# Decision-Making Modeling for Treating Intimate Partner Violence

> **NIH NIH R01** · CASE WESTERN RESERVE UNIVERSITY · 2021 · $45,016

## Abstract

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.

## Key facts

- **NIH application ID:** 10215622
- **Project number:** 5R01LM012518-04
- **Recipient organization:** CASE WESTERN RESERVE UNIVERSITY
- **Principal Investigator:** Gunnur Karakurt Koyuturk
- **Activity code:** R01 (R01, R21, SBIR, etc.)
- **Funding institute:** NIH
- **Fiscal year:** 2021
- **Award amount:** $45,016
- **Award type:** 5
- **Project period:** 2018-08-06 → 2023-07-31

## Primary source

NIH RePORTER: https://reporter.nih.gov/project-details/10215622

## Citation

> US National Institutes of Health, RePORTER application 10215622, Decision-Making Modeling for Treating Intimate Partner Violence (5R01LM012518-04). Retrieved via AI Analytics 2026-05-23 from https://api.ai-analytics.org/grant/nih/10215622. Licensed CC0.

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