Domestic violence among adult male victims in non-intimate relationships: a text mining study using NSW police narratives
Year: 2025
Type: article
Abstract: Domestic violence (DV) is a major public health problem and a violation of human rights. To date, research on DV has predominantly focused on women as victims and men as perpetrators. Male DV victims particularly in non-intimate relationships have received little attention in the literature. This study represents the first attempt to report on DV among male victims in non-intimate relationships using population-level data. This is a population-level retrospective observational study using data extracted from a large sample of police-attended narratives in New South Wales (NSW) from 2005 to 2016 using rule-based text mining. From 18,611 DV events involving non-intimate relationships, most of the Persons of Interest (POIs)—individuals suspected or charged with a DV offence—were male (78%) and members of the victims’ family (26.8%, cousins, uncles and aunts). A total of 42 different types of abuse were identified in 74.3% (n = 13,832) events, the most prevalent being physical abuse with assault (unspecified) accounting for half of the cases (53.9%, n = 7462) and punching for more than one third of cases (35.4%). Almost half of DV events (46.3%, n = 8616) recorded injury type to the victim, the most common being cut(s) (43.6%, n = 3754), followed by swelling (19.9%, n = 1716), and bruising (19.5%, n = 1679). A total of 2,903 (15.6%) events had a mental illness mentions for the POIs and 857 (4.6%) for the victims, with 23 different mental illnesses recorded. Schizophrenia and dementia were the most common mental illnesses among POIs (13.6%) and victims (13.0%), respectively. This study provides new insights and empirical evidence on abuse types, perpetrator-victim relationships, victim injuries and mental illness on DV events involving adult male victims in non-intimate relationships. The findings form an important evidence base to trigger further research in the future.
Source: Crime Science
Language: English
Subfield: Health
Field: Social Sciences
Domain: Social Sciences
Open Access status: gold
Estimated APC paid: $1,890
OpenAlex ID: W4409528892