiety disorders: Separation anxiety disorder, panic disorder, agoraphobia, generalized anxiety disorder, social anxiety specific phobia, obsessive

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24 compulsive disorder, posttraumatic stress disorder, acute stress disorder, and anxiety disorder NOS. This study focus ed on generalized anxiety disorder and social anxiety as they are among the most prevalent anxiety disorders du ring adolescence (Costello, Egger, & Angold, 2005). Although simple phobia is the most prevalent of anxiety disorders among youth, it is a very broad category that is difficult to measure. Thus, rates of simple phobia were not examined in the current study Although school avoidance and/or refusal is a not a specific disorder in the DSM IV TR, it was also selected for focus in the current study as it is a symptom in multiple anxiety disorders and associated with risky behaviors such as school failure and su bstance use (Kearney, 2008; Mattis, & Ollendick, 2003). In sum, the current study specifically examine d generalized anxiety disorder, social anxiety and school refusal. Generalized anxiety disorder (GAD). GAD typically has an onset in childhood or adoles cence and a lifetime prevalence rate of 5% (DSM IV TR, American Psychiatric Association, 2000) Rates of GAD may increase with age (Hersen, Thomas, Segal, Andrasik, & Ammerman, 2005). GAD is defined in the DSM IV TR as: Excessive anxiety and worry (appreh ensive expectation), occurring more days than not for at least 6 months, about a number of events or activities (such as work or school performance). The person finds it difficult to control the worry, and the anxiety and worry are associated with three (o r more) of the following si x symptoms (with at least some symptoms present for more days than not for the past 6 months): (a) restlessness or feeling keyed up or on edge, (b) being easi ly fatigued, (c) difficulty concentrating or mind going blank, (d) irritability (e) muscle tension, and (f) sleep disturbance (difficulty falling or staying asleep, or

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25 restless unsatisfyi ng sleep) (p. 476). physical symptoms cause clinically significant distress or impairment in social, occupational, 6). In youth with GAD, anxiety is often focused on school performance and sport activities even when these individuals or their performance are not being judged or evaluated by others (DSM IV TR, APA, 2000). Furthermore, these children and adolescents tend to doubt themselves and redo assignments due to perfectionist tendencies and extreme dissatisfaction with performance. In the current study, rates of anxiety symptomalogy among high school students were examined, in addition to risk levels for clinical d iagnoses of GAD. Symptoms of GAD range the full continuum, while GAD requires a clinical diagnosis and conceptualizes the experience of GAD on a dichotomy. Social anxiety Social anxiety generally has an onset during mid adolescence and a lifetime prevalen ce ranging from 3% to 13% (DSM IV TR, American Psychiatric Association, 2000). Costello et al. (2005) summarized the results of prevalence studies of mental health disorders in youth (ages 5 to 17) published since 1993; prevalence estimates for social anxi ety were between 1% and 12%. Social anxiety is defined in the DSM IV TR as: (a) A marked and persistent fear of one or more social or performance situations in which the person is exposed to unfamiliar people or to possible scrutiny by others. The individ ual fears that he or she will act in a way (or show anxiety symptoms) that will be humiliating or embarrassing. In children, there must be

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26 evidence of the capacity for age appropriate social relationships with familiar people and the anxiety must occur i n peer settings, not just in interactions with adults. (b) Exposure to the feared social situation almost invariably provokes anxiety, which may take the form of a situationally bound or situationally predisposed Panic Attack In children, the anxiety may be expressed by crying, tantrums, freezing, or shrinking from social situations with unfamiliar people. (c) The person recognizes that the fear is excessive or unreasonable. (d) The fe ared social or performance situations are avoided or else are endured with intense anxiety or distress. (e) The avoidance, anxious anticipation, or distress in the feared social or performance situation(s) interferes significantly with the person's normal routine, occupational (academic) functioning, or social activities or relationships, or there is marked distress about having the phobia (p. 456). School refusal/ avoidance. According to Kearney (2008), school avoidance behavior can consist of various beh aviors such as extended absences from school, periodic absences from school or missed classes, chronic tardiness, and intense fear or anxiety about school that leads to future nonattendance. School avoidance has manifested as a symptom of various mental he alth disorders in several studies. For instance, Kearney and Albano (2004) examined a clinical sample of 143 youth between the ages of 5 and 17 years who demonstrated school avoidance behaviors. The authors found that the most common primary diagnoses amon g these youth were separation anxiety (22.4%), generalized anxiety (10.5%), oppositional defiant disorder (8.4%), major depression (4.9%), specific phobia (4.2%), and social anxiety (3.5%). As school avoidance is not a formal psychiatric diagnosis, it is u ndecided how this

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27 behavior should be defined or classified (Kearney, 2008). Kearney and Albano (2004) identified four functions or reasons why children and adolescents might refuse to attend school. The first involves avoidance of school related stimuli that provoke general anxiety and depression, a function often associated with GAD. The second function involves escape from aversive social and evaluative situations in the school environment such as exams or athletic performance. This function generally a pplies to adolescents in middle or high school and is commonly associated with GAD and social anxiety The third function involves pursuing attention from significant others such as parents. This function is less pertinent to adolescents as it is linked to separation anxiety disorder. The final function is most prevalent in older children and adolescents who refuse to go to school in order to engage in more appealing activities such as substance use or spending time with friends. According to Kearney (2008) this fourth function is most often linked to externalizing disorders such as conduct disorder. In addition to these four primary functions, environmental risk factors such as poverty, school climate, and parental involvement, have been found to affect sc hool avoidance behavior (Kearney, 2008). In sum, anxiety disorders are quite prevalent with rates between 10 and 20% in youth (Albano, Chorpita, & Barlow, 2003; Costello & Angold, 1995). Generalized anxiety disorder and social anxiety are among the most pr evalent of anxiety disorders during the adolescent years. School refusal, also known as school avoidance, is also notable as it has manifested as a symptom of multiple mental health disorders including anxiety. Regarding the role of demographic variables, gender is a significant factor as more females than males are diagnosed with anxiety disorders during adolescence. Little empirical research to date has looked at the impact of culture and ethnicity on the

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28 prevalence rates of anxiety disorders among youth. Thus far, the prevalence of substance use and mental health disorders during youth, specifically depression and anxiety, has been discussed as well as the role of demographic variables within the occurrence of these disorders. In the following section, th e links between mental health problems and substance use among high school students are reviewed. Links between Mental Health Problems and Substance Use among Adolescents Epidemiological studies consistently report high rates of comorbid mental health p roblems amongst adolescents with substance use disorders (SUD; Armstrong & Costello, 2002; Kandel et al., 1999; Rohde et al., 1996). Multiple studies have identified clear links between substance use and externalizing behavior problems such as conduct diso rder, oppositional defiant disorder, and attention deficit hyperactivity disorder (Armstrong & Costello, 2002; Fergusson, Horwood, & Ridder 2007; King, Iacono, & McGue, 2004; Lillehoj, Trudeau, Spoth, & Madon, 2005; Young, Friedman, Miyake, Willcutt, Corle y, Haberstick, & Hewitt, 2009). However, links between substance use and internalizing problems are less clear (King et al., 2004). In 2007, among youth between the ages of 12 and 17 who had experienced MDE in the past year, approximately 35% used illicit drugs during the same period when compared to 17% for youth who had not experienced MDE during the past year. This trend was also noticeable for rates of daily cigarette use and heavy alcohol use during the past month. Youth who had been diagnosed with MDE had higher rates of use (4.8% and 3.8%, respectively) when compared with youth who had not experienced MDE (2.3% and 2.2%, respectively; NSDUH, 2008). Some investigators have found that internalizing disorders such as depression and anxiety, particularly in females, are related to substance use (Chassin,

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29 Pitts, DeLucia, &Todd, 1999; King et al., 2004) Notably, t he behaviors and symptoms underlying substance use disorder, mood disorders (e.g., major depressive disorder), and anxiety disorders may contribut e to each other, which has implications for understanding the development of these disorders as well as finding appropriate interventions (Valentiner, Mounts, & Deacon, 2004). The anxiety and mood disorders that are most co morbid with substance use are ma jor depressive disorder and social anxiety ( Valentiner et al., 2004). However, the relationship between substance use and symptoms of most internalizing disorders including anxiety and depression is complicated because, as (p.31). Kaplow, Curran, Angold, and Costello (2001) utilized data from a subsample of children ( N = 936) who participated in the Great Smoky Mountains Study of Youth. These youth were initially intervi ewed at ages 9, 11, and 13 years and followed for four years. The Child and Adolescent Psychiatric Assessment (CAPA) was used in this study to assess substance use and psychiatric disorders (e.g., depression, generalized anxiety, and separation anxiety). No immediate relation was found between overall anxiety symptomalogy and the initiation of alcohol use. However, children with elevated levels of earlier generalized anxiety symptomalogy or depressive symptomalogy during the initial interviews were signifi cantly more likely to initiate alcohol use later on. Some studies have specifically looked at the relationship between cigarette smoking and mental health problems. Chang, Sherritt, and Knight (2005) studied 486 adolescents between the ages of 14 and 18 y ears; approximately two thirds of the sample

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30 were females. The researchers administered a 10 item qu use of cigarettes, and other tobacco products, as well as the Adolescent Diagnostic Interview, which assesses substance use disorder and psychiatric symptoms (e.g., depression and anxiety) in the previous year. Current cigarette smoking was associated with significantly increased odds of having mental health symptoms. More specifically, girls smoking cigarettes reported mor e symptoms of depression and mania. The relationship between depression and cigarette smoking was also examined by Vogel, Hurford, Smith, and Cole (2003) in a study of 98 adolescents ages 16 to 19 years. Approximately half of the sample (20 males and 20 f emales) smoked between one cigarette daily to a pack or more per day. The remaining 58 youth did not smoke. In order to measure the severity of depressive symptomalogy, the Multiscore Depression Inventory (MDI) was administered. Adolescents who received hi gh scores on the total MDI were more likely to smoke, particularly adolescents who scored high on the subscales of helplessness and social introversion. Regarding anxiety, Rohde et al. (1996) found a trend for increased alcohol use in girls who were diagn osed as having an anxiety disorders. Comeau, Stewart, and Loba (2001) also found that trait anxiety among adolescents, which the authors defined as the general tendency to experience anxiety symptomalogy, was a significant predictor of coping motives for c igarette smoking and alcohol use. On the other hand, a stronger relationship between substance use and externalizing behaviors (e.g. ADHD and conduct disorder) in males has been noted in the literature (Poulin, Hand, Boudreau & Santor, 2005).

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31 Regarding l inks between psychopathology and use of illicit drugs, Diego et al. (2003) studied 89 high school seniors and found that adolescents with high self ratings of depressive symptomalogy measured via the CES D (Radloff, 1977) were more likely to smoke cigaret tes, drink alcohol, and smoke marijuana, but not more likely to use cocaine. This association between drug use and mental health problems is also found in other countries. For instance, Poulin et al. (2005) surveyed 12, 771 Canadian students with an averag e age of 15.1 years during 2002 and 2003. Depressive symptoms (measured via the CES D) in males were associated with increased cannabis use but not alcohol or tobacco use, whereas depression was associated with elevated use of all three substances for fema les. Some research has attempted to examine the factors that underlie psychopathology and the various reasons why these factors are associated with substance use. For instance, Comeau, Stewart, and Loba (2001) surveyed 508 adolescents from five secondary (junior and senior high) public schools. A total of 312 adolescents (61.4 % of the sample) reported using alcohol, 192 (37.8%) reported smoking cigarettes, and 154 (30.3%) reported using cannabis in the last year. Personality risk factors of trait anxiety and anxiety sensitivity were associated with alcohol, cigarette, and cannabis use; specifically, youth with these characteristics used substances in order to cope or conform. Taken together, these studies have demonstrated that adolescent substance use oft en co occurs with mental health problems, including depression and either GAD, social anxiety or anxious personality traits. These studies demonstrate that comorbidity issues need to be considered when trying to understand the behaviors that adolescents a re exhibiting and the emotions they are experiencing. More longitudinal research is needed

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32 to understand the relationship between substance use and mental health problems such as anxiety and depression as it is difficult to determine which problem behavio r occurs first and whether these internalizing disorders are a cause or consequence of using substances. Furthermore, studies looking at a variety of substances (e.g., tobacco, alcohol, marijuana, cocaine, and ecstasy) are needed. The majority of studies h ave focused on one or two substances such as alcohol or tobacco. However, looking at a variety of substances and their relationship with internalizing disorders would allow comparisons between categories of substances (e.g., tobacco, alcohol, and marijuana ). Additionally, more research is needed to examine links between substance use and mental health problems among low SES high school students. Functioning and School Services Subs tance use problems and internalizing problems are not only associated with immed iate symptoms such as difficulties in functioning and distress, but also long term consequences with regard to increased psychopathology and substance use. Furthermore, many of these mental health disorders or symptomalogy usually onset during late childhood and adolescence. The school setting offers a natural and logical place to provide help and support to those at risk for developing mental health problems. School psychologis ts and other mental health professionals are uniquely prepared to help with mental health related prevention and intervention efforts in the schools (Evans, Van Velsor, & Schumacher, 2002; Herman, Merrell, Reinke, & Tucker, 2004). In the following sections achievement/performance, relationships between substance use and academic

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33 achievement, as well as the role of school involvement as a possible protective factor in are discuss ed Links between mental health problems and academic achievement. According to Evans overlooked and under survey of 1400 mental health professionals working in public high schools, depression and substance abuse issues were cited as the most serious challenges. Because adolescents with depression often demonstrate errors in information processing, Evans and colleagues (2002) concentrate and think quickly which causes school performance to decline. Depressed and absences hav e the potential to adversely impact their academic achievement (Bhatia in depth interviews were conducted with five depressed adolescents between the ages of 13 and 17 years (F armer, 2002). A major theme that was discussed by these adolescents was the deterioration in academic performance. They explained that this decline in performance was due to difficulties in concentration and comprehension. The constant fatigue as well as t he lack of motivation also made it difficult to complete schoolwork. Furthermore, these adolescents expressed a loss in academic confidence and feelings of failure even though they had above average capabilities before their depression (Farmer, 2002). Fe rgusson and Woodward (2002) examined adolescents between the ages of 14 and 16 with depression and the potential adverse psychosocial and educational impact that depression had during later adolescence and early adulthood. The data utilized in this

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34 study w ere gathered as part of a longitudinal study entitled the Christchurch Health and Development Study. A total of 1265 children born in New Zealand participated in this 21 year longitudinal study. The data from the subsample of 964 youth without missing da ta were analyzed for this study. Between ages 14 and 16, depression was assessed using the self report and parent versions of the Diagnostic Interview Schedule for C hildren. At ages 18 and 21, depression, anxiety, and alcohol abuse was measured using it ems from the Composite International Diagnostic Interview. Educational achievement was assessed using three indicators regarding the age when adolescents withdraw from school, their in volvement in tertiary education, and enrollment in a university level or school dropout rate and higher education pursuit. At age 21, adolescents that were earlier diagnosed with depression had higher rates of school dropout and a reduced likelihood of enrolling in a university level program or another form of tertiary education. More specifically, of the participants who were diagnosed with depression between the ages of 14 and 16, approximately 26% reported leaving school prematurely as opposed to 17% for participants who were not diagnosed with depression. Furthermore, only 22% of participants with depression reported enrolling in a university as opposed to 32% for non depressed participants. It has also been demonstrated in the literat ure that adolescent anxiety negatively impacts academic performance and social functioning (Kessler, Foster, Saunders, & Stang, 1995; Van Ameringen, Mancini, & Farvolden, 2003). Students with anxiety disorders are more likely to doubt their academic compet ence which triggers continuous checking rituals and erasing when working on assignments, thus interfering with their ability to finish

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35 as signments by deadlines (Albano et al., 2003). The time these students spend academically engaged is also affected, as t he anxiety they experience in the classroom triggers overwhelming thoughts of worry which impede their concentration (Albano et al., 2003). A dolescents with anxiety disorders, especially social anxiety are at greater risk for academic underachievement a nd dropping out of school ( Kessler, et al., 1995). Van Ameringen and his colleagues conducted a retrospective study that examined the percentage of individuals that left school prematurely, the reasons why these individuals dropped out of school when they were adolescents, and the degree to which anxiety disorders affected their school functioning as well as their decision to leave school. A total of 201 patients from an anxiety disorders clinic, between the ages of 18 and 65 years, completed a questionnai re that contained questions regarding their highest high school grade completed and reasons why they decided to leave school prematurely. Additionally, each participant was assessed using a structured clinical interview (SCID DSM IV; First, Spitzer, Gibbon & Williams, 1995) and self report questionnaires such as the Beck Depression Inventory (BDI; Beck, Ward, Mendelson, Mock, Erbaugh, 1961) and the State Trait Anxiety Inventory (STAI; Spielberger, Gorsuch, & Lushene, 1970). Approximately 62% of participant s had a primary diagnosis of panic disorder/agoraphobia, 24% had social anxiety and 16% were diagnosed with OCD. Approximately half of the participants that were diagnosed with anxiety reported leaving school prematurely. Of the patients who reported drop ping out of school, 22% reported feeling too nervous in school and in class. Furthermore, a third of the sample reported staying at home for an extended period of time due to their worries and feelings of anxiety. This study demonstrates the detrimental im pact

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36 retrospe ctive design include that participants were asked to recall information from high school. In another study by Woodward and Fergusson (2001), the author s examined the relationship between anxiety disorders during adolescence (ages 14 to 16) and young the same data set presented in Woodward and Fergusson (2002). Between the age of 14 and 16 years anxiety was assessed using the self report and parent version of the Diagnostic Interview Schedule for Children; diagnoses were based on the DSM III R criteria for anxiety disorders. At ages 18 and 21, anxiety and alcoho l abuse were measured using items from the Composite International Diagnostic Interview. Educational outcomes were measured as in Woodward and Fergusson (2002). The authors found significant linear relationships between the number of diagnosed anxiety diso rders between the ages of 14 and 16 and the pursuit of higher education (ages 18 to 21). Of adolescents who were not diagnosed with an anxiety disorder between the ages of 14 and 16, approximately 34% of them enrolled in a university level program; compare d to 26% of adolescents diagnosed with 1 anxiety disorder, 19% with 2 anxiety disorders, and only 13% of adolescents with 3 or more anxiety disorders. Furthermore, association s between earlier anxiety disorder (ages 14 to 16) and later development of menta l health disorders (e.g., anxiety and depression) and illicit drug dependence in young adulthood were noted in this study. Taken together, these studies demonstrate not only the short term negative impact that internalizing disorders such as depression and achievement and educational outcomes, but also the long term consequences that these

