Domestic violence among adult male victims in non-intimate relationships: A text mining study using NSW police narratives

Abstract

This article presents a population-level text mining analysis of police-attended domestic violence (DV) event narratives in New South Wales involving adult male victims in non-intimate domestic relationships, such as with family members, carers, or housemates. Analysing 18,611 events from 2005 to 2016, the study identifies the prevalence and patterns of abuse types, threats, injuries, and mental illness mentions in DV cases where men are victims. Results reveal that most perpetrators were male, with over a quarter being second-degree family members. Physical violence, including assault and punching, was the most common form of abuse, and nearly half of the cases recorded physical injuries. Mental illness was mentioned more frequently among perpetrators than victims. The findings highlight significant underreporting, stigma, and gaps in service response for this under-researched group, calling for improved recognition and support pathways for male DV victims in non-intimate contexts.