Applying Classification and Regression Tree Analysis to Identify Prisoners with High HIV Risk Behaviors

Abstract

Among prisoners, past research has associated several factors with HIV risk behaviors, including illicit drug use, engaging in sex trade, older age (for drug-related risk), younger age (for sexrelated risk), low education, low income, type of offense, history of abuse, mental health disorders, vulnerability and low self-perceived efficacy. This study employs data collected through the Transitional Case Management study of the Criminal Justice Drug Abuse Treatment Studies collaborative to analyze characteristics of prisoners who engaged in high-risk behaviors prior to incarceration. For the first 787 participants of this study, we employed recursive partitioning techniques to better identify groups at varying levels of HIV risk behaviors. Those more likely to engage in risky needle use were White and either unemployed and less likely to justify their behavior, or employed with poor decision making capacity. Risky sexual behavior was associated with a general tendency toward risk-taking or a history of unstable housing. Those engaging in any type of HIV risk behavior were risk-takers in general and were aged 25 to 47 with a history of unstable housing. Recursive partitioning, a technique seldom used previously, offers a useful method for identifying subpopulations at elevated risk for HIV risk behaviors.

Keywords:

• drugs
• HIV
• prisoners
• recursive partitioning