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37 use has also been found to have deleterious impact on the academic achievement and school functioning of youth. Links between substance use and academic achievement. Diego and colleagues (2003) examined the relationships between adolescent substance use, academic performanc e, popularity, and depr ession a mong 89 high school seniors. This study was conducted in a primarily middle SES high school in Florida. As for substance use, students were asked to answer on a scale from 1 ( never ) to 4 ( regularly ) how often they used cigarettes, alcohol, marijuan a, and cocaine in the past year. Academic performance was report of their grade point average (GPA). The researchers found that adolescents who engaged in substance use were more likely to have a lower GPA. Substance use has also been associated with lower school attendance (Engberg & Morral, 2006). The researchers used data gathered for the Persistent Effects of Treatment Study Adolescent (PETS A) and used a subsample of 1, 084 adolescents between the ages of 12 and 19 years. PETS A is a longitudinal study that examined the psychosocial outcomes of youth admitted to a substance abuse treatment. Participants were first assessed prior to entering treatment (baseline) and 3, 6, 9, and 12 months follow up assessments were conducte d after baseline. A structured clinical interview, the Global Appraisal of Individual Needs, was administered to all participants. This interview gathers information on factors such as substance use, physical health, and mental health. To assess school sta tus, a single question was asked to participants: which of the following statements best describes your present work or school situation? Answers to this question indicated whether or not the adolescent was currently in school at the time

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38 of each assessmen t interval. Findings suggest that reductions in the frequency of alcohol, stimulants, and other drug use were associated with an increase in the likelihood of school attendance. Interestingly, a reduction in the use of marijuana was not enough to signifi cantly and positively impact school attendance. However, the secession of marijuana use was associated with an increase likelihood of attending school. In addition to adverse e ffects on academic performance and school attendance, adolescents who engage i n substance are more likely to quit school before high school graduation ( Aloise Young & Chavez, 2002). Aloise Young and Chavez (2002) examined the reasons why adolescents decide to drop out of school. A total of 1, 812 youth between the ages of 13 and 21 participated in this study. Approximately half of the participants were males (53%), half were school dropouts, and 63% were Mexican American youth. Substance use was measured using the Clinical Drug Assessment Scale from the American Drug and Alcohol Surv ey (ADAS; Oetting, Beauvais, & Ed wards, 1990). Frequency and intensity of alco hol, marijuana, and cocaine use was assessed in the ADAS. Regarding reasons for leaving school, participants were given a list of various reasons for dropping out of school and a sked to rate these reasons. Some of these reasons included factors such as school bonding, family, friends, grades, and substance use. Approximately 30% of participants reported that their use of substances was a significant contributor to their decision o f dropping out of school. Taken together, these studies demonstrate that the use of substances during effects have been found to be both short term (e.g., lower GPA poor school attendance) and long term (e.g., higher likelihood of dropping out of school, reduced likelihood of

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39 pursuit of higher education). Furthermore these studies demonstrate a need for school psychologists and other school based mental health prov iders to develop prevention and intervention programs that address internalizing disorders and substance use in or der to help students achieve their highest academic potential and integrate them in the school. Kessler et al. (1995) reported that in the Uni ted States, persons with psychiatric disorders account for 14.2% of high school dropouts which further shows that these students need to be proactively involved in the school experience, and in particular need to feel connected to their school, peers, teac hers, and school based mental health providers. Engaging in school based extracurricular activities might be one way that students at risk for experiencing mental health problems might feel more connected to their school and peers. As is discussed in the f ollowing section, participation in such activities might also help serve as a buffer against substance use among students with internalizing disorders. Extracurricular activities and a cademi c performance have been identified as protective factors that reduce the likelihood of substance use during adolescence (Diego, Field, & Sanders, 2003; Sutherland & Shepherd, 2001). On the other hand, adolescents who are not committed to school and who have weak academic records are more likely to use alcohol and drugs, both concurrently and in the future (Bogart, Collins, Ellickson, & Klein, 2006; Bryant, Schulenberg, O'Malley, Bachman, & Johnston, 2003). School based extracurricular activities prov ide a highly structured environment for adolescents in which they can express their identity and develop a social network while being monitored for deviant or delinquent behaviors (Darling, 2005). Thus, school involvement in the current study is defined as participation in school based extracurricular activities such as

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40 sports, performance and fine arts, and academically oriented activities (e.g., student government language ). Mahoney and Stattin (2000) defined highly structured activities as consisting of guided engagement, direction by one or more adult activity leaders, an emphasis on skill development that is continually increasing in complexity and challenge, activity performance that requires sustained active att 115). School based extracurricular activities meet the criteria for a highly structured leisure environment. Such school based extracurricular activities are differentiated from unsupervised activities outsid e of school or activities that are not performed on a regular basis. based extracurricular activities is associated with fewer adjustment problems and may protect against psychopat hology and substance use (Bohnert & Garber, 2007; Eccles & Barber, 1999; Fredricks & Eccles, 2006). Bohnert and Garber (2007) examined whether higher levels of organized activity involvement predicted lower levels of psychopathology, as well as which type of activity involvement predicted lower levels of symptomalogy. A total of 198 adolescents participated in this study. They were first assessed in sixth grade and further assessed annually through twelfth grade. At the time of the first assessment partici pants were, on average age, twelve years old; the majority of the sample (82%) was Caucasian. A semi structured interview was conducted using the Schedule for Affective Disorders and Schizophrenia for School Age Children Present and Lifetime Version (K SAD S PL; Kaufman et al. 1997) to gather information on substance use and psychiatric disorders. The Child Behavior Checklist (CBCL; Achenbach 1991

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41 internalizing and externalizing symptomalogy. school related and community based activities the Adolescent Activity Involvement mothers. This checklist asked mothers to indicate in w hich activities youth were involved during sixth through twelfth grade, with regard to seven extracurricular activities categories (sports, performance/fine arts, prosocial, academic clubs, school involvement such as cheerleading, press, and leadership suc h as student government). The authors found that involvement in organized activities was associated with lower levels of externalizing disorders, less tobacco use and fewer diagnoses of substance use disorder in twelfth grade. However, no relationship betw een involvement in organized activities and lower levels of internalizing symptoms was indicated. Peck, Roeser, Zarrett, and Eccles (2008) examined how extracurricular activity n this longitudinal study, ninth grade participants ( N = 1, 060) were asked to complete a 1 hour interview and a questionnaire. At the end of eleventh grade, the participants ( N = 1, 057) were again individually interviewed and completed a questionnaire. O ne year follow up (19 years old) and 3 year follow ups (21 years old) were conducted after the expected high school graduation date of participants. Approximately half (49%) of the participants were female and more than half (60%) were African American. Th e authors examined how the total amount of time that vulnerable youth (i.e., students at risk for dropping out of the educational system due to their levels of emotional distress, lack of motivation, poverty, and lower levels of parental education) spent i n positive extracurricular activities, and how specific patterns of extracurricular activity involvement during late

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42 adolescence contribute to educational attainments. Activity involvement was assessed using a measure developed by Eccles and Barber (1999) which asked, in terms of frequency, engagement in extracurricular activities in the past year such as school athletic teams, school clubs, community club, volunteer services, spending time with friends, and watching television. The authors found that vuln erable adolescents who were involved weekly in activities such as sports and other school clubs had greater educational resilience and higher rates of later college enrollment whereas engaging in activities such as watching television and hanging out with friends were less likely to lead to educational resilience. Darling (2005) examined whether involvement in school based extracurricular academic goals, and positive attitude s towards school. The data used for this study came from a 3 year longitudinal study of 3, 761 adolescents from six high schools in California that were diverse in terms of school size, socioeconomic background, and ethnicity of students (although the majo rity of the sample was Caucasian) To assess participation in school based extracurricular activities, students were asked to report during the first two years of the project what was the single most important school based activity in which they were invol ved during the year. During years 1 and 2, students were classified as participants if they named a valid school based extracurricular activity. During the third year of the project, students were given a list of 21 school based extracurricular activities and asked to report their levels of participation for each. During year 3, students were classified as participants if they were engaged in at least one of the school based activities listed. Regarding depression, a short version (8 items) of the CES D sca le was

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43 used to measure depressive symptomalogy. To assess substance use, adolescents reported, on a 4 point scale, how often since the beginning of the school they had used alcohol, used cigarettes or chewing tobacco, smoked marijuana, and/or used a drug o ther using three indicators: self report of their school grades, attitudes towards school using a 6 item scale developed for the study, and academic goals using one quest ion: based extracurricular activities were less likely to use substances other than alcohol (e.g. tobacco, marijuana, other illegal drugs). Important to this study, Caucasian students were the most likely to engage in school based extracurricular activities (60%), while Hispanic American students were the least likely to participate in such activitie s (39%). Furthermore, involvement in such highly structured activities was associated with more positive academic outcomes (e.g., better performance in school, more positive attitudes towards school, and the tendency to remain in school longer) and buffer ed students who experienced stressful life events from developing problematic outcomes (e.g., marijuana and hard drug use, reduced academic goals) However, there was no significant based extracurricu lar activities and depressi on Limitations of this study include the failure to examine if involvement in structured activities serves as a moderator in the relationship between depressive symptomalogy and substance use. Moreover, the researchers used a mo dified 8 item version of the CES D scale which might have affected the validity and reliability of the measure.

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44 extracurricular activities in the schools is linked to lower substance us e, as well as more positive academic outcomes and fewer externalizing problems. However, the relationship between involvement in such activities and mental health problems has not been extensively studied. In particular, not much research has looked at t he relationships between adolescent substance use, internalizing disorders (i.e., anxiety and depression) and engagement in school based extracurricular activities among low SES students. Conclusion s Substance use by adolescents adversely impacts various aspects of their lives such as their academic outcomes and educational attainment (Diego et al., 2003; Engberg & Morral, 2006; King et al., 2006), health (The National Survey on Drug Use and Health, 2008), and socio emotional functioning (The National Sur vey on Drug Use and Health, 2008). Furthermore, the prevalence of substance use during adolescence is very high; almost 75% of adolescents consume alcohol before twelfth grade, approximately half of American youth have tried cigarettes before the end of hi gh school, and approximately 35% of twelfth grade students have used illicit drugs (Johnston et al., 2007). Substance use is usually initiated during early adolescence and generally begins with substances such as tobacco and alcohol, followed by illegal d rugs such as marijuana (Diego et al., 2003; Kandel, Yamagushi, & Chen, 1992; The National Survey on Drug Use and Health, 2008). Demographic variables such as gender, SES, and ethnicity/race can influence the rate of substance use as well as the choice of s ubstance use d (Amaro et al., 2001; Bettes et al., 1990; Johnston et al., 2007; Luthar et al., 2005; Parker et al., 2000; Piko, 2006; Wagner et al., 2007; Wallace et al., 2003).

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45 Furthermore, it has been demonstrated in the literature that many adolescents experience psychological problems, with depression and anxiety being two of the most common internalizing disorders (Albano et al., 2003; Costello et al., 2005; Huberty, 2008; Rushton et al., 2002). Current estimates suggest that approximately 15 20% of youth have levels of anxiety and depressive symptomalogy that warrant intervention (Huberty, 2008). The prevalence of depression and depressive symptomalogy in youth ranges from 1% and 18% (Costello, Egger, Angold, 2005). As for anxiety, prevalence rates range widely, from 2% to 33% of children and adolescents (Costello, Egger, & Angold, 2005). Internalizing disorders such as depression and anxiety adversely affect esteem, substance use behavior, academ ic performance, and social interactions (Merrell, 2008). In addition to depression, the current study examine d the specific anxiety disorders of GAD and social anxiety due to their high prevalence during adolescence (Costello et al., 2005). School refusal is also an important focus of the current study as it is a symptom in multiple anxiety disorders, including GAD, social anxiety and specific phobia. Of importance, demographics characteristics such as gender and SES have been found to impact not only the rates of prevalence but also the expression and the severity of anxiety and depressive symptomalogy ( Angold et al., 1999; Cooley, 2004; Costello et al., 2006; Lewinsohn et al., 1998; Manassis et al., 2004; Roberts et al., 1997; Rushton et al., 2002; The Na tional Survey on Drug Use and Health, 2008 ). Additionally, several studies have identified links between internalizing mental health disorders an d substance use (e.g., alcohol, cigarette, and marijuana) during adolescence. However, it is unclear which prob lem behavior occurs first or whether the

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46 relationship is bidirectional. Preventing and ameliorating these mental health problems is important in part due to the deleterious academic outcomes of youth with internalizing disorders and/or substance use histo ries (Albano et al., 2003; Bhatia et al., 2007; Evans et al., 2002; Farmer, 2002; Kessler et al., 1995; Van Ameringen et al., 2003). School psychologists and other school based mental health providers have the opportunity to participate in efforts to prev ent and treat problems such as substance use, anxiety, and depression. Several researchers have found that adolescents who are involved in school based extracurricular activities, that are characterized by structure and supervision while at the same time a llowing youth to socialize and express their identity, are less likely to use substances and demonstrate externalizing behavior problems. Involvement in such activities has also been associated with better educational outcomes (Bohnert et al., 2007; Darlin g, 2005; Eccles et al., 1999; Fredricks et al., 2006; Peck et al., 2008). Links with internalizing forms of psychopathology, such as depression and anxiety, are less clear and in need of further study. Purpose of the Current Study Given that research has demonstrated that the use of substances and the presence of mental health problems, such as depression and anxiety, are common during adolescence, it would be valuable to identify prevalence rate s of substance use (e.g., alcohol, cigarettes, and marijuana) as well as prevalence rates of anxiety and depressive symptomalogy in a low SES population with a primarily Hispanic student populat ion. Thus the current study examine d the use of substances, as well as levels of internalizing symptoms of depression and anxiety, among students in a predominately low SES high school, attended primarily by Hispanic s tudents. The current study also examine d the

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47 links between anxiety and depressive symptomalogy and substance use among this population. Thus the specific relati onships that exist between mental health problems and substance use among a predominantly Hispanic and economically disadvantaged high school student population were examined in order to determine if correlations similar to the ones identified in the lit erature would be found In other words, these links were examine d in order to determine if findings from previous studies generalize to this specific population of high school students. To date, research on the relationship between ment al health problem s, involvement of adolescents in school based extracurricular activity and substance use among adolescents has been limited. Furthermore, when looking at the relationship between substance use and internalizing disorders such as depression and anxiety, th e majority of studies have focused on only one or two specific substances (i.e., tobacco or alcohol). As a result, research has not comprehensively examined substance use, mental health disorders, and engagement in school based activities to determine if f or adolescents experiencing mental health problems, engagement in school based extracurricular activities (e.g., athletics music, dance, student government, and social clubs) serves as a protective factor for substance use. The current study purposefully examine d the relationships between all these variables. Specifically the current study determine d if school involvement moderates the relationship between mental health issues and substance use, such that involvement in school related activities buffers students experiencing mental health issues from using substances. A moderator variable is defined as a variable that has an impact on the relationship between another independent variable (e.g., depression) and the dependent variable (e.g., substance use),

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48 so that the nature of the impact of the independent variable on the dependent variable fluctuates or changes based on the level of the moderator (e.g., involvement in school based extracurricular activities). In other words, this variable has an impact on the strength or direction of the relationship between an independent variable and the dependent variable (Baron & Kenny, 1986; Holmbeck, 1997). I nformation regarding the effect of involvement in school based extracurricular activities on the relationship between mental health problems and substance use is crucial to develop and implemen t effective preventive programs for youth.

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49 Chapter Three Method This chapter begins with a discussion of the participants involved in this study, as well as the m ethods used to select participants. The procedures for data collection are then discussed, including a review of the measures used to collect data. Finally, the variables that are examined in this study, as well as an overview of analysis procedures used are presented. Overview of Setting Participants included in the dataset that was analyzed in the current study were adolescents enrolled in grades nine through twelve at a local high school. The high school that participated in this study is a public scho ol in a large school district. This particular school was selected for participation for the following reasons: considerable ethnic diversity of the student population, including a large number of Hispanic youth, (b) high number of students who are econom ically disadvantaged, and (c) ongoing facilitative relationship between the university research team and the school; in particular, the primary investigator of the larger study had close ties with the high school and was able to influence study design in s uch a way that the research yielded meaningful information for the participating high school. The dataset analyzed in the current study was yielded from a larger study investigating the rate of substance use (e.g. alcohol, tobacco, marijuana, and other il licit

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50 education such as their perception of relationships with classmates and close friends, their participation in school related extracurricular activities and organi zations (e.g., dance, athletics, student government, music, language clubs, and honor societies), and their mental health. Thus the author of this study conduct ed a secondary analysis of an archival dataset. Of note, the author was an instrumental member of the research team that designed the study and collected the data. The local high school that participated in the larger study is considered to be a predominantly low SES school, with approximately 60% of the students receiving free or reduced lunch an d 75% of students qualifying as economically disadvantaged (Hillsborough County Public Schools 2008 2009 School Improvement Plan, 2008). This high school population is also predominantly Hispanic, with 65% of students classified as such. Approximately 18 % of the student population is Caucasian and 10% is African American. There are 1780 students enrolled at this Title I school (Hillsborough County Public Schools 2008 2009 School Improvement Plan, 2008). The total graduation rate for the 2008 2009 year in t his s chool was 57.5%, considerably lower than the rate of 76.3% for the school district and 69.8% for the state average (Florida Differentiated Accountability Program 2008 2009 School Improvement Plan 2008 ). Selection of Participants Certain groups of stu dents were intentionally excluded during data collection. In particular, English Language Learners who were not enrolled in an English course were excluded due their potential limited proficiency in the English language which might affect their ability to comprehend and complete the survey. Students exclusively served in self contained special education classrooms were also excluded due to a higher

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51 incidence of reading difficulties and higher risk of experiencing socio emotional/ behavioral problems while c ompleting the self report questionnaire. To ensure that only students who fit the criteria for participation were included in this study, parental consent forms were delivered only to students enrolled in English courses. Only students who returned the inf ormed consent form with the signature of a parent or a legal guardian were allowed to participate in this study. Students were not paid for their participation. However, incentives were offered to increase the participation rate at the school. Specifical ly, students were informed that names of students who returned signed parent consent forms would be entered in a raffle to win one of four fifty dollar gift cards redeemable at Best Buy. A total of 139 high school students who returned the signed parent c onsent forms and signed the child assent form participated in the current study. This equates to a 10.3% response rate of student participation within the sample targeted for participation ( N = 1353). The demographic characteristics of the sample along wit h the demographic characteristics of the entire school population are presented in Table 1.

