Predicting Intimate Partner Violence Perpetration Among Young Adults Experiencing Homelessness in Seven U.S. Cities Using Interpretable Machine Learning.

Young adults experiencing homelessness (YAEH) are at higher risk for intimate partner violence (IPV) victimization than their housed peers. This is often due to their increased vulnerability to abuse and victimization before and during homelessness, which can result in a cycle of violence in which YAEH also perpetrates IPV. Identifying and addressing factors contributing to IPV perpetration at an early stage can reduce the risk of IPV. Yet to date, research examining YAEH's IPV perpetration is scarce and has largely employed conventional statistical approaches that are limited in modeling this complex phenomenon. To address these gaps, this study used an interpretable machine learning approach to answer the research question: <i>What are the most salient predictors of IPV perpetration among a large sample of YAEH in seven U.S. cities?</i> Participants (<i>N</i> = 1,426) on average were 21 years old (<i>SD</i> = 2.09) and were largely cisgender males (59%) and racially/ethnically diverse (81% were from historically excluded racial/ethnic groups; i.e., African American, Latino/a, American Indian, Asian or Pacific Islander, and mixed race/ethnicity). Over one-quarter (26%) reported IPV victimization, and 20% reported IPV perpetration while homeless. Experiencing IPV victimization while homeless was the most important factor in predicting IPV perpetration. An additional 11 predictors (e.g., faced frequent discrimination) were positively associated with IPV perpetration, whereas 8 predictors (e.g., reported higher scores of mindfulness) were negatively associated. These findings underscore the importance of developing and implementing effective interventions with YAEH that can prevent IPV, particularly those that recognize the positive association between victimization and perpetration experiences.

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Publication Details

Journal
Carolina Digital Repository (University of North Carolina at Chapel Hill)
Published
2024-10-05
DOI
https://doi.org/10.17615/fday-b883
Primary Topic
Homelessness and Social Issues
Type
article
Field-Weighted Citation Impact
0.00

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article

Predicting Intimate Partner Violence Perpetration Among Young Adults Experiencing Homelessness in Seven U.S. Cities Using Interpretable Machine Learning.

Anamika Barman‐Adhikari, Lydia Manikonda, Mee Young Um, Robin Petering et al.
Carolina Digital Repository (University of North Carolina at Chapel Hill)
Homelessness and Social Issues
article

Predicting Intimate Partner Violence Perpetration Among Young Adults Experiencing Homelessness in Seven U.S. Cities Using Interpretable Machine Learning.

Anamika Barman‐Adhikari, Lydia Manikonda, Mee Young Um, Robin Petering, Kristin M. Ferguson, Sarah C. Narendorf, Diane Santa Maria, Doncy Joji Eapen, Hsun-Ta Hsu
article en

Abstract

Young adults experiencing homelessness (YAEH) are at higher risk for intimate partner violence (IPV) victimization than their housed peers. This is often due to their increased vulnerability to abuse and victimization before and during homelessness, which can result in a cycle of violence in which YAEH also perpetrates IPV. Identifying and addressing factors contributing to IPV perpetration at an early stage can reduce the risk of IPV. Yet to date, research examining YAEH's IPV perpetration is scarce and has largely employed conventional statistical approaches that are limited in modeling this complex phenomenon. To address these gaps, this study used an interpretable machine learning approach to answer the research question: <i>What are the most salient predictors of IPV perpetration among a large sample of YAEH in seven U.S. cities?</i> Participants (<i>N</i> = 1,426) on average were 21 years old (<i>SD</i> = 2.09) and were largely cisgender males (59%) and racially/ethnically diverse (81% were from historically excluded racial/ethnic groups; i.e., African American, Latino/a, American Indian, Asian or Pacific Islander, and mixed race/ethnicity). Over one-quarter (26%) reported IPV victimization, and 20% reported IPV perpetration while homeless. Experiencing IPV victimization while homeless was the most important factor in predicting IPV perpetration. An additional 11 predictors (e.g., faced frequent discrimination) were positively associated with IPV perpetration, whereas 8 predictors (e.g., reported higher scores of mindfulness) were negatively associated. These findings underscore the importance of developing and implementing effective interventions with YAEH that can prevent IPV, particularly those that recognize the positive association between victimization and perpetration experiences.

Carolina Digital Repository (University of North Carolina at Chapel Hill)
University of North Carolina at Chapel Hill (US)
Greater Houston Community Foundation, Arizona State University, Simon Fraser University, Centers for Disease Control and Prevention, University of Illinois at Urbana-Champaign, National Institute of Mental Health, National Center for Injury Prevention and Control
Gender equality
Openalex Percentile: Top 70%
Homelessness and Social Issues
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