Department of Psychiatry, Warneford Hospital, University of Oxford, Oxford, United Kingdom.
Department of Clinical Neuroscience, Karolinska Institutet, Stockholm, Sweden.
JAMA Netw Open. 2023 Jul 3;6(7):e2325494. doi: 10.1001/jamanetworkopen.2023.25494.
Current risk assessment tools for domestic violence against family members were developed with small and selected samples, have low accuracy with few external validations, and do not report key performance measures.
To develop new tools to assess risk of reoffending among individuals who have perpetrated domestic violence.
DESIGN, SETTING, AND PARTICIPANTS: This prognostic study investigated a national cohort of all individuals arrested for domestic violence between 1998 and 2013 in Sweden using information from multiple national registers, including National Crime Register, National Patient Register, Longitudinal Integrated Database for Health Insurance and Labour Market Studies Register, and Multi-Generation Register. Data were analyzed from August 2022 to June 2023.
Arrest for domestic violence.
Prediction models were developed for 3 reoffending outcomes after arrest for domestic violence: conviction of a new violent crime (including domestic violence), conviction of any new crime, and rearrest for domestic violence at 1 year, 3 years, and 5 years. The prediction models were created using sociodemographic factors, criminological factors, and mental health status-related factors, linking data from multiple population-based longitudinal registers. Cox proportional hazard multivariable regression was used to develop prediction models and validate them in external samples. Key performance measures, including discrimination at prespecified cutoffs and calibration statistics, were investigated.
The cohort included 27 456 individuals (mean [SD] age, 39.4 [11.6] years; 24 804 men [90.3%]) arrested for domestic violence, of whom 4222 (15.4%) reoffended and were convicted for a new violent crime during a mean (SD) follow-up of 26.5 (27.0) months, 9010 (32.8%) reoffended and were convicted for a new crime (mean [SD] follow-up, 22.4 [25.1] months), and 2080 (7.6%) were rearrested for domestic violence (mean [SD] follow-up, 25.7 [30.6] months). Prediction models were developed with sociodemographic, criminological, and mental health factors and showed good measures of discrimination and calibration for violent reoffending and any reoffending. The area under the receiver operating characteristic curve (AUC) for risk of violent reoffending was 0.75 (95% CI, 0.74-0.76) at 1 year, 0.76 (95% CI, 0.75-0.77) at 3 years, and 0.76 (95% CI, 0.75-0.77) 5 years. The AUC for risk of any reoffending was 0.76 (95% CI, 0.75-0.77) at 1 year and at 3 years and 0.76 (95% CI, 0.75-0.76) at 5 years. The model for domestic violence reoffending showed modest discrimination (C index, 0.63; 95% CI, 0.61-0.65) and good calibration. The validation models showed discrimination and calibration performance similar to those of derivation models for all 3 reoffending outcomes. The prediction models have been translated into 3 simple online risk calculators that are freely available to use.
This prognostic study developed scalable, evidence-based prediction tools that could support decision-making in criminal justice systems, particularly at the arrest stage when identifying those at higher risk of reoffending and screening out individuals at low risk of reoffending. Furthermore, these tools can enhance treatment allocation by enabling criminal justice services to focus on modifiable risk factors identified in the tools for individuals at high risk of reoffending.
目前针对家庭成员间家庭暴力的风险评估工具是在小样本和选定样本的基础上开发的，准确性较低，外部验证较少，并且没有报告关键性能指标。
开发新的工具来评估有过家庭暴力行为的个体再次犯罪的风险。
设计、地点和参与者：本预后研究使用来自多个国家登记处（包括国家犯罪登记处、国家患者登记处、健康保险和劳动力市场研究登记处的纵向综合数据库以及多代登记处）的信息，调查了 1998 年至 2013 年间在瑞典因家庭暴力被捕的所有个体的全国队列。数据于 2022 年 8 月至 2023 年 6 月进行分析。
因家庭暴力被捕。
为家庭暴力逮捕后的 3 种再犯罪结果（包括家庭暴力的新暴力犯罪、任何新犯罪的定罪以及 1 年、3 年和 5 年的家庭暴力再次被捕）制定了预测模型。预测模型是使用社会人口统计学因素、犯罪学因素和心理健康相关因素创建的，链接了多个基于人群的纵向登记处的数据。使用 Cox 比例风险多变量回归来开发预测模型，并在外部样本中进行验证。研究了关键性能指标，包括在预定切点的区分度和校准统计数据。
队列包括 27456 名（平均[标准差]年龄，39.4[11.6]岁；24804 名男性[90.3%]）因家庭暴力被捕的个体，其中 4222 名（15.4%）再次犯罪并被新的暴力犯罪定罪，平均（标准差）随访 26.5（27.0）个月，9010 名（32.8%）再次犯罪并被新犯罪定罪（平均[标准差]随访，22.4[25.1]个月），2080 名（7.6%）因家庭暴力再次被捕（平均[标准差]随访，25.7[30.6]个月）。预测模型是使用社会人口统计学、犯罪学和心理健康因素开发的，对于暴力再犯罪和任何再犯罪，均显示出良好的区分度和校准度。风险为暴力再犯罪的接收器操作特征曲线（AUC）的 AUC 为 0.75（95%CI，0.74-0.76），在 1 年、0.76（95%CI，0.75-0.77）和 3 年，0.76（95%CI，0.75-0.77）在 5 年。风险为任何再犯罪的 AUC 为 0.76（95%CI，0.75-0.77），在 1 年和 3 年，以及 0.76（95%CI，0.75-0.76）在 5 年。家庭暴力再犯罪的模型显示出适度的区分度（C 指数，0.63；95%CI，0.61-0.65）和良好的校准度。验证模型在所有 3 种再犯罪结果方面显示出与推导模型相似的区分度和校准度性能。预测模型已被翻译成 3 个简单的在线风险计算器，可免费使用。
本预后研究开发了可扩展的、基于证据的预测工具，可支持刑事司法系统的决策，特别是在逮捕阶段，以识别那些再次犯罪风险较高的个体，并筛选出再次犯罪风险较低的个体。此外，这些工具可以通过使刑事司法服务专注于在高风险再犯罪的个体中识别出可修改的风险因素，从而增强治疗分配。