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52 Table 1 Descriptive Statistics for Sample (n = 138) and School Population (n = 1780) Variable Sample % School Population % Gender Male Female 25.8 74.2 4 8 52 Ethnicity Hispanic Caucasian African American Asian Multiracial 51.5 25 9.1 6.8 7.6 65 17.64 9.55 1.74 5.79 Grade 9 th 10 th 11 th 12 th 31.3 21.4 22.1 25.2 31 27.9 22.7 18.4 Economically Disadvantaged Yes No 68.9 31.1 75.06 24.94 Note. Students meeting the economically disadvantaged category were determined by having students indicate whether or not they received free or reduced lunch. Procedures Approval to conduct the larger study was obtained from the University of South Florida (USF) Institutional Review Board (IRB) in August of 2008 Approval from the rights. Approval was also obtained from the school district a s well as the local high school in which the study was conducted. A faculty member of the school psychology

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53 program at the University of South Florida was the primary investigator (PI) of the larger study and supervised the data collection process. Prior to data collection, a small pilot study with students attending the high school was also conducted to explore readability issues, time needed to complete the measures, and the clarity of the survey as well as specific self report measures. The first pilot study involved approximately 20 students enrolled in an honors psychology class. Students did not encounter difficulties filling out the questionnaire and had no questions regarding readability. Time of completion was approximately 20 30 minutes. A second pilot study was conducted due to concerns about the representation of students in the first pilot study. The second pilot testing was conducted with 56 students from a general education English class. Similar to the first pilot study, no questions regardin g readability were reported by participants and surveys took approximately 25 to 30 minutes to complete. All surveys completed during the two pilot studies were filed in a cabinet and da ta were not recorded. Prior to data collection, the PI of this larger study distributed letters that described the study within an informed consent form to all students who met the inclusion criteria. and informed consent forms in both Engl ish and Spanish. Active parental consent was a requirement and parents were required to sign and return the consent form in which the potential risks and benefits associated with participation in this study were explained. The parental consent form is incl uded in Appendix A. Data collection took place in October of 2008; the PI and four members of the research team (including the author of this document ) were involved in this process. The

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54 PI compiled a list of all students who had returned signed parental c onsent forms prior to data collection. Hall passes were printed for all eligible participants which gave them permission to leave their classroom to participate in the study. The PI called the participating students by classroom to a large conference room located in the school building. Students completed the surveys in a small group format and d ata were collected on several dates during a one week period. The researchers were careful to leave sufficient space between each student to provide adequate privac y, as the surveys were anonymous. Prior to handing out the surveys, risks and benefits associated with participating in the study were explained to each participant and the student assent form was read aloud to each participant. At this time, students w ere allowed to ask the researchers any questions they had about the study and their involvement. Then, participants were required to complete the student assent form which outlined ethical considerations such as their right to decide whether they want ed to participate in the study or not and their right to withdraw from the study at any point in time during the course of data collection. All signed student assent forms were collected and kept in a box separate from surveys in order to maintain the confident After the student assent forms were signed, surveys packets were handed out to all students. In order to control for order effects, all survey measures included in packets were counterbalanced usin The student assent form is included in Appendix B. The PI and research assistants circled the room during the administration of surveys; participants were reminded to ask questions if any items were unclear or

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55 ambiguous. As part icipants returned the completed surveys, a member of the research team looked quickly for accidently skipped or unanswered sections. However, the members of the research team were careful not to analyze the content of the survey in order to respects the pa Members of the research team signed the pass that had given students permission to leave their classroom to participate in the study, and students were asked to return directly to their classroom. Students were calm and co operative thr oughout the data collection process. Data were entered during t he month of October 2008 and members of the research team randomly checked 15% of the data ( N = 21) for errors. Approximately 99.9% of data had been entered correctly initially; the few error s were corrected immediately. Measures Demographics questionnaire Students completed a demographics questionnaire in order for the researchers to gather information about the personal characteristics of the students in this study. Participants reported t heir gender, ethnicity, age, grade, estimated GPA, and whether or not they receive free or reduced lunch. The specific form used to collect t his information is included in A ppendix C Teen Alcohol and Drug Use Scale (TADUS; Harbor, 2008). In order to measu re how often participants used various substances, participants completed an 18 item self use. The TADUS is included in A ppendix D Item 18 was open ended and provided parti cipants the opportunity to note the use of any other substances that were not included in the questionnaire. This questionnaire was developed by the PI of the larger study, and members of his graduate research team. This measure was developed to include a more

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56 comprehensive list of substances; however the measure was based on the one used in t he Monitoring the Future study which is conducted annually (Johnston et al., 2007). The TADUS consists of a list of substances (e.g., cigarettes, beer, liquor, marijua na, cocaine, crack) that participants indicate they have used during the past year. Responses can range from 1 ( zero occasions ) to 7 ( 40 or more occasions ). The metric of occasions was chosen as it was the one used for the Monitoring the Future study which has been shown to have sound psychometric properties (Johnston et al., 2007). For the purpose of this study, substances were classified into three distinct categories: alcohol, cigarettes, and marijuana. Alcohol use include d the sum total of items involvi ng (a) wine wine coolers or malt beverages (e.g., Smirnoff), (b) beer, and (c) liquor (e.g., vodka, rum, whiskey). Studies were conducted to assess the reliability of the TADUS and the reliability was established using Cronbach a lpha coefficients. The re liability test was based on the data gathered during the pilot study and the coefficient for the entire scale was .82. In the current study, Cronbach alpha Center for Epidemiological Studies Depressi on Scale (CES D; Radloff, 1977). The CES D is a 20 item self report survey that was developed for use in studies of the epidemiology of depres sion. The CES D is included in A ppendix E It was designed to measure depressive symptomatology in the general po pulation and it is not intended to provide a clinical diagnosis of depression. Individuals completing this self report questionnaire are asked to indicate on a 4 point scale, with responses ranging from 0 ( rarely or none of the time) to 3 ( most or all of t he time ), the frequency with which they

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57 Four of the items on the CES D are worded positively to also assess positive pattern of responses and are reversed scored. Total scores can range from 0 to 60 with higher scores indicating the pre sence of more frequent depressive symptoms. Scores of 16 or higher are identified as at risk for a clinical diagnosis of depress ion. If a total of four items or more are missing, the CES D scale should not be used (Radloff, 1977). The CES D has high intern al consistency with a coefficient alpha of .85 (Radloff, 1977). The internal consistency for the CES D in the current simple was also high and (Radloff, 1977), t est re test reliability correlation was the highest ( .67 ) across a 4 week interval and lowest ( .49 ) across a 12 month interval. Higher correlations were not expected as the scale is designed to measure current levels of depressive symptomalogy (during the past we ek). However, it should be noted that in general, higher correlations were observed in participants that had shorter test retest intervals (2 to 8 weeks) than the ones that had longer test retest intervals (3 to 12 months). Factor analyses were conducted to assess the construct validity of the CES D in both adult and adolescent samples (Phillips, Shadish, Murray, Kubik, Lytle, & Birnbaum, 2006; Radloff, 1977). The CES D was found to measure four facets of depression: depressed affect (e.g., lonely, blues sad), positive affect (e.g., hopeful, happy, enjoy), somatic and activity level (e.g., bothered, effort, appetite, sleep), and interpersonal (e.g., unfriendly, dislike). Studies assessing construct validity of the CES D across race/ethnicity were also co nducted ( Posner, Stewart, Marin, & Perez Stable,

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58 2001). Posner and colleagues found the four fac tor model proposed by Radloff provide d an adequate fit to the data for Latino women but not for Latino men. E vidence for the criterion validity of this measure is provided through its positive correlation with other instruments measuring depressive symptomalogy (e.g. Bradburn Negative Affect, and Bradburn Balance; Radloff, 1977). Evidence for convergent validity is also provided due to its positive correlation ( r = .58) in a study in which a total of 1207 students in grades 4 through 12 participated (Doerfler, Felner, Rowlison, Raley, & Evans, 1988). Even though the CES convergent validity has not been thoroughly exam ined and compared to more recent measures such as the Beck Depression Inventory 2 nd Inventory, or the Reynolds Adolescent Depression Scale 2 nd Edition, the CES D has been used innumerous studies examining depression sympt omalogy among adolescents. With regards to factorial validity, each item on the CES D is correlated more highly with the CES D total score than with the Rosenberg Self State Trait Anxiety Inventory total scores (Orme, Re is, & Herz, 1986). Screen for Child Anxiety Related Disorders (SCARED; Birmaher, Khetarpal, Cully, Brent, & McKenzie, 1997). The SCARED is a 41 item self report survey that was developed to measure general anxiety symptomalogy among youth (Birmaher et al., 1997). This self report measure was designed to screen for five different anxiety disorders: generalized anxiety disorder, separation anxiety disorder, panic disorder, social anxiety and school avoidance Individuals completing this self report questionn aire are asked to indicate on a 3 point scale, with responses ranging from 0 ( not true or hardly ever true ) to 2 ( very true or often true ), the degree to which they experienced various

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59 hings working out schoo ppendix F For the purposes of this study, a total of 20 items measuring three of the five factors (generalized anxiety disorders, social anxiety disorders, and significant school avoidance) were administered. For the nine items measuring generalized anxiety symptomalogy, scores can range from 0 to 18, with a score of 9 or above indicating a student is at risk for a clinic al diagnosis of generalized anxiety disorder. For the seven items measuring social anxiety, scores can range from 0 to 14, with a score of 8 or above indicating a student is at risk for a clinical diagnosis of social anxiety disorder. Finally, a total of four items are used to identify students who are at risk for experiencing significant school avoidance. Scores can range from 0 to 8 with scores of 3 or higher indicating a significant risk for experiencing significant school avoidance. However, a speci fic number of missing items allowed for each factor or the total scale to be considered valid was not indicated by the authors of the scale. The developers of the SCARED initially presented the psychometric properties of the 38 item original scale in 199 7. Construct validity was assessed and the SCARED yielded five factors: somatic/panic, general anxiety, separation anxiety, social anxiety and school avoidance (Birmaher, Khetarpal, Cully, Brent, & McKenzie, 1997). The construct validity of the SCARED was also examined in another study using an ethnically diverse sample; the five factor structure identified by Birmaher et al. (1997, 1999) was found to be the best fit for this sample ( Hale, Raaijmakers, Muris, & Meeus, 2005)

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60 In addition, the SCARED demonst rated good criterion validity as the total score was positively correlated with other scales measuring anxiety symptomalogy such as the MASC ( r = .61) and the RCMAS ( r = .65; Boyd, Ginsburg, Lambert, Cooley & Campbell, 2003). Discriminant validity, both wi thin the five anxiety disorders and between anxiety disorders and other psychiatric disorders (disruptive disorders and depression) was also demonstrated (Birmaher et al., 1997). However the social factor did not discriminate well between patients with so cial anxiety and other anxiety disorders. A replication study was conducted using a new clinical sample of youth to assess the psychometric properties of a modified 41 item version of the SCARED in which 3 items were added to the social anxiety subscale to increase the discriminant validity (Birmaher, Brent, Chiappetta, Bridge, Monga, & Baugher, 1999). In terms of reliability, the 41 item total SCARED scale has high internal consistency (coefficient alpha= .90). For each of the five factors, the revised v ersion of the SCARED also demonstrated good internal consistency with coefficients ranging from .78 to .87 (Birmaher et al., 1999). Test retest reliability across a 4 day to 15 week interval with a median of 5 weeks, was also high ranging between .70 and .90 for the five individual factors and .86 for the total score (Birmaher et al., 1997). The internal consistency and test retest reliability of the 41 item version of the SCARED was also assessed in an Afr ican American adolescent sample, in which a tota l of 35% of the student population liv ed below the poverty level (Boyd et al., 2003). In this sample, the SCARED yielded borderline to excellent internal consistency with a coefficient alpha of .89 for the total scale and coefficient alphas ranging between .56 ( School Avoidance ) and .80 (Generalized Anxiety and Social Anxiety ) for each of the three subscales used in the

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61 current study. The internal consistency for the generalized anxiety and social anxiety subscales in the current sample were comparable to t he coefficient alphas obtained in previous studies looking at the psychometric properties of the SCARED. Coefficient alpha for the generalized anxiety subscale was .82, and .80 for the social anxiety subscale. In the current sample the internal consistency for the school avoidance subscale was poor (.38), and lower than the values obtained in previous research (Birmaher et al., 1997; Boyd et al., 2003). In prior research, t est retest reliability over a period of six months for the total score was .47 ( Boyd et al., 2003 ) Test retest reliability for each of the three subscales used in the study conducted by Boyd and colleagues (2003) was .36 ( School A voidance ), .47 ( Social A nxiety ), and .48 (Generalized Anxiety). In general, support for the reliability of the school avoidance subscale appears weak est Participati on in School Related Activities Questionnaire (PSRAQ; Harbor, 2008). A total of f in school related activities and organiza tions (e.g., dance, music, athletics, drama, student government). Item 14 was open ended and provided participants the opportunity to note any other involvement in school related activities that were not included in the questionnaire. The PSRAQ is included in A ppendix G Response s range from 0 ( never ) to 5 ( three or more times a week ). This scale was also developed by the PI of the larger study and other members of the research group. Because the measure is new, its reliability and validity have not been pr eviously examined. In order to evaluate the internal consistency reliabili ty of the PSRAQ, Cronbach alpha coefficients were calculated for each cluster created for use in the current study

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62 Consistent with prior research (e.g., Bohnert & Garber, 2007; Darl ing, 2005; Peck, Roeser, Zarrett, & Eccles, 2008), clusters representing mean involvement in various types of activities were analyzed in the current study. To determine which of the items on the PSRAQ constitute each cluster, an exploratory factor analys is (EFA) was conducted using 12 items from the PSRAQ. The two items that were excluded were ; consistent with prior research (e.g., Bohnert & Garber, 2007; Darling, 2005), athl etic involvement was purposefully analyzed separately (i.e., a 1 item indicator). The results of the EFA suggested the presence of four factors, each with eigenvalues exceeding 1.0. However, only two items loaded sufficiently (i.e., factor loadings at o r above .30 ) on the fourth factor (eigenvalue = 1.09, % of variance = 9.14); thus, this factor was not retained for further analyses. Of the two items that loaded on this fourth factor, one (school publications) loaded sufficiently on another factor, and t he second (ROTC) did not relate to any other item. Therefore the low frequency activity of ROTC was excluded from further analysis. Factor one (eigenvalue = 2.92, % of variance = 24.35) consisted of four items that involved prosocial and academically or iented activities. The internal consistency for the four items (i.e., community service, student government, language, and academic clubs) on this factor referred to as prosocial/ academically oriented activities throughout the remainder of the study was .62. Factor two (eigenvalue = 1.50, % of variance = 12.47) consisted of four items that involved special interests activities The internal consistency for the four items (i.e., school publications, business/career, social clubs, and h obby clubs) on this factor, referred to as special interests clubs throughout the remainder of the

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63 study was .53. Factor three (eigenvalue = 1.28, % of variance = 10.63) consisted of three items that involved performing arts activities. The internal consistency for the thre e items (i.e., music, drama, and dance) on this factor, referred to as performing arts throughout the remainder of the study was .58. In sum, f or the purpose of this study, school involvement was classified into four distinct categories: athletic activit ies performing arts (i.e., music, drama, and dance), prosocial/academically oriented activities (i.e., academic clubs, language, studen t government, and community service ), and special interests clubs (i.e., school publication, hobby clubs, social clubs, and business/career). Variables The measures discussed previously were employed as indicators of the variables relevant to this study. Some of the variables such as rate of substance use and mental health problems are bidirectional and can be conceptua lized as either independent or dependent varia bles. However, this study examine d substance use as an outcome variable. Independent. Several independent variables were studied. The first set of variable s involve information on demographic characteristics of the participants, more specifically, gender (0= Male; 1= Female), socioeconomic status (1 = receiving free/reduced lunch; 2 = not receiving free/reduc ed lunch), and ethnicity/race (1= African American/Black; 2= Asian/Pacific Islander; 3= Hispanic; 4= Other [e.g., Native American, multi racial], and 5 = White) The second set of independent variable s health problems in particular, anxiety and depressive symptomalogy. Scores were

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64 analyzed in their continuous and dichotomo us forms, using the aforementioned cut off scores for the latter. Dependent. The main dependent variable in this study was substance use in p articular alcohol, cigarette and marijuana. Moderator. This study tested a moderator variab le which is school involvement (i.e., school based extracurricular activities). School involvement could serve as a protective factor in the relation between substance use and mental health issues, namely depression and anxiety. This study sought to invest igate if inv olvement in school based extracurricular activities such as athletics, performing arts, and special interest clubs help ed protect students who experience mental health problems from abusing substances. Scores of school involvement were analyzed in the ir continuous forms. Overview of Analyses A series of statistical analyses were conducted to answer the four research questions Descriptive analyses were conducted for questions one and two, correlational analyses for question three, and predicti ve analyses for question four. Question 1: Among students attending a predominantly low SES high school, what is the rate of adolescent substance use with respect to the following substances : a. Alcohol (e.g., liquor, beer, and wine) b. Cigarettes c. Marijuana? D escriptive analyses. Frequen cies were obtained for all the substance use

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65 variables o f interest. For c igarette alcohol use, an marijuana use, frequency distribution data were presented using the following many occasions have you consumed liquor /beer/wine or wine coolers or malt beverages 1 (zero occas ions), 2 (one to two occasions), 3 (three to five occasions), 4 (six to nine occasions), 5 (10 to 19 occasions), 6 (20 to 39 occasions), and 7 (40 or more occasions). Question 2: Among students attending a predominantly low SES high school, what is the pe rcentage of students who have/are experiencing clinical levels of the following mental health problems: a. Depression b. Anxiety i. General Anxiety Disorder ii. Social Anxiety Disorder iii. Significant school avoidance? Descriptive analyses. Frequency distribution s w ere p r oduced for rates of anxiety and depressive symptomalogy among the sample. For depressive symptomalogy, frequency distribution data w ere presented in two forms: first, a distribution among each score within the complete range of score s and second, a distr ibution when using the data depression (as defined by the aforementioned cut scores) Each question allowed the respondent to answer 0 (less than 1 day) 1 (1 2 days) 2 (3 4 days) or 3 (5 7 days) For

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66 anxiety symptomalogy, frequency distribution data w ere also presented in two forms: first, a distribution among each score within the complete range of score s and se cond, distribution when using dichotomized variables i eneralized A nxiety D isorder Social Anxiety Disorder, and Significant School Avoidance (as defined by the aforementioned cut scores) Each question allowed participants to answer 0 ( not true or hardly ever true ), 1 ( somewhat true or sometimes true ), or 2 ( very true or often true ). Question 3: What are the relationships between substance use and mental health problems such as anxiety disorders and depression among high school studen ts? Correlational analyses. In order to determine the relationship (if any) between adolescents experiencing anxiety and depressive symptoms and their engagement in substance use (as defined as 3 variables: alcohol, cigarette and marijuana) Pearson p roduc t m oment correlations were calculated Correlation analyses in the current study employ ed one dichotomous variable (i.e., substance use) and one continuous variable (i.e., symptoms of depression or anxiety disorder). When one variable is dichotomous and th e other variable is continuous, a Pearson correlation is equivalent to a point biserial correlation. The coefficient can range from 1 to +1 with coefficients closer to 1 indicating a negative relationship between the two variables and coefficients close r to +1 indicating a positive relationship, and finally a coefficient equal to or close to 0 indicating no linear relationships between the two variables of interest.

