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INTRODUCTION. HIV/AIDS is a pressing public health concern for youth in South Africa (MacPhail & Campbell, 2001). Uncovering and addressing population-specific risk factors for sexual behavior may help reduce the transmission of HIV.
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INTRODUCTION • HIV/AIDS is a pressing public health concern for youth in South Africa (MacPhail & Campbell, 2001). Uncovering and addressing population-specific risk factors for sexual behavior may help reduce the transmission of HIV. • Previous cross-sectional research suggests that substance use is linked to both sexual intercourse and certain sexual risk behaviors in this population (e.g., Palen, Smith, Flisher, Caldwell, & Mpofu, 2006). • Longitudinal studies of U.S. adolescents have shown that substance use tends to predict sexual initiation (e.g., Blinn-Pike, Berger, Hewett, & Oleson, 2004; Guo et al., 2005; Santelli et al., 2004). • However, previous research has not examined populations from outside of the U.S., nor has it tested the alternative hypothesis that sexual activity plays a role in the initiation of substance use. • A clearer understanding of the developmental nature of associations between sex and substance use could inform efforts to prevent the transmission of HIV among South African youth. RESEARCH AIMS • Describe patterns of transition to substance use and sexual intercourse among South African high school students. • Determine whether these patterns differ by treatment status and time of year. Transitions to Sexual Intercourse and Substance Use Among South African High School Students Lori-Ann Palen, Edward A. Smith & Linda L. Caldwell The Pennsylvania State University Funded by NIH R01 DA01749, NIH T32 DA017629-01A1 METHOD RESULTS DISCUSSION • Of sexual intercourse and substance use, substance use was typically the first risk behavior to be initiated. • Youth were more likely to initiate new risk behaviors during the school year than during the summer months. • There were no significant treatment group differences in engagement in, or transitions to, risk behavior. Details of Model-fitting: • The best-fitting models fit reasonably well: G2boys(2031) = 740, G2girls(2031) = 497. • The final measurement parameters showed that participants had a high probability of being classified into the correct treatment group (ρboys = .89, ρgirls = .89) and risk behavior condition (Pboys = .91, Pgirls = .96). • The best-fitting models were the ones in which: • the proportion of participants in each risk behavior condition and probabilities of transition between these conditions were equal across treatment groups. • the probabilities of transition were different by timing (over school year vs. over summer) but otherwise equal (T1T2 = T3T4, T2T3 = T4T5). • These results suggest that researchers and practitioners should give greater attention to potential mechanisms driving the association between substances and the initiation of sexual behavior. • We should also attempt to understand the social and environmental factors underlying school/summer differences in transitions to risk behavior in this population. • While this study provided no evidence of treatment effects on risk behavior transitions, we believe recently-implemented program modifications may result in effects for future cohorts. PARTICIPANTS • 2,416 students from Mitchell’s Plain, South Africa • Participating in a research trial of a classroom-based leisure, life skill, and sexuality education program (42% program, 58% control) • Five assessments: beginning and end of Grades 8 and 9, beginning of Grade 10 • Baseline demographics: mean age 14.0 years, 51% female, 86% Coloured (derived from Asian, European and African ancestry) • MEASURES • Composite dichotomous substance use variable, indicating whether participants had used alcohol and/or marijuana in their lifetime • Dichotomous variable indicating whether participants had engaged in vaginal sexual intercourse in their lifetime Figure 1: Proportion of participants in each risk behavior condition at Time 1. ANALYSIS • Latent transition analysis (LTA; Lanza, Flaherty, & Collins, 2002) using WinLTA 3.1 software (Collins, Lanza, Schafer, & Flaherty, 2002) • Parameters estimated: • Measurement precision • Proportion of participants in each risk behavior condition (no risk behavior, substance use only, sexual intercourse only, both risk behaviors) • Probability of transition between conditions • Probabilities of “impossible” transitions (e.g., substance use no risk behavior) were fixed at zero. • Chi-square difference tests were used to compare competing models of risk behavior. • Preliminary analyses showed that the measurement parameters varied significantly by gender. Consequently, separate models were fit for boys and girls. Figure 2: Probability of remaining in previous risk behavior condition. Figure 3: Proportion of participants in each risk behavior condition at Time 5.