Innovative approaches to measuring and identifying risky sexual behaviors

PROJECT ABSTRACT Trading sex for compensation (e.g., money, drugs, alcohol) is a complex public health problem. Significant increases in internet usage have drastically changed the landscape of virtual sex trading (e.g., photos, webcamming). However, our understanding of sex trading is methodologically limited, as it most often relies on a single item, e.g., “have you ever traded sex for money or drugs?” Extant research does not differentiate between sex trading type (e.g., virtual vs. in-person), circumstances (e.g., economic need), compensation type (e.g., money, substances), risks (e.g., unprotected sex, victimization) and protective factors (e.g., harm reduction strategies). We have developed a multi-item sex trading measure to identify sex trading behaviors and their associated compensations, circumstances, risks, and harms. We validated our measure in a sample of university students, and we found that 11% of undergraduate students and 18.1% of graduate students reported at least one sex trading behavior, as compared to 2 to 4.5% of students in prior studies. Therefore, in- person and virtual sex trading may be more widespread and relevant to a larger segment of the population than previously assumed. Guided by the Risk Amplification and Abatement Model, this novel, multi-phase, mixed-methods proposal aims to: (1) adapt our validated sex trading measure for the general population; (2) use the resulting measure to identify the prevalence and associated characteristics (e.g., adverse experiences, substance use, mental health problems, and violence) of sex trading in a nationally representative sample of young adults (ages 18-34); and (3) examine the characteristics of sex trading in a non-probability sample of young people who report having participated in at least one sex trading behavior (ages 18-34). In aim 1, we will conduct 2-3 waves of cognitive interviews with people with who have traded sex to ensure clarity and relevance of our measure for a more diverse general population. In aim 2, we will use our resulting measure to assess sex trading in a nationally representative, probability-based sample (Amerispeak). In addition to reporting the prevalence of sex trading and associated characteristics (e.g., STIs, substance use), we will use Latent Class Analysis (LCA) to examine typologies of sex trading based on acts and associations between the resulting classes and compensation types, circumstances, and consequences. In aim 3, we will use web- based, Respondent Driven Sampling (webRDS) and replicate aim 2’s LCA to understand differences and similarities in sex trading among young adults who report sex trading and are at high risk of adverse outcomes. Data gleaned from these two samples will allow us to understand whether and how circumstances and associated harms differ between those who are captured in a nationally representative sample and those targeted based on identified sex trading, thereby ensuring that the experiences of the most vulnerable are made visible. Findings have the potential to transform our understanding of sex trading, which is needed to advance interventions and policies to support youth across settings.