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67 Question 4: Is school involvement a moderator in the relationship between mental healt h problems and substance use, such that high levels of school involvement protect students who experience mental health problems from abusing substances? Correlational analyses. To first determine the presence of bivariate relationships between school ba Pearson correlations were calculated between involvement in each of the four types of three substance categories (with student data retained in its continuous form). Logistic r egression analyses. T he dependent variables in the present study (alcohol use, cigarette use, and marijuana use) were eventually coded as categorical variables (used vs. no t used) and therefore logistic regression analysis was used to test the relationships between substance use, mental health problems, and involvement in school based extracurricular activities. For each outcome variable, the demographics variables of gend er, grade, SES, and ethnicity were entered first and served as control variables. Then, one of the four mental health problems variables was entered (i.e., depression, generalized anxiety disorder, social anxiety disorder, and school avoidance) as well as one of the four potential moderator variables (i.e., prosocial/academically oriented activities, performing arts, special interests clubs, and athletics). The interaction of the two variables that were entered in the previous steps (e.g., depression and pr osocial/academically oriented activities) was then added into the model. This process was repeated using each two variable combination of mental health problems and involvement in school based extracurricular activities. The an alyses of inte raction terms

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68 were used to determine if there were significant interactions between different levels of the independen t variables (e.g., depression*prosocial/ academically oriented activities).

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69 Chapter Four Results Overview This chapter begins with a discussio n of the treatment of the data. Then, prevalence rates of substance use among students in 9 th to 12 th grade in a predominantly low SES high school are provided. Frequencies were obtained for all three variables of interest: alcohol (i.e., wine, beer, and l iquor), cigarettes, and marijuana. Additionally, the frequency and percentage of students who were at risk for experienc ing clinical levels of depression, generalized anxiety disorder, social anxiety disorder, as well as school avoidance are provided. Fre quency distributions are presented in two forms: distribution for each score within the complete range of scores and a distribution using the data in dichotomous form (at risk vs. not at risk) based on clinical cut point scores. Next, correlations between symptoms of anxiety and depression, student use of substances, and based extracurricular activity involvement are presented. Finally, results from logistic regression analyses conducted to examine the extent to which involvement in school based extra curricular activities is a moderator of the relationship between mental health problems and the engagement in substance use are presented. Treatment of the Data Graduate student members of the research team involved in the data collection for t he larger study entered the data into SPSS and randomly checked approximately 15% of the entire dataset for accuracy. Approximately 99.9% of the data had been correctly

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70 entered initially with the few mistakes being corrected immediately. Furthermore, the dataset was also reviewed for scores that fell outside the possible range of scores. This analysis was conducted by reviewing descriptive statistics for all variables of interest. CES D data for 1 of the 139 participants could not be used because more tha n four items were incomplete. Thus, the final sample retained for all data analyses consisted of 138 participants. Descriptive Analyses Frequency distributions were calculated to determine specific rates of substance use in the sample within the past yea r The frequency distribution for substance use was obtained for data retained both in continuous form and in dichotomized form (i.e., use or no use in the past twelve months) Based on the infrequent use of most of the substances that were included in the TADUS (e.g., ecstasy, cocaine, and heroin) as discussed by Snodgrass (2009), data were collapsed by combining substances into three clusters: alcohol (i.e., wine/wine coolers/malt beverages, beer, and liquor), cigarettes, and marijuana. The remaining 12 c ategories of substances were therefore not analyzed. The internal consistency reliability for the 3 item alcohol cluster was .77 in the current sample. The internal consistency reliability for marijuana and cigarettes was not calculated as both of these cl usters included on ly one item. Table 2 displays the frequency of substance use (i.e., alcohol, cigarettes, and marijuana) with data presented in continuous form. Frequencies are provided for each of the seven different response choices that were provided to participants with choices ranging from 1 (zero occasions) to 7 (40 or more occasions).

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71 Table 2 Frequency of Substance Use on a Continuum (n = 138) Cigarettes Marijuana Alcohol Number of Times Used in the Last 12 Months Wine Beer Liquor 0 115 111 75 91 84 1 2 9 8 31 25 19 3 5 2 6 13 7 11 6 9 4 1 7 4 3 10 19 1 3 5 6 7 20 39 1 3 4 1 8 40 + 6 6 3 3 5 Missing Data 0 0 0 1 1 Total 138 138 138 138 138 The majority of participants reported engaging in substance use on zero occasions. It should be noted that 83.3% of the students in the sample reported not smoking a cigarette in the past year. Comparably, 80.4% of students in the sample reported not using marijuana in the past year. As for alcohol, the substance that was reported being us ed the least was beer, with 66% of participants reporting never having consumed a beer within the past 12 months. A wine/wine cooler was the alcoholic beverage most often consumed by the sample, with 46% of participants reporting having consumed wine and/ or wine coolers within the past year. Notably, there was limited variability among frequency of use reported (e.g., reporting use of the substance 1 to 2 times or 6 to 9 times); most participants who reported any use in the past year indicated they used th e substance only 1 2 times. Due to the limited variability of responses, the frequency of substance use was

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72 also dichotomized into two categories: use on zero occasions, and use on any occasion (1 or more) in the past year. This resulted in two categories of data indicating that the substance had been used within the past year, or had not been used within the past year. Table 3 displays frequency of substance use by category (i.e., alcohol, cigarettes, and marijuana) within the sample with the frequencies of substance use dichotomized into two response categories (yes and no). Table 3 Frequency of Substance Use in its Dichotomous Form (n=138) Yes No Substance Use Category N % N % Alcohol 76 55.1 62 44.9 Cigarettes 23 16.7 115 83.3 Marijuana 27 19.6 111 80.4 Note. The dichotomous form was determined by categorizing all students who reported using substances at least once or mo re into one group (i.e., Yes) and all students indicating never using substances into a second group (i.e., No) Alcohol was the most frequently used substance by participants, with 55.1% of the sample acknowledging having consumed some form of alcohol (Wi ne/Wine Coolers/Malt Beverages, Beer, and Liquor) at least 1 to 2 times within the previous year. As mentioned earlier only 16.7% and 19.6% of the sample reported having consumed c ig arettes or marijuana, respectively, at least 1 to 2 times within the prev ious year. Frequency distributions were also constructed to determine specific rates of anxiety and depressive symptomalogy among the sample. The frequency distribution for depressive and anxiety symptomalogy was obtained with data presented both in conti nuous and dichotomized form. Table 4 displays the frequency distribution of depressive symptomalogy for each score within the complete range of scores.

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73 Table 4 Frequency of Depressive Symptomalogy within Com plete Range of Scores (n = 138) Score n % 0 1 0.7 1 1 0.7 2 1 0.7 3 4 2.9 5 6 4.3 6 4 2.9 7 5 3.6 8 7 5.1 9 6 4.3 10 4 2.9 11 4 2.9 12 7 5.1 13 2 1.4 14 1 0.7 15 7 5.1 16 4 2.9 17 6 4.3 18 3 2.2 19 4 2.9 20 5 3.6 21 9 6.5 22 7 5.1 23 5 3.6 24 3 2.2 25 4 2.9 26 4 2.9 28 5 3.6 29 3 2.2 30 3 2.2 31 1 0.7 32 4 2.9 34 2 1.4 35 1 0.7 36 2 1.4 37 1 0.7 40 1 0.7 42 1 0.7 Note. Data obtained from the CES D are presented on a continuum depicting the di stribution among each score within the complete range of scores.

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74 In this sample of adolescents, total depressive symptomalogy scores ranged from 0 to 42. Each of the 20 items on the CES D asked participants to indicate on a 4 point scale with responses ra nging from 0 (less than 1 day) to 3 (5 7 days), the frequency with which they experience such emotions, thoughts, and behaviors during the past week. Total scores could range from 0 to 60 with higher scores suggesting the presence of more frequent depressi ve symptoms and the endorsement of more symptoms associated with depression. Total depression scores were employed in analyses that examine the correlation between depressive symptomalogy and substance use. Regarding the distribution of the depression tota l score index, the mean score was 17.59 ( SD = 9.36), median score was 17, and the mode 21 Frequenc ies of total scores were fairly evenly distributed with a relatively distinct peak (skew = 0.29, kurtosis = 0.62). For anxiety symptomalogy, the frequency d istribution was also analyzed by examining the composite scales in continuous forms. Table 5 displays the frequency distribution s of total scores for the three anxiety subscales (i.e., generalized anxiety, social anxiety, and school avoidance).

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75 T able 5 Frequency of Anxiety Symptomalogy Within the Complete Range of Scores ( n = 138) Generalized Anxiety Social Anxiety School Avoidance Score n % n % n % 0 4 2.9 9 6.5 13 9.4 1 6 4.3 10 7.2 30 21.7 2 12 8.7 11 8.0 42 30.4 3 8 5.8 12 8.7 26 18.8 4 11 8.0 14 10.1 14 10.1 5 14 10.1 19 13.8 8 5.8 6 5 3.6 17 12.3 4 2.9 7 8 5.8 1 3 9.4 0 0.0 8 6 4.3 8 5.8 1 0.7 9 15 10.9 10 7.2 10 14 10.1 2 1.4 11 14 10.1 5 3.6 12 7 5.1 5 3.6 13 6 4.3 2 1.4 14 2 1.4 1 0.7 15 2 1.4 16 2 1.4 17 2 1.4 Total 138 100 138 100 138 100 Note. Data obtained from the SCARE D are presen ted on a continuum depicting the distribution among each score within the complete range of scores for each of the three factors (i.e., Generalized Anxiety Disorder, Social Anxiety Disorder, and Significant School Avoidance). In the current sam ple of adolescents, total generalized anxiety symptomalogy scores ranged from 0 to 17. Each of the nine items on this subscale asked participants to indicate on a 3 point scale with responses ranging from 0 (not true or hardly ever true) to 2 (very true or often true), the degree to which they agreed with or experienced various emotions, thoughts, and behaviors in the last three months. Total scores could range from 0 to 18, with higher scores suggesting more frequent and severe symptoms of generalized anxi ety. Frequenc ies of total scores were fairly evenly distributed, however, two peaks

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76 we re somewhat noticeable (skew = 0.10, kurtosis = 0.84). Specifically, m ost common total scores f or g eneralized anxiety symptomalogy fell between 2 and 5 as well as 9 an d 11 with a median score of 8, a mean of 7.37 ( SD = 4.17), and a mode of 9. As for total social anxiety symptomalogy (7 items), scores ranged from 0 to 14. T he most frequent total scores for social anxiety symptomalogy fell between 4 and 7 with a median score of 5, a mean of 5.37 ( SD = 3.32), and a mode of 5. Frequenc ies of total scores were fairly evenly distributed, with the exception of a few relatively high scores (skew = 0.39, kurtosis = 0.37). Total school avoidance symptomalogy (4 items) scores r anged from 0 to 8. T he majority of total school avoidance scores fell between 0 and 4, with a median score of 2, a mean of 2.32 ( SD = 1.53), and a mode of 2. The distribution was somewhat positively skewed, with relatively few high scores (skew = 0.78, kur tosis = 0.76). In order to examine what percentage of the sample was identified as at risk of risk point scores suggested by the a uthors of b oth measures. Table 6 for a clinical diagnosis of depression, generalized anxiety disorder, social anxiety disorder, and/or significant school avoidance.

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77 Table 6 Frequency of Anxiety a nd Depressive Symptomalogy According to Cut Point Scores ( n = 138) Yes At Risk Category No Low Risk Category N % N % Depression 78 56 .5 60 43.5 Generalized Anxiety 64 46.4 74 53.6 Social Anxiety 33 23.9 105 76.1 School Avoidance 53 38.4 85 61.6 Note Data w ere categoriz ed into two categories for all four mental health problems based on whether or not participants met the aforementioned cut diagnosis With regards to depression and generalized anxiety disorder, approxi mately half and 46.4% of adolescents, respectively, falling in that category. Regarding school avoidance, 38.4% of the participants fell in the at risk category. Fin ally, 23.9% of disorder. Correlational Analyses To examine the relationships between anxiety or depressive symptoms and engagement in substance use (i.e., alcohol, ciga rettes, and marijuana), Pearson correlation coefficients were calculated. Independent variables (i.e., depression, generalized anxiety, social anxiety, and school avoidance) were treated as continuous variables, whereas for the dependent variables (i.e., a lcohol, cigarettes, and marijuana use) data were Correlation coefficients are presented in Table 7

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78 Table 7 Correlation between Mental Health Symptomalogy and Substance Use ( n = 138) mmmmmmmm. Alcohol Cigarettes Marijuana 1. Depression .11 .14 .11 2. Generalized Anxiety .02 .00 .04 3. Social Anxiety .13 .06 .12 4. School Avoidance .06 .17* .17* Note Fo r all three substances analyses were conducted using data dichotomized into two categories (use or no use) due to the limited variability in student responses. However, data were kept in its continuous form for all four mental health problems. p < 05 O nly a few correlations were statistically significant. As predicted, school avoidance was positively correlated with use of cigarettes ( r = .17, p < .05) and marijuana ( r = .17, p <.05). This indicates that higher scores on the school avoidance measure cor relate with use of cigarettes and marijuana. Symptoms of depression, generalized anxiety, and social anxiety were not related to alcohol consumption, cigarette use, or marijuana use. To determine the relationship between school based extracurricular activi ties and self reported use of alcohol, cigarettes, and marijuana, Pearson correlation coefficients were calculated. Again, the dichotomized form of the dependent variable, substance use, was used for correlation analyses. Measures of engagement in school based extracurricular activities were treated as continuous variables. Correlation coefficients are presented in Table 8

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79 Table 8 Correlation between Participation in School Based Extracurricular Activities and Substance Use ( n = 138) mmmmmmmm. Alcohol Cigarettes Marijuana 1. Prosocial/Academic Clubs .08 .24** .15 2. Special Interests Clubs .07 .19* .06 3. Performing Arts Clubs .06 .01 .01 4. Athletics Clubs .06 .09 .16 Note Substance use data dichotomized into two categories (use or no use) were used for the analyses and categories of school based extracurricular involvement were scaled using data into continuous form. p <.05. ** p <.01 All significant correlations occurred in the expected directions. Specifically, cigarette use had a significant, inverse relationship with involvement in prosocial/ academic clubs ( r = .24, p <.01) This indicates that the more adolescents are involved in prosocial/academically oriented sch ool based extracurricular activities, the less likely they are to report smoking cigarettes. Cigarette use was also significantly negatively correlated with involvement in special interest clubs ( r = .1 9 p <.05) This also indicates that the more adolesc ents are involved in special interest clubs at school, the less likely they are to smoke cigarettes. It should be noted that none of the four school based extracurricular activity clusters w as alcohol or marijuana use However, it should be highlighted that there was a trend toward a significant result with regards to the correlation between marijuana use and involvement in athletics ( r = .16, p = .07). Predictive A nalyses To examine the relationships between the TADU S (i.e., alcohol, cigarettes, and marijuana), PSRAQ (i.e., Prosocial/Academic, special interests, performing arts, and athletics), CES D tot al score, and the total score for three of the subscales on the

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80 SCARED (i.e., generalized anxiety disorder, social anxiety disorder, and school avoidance), Pearson correlation coefficients were calculated. Intercorrelations are presented in Table 9.

