Decision-Making Modeling for Treating Intimate Partner Violence

治疗亲密伴侣暴力的决策模型

• 批准号: 10215622
• 负责人: Gunnur Karakurt Koyuturk
• 金额: $ 4.5万
• 依托单位: CASE WESTERN RESERVE UNIVERSITY
• 依托单位国家: 美国
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-08-06 至 2023-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10215622
• 关键词: Address; Affect; Age; Bayesian Network; Cessation of life; Clinical; Cluster Analysis; Communities; Complex; Custom; Data; Data Analyses; Decision Making; Dimensions; Economics; Effectiveness; Ethnic Origin; Evaluation; Evidence based treatment; Factor Analysis; Family; Female; Gender; Goals; Group Therapy; Grouping; Guidelines; Immigration; Individual; Inequality; Injury; Intervention; Investigation; Lead; Literature; Meta-Analysis; Methods; Mining; Modeling; Outcome; Outcomes Research; Participant; Pattern; Play; Population; Psychopathology; Quality of life; Race; Recovery; Reporting; Research; Resources; Role; Series; Severities; Sexual abuse; Site; Social Environment; Societies; Subgroup; Support Groups; Survivors; System; Techniques; Treatment Effectiveness; Treatment outcome; Validation; Victimization; Violence; Woman; Work; age related; anger management; base; data mining; demographics; disparity reduction; effective therapy; effectiveness study; emotional abuse; experience; feature selection; handbook; improved; intimate partner violence; men; model building; offender; optimal treatments; partner violence; perpetrators; physical abuse; recidivism; relationship violence; research study; response; satisfaction; social; socioeconomics; standard care; success; systematic review; tool; treatment group; treatment response

Project Summary Intimate partner violence (IPV) is defined as any physical, sexual, or emotional abuse of a current or former intimate partner. Approximately one in four women will experience some form of severe partner violence during their lifetime, and many of these situations result in serious injury or death. Although men can also be victims of IPV, most cases involve female victimization. Gender specific group therapy is widely considered as the standard treatment for IPV, but some participants of these groups do not experience a decrease in violence in response to these treatments. Reports on the effectiveness of standard treatments, as well as research findings suggest that different treatments may be more effective in reducing violence recidivism in certain situations. Many factors influence how participants respond to treatment. These factors include demographics, types of violence, and treatment delivery. Standard IPV treatment does not reflect this variability, and does not provide equal opportunity for recovery to all who are struggling with IPV. If we can determine which subgroups of the population respond similarly to treatment, and which treatments lead to the best outcomes for each subgroup, we will be able to reduce treatment inequalities and improve the quality of life for people suffering from IPV. This study will address this problem in three aims: Aim 1 – We will conduct a systematic review and meta-analysis of existing evidence to characterize treatment outcomes in response to different treatment models. We will examine data from pre-existing research studies to assess levels of violence and relationship satisfaction. This will reveal which treatment is most effective in reducing violence recidivism for each subgroup. Aim 2 – We will use a data-driven approach to systematically investigate patterns of violence to identify subgroups of individuals who respond similarly to treatment. Demographic, socioeconomic, cultural, and age related factors will be considered during subgroup identification. This will involve latent class analysis. Aim 3 – We will develop a decision making tool for clinicians to help them choose between evidence based treatments for each situation. Results from Aims 1 and 2 will be used in the selection of features. This will involve Bayesian and regression networks. We will compare the resulting decision making models to models that are built using traditional features. The outcome of this research will reduce the inequality faced by many individuals who are currently only offered generic treatment for this complex problem, although their circumstances call for tailored solutions.

项目概要 亲密伴侣暴力 (IPV) 被定义为对当前伴侣的任何身体、性或情感虐待。 或前亲密伴侣。大约四分之一的女性会经历某种形式的严重症状 伴侣在其一生中实施暴力，其中许多情况会导致严重伤害或死亡。 尽管男性也可能成为 IPV 的受害者，但大多数案件涉及女性受害。特定性别 团体治疗被广泛认为是 IPV 的标准治疗方法，但一些参与者 这些群体因接受这些治疗而遭受的暴力并未减少。 关于标准治疗有效性的报告以及研究结果表明： 在某些情况下，不同的治疗方法可能更有效地减少暴力累犯。 许多因素影响参与者对治疗的反应。这些因素包括 人口统计、暴力类型和治疗提供。标准 IPV 处理不反映 这种可变性，并没有为所有正在与这种情况作斗争的人提供平等的康复机会 IPV。如果我们能够确定哪些人群对治疗有类似的反应，并且 哪些治疗可为每个亚组带来最佳结果，我们将能够减少治疗 不平等并改善 IPV 患者的生活质量。这项研究将解决 这个问题的三个目标： 目标 1 – 我们将对现有证据进行系统审查和荟萃分析，以 描述针对不同治疗模式的治疗结果。我们将 检查现有研究的数据以评估暴力程度 关系满意度。这将揭示哪种治疗方法最有效地减少 每个亚组的暴力累犯。 目标 2 – 我们将使用数据驱动的方法来系统地研究 暴力，以确定对治疗反应相似的个人亚组。 人口统计、社会经济、文化和年龄相关因素将在 亚组识别。这将涉及潜在类别分析。 目标 3 – 我们将为临床医生开发一个决策工具，帮助他们做出选择 针对每种情况的基于证据的治疗。目标 1 和 2 的结果将用于 特征的选择。这将涉及贝叶斯和回归网络。我们将 将生成的决策模型与使用传统方法构建的模型进行比较 特征。 这项研究的结果将减少许多个人所面临的不平等 目前仅针对这一复杂问题提供通用治疗，尽管他们的情况 呼吁量身定制的解决方案。