Related Experiment Video
Updated: Jun 19, 2025

07:31
Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
7.1K
Predicting Intimate Partner Violence Perpetration Among Young Adults Experiencing Homelessness in Seven U.S. Cities
Mee Young Um1, Lydia Manikonda2, Doncy J Eapen3
1Arizona State University, Phoenix, AZ, USA.
Journal of Interpersonal Violence
|July 24, 2024
Summary
Intimate partner violence (IPV) victimization while homeless is a key predictor of IPV perpetration among young adults experiencing homelessness. Interventions should address this cycle of violence and related factors like discrimination.
Area of Science:
- Social Sciences
- Public Health
- Psychology
Background:
- Young adults experiencing homelessness (YAEH) face elevated risks of intimate partner violence (IPV) victimization and perpetration.
- A cycle of violence can emerge due to pre-existing vulnerabilities and experiences during homelessness.
- Limited research exists on factors influencing IPV perpetration among YAEH, with conventional statistical methods showing limitations.
Purpose of the Study:
- To identify salient predictors of IPV perpetration in a large sample of YAEH.
- To address gaps in understanding the complex dynamics of IPV perpetration within this population.
- To utilize an interpretable machine learning approach for novel insights.
Main Methods:
- Employed an interpretable machine learning approach.
- Analyzed data from 1,426 YAEH across seven U.S. cities.
- Examined predictors associated with IPV perpetration, including victimization, discrimination, and mindfulness.
Main Results:
- IPV victimization experienced while homeless was the most significant predictor of IPV perpetration.
- Eleven additional factors, such as frequent discrimination, were positively associated with IPV perpetration.
- Eight factors, including higher mindfulness scores, were negatively associated with IPV perpetration.
Conclusions:
- Findings highlight the critical link between IPV victimization and perpetration among YAEH.
- Interventions must address the cycle of violence and associated risk factors.
- Developing targeted prevention strategies for YAEH is crucial to reduce IPV.
Related Concept Videos
Steps in Outbreak Investigation
119
In the ever-evolving field of public health, statistical analysis serves as a cornerstone for understanding and managing disease outbreaks. By leveraging various statistical tools, health professionals can predict potential outbreaks, analyze ongoing situations, and devise effective responses to mitigate impact. For that to happen, there are a few possible stages of the analysis:
119
Prediction Intervals
2.2K
The interval estimate of any variable is known as the prediction interval. It helps decide if a point estimate is dependable.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
However, the point estimate is most likely not the exact value of the population parameter, but close to it. After calculating point estimates, we construct interval estimates, called confidence intervals or prediction intervals. This prediction interval comprises a range of values unlike the point estimate and is a better predictor of the observed sample value, y.
2.2K
Stereotype Content Model
14.7K
The Stereotype Content Model (SCM) was first proposed by Susan Fiske and her colleagues (Fiske, Cuddy, Glick & Xu, 2002; see also Fiske, 2012 and Fiske, 2017). The SCM specifies that when someone encounters a new group, they will stereotype them based on two metrics: warmth—or that group’s perceived intent, and how likely they are to provide help or inflict harm—and competence—or their ability to carry out that objective. Depending on the warmth-competence...
14.7K
Fundamental Attribution Error
12.8K
According to some social psychologists, people tend to overemphasize internal factors as explanations—or attributions—for the behavior of other people. They tend to assume that the behavior of another person is a trait of that person, and to underestimate the power of the situation on the behavior of others. They tend to fail to recognize when the behavior of another is due to situational variables, and thus to the person’s state. This erroneous assumption is...
12.8K
Statistical Methods for Analyzing Epidemiological Data
344
Epidemiological data primarily involves information on specific populations' occurrence, distribution, and determinants of health and diseases. This data is crucial for understanding disease patterns and impacts, aiding public health decision-making and disease prevention strategies. The analysis of epidemiological data employs various statistical methods to interpret health-related data effectively. Here are some commonly used methods:
344

