Protective factors in the prediction of criminal outcomes for youth with sexual offenses using tools developed for adults and adolescents: Tests of direct effects and moderation of risk.

Abstract

Interest in protective factors in risk assessment work with adjudicated populations is increasing and evidence suggests that protective factors in structured professional judgment (SPJ) tools predict the absence of one or more types of recidivism with some evidence also of incremental validity in recidivism-desistance prediction models with risk scales. But, there is little evidence of interactions, demonstrated using formal tests of moderation, between scores on risk- and protective factor-focused applied assessment tools, despite the documentation of interactive protective effects with nonadjudicated populations. In this study, with 273 justice-involved male youth and a fixed 3-year follow-up, direct effects of medium size were found for sexual recidivism, violent (including sexual) recidivism, and any new offense with totals for tools developed for adult offending populations (modified versions of the actuarial risk-focused Static-99 and the SPJ protective factor-focused Structured Assessment of PROtective Factor [SAPROF]) and tools developed for adolescent offending populations (the actuarial risk-focused Juvenile Sexual Offense Recidivism Risk Assessment Tool-II [JSORRAT-II] and the SPJ protective factor-focused DASH-13). As well, incremental validity and interactive protective effects, in the small-to-medium size range, were found for the prediction of violent (including sexual) recidivism using various combinations of these tools. The value-added information provided by strengths-focused tools indicated by these findings suggest their inclusion in comprehensive risk assessments in applied practice has promise for improving prediction and also intervention and management planning with justice-involved youth. The findings also highlight the need for further research on developmental considerations and practical questions about how to integrate strengths with risks to inform such work empirically. (PsycInfo Database Record (c) 2023 APA, all rights reserved).