A More Consistent Application of the RNR Model

Abstract

The development of risk–needs assessments has substantially expanded assessment content, which is reflected in the now regular use of both static and dynamic items. However, while the risk–need–responsivity model differentiates between risks and needs theoretically, the scoring of risks and needs does not make for a clear demarcation. We argue that an assessment of an offender’s needs should be scored separately and solely on items that are changeable and predict recidivism. This article describes the conceptualization and development of Washington State’s offender needs assessment. Designed to complement an offender’s assessment of risk, we make use of key design elements to avoid many theoretical and methodological caveats. Using preexisting item selection, weighting, and validation methods, we present domain-based needs models that maximize item content and provide substantial performance in the prediction of recidivism.

Optimizing Youth Risk Assessment Performance: Development of the Modified Positive Achievement Change Tool in Washington State

“…Specifically, tools implemented without an understanding of local context and agency needs often lack fidelity upon implementation (Taxman & Belenko, 2011). An understanding of not just the likelihood but also the type/severity of recidivism is another important consideration (Barnoski & Drake, 2007; Hamilton et al, 2017; Hamilton et al, 2016). Finally, the varying pathways and predictors of male and female offending influence prediction (Broidy, Payne, & Piquero, 2018; Schwalbe, Fraser, & Day, 2007).…”

“…Risk instruments often take a diagnostic perspective, where an individual’s response scores are counted until an agreed upon threshold is exceeded. An assumption concerns the outcome being observed similarly within all humans who have a similar set of indicators (Desmarais & Singh, 2013; Hamilton et al, 2017; Hamilton et al, 2016). When risk for reoffending is predicted, variations in local statutes and populations differentially impact item selection, response prevalence, outcome operationalizations, and the weight each response should have in the prediction equation.…”

“…Recent changes in assessment development have involved tailoring an instrument to the local population and a jurisdiction’s needs (Hamilton et al, 2017; Hamilton et al, 2016). Instrument tailoring involves taking an off-the-shelf assessment and adapting it to align with a given population’s prevalence of risk factors, allowing for optimization of predictive performance.…”

“…Since their initial expansion from adult to youth tools, assessments have advanced to provide ever-increasing detail and prediction (see Andrews & Bonta, 2010; Hamilton et al, 2016). However, while advanced modeling efforts have sought to improve the accuracy of adult assessments (Hamilton, Campagna, Tollefsbol, van Wormer, & Barnoski, 2017; Taxman, 2017), risk assessments for justice-involved youth have notably lagged (Vincent, Laura, & Grisso, 2012). Appropriate assessment of justice-involved youths’ risk and needs is a core focus in juvenile justice reform in Washington State specifically (Hamilton, van Wormer, & Barnoski, 2015).…”

“…Initial findings indicated substantial improvements in predictive strength; however, greater methodological advancements were desired, and subject matter experts (SMEs) requested several variations and recategorization of study outcomes. Based on prior findings modifying adult assessment tools (Hamilton et al, 2017; Hamilton et al, 2016) and in collaboration with the WAJCAs, the current study sought to tailor the M-PACT for Washington State probation youth.…”