The Relationship Between Patterns of Change in Dynamic Risk and Strength Scores and Reoffending for Men on Community Supervision

Kayla A Wanamaker,Shelley L Brown

doi:10.1177/0093854821993512

Abstract

Research is needed focusing on the predictive nature of dynamic risk and strength score changes. The current study includes 11,953 Canadian men under community supervision with Service Planning Instrument re-assessment data. Using a retrospective, multi-wave longitudinal design, hierarchical linear modeling (HLM) was conducted to assess patterns of change in total dynamic risk and strength scores across three to five timepoints over 30 months. Change parameters from the HLM were incorporated into regression models, linking change to three reoffending outcomes: technical violations, new charges, and new violent charges. Results indicated that total dynamic risk scores decreased over time and total dynamic strength scores increased over time, although the rate of change for both was gradual. Change in total dynamic risk scores was predictive of all outcomes, whereas change in total dynamic strength scores only predicted technical violations. Results demonstrated the utility of re-assessing dynamic risk and strength scores over time.

Highlights

Assessing an individual’s risk to reoffend while on community supervision is a fundamental task of correctional organizations
The purpose of this study is to examine how dynamic strength and dynamic risk factors change over time and how they may change in conjunction, which is essential to further advance the correctional field of risk assessment, and how we approach treatment and rehabilitative efforts
Using a sample of 136 justice-involved men released from federal institutions in Ontario, Canada, Cox regression with time-dependent covariates and receiver operating characteristics (ROC) analyses revealed the re-assessment of dynamic risk factors significantly predicted recidivism over and above static risk factors alone

Summary

Introduction

Assessing an individual’s risk to reoffend while on community supervision is a fundamental task of correctional organizations. Static risk factors either do not change, such as “age at first arrest,” or if they do change, it is not as a function of intervention, such as “number of Wanamaker, Brown / Dynamic Risk and Strength 1209 prior convictions.” These factors, cannot act as treatment targets but are useful for classifying an individual’s degree of risk for reoffending (Mann et al, 2010). The purpose of this study is to examine how dynamic strength and dynamic risk factors change over time and how they may change in conjunction, which is essential to further advance the correctional field of risk assessment, and how we approach treatment and rehabilitative efforts. While Cox regression with time-dependent covariates is useful for comparing the predictability of models using data from different timepoints and can inform the predictability of incremental change among assessments, it does not examine a person’s overall rate of change and how that change predicts reoffending

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Discussion

Conclusion