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81 Table 9 Intercorrelations between Substance Clusters on TADUS, School Involvement Clusters, SCARED, and CES D scores I tem mmmmmmmm. 1 2 3 4 5 6 7 8 9 10 11 1. Alcohol Use 1 2. Cigarette Use .37** 1 3. Marijuana Use .41** .56** 1 4. Depression .11 .14 .11 1 5. Generalized Anxiety .02 .00 .04 .56* 1 6. Social Anxiety .13 .06 .12 .42** .52** 1 7. School Avoidance .06 .17* .17* .48** .41** .33** 1 8. Prosocial/Academic Clubs .08 .24** .15 .14 .02 .01 .12 1 9. Special Interest Club s .07 .19* .06 .15 .09 .14 .09 .41** 1 10. Performing Arts Clubs .06 .01 .01 .01 .09 .05 .17* .26** .21* 1 11. Athletics .06 .09 .16 .14 .08 .21* .18* .28** .38** .15 1 Note. p <.05. ** p <.01

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82 Independent variables were assessed for multicollinearity, prior to conducting the logistic regression analyses. Multicollinearity occurs when strong correlations exist between independent variables. When the independent variables are significantly alike, it becom es difficult to determine which of the independent variables is producing the effect on the dependent variable. The existence of multicollinearity is undesirable, as it can lead to inaccurate regression coefficients and can therefore result in erroneous co nclusions regarding the relationships between the independent and dependent variables (Ying, Peng, Lee, & Ingersoll, 2002) Correlations between independent variables ranged from 21 to .56, and were in general not strong enough to indicate the presenc e of multicollinearity according to guidelines set forth by Myers (1990). Within the anxiety subscale s correlations ranged from .33 to .5 2 which also fail to indicate multicollinearity These subscales appear to measure distinct constructs and such resul ts confirm the need to analyze each of the three anxiety subscales separately. Regarding types of extracurricular activities, correlations between the four clusters (determined using factor analysis) ranged from .15 to .41. These correlations also confirm the need to analyze each of these school based extracurricular activities clusters separately. The highest correlation between two independent variables was the correlation between depressive symptomalogy and generalized anxiety diso rder with a coefficient of .56. To test the relationships between substance use (i.e., alcohol, cigarettes, and marijuana) each of the four mental health problems, and involvement in school based extracurricular activities, data were subjected to a series of logistic regression analyses. For each outcome variable the demographics variables of gender, grade, SES, and ethnicity were entered first and served as control variables. Then, one of the four mental

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83 health problems variables was entered (i.e., depression, generalized anxi ety disorder, social anxiety disorder, and school avoidance) as well as one of the four potential moderator variables (i.e., prosocial/academically oriented activities, performing arts, special interests clubs, and athletics). The interaction of the two va riables that were entered in the previous steps (e.g., depression and prosocial/academically oriented activities) was then added into the model. This process was repeated using each two variable combination of mental health problems and involvement in sch ool based extracurricular activities. Logistic regression analyses were conducted for each of the three substances (i.e., alcohol, cigarettes, and marijuana) to determine which of the two variable combinations of mental health problems and involvement in school based extracurricular activities, if any, are most predictive of whether or not high school students use substances. The results pertinent to the interaction terms are presented in detail in Table 10 (criterion: alcohol use), Table 11 (criterion: ci garette use), and Table 12 (criterion: marijuana use) Notably, significant differences obtained in the logistic regression analyses should be interpreted with caution given the large number of comparisons that were made, which increases the possibility of making a Type I error. For the dependent variable alcohol use, when all seven covariates, main effects, and each two variable combinations (e.g., depression*prosocial/ academically oriented activities, school avoidance*athletic activities, generalized anx iety*performing arts, social anxiety*special interest clubs, etc.) were considered together in separate models, none of the sixteen interaction terms was statistically significantly ( p > .05). The results indicated that students with varying levels of anxi ety disorders and depression were similarly likely to use alcohol regardless of the extent of their participation in any of the

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84 four types of extracurricular activities. It should also be noted that when each independent variable was considered independen tly, none of the focal independent variables or potential moderators significantly predicted alcohol use. Thus, alcohol was e involvement in extracurricular activities. These findings a re consistent with the null results yielded in the use and either mental health or involvement in extracurricular activities. Tables 13 through 16 contain the result s of the main effects of the logistic regressions for all the independent variables in predicting alcohol use. For the dependent variable of cigarette use, when all covariates, main effects, and two variable combinations were considered together in separat e models, one of the sixteen interaction terms was statistically significant ( p < .05). This interaction involved social anxiety x athletics ( X 2 = 3.99, df = 1, p < .05). Follow up examinations of odds ratios predicting cigarette use under different condi tions (low vs. high) of athletic activity involvement and social anxiety indicated that high athletic activity involvement served to buffer students with high social anxiety from using cigarettes. Specifically, students with high athletic activity were les s likely to smoke cigarettes regardless if their level of social anxiety was low (odds ratio = .12) or high (odds ratio = .52). On the other hand, for students with low levels of involvement in athletic involvement, the likelihood of using cigarettes was quite high for students with low levels of social anxiety (odds ratio = 3.51) and also el evated, albeit to a less extent, for students with high social anxiety (odds ratio = 1.41) In sum, athletic involvement served as a protective factor for students with social anxiety, as students with high levels of social anxiety were less likely to use

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85 cigarettes only in the event that they reported high participation in athletic extracurricular activities. In addition to the significant interaction term, there w ere s everal significant main effects for cigarette use. Tables 17 through 20 contain the results of the main effects of the logistic regressions for all the independent variables in predicting cigarette use. As can be seen in Table 17, i nvolvement in pro social/academic clubs had a statistically significant effect on cigarette use in each of the models in which it was paired with one of the four mental health problems (i.e., depression, generalized anxiety, social anxiety, and school avoidance). In each of these four cases, involvement in prosocial/academic clubs decreased the odds of using cigarettes, a main effect consistent with the aforementioned inverse bivariate correlation between prosocial/academic clubs and cigarette use. In all four models, stude nts who indicated higher levels of involvement were less likely than other participants to report the use of cigarettes. Specifically, in the model containing all covariates, depression, and involvement in prosocial/academically oriented activities, studen ts who indicated higher levels of involvement were less likely (odds ratio = .75) than other participants to report the use of cigarettes ( X 2 = 6.54, df = 1, N = 137, p < .05). In the model containing generalized anxiety, students who indicated higher leve ls of involvement in prosocial/academically oriented activities were less likely (odds ratio = .75) than other participants to report the use of cigarettes ( X 2 = 6.8 6 df = 1, N = 137, p < .05). In the model containing social anxiety, students who indicat ed higher levels of involvement were also less likely (odds ratio = .75) than other participants to report the use of cigarettes ( X 2 = 6.8 1 df = 1, N = 137, p < .05). Lastly, in the model containing school avoidance, students who indicated higher levels o f involvement were less likely

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86 (odds ratio = .75) than other participants to report the use of cigarettes ( X 2 = 6.5 3 df = 1, N = 137, p < .05). As can be seen in Table 18, i nvolvement in special interests clubs also had a statistically significant effect on cigarette use in each of the models in which it was paired with one of the four mental health problems (i.e., depression, generalized anxiety, social anxiety, and school avoidance). In each of these four cases, involvement in special interest clubs dec reased the odds of using cigarettes, a main effect consistent with the aforementioned inverse bivariate correlation between involvement in special interest clubs and cigarette use. In the model containing all covariates, depression, and involvement in spec ial interest clubs, students who indicated higher levels of involvement were less likely (odds ratio = .83) than other participants to report the use of cigarettes ( X 2 = 3.99, df = 1, N = 137, p < .05). In the model containing generalized anxiety, students who indicated higher levels of involvement in special interest clubs were less likely (odds ratio = .83) than other participants to report the use of cigarettes ( X 2 = 4.5 4 df = 1, N = 137, p < .05). In the model containing social anxiety, students who i ndicated higher levels of involvement were also less likely (odds ratio = .82) than other participants to report the use of cigarettes ( X 2 = 4.80, df = 1, N = 137, p < .05). Lastly, in the model containing school avoidance, students who indicated higher le vels of involvement were less likely (odds ratio = .82) than other participants to report the use of cigarettes ( X 2 = 4.33, df = 1, N = 137, p < .05). For the criterion variable marijuana use, when all predictor variables were considered together in a mod el, none of the sixteen interaction s were statistically significant. The results indicated that the predictors, as a set, did not reliably distinguish

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87 between participants who reported using marijuana and those who did not. However, one of the independent variables significantly predicted whether or not participants reported using marijuana, indicating a main effect of involvement in a particular type of school based extracurricular activity on student marijuana use. Tables 21 through 24 contain the resul ts of the main effects of the logistic regressions for all the independent variables in predicting marijuana use. As can be seen in Table 24, i nvolvement in athletics was statistically significant in the prediction model containing all seven covariates, s ocial anxiety, and athletics ( X 2 = 4.83, df = 1, N = 133, p < .05). Specifically, students who indicated high levels of involvement in athletics were less likely (odds ratio = .72) to report the use of marijuana than other participants. This finding is con sistent with the bivariate correlational analyses obtained earlier in this paper, that suggested a trend ( p = .07) for an inverse relationship between athletics involvement and marijuana use, even though that correlation was not significant at the .05 leve l.

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8 8 Chapter Five Discussion Study Summary The current study examine d the rates of substance use among ninth to twelfth grade students in a predominantly Hispanic and low SES high school loc ated in Florida. T his study also examined the percentage of adolescents in this population who are experiencing anxiety and depressive symptomalogy. Furthermore, this study determined the relationship(s) between several substances used, anxiety, and depressive symptomalogy. The current study also contributed to current literature by determining the types of school based extracurricular activities that co occur with use of specific substances Finally, this study looked at the unique interactions between each of the four mental health problems discussed and each o f the four categories of school based activities and determined if any of these interactions significantly predicted the extracurricular activity conditions under which high school students with varying levels of mental health problems are more or less lik ely to use alcohol, cigarettes, and marijuana. In this chapter, the results of the current study are summarized and notable findings are highlighted Similarities and differences between findings in the literature and findings in the current study are discu ssed. Furthermore, the implications of the results for school psychologists and other mental health professionals as well as th e importance of addressing issues pertinent to substance use, mental health, and student involvement in

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89 extra curricular activiti es, are addressed. Lastly, this chapter identifies the limitation s of the current study and offer s directions for future research. Findings Regarding Frequency of Substance Use a mong High School Students The majority of participants in the current study reported not using drugs, in the past year. Several substances (e.g., crack, cocaine, heroin) listed in the TADUS were virtually never endorsed by participants. In contrast the three most co mmonly used substances by youth within the last year were alcohol cigarettes, and marijuana. This finding is consiste nt with the results from the MFS study in which these three substances were also identified as the main substances used by adolescents (Johnston et al., 2007). It should be noted that alcohol was the mo st used substance among this sample of 9 th to 12 th grade students, with over half of the participants (55.1%) reporting having consumed wine/wine cooler, beer, and/or liquor in the past twelve months. The most used type of alcohol was wine/wine coolers wi th almost half of the sample (45.7%) having consumed it. In this sample, very few of the students who reported drinking in the past year did not consume wine/wine coolers and instead consumed beer and/or liquor. Marijuana and cigarettes were not as frequen tly being used in the past year with only 19.6% and 16.7% of the students in the sample reporting having used these substances at least once. Previous research examining rates of substance use among adolescents also noted that alcohol remains the most com monly used substance and is considerably widespread among current adolescents. The prevalence rate of alcohol use in the current study is comparable to the annual prevalence rate of alcohol use (56.3%) among 10 th grade students in the MFS na tional survey o f adolescent substance use (Johnston et al., 2007). In that study, almost three quarters of students had consumed alcohol before the

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90 end of twelfth grade. Numbers obtained in the current study provide a snapshot of use in a one year period rather than duri ng the entire high school experience. Regarding cigarettes, the rate of cigarette use in the current study was somewhat lower than the prevalence of students who reported smoking cigarettes in the MFS study by twelfth grade (specifically, 46%) Even thou gh the rates of cigarette use in the current study and in the MFS study are not directly comparable because the questions asked in both surveys were not the same, it should be noted that one quarter of eight grade students reported having tried cigarettes (Johnston et al., 2007). The use rate in the current study may be lower than the rate of cigarette use in national studies due to the specific profile of students in the current study. Specifically, 60% of p articipants in this study were Hispanic. The lite rature on trends in substance use tend s to show that Hispanic students have lower rates of cigarette use as compared to Caucasian students (Johnston et al., 2007; NSDUH 2008). Another reason for the disparate rates may pertain to features of the current s ctive parental con sent as well as child assent was also required for participation. The use of only students with active parental consent might have resulted in the participation of a subgroup of high school students that are very different from high school students nationwide and even in that particular school (as suggested by the low participation rate of 10.3 %). Thus, the current sample might not optimally represent the larger high school student population. Another common ly endorsed substance in the current sample was marijuana, with 19.6% of the participants reporting having used marijuana within the past year. This rate is pretty comparable to the rate of marijuana use (15.5%) reported by eight and tenth grade students within the past year in the national study conducted by Johnston et al.

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91 (2007). In the MFS 22.6% of 8 th and 10 th grade students reported using marijuana at some point during their lifetime. Similarly, the Youth Risk Behavior Survey (YRBS), which is anot her source of data that provides annual trends in the use of substances among students in 9 th through 12 th grade, reported that 19.7% of youth used marijuana in 2007. Also noteworthy, the majority of people who used illicit substances for the first time wi thin the past 12 months reported using marijuana as their first drug (Johnston et al., 2007). Marijuana has been described as a gateway drug in numerous studies and current numbers demonstrate that many high school students use marijuana. Furthermore, appr oximately half of the youth aged 12 to 17 years in the sample from the MFS reported consume some (Johnston et al., 2007). Findings Regarding Depressive Symptomalogy among High School Students As reported in previous research that examined the prevalence of mental health problems among youth, depression and anxiety are two of the most common psychological problems that children and adolescents experience (Huberty, 2008). Rec ent estimates suggest that as many as 15 20% of children and youth have depressive or anxiety problems that warrant direct intervention (Huberty, 2008) In the current study a total of 78 participants, which represents 56.5% of the sample, were considered at risk for depression. However, this number should be interpreted with caution, as the CES D has been used in num erous studies and found to over identify the number of individuals who are at risk for depression due to its low cutoff score of 16 (Doerfler, Felner, Rowlison, Raley, & Evans, 1988; Roberts, Lewinsohn, & Seeley, 1991; Rushton et al., 2002 ) In fact, Roberts et al. (1991) recommend using a cutoff score of 24 for the CES D when

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92 screening for adolescent depression. While taking into consideratio n the over identification of adole scents at risk for depression, it is still important to note that even if diagnostic crit eria for depression are not met, sub syndromal depressive symptoms are n & Rudolph, 2003). According to Costello et al. (2005), the prevalence of depressive symptomalogy and depression in youth between the ages of 5 to 17 years ranges between 1% and 18%. In a study that collected data using the CES D from 13, 568 adolescents in grades seven through twelve, the authors found that approximately 30% of the sample reported depressive symptomalog y, when a cut point score of 24 was used (Rushton et al., 2002). This prevalence rate, even though not as high as the one obtained in the current study due to the use of different cut point scores emphasizes the n eed to address and prevent depression as it is very co mmon during adolescence and has been shown to negatively affe umerous studies h ave identified short and long term adverse impacts of depression on school functioning, family and peer relationships, and substance use (Bhatia et al., 2007; Evans et al., 2002). Findings Regarding Anxiety Symptomalogy among High School Students Within t he category of anxiety disorders, the percent of par ticipants who were and school avoidance were examin ed. Total scores looking at the continuum of scores were also taken into consideration to look more closely at the severity of sub syndromal symptoms. A pproximately half of the participants in the current study tegory for a clinical diagnosis of one of the three anxiety disorders examined. Prev ious studies examining rates of any anxiety disorders in youth have estimated that

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93 the prevalence rate falls between 10 and 20% (Albano, Chorpita, & Barlow, 2003; Costello & Angold, 1995). This number is significant considering that these youth meet full criteria for a clinical disorder. The high proportion of students in the current study at disorder underscores that there is a nee d to address anxiety in adolescents. Y outh who experience numerous or significa nt symptoms of generalized anxiety disorder are often overly focused on school performance and sport activities even wh en they or their performance is not being evaluated by others (DSM IV TR, APA, 2000). Such preoccupation, even if not sufficiently elevat ed to meet criteria for a diagnosis, might still negat ively impact their schooling as well as functioning in other i mportant areas of life In the current sample, 46.4% of students with a mean score of 7.37 ( SD = eneralized anxiety. When compared to a study the SCARED generalized anxiety subscale in the current sample was higher than the mean score of adolescent students between th e ages of 13 and 16 years ( M = 4.33, SD = 3.49). A lower mean was also observed in a sample of African American high school students ( M = 5.70, SD = 3.97) from an economically disadvantaged community (Boyd et al., 2003). However, the mean score in the curr ent sample was lower than the mean score of a sample of students between the ages of fourteen to eighteen ( M = 12.77, SD = 3.68) in the Netherlands (Hale, Raaijmakers, Muris, & Meeus, 2005). These differences in mean scores might be due to differences in c ulture, values, circumstances and way of life ; these hypotheses that were also discussed by Crocetti, Hale, Fermani, Raaijmakers, and Meeus ( 2009 )

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94 With regards to social anxiety disorder, the percent of students in the current ri generalized anxiety disorder. Approximately one fo u anxiety is consist ent with previous studies that indicated that social anxiety disorder is one of the most prevalent anxiety disorders during adolescence ( Costello et al., 2005; Kessler, Berglund, Demler, Jin, Merikangas, & Walters, 2005; Nat ional Mental Health Information Center, 2003 ). National prevalence rates of social anxiety vary greatly with a li fetime prevalence ranging from 1% to 12 % in youth ages 5 to 17 years (Costello e t al., 2005; DSM IV TR, APA 2000). It should also be noted that the median age of onset identi fied for social anxiety is at the age of 13 which is the approximate age when young adolescents are finishing middle school and entering high school (Kessler et al., 2005). Kessler and colleagues found that the prevalence rate of social anxiety was highes t during adolescence and early adulthood. When compared to other studies examining the mean score of adolescent students on the SCARED social anxiety subscale, the mean score of 5.37 ( SD = 3.32) of students in the current sample was comparable to the mean score of 5.56 ( SD = 3.44) obtained in a sample of African American students attending a low SES high school (Boyd et al., 2003) and somewhat higher than the mean obtained in a sample of Chinese adolescent students (mean score 4.10, SD = 3.22; Linyan et al. 2007). Prevalence rates of students exceeding the cut point for the at risk range could not be compared, as they were not discussed in previous published studies. These similarities and differences in mean scores might again be due to similarities or dif ferences in culture, values, and circumstances. It should be noted that more similarities were found

