Adolescent Recovery Capital and Recovery High School Attendance: An Exploratory Data Mining Approach

Recovery high schools (RHSs) provide a recovery-supportive academic environment for adolescents in recovery from a substance use disorder and are located across the United States. However, only a small proportion of the 160,000 youth in recovery each year in the United States enroll in RHSs posttreatment, indicating that many youth do not access this relapse prevention resource despite its effectiveness. Thus, this study uses the adolescent-adapted recovery capital model (RCAM) to understand individual- and community-level predictors of attendance and identify disparities leading to barriers to accessing RHSs. Data were collected as part of a multisite observational study of adolescents in recovery (N = 294). Logistic regressions and classification trees explored which different recovery capital factors predicted the odds of attending an RHS for at least 28 days during a 12-month period (n = 171) versus a non-RHS (e.g., traditional school: n = 123). The RCAM model is a useful theoretical framework for examining predictors of RHS attendance, and both analysis methods identified multiple unique predictors of RHS attendance. The strongest predictors of RI IS attendance were individual-level factors, including problem-solving skills, 12-Step frequency, and financial resources. The classification trees highlighted additional interactions that should be explored in future empirical research.