Decision-Making Modeling for Treating Intimate Partner Violence

治疗亲密伴侣暴力的决策模型

• 批准号: 10465052
• 负责人: Gunnur Karakurt Koyuturk
• 金额: $ 30.52万
• 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 2024-07-31
• 项目状态: 已结题
• 来源: https://reporter.nih.gov/project-details/10465052
• 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; Persons; 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.

项目总结

项目成果

Brain Injury and Mental Health Among the Victims of Intimate Partner Violence: A Case-Series Exploratory Study.

• DOI: 10.3389/fpsyg.2021.710602
• 发表时间: 2021
• 期刊: Frontiers in psychology
• 影响因子: 3.8
• 作者: Karakurt G;Whiting K;Jones SE;Lowe MJ;Rao SM
• 通讯作者: Rao SM

Systematic Investigation of Meta-Analysis Data on Treatment Effectiveness for Physical, Psychological, and Sexual Intimate Partner Violence Perpetration.

• DOI: 10.5093/pi2023a6
• 发表时间: 2023-05
• 期刊: Psychosocial intervention
• 影响因子: 4.8
• 作者: Oğuztüzün Ç;Koyutürk M;Karakurt G
• 通讯作者: Karakurt G

Treatments for Female Victims of Intimate Partner Violence: Systematic Review and Meta-Analysis.

• DOI: 10.3389/fpsyg.2022.793021
• 发表时间: 2022
• 期刊: Frontiers in psychology
• 影响因子: 3.8
• 作者: Karakurt G;Koç E;Katta P;Jones N;Bolen SD
• 通讯作者: Bolen SD

Identifying health correlates of intimate partner violence against pregnant women.

确定亲密伴侣暴力侵害孕妇的健康相关性。

• DOI: 10.1007/s13755-020-00124-6
• 发表时间: 2020
• 期刊: Health information science and systems
• 影响因子: 6
• 作者: Yılmaz,Serhan;Alghamdi,Bushra;Singuri,Srinidhi;Hacialiefendioglu,AhmetMert;Özcan,Tülin;Koyutürk,Mehmet;Karakurt,Günnur
• 通讯作者: Karakurt,Günnur

Adverse health correlates of intimate partner violence against older women: Mining electronic health records.

对老年妇女的亲密伴侣暴力行为的不利健康相关：采矿电子健康记录。

• DOI: 10.1371/journal.pone.0281863
• 发表时间: 2023
• 期刊: PloS one
• 影响因子: 3.7
• 作者: Yılmaz S;Gunay E;Lee DH;Whiting K;Silver K;Koyuturk M;Karakurt G
• 通讯作者: Karakurt G