ArticleJournal of medical Internet research2020
Prevalence of Mental Illnesses in Domestic Violence Police Records: Text Mining Study.
Article in Journal of medical Internet research, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers, 1 of them a synthesis that pooled it.
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Who cites it
6 citing papers in PubMed, 1 synthesis or guideline pooled it, 22 citations in OpenAlex.
- Artificial intelligence in intimate partner violence risk pathways: a PRISMA-ScR review of femicide prevention and medico-legal accountability.Frontiers in digital health · 2026Pooled it
- Characteristics of domestic violence perpetrators with dementia from police records using text mining.Frontiers in psychiatry · 2024Article
- Harnessing Machine Learning in Tackling Domestic Violence-An Integrative Review.International journal of environmental research and public health · 2023Review
- Mental Illness Concordance Between Hospital Clinical Records and Mentions in Domestic Violence Police Narratives: Data Linkage Study.JMIR formative research · 2022Article
- Surveillance of Domestic Violence Using Text Mining Outputs From Australian Police Records.Frontiers in psychiatry · 2021Article
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Corrections and comments
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Authors and funding
8 authors at 3 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundThe New South Wales Police Force (NSWPF) records details of significant numbers of domestic violence (DV) events they attend each year as both structured quantitative data and unstructured free text. Accessing information contained in the free text such as the victim's and persons of interest (POI's) mental health status could be useful in the better management of DV events attended by the police and thus improve health, justice, and social outcomes.
objectiveThe aim of this study is to present the prevalence of extracted mental illness mentions for POIs and victims in police-recorded DV events.
methodsWe applied a knowledge-driven text mining method to recognize mental illness mentions for victims and POIs from police-recorded DV events.
resultsIn 416,441 police-recorded DV events with single POIs and single victims, we identified 64,587 events (15.51%) with at least one mental illness mention versus 4295 (1.03%) recorded in the structured fixed fields. Two-thirds (67,582/85,880, 78.69%) of mental illnesses were associated with POIs versus 21.30% (18,298/85,880) with victims; depression was the most common condition in both victims (2822/12,589, 22.42%) and POIs (7496/39,269, 19.01%). Mental illnesses were most common among POIs aged 0-14 years (623/1612, 38.65%) and in victims aged over 65 years (1227/22,873, 5.36%).
conclusionsA wealth of mental illness information exists within police-recorded DV events that can be extracted using text mining. The results showed mood-related illnesses were the most common in both victims and POIs. Further investigation is required to determine the reliability of the mental illness mentions against sources of diagnostic information.
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