RISKY SEXUAL BEHAVIOR AND SUBSTANCE USE AMONG ADOLESCENTS: A META-ANALYSIS BY TIARNEY D. RITCHWOOD JOHN E. LOCHMAN, COMMITTEE CHAIR JAMIE DECOSTER EDWARD D. BARKER RANDALL T. SALEKIN THOMAS B. WARD A DISSERTATION Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the Department of Psychology in the Graduate School of The University of Alabama TUSCALOOSA, ALABAMA 2012 Copyright Tiarney Dannone Ritchwood 2012 ALL RIGHTS RESERVED ABSTRACT Adolescents’ participation in risky sexual behavior has continued to grow over the past 15 years, as they account for approximately 25% of all new STD cases (4). These elevated rates of STD infection have created a sense of urgency in the need to understand the predictors of risky sexual behavior (RSB). Due to its disinhibiting effects on decision-making, the influence of substance use on sexual behavior has been the focus of research for at least two decades. While substance use and risky sexual behavior are among the top predictors of HIV infection in adults, less is known about the moderators of the relation between these two variables across studies amongst adolescents. In response to this crisis, the purpose of this meta-analysis is to examine the strength of the relation between risky sexual behavior and substance use among adolescents and elucidate the gaps in the literature. It will also enable researchers to generate hypotheses that will guide empirical investigations. We employed a multiple pathways approach to investigate the moderators (i.e., gender, type of drug) of the relation between adolescent substance use and risky sexual behavior. Results indicated that gender, type of drug, and level of analysis were significant moderators of the relation between RSB and substance use. Implications and suggestions for future directions will be discussed. ii DEDICATION This dissertation is dedicated to the family members and close friends who offered their support and words of encouragement during this very important time in my life. I am especially thankful for my mother, Mary, father, Vincent, and grandmother, Clara. Hearing how proud they were of me was invaluable. iii LIST OF ABBREVIATIONS AND SYMBOLS α Cronbach’s index of internal consistency df Degrees of freedom: number of values free to vary after certain restrictions have been placed on the data F Fisher’s F ratio: A ration of two variances M Mean: the sum of a set of measurements divided by the number of measurements in the set p Probability associated with the occurrence under the null hypothesis of a value as extreme as or more extreme than the observed value Q a statistic used for multiple significance testing across a number of means r Pearson product-moment correlation t Computed value of t test < Less than = Equal to iv ACKNOWLEDGMENTS This is a great opportunity to thank Dr. Jamie DeCoster, who graciously shared his research expertise and vast knowledge of meta-analysis with me. Throughout this process, Jamie has been extremely patient and has provided me with priceless guidance and advice. I am very grateful for his mentorship and friendship during my graduate studies. I would also like to thank my advisor, Dr. John Lochman. I have had the opportunity to work with a great level of independence as a graduate student, which has enabled me to further develop my research interests and skills. Although my research interests differed significantly from his area of expertise, John was very supportive of my goals and connected me to valuable research presentation and training opportunities throughout the years. I would like to thank Dr. Melissa Jackson, who mentored and advised me during my first year in the clinical psychology program. Melissa helped me to set the foundation of my graduate career and provided me with valuable guidance on how to successfully matriculate. I have made use of her early advice throughout graduate school. Thank you to all of my committee members, John Lochman, Jamie DeCoster, Ted Barker, Tom Ward, and Randy Salekin, for their helpful suggestions and support of my dissertation research. I would also like to thank my fellow graduate students and collaborators, Haley Ford and Marnie Sutton, for their assistance with this meta-analysis. I would like to express my sincere gratitude to my family and friends for their support during my entire academic career. They have kept me uplifted in prayer and encouragement and for this, I am truly grateful. v CONTENTS ABSTRACT…………………………………………………………………………….ii DEDICATION…………………………………………………………………………iii LIST OF ABBREVIATIONS AND SYMBOLS………………………………………iv ACKNOWLEDGMENTS…………………………...……………………………….....v LIST OF TABLES……………………………………………………………………..vii LIST OF FIGURES.…………………………………………………………………..viii 1. INTRODUCTION……………….………………………………………..…………..1 2. METHOD………..…………………………………………………………………..24 a. Sample of studies……………………………………………………………......…..24 b. Inclusionary and exclusionary criteria………………....………………………...….25 c. Sample characteristics coded………………………………………………...……...27 d. Reliability……………………………………………………………………………27 e. Computation of effect sizes………………………………………………………….28 3. RESULTS…………………………………………………………………….…..….31 a. Descriptive analyses…………………………………………………………...…….31 b. Moderator analyses……………………………………………………………...…..32 4. DISCUSSION……………………………………………………………………......39 5. REFERENCES…………………………………………………………………….....70 vi LIST OF TABLES 1. Descriptives from included studies…………………………………………………....94 2. Effect sizes……………………………………………………………………………113 3. Summary of effect size characteristics……………………………………………….116 4. Results of categorical moderator analyses.…………………………………………...117 5. Results of continuous moderator analyses……………………………………………122 6. Significant relations among moderators………………………………………………124 vii TABLE OF FIGURES 1. Document type……………………………………………………………..……..128 2. Nationality…………………………………………………………………..…….128 3. Sample type…………………………………………………………………..…...129 4. Type of drug…………………………………………………………………..…..129 5. Drug use assessment…………………………………………………………...….130 6. Sexual behavior assessment…………………………………………………...…..130 7. Drug use definition……………………………………………………………...…131 8. Risky sexual behavior definition…………………………………………………..131 9. Drug use relation measurement…………………………………………………....132 10. Risky sexual behavior relation measurement……………………………………...132 11. Ethnicity……………………………………………………………………………133 10. Sexuality……………………………………………………………………………133 viii INTRODUCTION Over the past ten years, we have witnessed significant changes in adolescent sexual behavior. Specifically, there has been an overall decline in early onset sexual activity and an overall increase in contraceptive use (Brener, Kann, Lowry, & Wechler, 2006). Despite these improvements, adolescent risky sexual behavior (RSB) remains a significant public health challenge. Rates of sexually transmitted infections (STIs) and sexually transmitted diseases (STDs) have continued to grow, reaching epidemic proportions. Adolescents, for example, comprise approximately 50% of all new STI cases (Weinstock, Berman, & Cates, 2004) and of particular concern are the increases in the rates of HIV infection in this group. Since the development of a vaccine or cure for HIV/AIDS remains a remote possibility, researchers and clinicians have focused their efforts on prevention. In addition to the personal costs of contracting HIV, there is also a substantial societal cost associated with HIV infection. The development of antiretroviral therapy (ART) not only significantly prolonged the lives of individuals infected with HIV, but it also significantly impacted HIV-related medical care costs (Gebo, Chalsson, Folkemer, Bartlett, & Moore, 1999). The life expectancy for individuals in the United States entering ART at the recommended time (CD4 cell count greater than 500 cells/µL) is approximately 24.2 years (Schackman et al., 2006). The lifetime costs, most of which are accounted for by the high costs of medications, are approximately $618,900. HIV infection presents serious repercussions for adolescents, as there are many associated complications, including neurological problems (McArthur, Brew, & Nath, 2005) and cardiovascular disease (Wang, Chai, Yao, & Chen, 2007). 1