Predicting self-harm in survivors and perpetrators of domestic abuse

Abstract

Objective: Despite legislative developments within the UK seeking to reduce domestic abuse, not only are reports of domestic abuse increasing, but both survivors and perpetrators of domestic abuse engage in self-harming behavior and suicide attempts. Some of whom ultimately die by suicide. As such, identifying those at risk of self-harm within this population is paramount. Method: This study presents an analysis of a secondary dataset of 836 adults who presented at a UK-based domestic abuse charity between 2017 and 2022. The dataset was derived through a knowledge exchange partnership and featured both survivors and perpetrators of domestic abuse. Results: Though the logistic regression model was more proficient at predicting those more likely to not engage in self-harm, than those more likely to engage in self-harm, self-harm was predicted by witnessing domestic abuse as a child, reporting aggressive behavior, and previously or currently abusing alcohol, with the presence of aggressive behavior being the strongest predictor. Opposing existing literature, neither abusing drugs nor (not) having children contributed significantly to this model. Conclusions: Though results of this study require replication and extension, they indicate a series of variables which might serve as internationally relevant key indicators of risk for self-harm in survivors and perpetrators of domestic abuse. Charities which serve this population might seek to develop further educational material and interventions to rapidly deliver to service users who indicate risk during initial and subsequent consultations.