Domestic violence (DV) is one of the most important public health problems with economic and heath burdens on community populations. In Australia, the annual burden against women (and their children) is estimated to be $AUD22.2 billion. In 2016 the NSWPF worked in collaboration with the Kirby Institute of the University of NSW (Kirby) under ethics approval from the University of New South Wales Human Research Ethics Committee (reference: HC16558). Kirby was provided with 492,393 Domestic Violence events from the Computerised Operational Policing System between 2005 to 2016 to explore whether text mining can automatically identify mental health disorders from unstructured text in COPS event narratives to support further public health research into the nexus between mental health disorders and DV.
The extracted mentions of mental health conditions were mapped to the International Classification of Diseases, Tenth Revision (ICD-10) and in their paper published in the Journal of medical internet research in 2018 they identified 77,995 events (15.83%) that mentioned mental health disorders, with 76.96% (60,032/77,995) of those linked to offenders versus 16.47% (12,852/77,995) for the victims and 6.55% (5111/77,995) for both. Depression was the most common mental health disorder mentioned in both victims (22.25%, 3269) and offenders (18.70%, 8944), followed by alcohol abuse for persons of interest (12.19%, 5829) and various anxiety disorders (e.g., panic disorder, generalized anxiety disorder) for victims (11.66%, 1714).
In 2019 the NSWPF worked with Kirby and IBM to develop the research and findings into a mobile application for front line police to assist them in identified persons at risk in domestic violence situations, how to better communicate with those suffering from certain mental illnesses such as schizophrenia, bipolar and depression to de-escalate potential violent behaviour for better community outcomes. This application is due for use by front line police in 2021.
Source: Karystianis G, Adily A, Schofield P, Knight L, Galdon C, Greenberg D, Jorm L, Nenadic G, Butler T. Automatic extraction of mental health disorders from domestic violence police narratives: text mining study. Journal of medical internet research. 2018 Sep;20(9).
Last updated 07 Jun 2021