Department of Psychology, University of Saskatchewan.
Sand Ridge Secure Treatment Centre.
Psychol Assess. 2018 Jul;30(7):941-955. doi: 10.1037/pas0000538. Epub 2018 Apr 30.
The present study sought to develop updated risk categories and recidivism estimates for the Violence Risk Scale-Sexual Offense version (VRS-SO; Wong, Olver, Nicholaichuk, & Gordon, 2003-2017), a sexual offender risk assessment and treatment planning tool. The overarching purpose was to increase the clarity and accuracy of communicating risk assessment information that includes a systematic incorporation of new information (i.e., change) to modify risk estimates. Four treated samples of sexual offenders with VRS-SO pretreatment, posttreatment, and Static-99R ratings were combined with a minimum follow-up period of 10-years postrelease (N = 913). Logistic regression was used to model 5- and 10-year sexual and violent (including sexual) recidivism estimates across 6 different regression models employing specific risk and change score information from the VRS-SO and/or Static-99R. A rationale is presented for clinical applications of select models and the necessity of controlling for baseline risk when utilizing change information across repeated assessments. Information concerning relative risk (percentiles) and absolute risk (recidivism estimates) is integrated with common risk assessment language guidelines to generate new risk categories for the VRS-SO. Guidelines for model selection and forensic clinical application of the risk estimates are discussed. (PsycINFO Database Record
本研究旨在为性犯罪者风险评估和治疗计划工具——性暴力风险量表（VRS-SO；Wong、Olver、Nicholaichuk 和 Gordon，2003-2017 年）开发更新的风险类别和再犯率估计。总体目的是提高风险评估信息的准确性和清晰度，包括系统地纳入新信息（即变化）来修改风险估计。将具有 VRS-SO 预处理、后处理和静态-99R 评级的四个治疗性罪犯样本与至少 10 年的释放后随访期（N=913）相结合。使用逻辑回归对 6 种不同的回归模型进行建模，这些模型分别使用 VRS-SO 和/或静态-99R 的特定风险和变化评分信息，以预测 5 年和 10 年的性和暴力（包括性）累犯率。介绍了在跨重复评估中使用变化信息时为特定模型选择和控制基线风险的临床应用的基本原理。有关相对风险（百分位数）和绝对风险（累犯率估计）的信息与常见的风险评估语言指南相结合，为 VRS-SO 生成新的风险类别。讨论了模型选择和风险估计的法医临床应用的指南。
