How well do dynamic needs predict recidivism? Implications for risk assessment and risk reduction

Abstract

PurposeThe current study assessed the predictive validity of nine dynamic risk factors in two samples of justice-involved individuals (n=24,972) to identify promising targets for correctional programming. The study also tested the incremental predictive validity of dynamic risk relative to static indicators of recidivism risk (i.e., criminal history, age and sex). MethodsThe study relied on bivariate correlations and stepwise multivariate logistic regression analyses to test the predictive and incremental validity of dynamic risk constructs measured by the Level of Service Inventory-Revised (LSI-R). ResultsStudy findings revealed that while several dynamic risk constructs were significantly related to recidivism (antisocial attitudes, antisocial peers, education/employment, and substance abuse) over a 36-month follow-up period, the inclusion of dynamic risk items on the LSI-R did little to improve the overall predictive validity of the instrument. Across both study samples, static criminal history risk emerged as the most robust predictor of recidivism. ConclusionsThe advantages of third and fourth generation risk-need assessment tools are noted for classification purposes, but the study findings imply that risk prediction is better served by static risk factors. Implications for risk assessment and offender case management are discussed.