Differential Efficacy of Behavioral Health Interventions Across Latent Classes of Justice-involved Treatment Clients: A Test of the RNR Principles

• In Event: Substance Use Treatment for Criminal Offenders

Abstract

The risk, needs, responsivity (RNR) model of correctional programming and treatment posits that the recidivism reduction potential of rehabilitative correctional interventions is maximized when programs target high-risk (for recidivism) clients, address criminogenic needs, and use cognitive-behavioral treatment strategies tailored to the learning style of the individual (Andrews & Bonta, 2010). Utilizing a sample of 8,414 community corrections-involved treatment clients, the current study tests the differential effectiveness of six behavioral health treatment modalities across different types of clients defined by their risk and need factors. Latent class analysis (LCA) is used to identify four classes of treatment clients based on their criminal justice risk and needs profiles. These four latent classes are subsequently used to predict recidivism and treatment completion outcomes controlling for other relevant factors. The purpose of this study is to test the differential effectiveness of behavioral health interventions when they are appropriately matched to the risk and needs of justice-involved clients as defined by the RNR model. The implications of study findings for criminal justice and behavioral health treatment are discussed.

Authors

• Michael S. Caudy, University of Texas at San Antonio

• Faye S. Taxman, George Mason University