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改进我们的风险沟通:简要评估再犯风险-2002R 的标准化风险水平。

Improving Our Risk Communication: Standardized Risk Levels for Brief Assessment of Recidivism Risk-2002R.

机构信息

Department of Psychology and Neuroscience, 3688Dalhousie University, Halifax, NS, Canada.

Department of Psychology, 6339Carleton University, Ottawa, ON, Canada.

出版信息

Sex Abuse. 2022 Sep;34(6):667-698. doi: 10.1177/10790632211047185. Epub 2021 Oct 20.

Abstract

A Five-Level Risk and Needs system has been proposed as a common language for standardizing the meaning of risk levels across risk/need tools used in corrections. Study 1 examined whether the Five-Levels could be applied to BARR-2002R ( = 2,390), an actuarial tool for general recidivism. Study 2 examined the construct validity of BARR-2002R risk levels in two samples of individuals with a history of sexual offending ( = 1,081). Study 1 found reasonable correspondence between BARR-2002R scores and four of the five standardized risk levels (no Level V). Study 2 found that the profiles of individuals in Levels II, III, and IV were mostly consistent with expectations; however, individuals in the lowest risk level (Level I) had more criminogenic needs than expected based on the original descriptions of the Five-Levels. The Five-Level system was mostly successful when applied to BARR-2002R. Revisions to this system, or the inclusion of putatively dynamic risk factors and protective factors, may be required to improve alignment with the information provided by certain risk tools.

摘要

已提出五级风险和需求系统,作为在矫正中使用的风险/需求工具中标准化风险水平含义的通用语言。研究 1 检验了五级风险和需求系统是否可应用于 BARR-2002R(=2,390),这是一种用于一般累犯的计量风险工具。研究 2 在两个有性犯罪史的个体样本(=1,081)中检验了 BARR-2002R 风险水平的结构有效性。研究 1 发现 BARR-2002R 分数与五个标准化风险水平中的四个(没有第五级)有合理的对应关系。研究 2 发现,第二、三和四级个体的特征与预期基本一致;然而,处于最低风险水平(第一级)的个体比五级风险和需求系统的原始描述所预期的有更多的犯罪倾向需求。五级风险和需求系统在应用于 BARR-2002R 时基本成功。可能需要对此系统进行修订,或者纳入推测性的动态风险因素和保护因素,以提高与某些风险工具提供的信息的一致性。

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Improving Risk Communication: Developing Risk Ratios for the VRAG-R.改善风险沟通:为VRAG-R制定风险比率。
J Interpers Violence. 2022 Jan;37(1-2):835-862. doi: 10.1177/0886260520914555. Epub 2020 Apr 22.
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The case against categorical risk estimates.反对分类风险估计的理由。
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