Citation

Olver ME, Mundt JC, Hogan NR, Coupland RBA, Eggert JE, Higgs T, Lewis K, Cortoni F, Gordon A, Morgan PJ, Wong SCP. Psychol. Assess. 2022; ePub(ePub): ePub.

Copyright

(Copyright © 2022, American Psychological Association)

DOI

10.1037/pas0001116

PMID

35175077

Abstract

The present study features the development of new risk categories and recidivism estimates for the Violence Risk Scale (VRS), a violence risk assessment and treatment planning tool. We employed a combined North American multisite sample (k = 6, N = 1,338) of adult mostly male offenders, many with violent criminal histories, from correctional or forensic mental health settings that had complete VRS scores from archival or field ratings and outcome data from police records (N = 1,100). There were two key objectives: (a) to identify the rates of violent recidivism associated with VRS scores and (b) to generate updated evidence-based VRS violence risk categories with external validation. To achieve the first objective, logistic regression was applied using VRS pretreatment and change scores on treated samples with a minimum 5-year follow-up (k = 5, N = 472) to model 2-, 3-, and 5-year violent and general recidivism estimates, with the resulting logistic regression algorithms retained to generate a VRS recidivism rates calculator. To achieve the second objective, the Council of State Governments' guidelines were applied to generate five risk levels using the common language framework using percentiles, risk ratios (from Cox regression), and absolute violent and general recidivism estimates (from logistic regression). Construct validity of the five risk levels was examined through group comparisons on measures of risk, need, protection, and psychopathy obtained from the constituent samples. VRS applications to enhance risk communication, treatment planning, and violence prevention in light of the updated recidivism estimates and risk categories are discussed. (PsycInfo Database Record (c) 2022 APA, all rights reserved).

Language: en