A Decision-Making Framework for Selecting Intimate Partner Violence Measures in Health Research

Measuring intimate partner violence (IPV) remains a challenge in health research due to the wide range of available measures, with each designed for different purposes, populations, and types of violence. Selecting the most appropriate IPV measure requires careful alignment with a study's overall goals while balancing conceptual, ethical, and pragmatic considerations.

To introduce a decision-making framework to guide researchers in selecting IPV measures for use in health-focused research.

A targeted review was completed to identify all published systematic reviews focused on IPV measures. Using a consensus-driven approach, systematic reviews were appraised to determine the criteria and characteristics most commonly used to categorize and evaluate measures. A set of commonly recurring measurement characteristics was identified across reviews, including shared challenges in IPV measurement.

We identified six domains characterizing variation across IPV measures, including: purpose, populations, types of violence, time frame, context, and data collection methods. Some reviews considered additional characteristics including psychometric evidence and cultural relevance. Others discussed practical considerations, such as language availability and respondent burden. Based on these findings, we developed a decision-making framework and accompanying checklist designed to support researchers in evaluating the fit and appropriateness between available IPV measures and the specific aims, populations, and contextual considerations of their studies.

Structured guidance that draws on the broader IPV field can support intentional and transparent decision-making, improving the quality and fit of IPV measurement.

The proposed framework, along with the IPV measure checklist, supports both researchers and clinicians in selecting the strongest IPV measure for their study. By offering structured guidance on navigating the wide variety of available IPV measures, this framework supports more consistent, interpretable, and methodologically rigorous IPV measurement.