Risk Assessment Trajectories of Youth During Juvenile Justice Residential Placement

Abstract

Although the Risk–Needs–Responsivity framework has become the dominant paradigm in criminal and juvenile justice, little empirical attention has been given to the reassessment component of the model. Here, we examine dynamic risk and promotive factor trajectories of 6,442 residential commitment placements to assess differences in progression with respect to risk reduction and promotive enhancement through a buffer score rubric (buffer = promotive − risk). Results indicate that youth progress along different buffer trajectories throughout residential placement. Multinomial models also demonstrate that dynamic, changeable factors are more essential in distinguishing trajectory group membership than demographic or criminal history indicators. Finally, there were significant differences in recidivism rates across trajectories postcompletion, suggesting that improvement in (the rate of change in) buffer scores may account for some of the variation in offending behavior postrelease. Programmatic and policy implications are discussed.

The Role of Protective Factors in the Predictive Accuracy of the Structured Assessment of Violence Risk in Youth (SAVRY)

“…Finally, regardless of the way the protective items were measured (e.g., items, domain) and modeled (e.g., direct effects, moderation), the individual risk domain was found to be the strongest and most consistent predictor of reoffending. The importance of the dynamic, individual-level risk factors has been confirmed in previous studies using the SAVRY (Penney et al, 2010) and other RAIs (Baglivio, Wolff, Piquero, Howell, & Greenwald, 2017;McGrath & Thompson, 2012;Peterson-Badali, Skilling, & Haqanee, 2015). This finding provides further support for the inclusion of dynamic risk factors, or needs factors, in RAIs.…”

The Interrelationship Between Empathy and Adverse Childhood Experiences and Their Impact on Juvenile Recidivism

“…Additionally, the ability of dynamic changes in R-PACT domain risk scores to predict recidivism post-release has multi-sample support from several studies (c.f. Baglivio et al, 2017; Baglivio et al, 2018; Wolff et al, 2017).…”

Understanding Changes in Youth Offenders’ Risk Profiles: A Latent Transition Analysis

“…Brown, Amand, and Zamble (2009) identified six risk factors (substance abuse, social support, employment, negative affect, perceived problem index, and expectation of positive outcomes of crime) that changed over time and contributed to explaining recidivism. In a study with 12,302 youth from residential placement, Baglivio and colleagues (2017)[Please clarify whether Baglivio and colleagues (2017) refers to Baglivio, M. T., Wolff, K. T., Jackowski, K., & Greenwald, M. A. (2017).…”

“…In addition, group-based method was used to track changes at multiple time points and examine subgroups of trajectories. Based on multiple assessment in residential service, Baglivio and colleagues (2017)[Please clarify whether Baglivio and colleagues (2017) refers to Baglivio, M. T., Wolff, K. T., Jackowski, K., & Greenwald, M. A. (2017).…”