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Psychosocial Intervention

On-line version ISSN 2173-4712Print version ISSN 1132-0559


LILA, Marisol et al. Identifying key predictors of recidivism among offenders attending a batterer intervention program: a survival analysis. Psychosocial Intervention [online]. 2019, vol.28, n.3, pp.157-167.  Epub Jan 27, 2020. ISSN 2173-4712.

Strategies to reduce intimate partner violence against women (IPVAW) can be targeted at different levels. Batterer intervention programs (BIPs) are among the main treatment approaches for IPVAW offenders. The most common outcome used in the evaluation of BIP effectiveness is recidivism. Efforts to increase BIP effectiveness in reducing recidivism should focus on key predictive variables of this outcome. The aim of this study was to identify key predictors of official recidivism from a large set of variables drawn from a sample of IPVAW offenders court-mandated to a community-based BIP (N = 393), with a follow-up period of between 0 and 69 months. To this end, a survival analysis was conducted using four sets of variables: individual-level, relational- and contextual-level, violence-related, and intervention process-related variables. To include all variables in the analysis simultaneously, a Cox regression model was estimated with the adaptive least absolute shrinkage and selection operator (ALASSO). From a pool of eighty-nine variables, six were selected as key predictors of recidivism: dropout, risk of future violence against non-partners, family violence exposure, immigrant status, accumulation of stressful life events, and trait anger. The area under the receiving operator characteristic (ROC) curve was .808, indicating good prediction of the model. The key predictors of recidivism found in this study should be considered by professionals and researchers in the BIP field to improve their evaluation and intervention strategies. Practical implications for future research are also discussed.

Keywords : Intimate partner violence; Offenders; Batterer intervention programs; Recidivism; Predictors.

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