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.

需要研究的重点是动态风险和强度得分变化的预测性质。当前的研究包括11953名加拿大男子，他们在社区监督下拥有服务计划工具的重新评估数据。使用回顾性多波纵向设计，进行了分层线性建模（HLM），以评估30个月内三到五个时间点的总动态风险和强度得分的变化模式。来自HLM的变更参数被纳入回归模型，将变更与三个令人反感的结果相关联：技术违规，新指控和新暴力指控。结果表明，总的动态风险评分随时间降低，而总的动态强度评分随时间升高，尽管两者的变化率都是渐进的。动态风险总分的变化可预测所有结果，而动态强度总分的变化仅预测技术违规。结果表明，随着时间的推移重新评估动态风险和强度得分的实用性。