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95 between the current sample and the sample of African American high school students in a economically disadvantaged community. Although not formally class ified as an anxiety disorder, school avoidance has been discussed in the literature as a manifestation of symptom of various mental health disorders particularly anxiety disorders ( Kearney & Albano, 2004; Kearny, 2008) T he percentage of participants who ( 38.4 %) was fairly high, possibly because the cut point score identified (i.e., raw score of 3 among scores that can range from 0 to 8). The avoida nce of school related stimuli that provoke general anxiety and depression as well as the escape from aversive social and evaluative situations in the school environment have been found to be related to GAD, social anxiety and depression ( Kearney & Albano, 2004) Because generalized a nxiety disorder and depressive symptomalogy w ere rather prevalent in th e current study, this may also explain why the percentage of students considered fairly high When compared to others studies examining the mean score of adolescent students on the SCARED school avoidance subscale, the mean score of students in the current sample ( M = 2.32, SD = 1.53) was again comparable to the mean score of students in the African Ame rican sample ( M = 1.90, SD = .79), but higher than the mean score of adolescent students in the Chinese sample ( M = 0.98, SD = 1.34; Boyd et al., 2003; Linyan et al., 2007). However, current mean scores on the school avoidance subscale were much lower than the mean score of 6.14 ( SD = 2.15) in the sample of adolescent students in the Netherlands (Hale et al., 2005). A discussion of differences

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96 avoidance is not possible as specific rates were not discussed in previous studies. Notable Findings Regarding Interrelationships between Variables The current study identified a few significant rela tionships between mental health problems and substance use, specifically with r egards to school avoidance and the use of cigarette s and marijuana. In particular symptoms and behaviors associated with school avoidance co occurred with cigarette and marijuana use. Even though previous research has demonstrated that adolescent substan ce use often co occurs with mental health problems, particularly depression and either GAD, social anxiety or anxious personality traits (Armstrong et al., 2002; Chang et al., 2005; Comeau et al., 2001; Kaplow et al., 2001; Poulin et al., 2005) studies h ave not specifically looked at the relationship between significant school avoidance/ school refusal and substance use In the current study, substance use was inversely corre lated with school avoidance but not with social anxiety, generalized anxiety, or depressive symptomalogy. The links found between cigarette and marijuana use and students refusing to attend school might be related to untreated mental health symptoms (e.g., generalized anxiety, depression) but also associated with other variables not discussed or analyzed in the current study (e.g., externalizing disorders). This last hypothesis is in line with the notion that adolescent students sometimes refuse to go to school in order to engage in more appealing activities such as substance use. Ke arney (2008) explained that there are several functions or reasons why children and adolescents might refuse to attend school and according to his research, such a function is most often linked to externalizing disorders (e.g., oppositional defiant disord er). Contrary to some findings (Chang et al., 2005; Chassin et al., 1999; Diego et al.,

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97 2003; King et al., 2004, Valentiner et al.,Vogel et al., 2003), no significant relationship was found between any of the three substances and depression, generalized anxiety, or social anxiety. It should be noted, however, that it has been explained in the literature that the links between substance use and internalizing disorders are less clear (King et al., 2004). Numerous studies have identified clear links between substance use and externalizing disorders, and a positive relationship between substance use and internalizing problems has been found to be more significant in females than in male adolescents (Chassin et al., 1999; Chang et al., 2003; Diego et al., 2003; King et al., 2004; Rhode et al., 1996). One of the hypotheses for the gender difference involves the higher prevalence rate of internalizing disorders among females (Brady & Randall, 1999). However, some of the reasons why similar findings might not have been obtained in the current study which consisted of a predominantly female sample could be due to unique features of the current sample in relation to samples used in previous studies. The small sample size in this study as well as the large number of Hi spanic students might have contributed to current findings. One hypothesis is that the females in this sample, which was largely Hispanic, might have a different way of dealing with the symptoms associated with internalizing mental health disorders, such a s seeking options (e.g., family support) other than using substances. With regards to the relationship between school based extracurricular activities and self reported substance use, a couple of signific ant correlations were found. S pecifically, a mode rate negative relationship was indicated between cigarette smoking and involvement in prosocial/academic activities (i.e., community service, student government, language, and academic clubs ), as well as special interests clubs (i.e., school

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98 publicatio ns, business/career, social clubs, and h obby clubs). Previous research has demonstrated that adolescents who are involved in school based extracurricular activities, that are characterized by structure and supervision while at the same time allowing youth to socialize and express their identity, are less likely to use substances (Bohnert et al., 2007; Darling, 2005; Eccles et al., 1999; Fredricks et al., 2006; Peck et al., 2008). Darling (2005) examined involvement in school based extracurricular and found that students who were involved in school based extracurricular activities were less likely to use substances other than alcohol (e.g., tobacco, marijuana, other illegal drugs). These findings are similar to the ones from the current study, in which a sign ificant negative relation ship was noted between use of cigarettes and marijuana, and involvement in certain structured and supervised school based extracurricular activities. Furthermore, Bohnert and Garber (2007) also found that involvement in organized a ctivities during high school was associated with lower levels of tobacco use. However, no relationship s were found between alcohol use and involvement in school based extracurricular activities. In general, involvement in prosocial/academic activities was the strongest correlate of lower substance use. Also important to note, in students were the most likely to engage in school based extracurricular activities while Hispanic American students were the least likely to participate i n such activities (2005). The majority of participants in the current study id entified themselves as Hispanic. Thus, the current study extends the literature by showing that the positive relationship between involvement in school based extracurricular acti vities and reduced cigarette use also applies to samples of youth that include minority ethnic and racial groups. No significant bivariate correlations were found between use of marijuana or

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99 alcohol and any of the extracurricular school based activities Even though there was no statistically significant correlations between marijuana and involvement in prosocial/academic clubs or athletics clubs, the relationships occurred in the expected direction (and the inverse relationship between athletic involvem ent and marijuana use emerged as a significant main effect in logistic regressions conducted to test for interactions between specific variables), suggesting that the more adolescents are involved in both these activities, the less likely they may be to u se marijuana. Such preliminary results augment the literature, as the relationship between involvement in school based extracurricular activities and substance use has not been extensively studied. Specifically, previous studies did not examine specific ty pes of extracurricular activities. In the study by Bohnert and colleague (2007), although the authors identified seven distinct categories of activities (i.e., sports, performance/fine arts, prosocial, and academic clubs, school involvement, press, and lea dership), the authors analyzed the mean number of activities in which adolescents were involved in each year, thus using an overall index of activity involvement. Less emphasis was placed on identifying involvement in specific school based activities that are associated with lower substance use, but a significant negative relationship was found between involvement in three of the categories of activities (i.e., sports, performance arts, and prosocial clubs) and tobacco use. The authors did not analyze alcoh ol or marijuana use in their study. Furthermore, Darling (2005) in her study failed to find a significant relationship between adolescents who participated in extracurricular activities and alcohol use. The author noted a significant negative correlation b etween involvement in extracurricular activities and cigarette as well as marijuana use. However, the relationship between specific school

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100 based extracurricular activities and substance was not analyzed in depth. The lack of detailed information regarding the variety of experiences adolescents have across different extracurricular activities was noted as the primary limitation of that study. Darling noted that information regarding various activities would provide a more detailed portrait and a better under standing of the type of activities that are most likely to facilitate positive development and better adolescent adjustment. The current study fills such a gap in the literature and suggests that prosocial/academic and special interest clubs may be particu larly adaptive with regard to prevention of cigarette use, and athletics involvement may help in reducing the risk for marijuana use. Further study with larger sample sizes that would increase power to detect even small (but clinically significant) relati onships are needed to test these preliminary conclusions. The current study was the first to examine involvement in school based extracurricular activities as a moderator in the relationship between internalizing mental health problems and substance use am ong high school students. Thus, findings from this line of inquiry cannot be fully compared to findings in prior research. However, it should be noted that Darling (2005) and Bohnert and Garber (2007) looked at the bivariate relationship between involvemen t in extracurricular activities in high school and internalizing problems (e.g., mood and anxiety disorders) and both studies concluded that the relation between both variables was marginal. Both studies noted a nonsignificant trend for higher involvement in extracurricular activities to be associated with lower levels of depression as well as mood and anxiety disorders in general. The current study suggest s that a link between internalizing forms of psychopathology and extracurricular activity involvement likely ranges from non existent (for instance, in the case of

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101 depression and generalized anxiety) to weak and inverse (specifically, in the case of school avoidance and social anxiety when examined in relation to involvement in athletics and performing ar ts clubs). However, p reliminary findings in the current study suggest that high levels of athletic involvement serve as a protective factor against cigarette use for those students with a specific form of anxiety social anxiety Among students with high social anxiety who were not engaged in athletic activities, the likelihood of cigarette use was elevated. In sum, these findings suggest that athletics may serve as a moderator in the relationship between social anxiety and cigarette use. Implications for School Psychologists and other Mental Health Professionals As previously stated, alcohol was the most used substance among this sample of 9 th to 12 th grade students, with over half of the participants (55.1%) reporting having consumed wine/wine cool er, beer, and/or liquor in the past twelve months. The rate of cigarette use in the current study was somewhat lower than the prevalence of 12 th grade students who reported smok ing cigarettes in the MFS (specifically, 46%) However, the prevalence rate sti ll warrants attention as 16.7% of participants reported smoking cigarettes within the past year. Another commonly endorsed substance in the current sample was marijuana, with 19.6% of the participants reporting having used marijuana within the past year. Substance use during adolescence is associated with numerous undesirable as well as negative consequences including decreased academic functioning and lower educational attainment (Diego et al., 2003; Engberg et al., 2006; King et al., 2006), diminished socio emotional functioning (The National Survey on Drug Use and Health, 2008; Johnston et al. 2007), and later dependency on subst ances and the development of

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102 s ubstance use disorders (Dewit, Adlaf, & Offord, 2000; Diego et al., 2003; Johnston et al., 200 7). With regards to the negative impact of substance abuse on education, substance abuse in youth is commonly followed by lower expectations, poor performance in school, a drop in grades, higher rates of truancy, higher rates of drop out, as well as lowere d aspirations to pursue a higher education (Dewey, 1999; Ellickson, McGuigan, Adams, Bell, & Hays, 1996; Hays & Ellickson, 1996). The current study extends this list of negative educational outcome to include school avoidance. Such relationships confirm th e need for school psychologists and other mental health professionals to help prevent the use of substances in high school and thus the many consequences associated with it. Several groups, organizations and government funded programs have developed prev ention education programs on substance use and abuse for youth as young as elementary school. One such drug prevention program and non profit public benefit organization, Narconon, recruited fourteen schools from two states (Oklahoma and Hawaii) to conduct a study on the effectiveness of its drug education curriculum program for high students (Lennox & Cecchini, 2008). Schools were assigned to a control group or another group in which the program was delivered. Baseline data, as well as data at a one month and six month follow up w ere collected and pretest levels of substance use were controlled for between the two groups. The Narconon drug education curriculum curriculum are interactive activities, a family and community component, take home assignments, and social influence skills. At the six month follow up, students who participated in the program were less likely to use substances, more likely to perceive

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103 risks associated with substance use, had more positive attitudes and stronger commitment to a drug free lifestyle than students in the control group. This program was shown to empow er youth to make their own decisions and draw their own conclusions, correct common but false message regarding substance use and its effects, improve interpersonal skills which, the authors explain, may result in a shift in the perception of risks as well as attitudes about substance use (Lennox & Cecchini, 2008). Programs such as this one help efforts are important as various organizations and government agencies find a nee d to develop effective substance use prevention programs in schools. Even though the links between substance use and symptoms of mental health problems were small in the current study, the high prevalence rates of depression and some anxiety disorders de monstrate a need to screen adolescents f or internalizing mental health disorders. E ven though such problem s are very common in school age students they often remain under the radar Such youth who need help often fail to receive the necessary help due to a lack of systematic procedures to identify those at risk of developing internalizing disorders (e.g., depression, anxiety). In the current system, even w ith the new approach to problem solving and using a response to intervention model, mental health prob lems are not as easily identifiable as academic and externalizing behavior problems There currently considerable emphasis on prevention and early intervention with regards to academic and behavior progress; however, socio emotional aspects of st By catching and addressing early signs of depressive and anxiety symptomalogy, mental health professionals and other school employees have the potential t o prevent more serious problems, as well as

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104 have more chances of having behavior. The results from this study can assist in informing school psychologists about specific school based extracurricular activities that may protect students from developing maladaptive behaviors such a s substance abuse or school avoidance. At a school wide level or Tier I level, prevention efforts and interventions that target the advantages and importance of structured and constructive activities that are supervised but yet allow studen ts to express their individuality and uniqueness as well as provide them with opportunitie s to develop talents and pursue interests, might dete r certain students f rom engaging in substance use. Involvement in s uch activities might also provide students wit h a safe place where they can blossom and express themselves in a constructive way, while still accessing support and structure These recommendations that involve improving and expanding school mental health programs, are in line with the conclusions a dvanced in the document entitled Achieving the Promise: Transforming Mental Health Care in America that was published cited research indicating that youth with emotional dis turbances have the highest rate of school failure with 50% of these students dropping out of high school in comparison with 30% of all students who have a disability (United States Department of Education Office of Special Education Programs, 2003). As exp Commissions on Mental Health (2003), early detection and prevention of mental health problems, as well as delivering mental health services and supports early, are important to avoid long term or permanent negative con sequences. An effective way of addressing the issue is to create a partnership between schools and mental health providers. School

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105 based mental health programs can attend to the needs and concerns of all children, which can help ensure academic achievement as well as their overall functioning in and outside of school. The commission noted that efforts to address mental health problems in the schools need to include collaboration between parents and local mental health providers, early screenings and assess ment, prevention efforts, as well as effective interventions. The Columbia University TeenScreen program was discussed as an example of a model program that focuses on identification and early intervention. The TeenScreen program involves several steps: ob taining parental consent and child assent, administering several clinician to determine if further evaluation is warranted, and finally students who are identified as needing additional services are assigned a case manager who will ensure the implementation of appropriate intervention (Columbia University TeenScreen Program, 2005). This program, even though intensive and comprehensive, illustrates a more systematic, proactive, and effective way of identifying students at risk for and/or having mental health problems. Achieving the Promise: Transforming Mental Health Care in America (2003) also discusses the need to address the co occurrence of mental health disorders and substa nce use, as this co occurrence worsens during adulthood if it remains untreated (Substance Abuse and Mental Health Services Administration, 2002). Limitations of the Current Study Several precautions were taken during the design of the study and data coll ection process to reduce potential threats to validity. The remaining threats to validity inherent to the design of the study and features of the sample are delineated next

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106 Internal v alidity. Internal validity is the degree to which a study is confound f ree (Goodwin, 2006). In the current study, some extraneous factors could not be controlled attitudes towards substance use and mental health, the influence of the fam ily and their beliefs, and possible protective factors (e.g., the support of the family and parent involvement, involvement of students in other structured activities that are not school based, religious beliefs). Those factors were not examined systematic ally in the current disclosure of substance use and mental health problems, as well as impacted their actual behaviors and beliefs in unknown ways. Such problems are common to studies with non experimental designs, as multiple factors more distal from the research questions cannot be controlled. Ecological validity. Ecological validity is the extent to which findings from one study can be generalized to other populations and across settings. W hen ecological validity is affected, it can lead to erroneous conclusions if results are generalized to populations in different settings without taking into account unique characteristics of the sample. In the current study, all participants were current students at a primarily low SES high school located in Florida with a large population of Hispanic students. The results obtained in this study may not generalize to other populations or across settings due to the many unique characteristics of the current sample. As a result, the findings of the study may not generalize to a higher SES high school or to other ethnic groups. Population validity. Population validity refers to the ability to generalize the results of a sample to a population. Due to the use o f a convenience sampling method to collect data at a pre selected high school, as well as the requirement for active parent

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107 consent and active student assent to participate in the current study, the students in the current sample may differ significantly f rom students in the overall population. The unique characteristics of students who chose to participate in the study and whose parents allowed participation may differ from students who refused to participate and/or failed to return the consent forms, as w ell as whose parents declined participation. This problem is also referred to as sampling bias. Due to the target population being studied (i.e., adolescents), as well as the sensitive subject areas (i.e., substance use, depression, anxiety), active parent al consent is almost always required by the Institutional Review Board (IRB) and the Ethics Review Boards (ERB). Passive consent procedures would improve the likelihood of obtaining random sample of adolescents which would also improve the probability of o btaining a representative sample (Baker, Yardley, & McCaul, 2001). It has been discussed and documented in previous research (Baker et al., 2001; Beck, Collins, Overholser, & Terry, 1984; Weinberger, Tublin, Ford, & Feldman, 1990; White, Hill, & Effendi, 2 004) that studies requiring active parental consent have a higher rate of sampling bias and a lower sample size as a result of the underrepresentation of certain populations (e.g., students at risk for engaging in problem behaviors such as substance use, s tudents who are not satisfied, students with parents that might be less active parental consent may have led to a lower sample size. The sample s ize for the study is fairly small (13 8 participants) with a low response rate (10.3%). The sample size

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108 representative of the overall population at the participating school In addition to a sampling bias or nonresponse bias, which makes it more difficult and risky to draw conclusion about a population, a social desirability bias may have also affected the results. Since a survey method was use in the current study, students may have responded to survey questions based on how they think they should answer or what is expected and their answers may not reflect what they truly feel and their true behaviors (Goodwin, 2006). This limitation should be noted even though surveys were anonymous, as surveys were completed in the school setting and around a few other students, with the social desirability bias, but it may have not eliminated the problem. Another limitation is that all the information in the archival dataset came from only one source, report, which might result in source bias. Moreover, biases might occur due to normal mood changes that youth experience during adolescence The instruments used to assess current and/or recent anxiety and depressive symptomalogy may have also limited the findings as past levels of symptomalogy were not assessed and might have influenced substance use in the past year. Another important limi tation to consider is the possibility for Type I errors. The large number of comparisons that were made including the use of numerous variables in the logistic regression models increased the possibility of making a Type I error. A Type I error occurs wh en the null hypothesis is rejected when it is in fact true, and no significant differences actually exist between the two groups (e.g., substance user vs. no use of substances). Significant differences obtained in the current study between students

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109 who rep orted using substances and those who did not should be interpreted with caution pending independent replication of findings. Directions for Future Research The current study attempted to comprehensively examine the interrelationships between adolescent sub stance use anxiety and depressi on, as well as student involvement in school based extracurricular activities. The current study i s among the first to examine school avoidance as a form of anxiety, as well as one of the few studies to examine various cate gories of school based extracurricular activities and their unique contributions to student outcomes. A greater understanding of the relationship between mental health problems substance use and school involvement in extracurricular activities adds to th e literature by providing more det ailed information on these topics specific to students attending a predominantly low SES high school with a large Hispanic student population Future replications of this study with larger samples that are more representat ive of typical U.S. students are needed, in part to confirm the existence of relationships suggested by the current study as well as to address threats to validity. Future research efforts should focus on limiting non response or sampling biases, for insta nce by sending follow up reminders and/or distributing consent forms multiple times to students who do not initially return parent consent forms. Future research should also consider the use of a longitudinal, prospective design to limit errors and biases inherent to reliance on self report data of past behaviors, attitudes, feelings, and moods. Efforts made towards preventing substance use and internalizing problems such as depression and anxiety among high school students are essential due to the numerous term and long

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110 term educational outcomes. Replication of this study will add to the existing literature base and may strengthen the rationale for the need to develop effective schoo l based preventive programs for youth who are at risk of using/abusing substances and/or at risk of developing mental health problems. Final Thoughts Results of the current study suggest a substantial percentage of students serving a predominantly Hispanic and low SES school experience clinical levels of anxiety disorders and depression, as well as substance use (particularly alcohol use). Such findings should be conveyed to educators of such populations in part to raise their awareness of the mental healt h needs of their students. Current findings support marijuana, underscoring the relationship between forms of anxiety and student substance use. Furthermore, inverse li nks between cigarette use and involvement in particular school based extracurricular activities (i.e., prosocial/academic clubs and special interest clubs) were noted. These results may provide a further rationale for efforts to encourage availability and use of school based activities that are structured.

