Citation

Babcock JC, Cooper J. Safety (Basel) 2019; 5(1): e2.

Copyright

(Copyright © 2019, MDPI: Multidisciplinary Digital Publishing Institute)

DOI

10.3390/safety5010002

PMID

unavailable

Abstract

Risk assessments are typically based on retrospective reports of factors known to be correlated with violence recidivism in simple linear models. Generally, these linear models use only the perpetrators’ reports. Using a community sample of couples recruited for recent male-to-female intimate partner violence (IPV; N = 97 couples), the current study compared non-linear neural network models to traditional linear models in predicting a history of arrest in men who perpetrate IPV. The neural network models were found to be superior to the linear models in their predictive power. Models were slightly improved by adding victims’ report. These findings suggest that the prediction of violence arrest be enhanced through the use of neural network models and by including collateral reports.

Language: en

Keywords

intimate partner violence; neural network; violence risk assessment