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125 Appendices

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126 Appendix A : Parent Consent Form Dear Parent or Caregiver: This letter provides information about a research study that will be conducted at X High School by investigators from the University of South Florida. Our goal in conducting the study is to determine the school, home, and with friends on their psychological wellness and health Who We Are : The research team consists of Rance L. Harbor, Ph.D., a Hillsborough County School Psychologist who is also a visitor professor in the College of Education at the U niversity of South Florida (USF), and several graduate students in the USF School Psychology Program. We are planning the study in cooperation with the principal of X High School ( X ) to make sure the study provides information that will be helpful to the school. : This study is being conducted as part of a project Risk and Protective Factors Associated with Substance Use Among High School Students e he or she is a student at X High School. Why Your Child Should Participate : We need to learn more about what leads to alcohol and drug use while students are in high school. The information that we collect from students may increase our overall knowled ge of risk factors that lead to drug and/or alcohol use as well as what characteristics and activities serve as a protective factor. In addition, information from the study will be shared with the teachers and administrators at X in order to increase their knowledge of specific school experiences that participation in the study. However, all students who participate in the study will be entered into a drawing for one of several gift certificates. What Participation Requires : If your child is given permission to participate in the study, he or she will be asked to complete several paper and pencil questionnaires. These questionnaires will ask about your chi activities, sports, peer relationships, and mental health history. Completion is expected to take your child between 30 and 45 minutes. We will personal ly administer the questionnaires at X during regular school hours in the Winter 2008 semester, to large groups of students who have parent permission to day. : There is minimal risk to your child for participating in this research. We will be present during administration of the questionnaires in order to provide assistance to your child if he or she has any questio ns or concerns. In addition, after your child has completed the questionnaires, we will give your child a list of community mental health resources in case he or she would like to discuss personal issues or find out more information about tobacco, alcohol and drug use. This study is anonymous will not be able to identify w hich student completed which questionnaires. Only we will have access to the locked file cabinet stored at USF that will contain the form your child must sign in order to take part in this study. This permission form will be explained, signed, and collec ted before questionnaires are research records will be kept confidential to the extent of the law. Authorized research personnel, employees of the Departmen t of Health and Human Services, the USF Institutional Review Board and its staff, and other individuals acting on behalf of USF may inspect the records from this research personnel or anyone other than Dr. Harbor and his research assistants.

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127 Appendix A : Parent Consent Form (Continued) Please Note : Your decision to allow your child to participate in this research study must be completely voluntary. You are free to allo w your child to participate in this research study or to withdraw him or her at any time. Your decision to participate, not to participate, or to withdraw participation at any point r her grades, or your relationship with X Hillsborough County Schools, USF, or any other party. : We plan to use the information from this study to inform educators and psychologists about the effects of variou s risk and protective factors associated with high school alcohol and/or drug use. The results of this study may be published. However, the data obtained from your child will be combined with data from other people in the publication. The published results personally identify your child. Questions? If you have any questions about this research study, please contact Dr. Harbor at (813) 872 5300 ext 303. If you have question research study, you may contact a member of the Division of Research Compliance of the USF at (813) 974 9343. Want Your Child to Participate? To permit your child to participate in this stu dy, complete the attached consent form and have your child turn it in to his or her homeroom teacher. Sincerely, Rance L. Harbor, Ph.D. School Psychologist Hillsborough County Public Schools Visiting Professor, University of South Florida Departmen t of Psychological and Social Foundations Consent for Child to Take Part in this Research Study I freely give my permission to let my child take part in this study. I understand that this is research. I have received a copy of this letter and consent f orm for my records. ________________________ ________________ Printed name of chil d Grade level of child ________________________ __________________________ ____________ Signature of parent of Printed name of parent Date child taking part in the study Statement of Person Obtaining Informed Consent I certify that participants have been provided with an informed consent form that has been approved by the al Review Board and that explains the nature, demands, risks, and benefits involved in participating in this study. I further certify that a phone number has been provided in the event of additional questions. _______________________ ___________ _______________ ___________ Signature of person Printed name of person Date obtaining consent obtaining consent

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128 Appendix B : Student Assent Form Hello! Today you will be asked to take part in a research study by filling out several questionnaires. Our goal in on their psychological wellness and health Who We Are : The research team consists of Rance L. Harbor, Ph.D., the School Psychologist here at X High School and a professor in the College of Education at the University of South Florida (USF), and several graduate students in the USF School Psychology Program. We are working with your principal to make sure the study provides information that will be helpful to your school. Why We Are Asking You to Take Part in the Study Risk and Protective Factors Associated with Substance Use Among High School Students asked to take part because you are a student at X High School. Why You Should Take Part in the Study : We need to learn more about what leads to drug and/or alcohol use during high school. The information that we gather may help us bette r understand what causes psychological wellness during high school and specifically what factors help students not to use alcohol and/or drugs. In addition, information from the study will be shared with the teachers and administrators at X to help them un derstand which specific school experiences lead to wellness in students. Please note you will not be paid for taking part in the study. However, all students who participate in the study will be entered into a drawing for one of several gift certificates. Filling Out the Questionnaires : These questionnaires ask you about your thoughts, behaviors, and attitudes towards alcohol and drugs as well as peer relationships, participation in extra curricular activities, and athletics, and life in general. We exp ect it will take between 30 and 45 minutes to fill out the questionnaires. Please Note : Your involvement in this study is completely voluntary. By signing this form, you are agreeing to take part in this research. Your decision to participate, not to p articipate, or to withdraw participation at any point during the study will in no way affect your student status or your grades; you will not be punished in any way. If you choose not to participate, it will not affect your relationship with X High School USF, or anyone else. Privacy of Your Responses : We do not expect that t here will be more than minimal risk to you for taking part in this research. We will be here to help the entire time you are filling out the surveys in case you have any question s or concerns. When you hand in your completed questionnaires, we will give you a piece of paper that lists places you can call and go to in the community if you would like to discuss personal issues. The paper also tells you how to find out more informa tion about tobacco, alcohol, and drug use. This study is anonymous Your name will not be linked in any way to your responses. Your completed packet of questionnaires will be added to the stack of packets from other students; we will not be able to tell which student completed which questionnaires. Only we will have access to the locked file cabinet stored at USF that will contain this signed permission form. Your privacy and research records will be kept confidential (private, secret) to the extent of the law. People approved to do research at USF, people who work for the Department of Health and Human Services, the USF Institutional Review Board and its staff, and other individuals acting on behalf of USF may look at the records from this research pro ject, but your individual responses will not be shared with people in the school system or anyone other than us and our research assistants.

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129 Appendix B : Student Assent Form (Continued) : We plan to use the informa tion from this study to let others happiness and risky health behavior. The results of this study may be published. However, your responses will be combined wit h responses from other people in the publication. The published results will not include your name or any other information that would in any way identify you. Questions? If you have any questions about this research study, please raise your hand now or at any point during the study. Also, you may contact us later at (813) 872 5300 ext 303 (Dr. Harbor). If you have questions about your rights as a person who is taking part in a research study, you may contact a member of the Division of Research Complia nce of the USF at (813) 974 9343, or the Florida Department of Health, Review Council for Human Subjects at 1 850 245 4585 or toll free at 1 866 433 2775. Thank you for taking the time to take part in this study. Sincerely, Rance L. Harbor, Ph.D. School Psychologist, Hillsborough County Public Schools Visiting Professor, University of South Florida Department of Psychological and Social Foundations -------------------------------------------------------------------------------------------------------------------Assent to Take Part in this Research Study I freely give my permission to take part in this study. I understand that this is research. I have received a copy of this letter and assent form for my records. ________________________ ______________________ ____________ Signature of child taking Printed name of child Date part in the study Statement of Person Obtaining Informed Consent I certify that participants have been provided with an in formed consent form that has been approved by the benefits involved in participating in this study. I further certify that a phone number has been p rovided in the event of additional questions. _______________________ ______________________ ___________ Signature of person Printed name of person Date obtaining consent obtaining consent

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130 Appendix C: Demographi cs Questionnaire 1. Gender 1) Female 2) Male 2. Ethnicity 1. African American/Black 2. Asian/ Pacific Islander 3. White 4. Hispanic 5. Native American/ Alaska Native 6. Other (Specify ______________) 3. Age 13 18 14 19 1 5 20 16 21 17 22 4. Grade 9 10 11 12 5. Estimated GPA 4.0 or higher (A) 3.0 3.9 (B) 2.0 2.9 (C) 1.0 1.9 (D) Less than 1.0 (F) 6. Are you on Free or Reduced Lunch? 1. Yes 2. No 7. Do you attend sch ool regularly 1. No 2. Sometimes 3. Yes 9. Including last year, and this year, have you received any discipline referrals for behaviors other than being tardy? 1. Often (More than 5) 2. Some (1 5) 3. Never 10. Including last year, and this year, have you been suspended out of school (including ATOSS)? 1. Often (More than 5 days total) 2. Some (1 5 days total) 3. Never 11. Including last year, and this year, have you been arrested? 1. Often (More than 2 times) 2. Some (1 2 tim es) 3. Never 12. Have you ever been diagnosed with ADHD? 1. Yes 2. No 13. Have you ever been diagnosed with Anxiety, Depression, or other mental health problems? 1. Yes 2. No 14. Have you ever been prescribed medication for ADHD? 1. Yes, and I st ill take the medication. 2. Yes, but I no longer take medication. 3. No 15. Have you ever been prescribed medication for Anxiety, Depression, or other mental health problems? 1. Yes, and I still take the medication. 2. Yes, but I no longer take medica tion. 3. No

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131 Appendix D: Teen Alcohol and Drug Use Scale Circle the number that best describes on how many occasions? In the past 12 months, on how many occasions (if any) have you used the following drugs? Zero occasions 1 2 occasion s 3 5 occasions 6 9 occasions 10 19 occasions 20 39 occasions 40 or more occasions 1. Cigarettes/Cigars 1 2 3 4 5 6 7 2. Chewing Tobacco 1 2 3 4 5 6 7 3. Wine/Wine Coolers/Malt Beverages (e.g., Smirnoff Ice) 1 2 3 4 5 6 7 4. Beer 1 2 3 4 5 6 7 5. Liquor (e.g., vodka, rum, whiskey) 1 2 3 4 5 6 7 6. Marijuana 1 2 3 4 5 6 7 7. Inhalants (e.g., glue or gasoline) 1 2 3 4 5 6 7 8. Over the counter drugs when you are NOT Sick/hurt (e.g., cough medicine) 1 2 3 4 5 6 7 9. Prescription drugs NOT prescribed to you(e.g., Zanex, Prozac) 1 2 3 4 5 6 7 10. Prescription drugs prescribed to you (e.g., Zanex, Prozac) 1 2 3 4 5 6 7 11 Ecstasy 1 2 3 4 5 6 7 12 Hallucinogens (e.g., LSD, Mus hrooms) 1 2 3 4 5 6 7 13 Stimulants (uppers) 1 2 3 4 5 6 7 14 Barbiturates (downers) 1 2 3 4 5 6 7 15 Cocaine 1 2 3 4 5 6 7 16 Crack 1 2 3 4 5 6 7 17 Heroine (e.g., cheese) 1 2 3 4 5 6 7 18 Other ____________________________ 1 2 3 4 5 6 7

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132 Appendix E: CES D Below is a list of the ways you might have felt or behaved. Please tell me how often you have felt this way during the past week (Circle one number on each line) Rarely or none of the time (less than 1 day) Some or a little of the time (1 2 days) Occasionally or a moderate amount of time (3 4 days) Most or all of the time (5 7 days) 1 I was bothered by things that usually 0 1 2 3 2. I did not feel like eating; my appetite w as poor. 0 1 2 3 3. I felt that I could not shake off the blues even with help from my family or friends. 0 1 2 3 4. I felt I was just as good as other people. 0 1 2 3 5. I had trouble keeping my mind on what I was doing. 0 1 2 3 6. I felt depressed 0 1 2 3 7. I felt that everything I did was an effort. 0 1 2 3 8. I felt hopeful about the future. 0 1 2 3 9. I thought my life had been a failure. 0 1 2 3 10. I felt fearful. 0 1 2 3 11. My sleep was restless. 0 1 2 3 12. I was happy. 0 1 2 3 13. I talked less than usual. 0 1 2 3 14. I felt lonely. 0 1 2 3 15. People were unfriendly. 0 1 2 3 16. I enjoyed life. 0 1 2 3 17. I had crying spells. 0 1 2 3 18. I felt sad. 0 1 2 3 19. I felt that people dislike me. 0 1 2 3 20. 0 1 2 3

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133 Appendix F: SCARED Below is a list of sentences that describe how people feel. Read each phrase and decide 0 1 ) 2 ) for you Then for each sentence, circle the number that corresponds to the response that seems to describe you for the last three months How much does this describe you for the last three months? Not True or Hardly Ever True Somewhat True or Sometimes Tru e Very True or Often True 1. I get headaches when I am at school. (Scl A) 0 1 2 2. (Soc A) 0 1 2 3. I worry about other people liking me. (GA) 0 1 2 4. I am nervous. (GA) 0 1 2 5. I feel nerv (Soc A) 0 1 2 6. I get stomachaches at school. (Scl A) 0 1 2 7. I worry about being as good as other kids. (GA) 0 1 2 8. I worry about going to school. (Scl A) 0 1 2 9. I worry about things working out for me (GA) 0 1 2 10. I am a worrier. (GA) 0 1 2 11. well. (Soc A) 0 1 2 12. People tell me that I worry too much. (GA) 0 1 2 13. (Soc A) 0 1 2 14. I worry about w hat is going to happen in the future. (GA) 0 1 2 15. I worry about how well I do things. (GA) 0 1 2 16. I am scared to go to school. (Scl A) 0 1 2 17. I worry about things that have already happened. (GA) 0 1 2 18. I feel nervous when I am with other c hildren or A dults and I have to do something while they watch me (for example: read aloud, speak, play a game, play a sport ; Soc A) 0 1 2 19. I feel nervous when I am going to parties, dances, or any place where there will be people that I now well. (Soc A) 0 1 2 20. I am shy. (Soc A) 0 1 2 Note. GA = G eneralized A nxiety scale Soc A = S ocial A nxiety scale and Scl A = S chool A nxiety scale.

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134 Appendix G: Participation in School Related Activities Questionnaire Circle the number that best describes how often? How often do you participate in these activities or organizations at school? Three or more times a week Once or twice a week Once or twice a month Less than once a month Never 1. School Publications (i.e., Yearbo ok Staff, Newspaper, Literary Journal). 1 2 3 4 5 2. Music (i.e., Band, Orchestra, Chorus, etc) 1 2 3 4 5 3. Athletics (Baseball, Gymnastics, Cheerleading, etc) 1 2 3 4 5 4. Community Service (i.e., Anchor, Key Club Keyettes, etc) 1 2 3 4 5 5. Drama/Thespians 1 2 3 4 5 6. Dance 1 2 3 4 5 7. Student Government 1 2 3 4 5 8. Business/Career (i.e., Fashion, Cosmetology, Culinary Arts, Computer, Law) 1 2 3 4 5 9. Language Club s (i.e., French, Spanish, Asian, etc.) 1 2 3 4 5 10. ROTC 1 2 3 4 5 11. Social Clubs/Groups 1 2 3 4 5 12. Academic (i.e., National Honors Society, etc.) 1 2 3 4 5 13. Hobby Clubs (i.e., Chess, RC Cars, etc.) 1 2 3 4 5 14. Other: ______________________ 1 2 3 4 5

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135 Appendix H Logistic Regression Analysis: Interaction Effects Yielded for Alcohol Use, Mental Health Problems, and Involvement in School Based Extracurricular Activities Interaction Terms B S.E d f p Odds Ratio Depression*Prosocial/ Academically Oriented Activities Depression*Special Interest Clubs Depression*Performing Arts Clubs Depression*Athletics Generalized Anxiety* Prosocial/ Academically Oriented Activities Generalized Anxiety* Special Interest Clubs Generalized Anxiety* Performing Arts Clubs Generalized Anxiety* Athletics .003 .001 .009 .002 .007 .005 .005 .012 .006 .006 .009 .012 .012 .012 .022 .027 .286 .011 1.025 .027 .342 .188 .052 .181 1 1 1 1 1 1 1 1 .593 .917 .311 .870 .559 .665 .819 .670 .997 1.001 .991 .998 .993 1.005 1.005 .988 Note All values for interaction terms were obtained by first entering control variables (i.e., gender, grade, SES, and ethnicity), then the main effect of mental health problem, and finally the main effect of each ext racurricular activity type for every logistic regression A table was created for each of the three substance types. p < .05.

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136 Logistic Regression Analy sis: Interaction Effects Yielded for Alcohol Use, Mental Health Problems, and Involvement in School Based Extracurricular Activities continued Predictor B S.E df p Odds Ratio Social Anxiety* Prosocial/Academically Oriented Activities Social Anxiety* Special Interest Clubs Social Anxiety* Performing Arts Clubs Social Anxiety* Athletics Sc hool Avoidance* Prosocial/Academically Oriented Activities School Avoidance* Special Interest Clubs School Avoidance* Performing Arts Clubs School Avoidance* Athletics .008 .011 .004 .007 .026 .023 .034 .081 .018 .019 .023 .037 .040 .040 .055 .079 .177 .376 .027 .033 .434 .338 .386 1.058 1 1 1 1 1 1 1 1 .674 .540 .869 .856 .510 .561 .535 .304 1.008 1.011 .99 6 .993 1.026 .977 1.035 1.084 Note. All values for interaction terms were obtained by first entering in the model all control variables (i.e., gender, grade, SES, and ethnicity), then the main effect of each mental health problem, and finally the main effect of each extracurricular activity type for every logistic regression A table was created for each of the three substance types. p < .05.

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137 Logistic Regression Analysis: Interaction Effects Yielded for Cigarette Use Mental Healt h Problems, and Involvement in School Based Extracurricular Activities Predictor B S.E df p Odds Ratio Depression* Prosocial/ Academically Oriented Activities Depression* Special Interest Clubs Depres sion*Performing Arts Clubs Depression*Athletics Generalized Anxiety* Prosocial/Academically Oriented Activities Generalized Anxiety* Special Interest Clubs Generalized Anxiety* Performing Arts Clubs Ge neralized Anxiety* Athletics .012 .004 .006 000 .034 .026 .034 .0 49 .013 .009 .011 .015 .024 .021 .029 .03 7 .802 .148 .323 .000 2.034 1.507 1.376 1 754 1 1 1 1 1 1 1 1 .371 .7 01 .570 .987 .154 .220 .241 185 1.012 .996 .994 1.000 1.558 1.027 1.035 1 051 Note. All values for interaction terms were obtained by first entering control variables (i.e., gender, grade, SES, and ethnicity), then the main effect of mental health problem, and finally the main effect of each extracurricular activity type for every logistic regression A table was created for each of the three substance types. p < .05.

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138 Logistic Regression Analy sis: Interaction Effects Yielded for Cigarette Use, Mental Health Problems, and Involvement in School Based Extracurricular Activities continued Interaction Terms B S.E df p Odds Ratio Social Anxiety* Prosocial/Academically Oriented Activities Social Anxiety* Special Interest Clubs Social Anxiety* Performing Arts Clubs Social Anxiety* Athletics School Avoidance* Prosocial/Academically Oriented Activities School Avoidance Special Interest Clubs School Avoidance* Performing Arts Clubs School Avoidance* Athletics .056 .047 .013 .106 .125 .017 .138 .057 .032 .029 .031 .053 .067 .056 .084 .103 3.047 2.676 184 3.992 3.498 .091 2.698 .304 1 1 1 1 1 1 1 1 .081 .102 .668 .046* .061 .763 .100 .581 1.058 1.048 .987 1.112 1.133 1.017 1.148 1.058 Note. All values for interaction terms w ere obtained by first entering in the model all control variables (i.e., gender, grade, SES, and ethnicity), then the main effect of each mental health problem, and finally the main effect of each extracurricular activity type for every logistic regression A table was created for each of the three substance types. p < .05.

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139 Logis tic Regression Analysis: Interaction Effects Yielded for Marijuana Use, Mental Health Problems, and Involvement in School Based Extracurricular Activities Interaction Terms B S.E df p Odds Ratio Depression*Prosocial/ Academically Oriented Activities Depression*Special Interest Clubs Depression*Performing Arts Clubs Depression*Athletics Generalized Anxiety* Pr osocial/ Academically Oriented Activities Generalized Anxiety* Special Interest Clubs Generalized Anxiety* Performing Arts Clubs Generalized Anxiety* Athletics .001 .006 .014 .004 .000 .000 .027 0 .24 .009 .007 .011 .014 .018 .015 .029 .035 .013 .599 1.633 .066 .000 .000 .901 472 1 1 1 1 1 1 1 1 .909 .439 .201 .797 .997 .997 .343 .492 .999 .994 .986 .996 1.000 1.000 1.028 1.024 Note. All values for interaction terms were obtained by first entering control variables (i.e., gender, grade, SES, and ethnicity), then the main effect of mental health problem, and finally the main effect of each extracurricular activity type f or every logistic regression A table was created for each of the three substance types. p < .05.

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140 Logistic Regression Analy sis: Interaction Effects Yielded for Marijuana Use, Mental Health Problems, and Involvement in School Based Extracurricular Act ivities continued Predictor B S.E df p Odds Ratio Social Anxiety* Prosocial/Academically Oriented Activities Social Anxiety* Special Interest Clubs Social Anxiety* Performing A rts Clubs Social Anxiety* Athletics School Avoidance* Prosocial/Academically Oriented Activities School Avoidance* Special Interest Clubs School Avoidance* Performing Arts Clubs School Avoidance* Athletics .001 .013 .021 .050 .046 .090 .011 .092 .026 .025 .031 .050 .052 .051 .072 .103 .001 .272 .461 .968 .774 3.070 .022 .796 1 1 1 1 1 1 1 1 .972 .602 .497 .325 .379 .080 .881 .372 1.001 1.013 .979 1.051 .955 .914 1.011 1.096 Note. All values for interaction terms were obtained by first entering in the model all control variables (i.e., gender, grade, SES, and ethnicity), then the main eff ect of each mental health problem, and finally the main effect of each extracurricular activity type for every logistic regression A table was created for each of the three substance type. p < .05.

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141 Appendix I Logistic Regression Analy sis: Main Eff ects Yielded for Alcohol Use, Mental Health Problems, and Involvement in Prosocial/Academically Oriented Activities B Predictor Gender .071 .002 .042 .055 .050 Age .244 .325 .312 .296 .311 SES .496 .462 .491 .530 .494 African American a .465 .297 .338 .219 .339 Asian a 2.162 1.940 2.035 2.135 2.054 Hispanic a .308 .451 .430 .473 .432 Multiracial/Other a .345 .338 .253 .296 .251 Depression .024 Prosocial/Academic Clubs .073 Generalized Anxiety .002 Prosocial/Academic Clubs .082 Social Anxiety .093 Prosocial/Academic Clubs .081 School Avoidance .012 Prosoci al/Academic Clubs .083 Note. All main effect variables take into account all seven covariates. Coefficients reported in the table are log odds units. For gender, 0 = Male, 1 = Female For SES, 1 = student receives free or reduced price lunch, 2 = student does not qualify for free or reduced price lunch. a For ethnicity, the reference category is white. p < .05.

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142 Logistic Regression Analy sis: Main Effects Yielded for Alcohol Use, Mental Health Problems, and Involvement in Special Interest Clubs B Predictor Gender .071 .129 .084 .060 .095 Age .244 .250 .231 .225 .236 SES .496 .454 .492 .536 .487 African American a .465 .455 .498 .366 .496 Asian a 2.162 2. 062 2.178 2.283 2.151 Hispanic a .308 .341 .302 .350 .303 Multiracial/Other a .345 .450 .354 .391 .349 Depression .029 Special Interest Clubs .034 Generalized Anxiety .004 Special Interest Clubs .023 Social Anxiety .093 Special Interest Clubs .010 School Avoidance .017 Special Interest Clubs .023 Note. All main effect variables take into account all seven covariates. Coefficients report ed in the table are log odds units. For gender, 0 = Male, 1 = Female. For SES, 1 = student receives free or reduced price lunch, 2 = student does not qualify for free or reduced price lunch. a For ethnicity, the reference category is white. p < .05.

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143 Logistic Regression Analy sis: Main Effects Yielded for Alcohol Use, Mental Health Problems, and Involvement in Performing Arts Clubs B Predictor Gender .071 .121 .084 .066 .072 Age .244 .261 239 .225 .233 SES .496 .413 .444 .487 .449 African American a .465 .602 .651 .525 .659 Asian a 2.162 2.127 2.224 2.327 2.257 Hispanic a .308 .358 .325 .372 .325 Multiracial/Other a .345 .626 .527 .565 .53 6 Depression .028 Performing Arts Clubs .097 Generalized Anxiety .003 Performing Arts Clubs .094 Social Anxiety .092 Performing Arts Clubs .088 School Avoidance .020 Performing Arts Clubs .095 Note. All main effect variables take into account all seven covariates. Coefficients reported in the table are log odds units. For gender, 0 = Male, 1 = Female. For SES, 1 = student receives free or reduce d price lunch, 2 = student does not qualify for free or reduced price lunch. a For ethnicity, the reference category is white. p < .05.

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144 Logistic Regression Analy sis: Main Effects Yielded for Alcohol Use, Mental Health Problems, and Involvement in Athl etic Activities B Predictor Gender .009 .010 .019 .024 .016 Age .231 .238 .222 .220 .224 SES .524 .486 .521 .572 .519 African American a .558 .513 .563 .439 .563 Asia n a 2.178 2.074 2.188 2.280 2.179 Hispanic a .261 .294 .261 .305 .262 Multiracial/Other a .249 .366 .278 .288 .275 Depression .023 Athletics .038 Generalized Anxiety .003 Athletics .027 Social Anxiety .093 Athletics .009 School Avoidance .006 Athletics .027 Note. All main effect variables take into account all seven covariates. Coefficients reported in the table are log odds units. For ge nder, 0 = Male, 1 = Female. For SES, 1 = student receives free or reduced price lunch, 2 = student does not qualify for free or reduced price lunch. a For ethnicity, the reference category is white. p < .05.

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145 Logistic Regression Analy sis: Main Effects Yielded for Cigarette Use, Mental Health Problems, and Involvement in Prosocial/Academically Oriented Activities B Predictor Gender .002 .183 .270 .276 .074 Age .125 .017 .006 .005 .048 SES .167 .209 .101 .106 .160 African American a .337 .230 .008 .020 .067 Asian a 20.020 19.518 19.730 19.720 19.328 Hispanic a .295 .019 .112 .100 .158 Multiracial/Other a .131 .058 .165 .159 155 Depression .036 Prosocial/Academic Clubs .286* Generalized Anxiety .015 Prosocial/Academic Clubs .293* Social Anxiety .048 Prosocial/Academic Clubs .284* School Avoidance .229 Prosocial/Academic Clubs .285* Note. All main effect variables take into account all seven covariates. Coefficients reported in the table are log odds units. For gender, 0 = Male, 1 = Female. For SES, 1 = student receives free or reduced price lunch, 2 = student does not qualify for free or reduced price lunch. a For ethnicity, the reference category is white. p < .05.

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146 Logistic Regression Analy sis: Main Effects Yielded for Cigarette Use, Mental Health Problems and Involvement in Special Interest Clubs B Predictor Gender .002 .030 .064 .092 .155 Age .125 .018 .026 .038 .013 SES .167 .228 .133 .102 .174 African American a .337 .009 .148 .007 .125 Asian a 20.020 19.698 19.847 19.822 19.392 Hispanic a .295 .250 .287 .253 .344 Multiracial/Other a .131 .317 .102 .129 .140 Depression .036 Special Interest Clubs .181* Generalized Anxiety .012 Special Interest Clubs .189* Social Anxiety .073 Special Interest Clubs .193* School Avoidance .257 Special Interest Clubs .193* Note. All main effect variables take into account all seven covariates. Coefficients reported in the table are log odds units. For gender, 0 = Male, 1 = Female. For SES, 1 = student receives free or reduced price lunch, 2 = student does not qualify for free or reduced price lunch. a For ethnicity, the reference category is white. p < .05.

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147 Logistic Regression Analy sis: Main Effects Yielded for Cigarette Use, Mental Health Problems, and Involvement in Performing Arts Clubs B Predi ctor Gender .002 .063 .000 .001 .173 Age .125 .093 .125 .135 .072 SES .167 .270 .175 .150 .217 African American a .337 .237 .364 .305 .260 Asian a 20.020 19.852 20.028 20.043 1 9.585 Hispanic a .295 .235 .292 .268 .355 Multiracial/Other a .131 .358 .157 .176 .098 Depression .041 Performing Arts Clubs .022 Generalized Anxiety .002 Performing Arts Clubs .013 Social Anxiety .056 Performing Arts Clubs .009 School Avoidance .014 Performing Arts Clubs .927 Note. All main effect variables take into account all seven covariates. Coefficients reported in the tab le are log odds units. For gender, 0 = Male, 1 = Female. For SES, 1 = student receives free or reduced price lunch, 2 = student does not qualify for free or reduced price lunch. a For ethnicity, the reference category is white. p < .05.

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148 Logistic Regr ession Analy sis: Main Effects Yielded for Cigarette Use, Mental Health Problems, and Involvement in Athletic Activities B Predictor Gender .002 .080 .020 .037 .172 Age .125 .063 .088 .091 .048 SES .167 .253 .166 .141 .246 African American a .337 .172 .354 .285 .279 Asian a 20.020 19.898 20.049 20.039 19.603 Hispanic a .295 .242 .293 .255 .326 Multiracial/Other a .131 .172 .022 .003 .028 Depression .037 Athletics .128 Generalized Anxiety .006 Athletics .138 Social Anxiety .068 Athletics .162 School Avoidance .239 Athletics .109 Note. All m ain effect variables take into account all seven covariates. Coefficients reported in the table are log odds units. For gender, 0 = Male, 1 = Female. For SES, 1 = student receives free or reduced price lunch, 2 = student does not qualify for free or red uced price lunch. a For ethnicity, the reference category is white. p < .05.

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149 Logistic Regression Analy sis: Main Effects Yielded for Marijuana Use, Mental Health Problems, and Involvement in Prosocial/Academically Oriented Activities B Predictor Gender .302 .452 .496 .517 .341 Age .012 .114 .102 .093 .141 SES .664 .634 .677 .676 .628 African American a 1.472 1.190 1.217 1.124 1.212 Asian a 20.441 20.157 20.227 20.3 08 19.930 Hispanic a .527 .379 .399 .385 .437 Multiracial/Other a 1.314 1.405 1.459 1.497 1.482 Depression .016 Prosocial/Academic Clubs .145 Generalized Anxiety .028 Prosocial/Academic Clubs .157 Social Anxiety .095 Prosocial/Academic Clubs .150 School Avoidance .188 Prosocial/Academic Clubs .143 Note. All main effect variables take into account all seven covariates. Coefficients reported in the table are log odds units. For gender, 0 = Male, 1 = Female. For SES, 1 = student receives free or reduced price lunch, 2 = student does not qualify for free or reduced price lunch. a For ethnicity, the reference category is white. p < .05.

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150 Logistic Regression Analy sis: Main Effects Yielded for Marijuana Use, Mental Health Problems, and Involvement in Special Interest Clubs B Predictor Gender .302 .305 .334 .365 .183 Age .012 055 .036 .027 .084 SES .664 .647 .692 .715 .646 African American a 1.472 1.404 1.432 1.252 1.435 Asian a 20.441 20.284 20.389 20.474 20.034 Hispanic a .527 .495 .528 .497 .558 Multiracial/Other a 1.314 1. 241 1.297 1.347 1.332 Depression .022 Special Interest Clubs .037 Generalized Anxiety .019 Special Interest Clubs .046 Social Anxiety .104 Special Interest Clubs .058 School Avoidance .216 Special Interest Clubs .041 Note. All main effect variables take into account all seven covariates. Coefficients reported in the table are log odds units. For gender, 0 = Male, 1 = Female. For SES, 1 = student re ceives free or reduced price lunch, 2 = student does not qualify for free or reduced price lunch. a For ethnicity, the reference category is white. p < .05.

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151 Logistic Regression Analy sis: Main Effects Yielded for Marijuana Use, Mental Health Problems, and Involvement in Performing Arts Clubs B Predictor Gender .302 .280 .307 .316 .164 Age .012 .030 .003 .014 .060 SES .664 .617 .666 .686 .626 African American a 1.472 1. 530 1.545 1.400 1.495 Asian a 20.441 20.332 20.446 20.550 20.077 Hispanic a .527 .494 .531 .503 .562 Multiracial/Other a 1.314 1.157 1.231 1.271 1.315 Depression .025 Performing Arts Clubs .035 Generalized Anxiety .022 Performing Arts Clubs .027 Social Anxiety .097 Performing Arts Clubs .021 School Avoidance .221 Performing Arts Clubs .007 Note. All main effect va riables take into account all seven covariates. Coefficients reported in the table are log odds units. For gender, 0 = Male, 1 = Female. For SES, 1 = student receives free or reduced price lunch, 2 = student does not qualify for free or reduced price lu nch. a For ethnicity, the reference category is white. p < .05.

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152 Logistic Regression Analy sis: Main Effects Yielded for Marijuana Use, Mental Health Problems, and Involvement in Athletic Activities B Predictor Gender .351 .180 .196 .173 .094 Age .007 .104 .090 .090 .126 SES .691 .670 .699 .725 .638 African American a 1.539 1.448 1.507 1.366 1.455 Asian a 20.501 20.316 20.383 20.457 20.073 Hispanic a 570 .550 .574 .530 .582 Multiracial/Other a 1.384 1.518 1.575 1.634 1.557 Depression .016 Athletics .266 Generalized Anxiety .011 Athletics .273 Social Anxiety .128 At hletics .330 * School Avoidance .169 Athletics .253 Note. All main effect variables take into account all seven covariates. Coefficients reported in the table are log odds units. For gender, 0 = Male, 1 = Female. For SES, 1 = student receives free or reduced price lunch, 2 = student does not qualify for free or reduced price lunch. a For ethnicity, the reference category is white. p < .05.