Abstract
In Australia, domestic violence reports are mostly based on data from the police, courts, hospitals, and ad hoc surveys. However, gaps exist in reporting information such as victim injuries, mental health status and abuse types. The police record details of domestic violence events as structured information (e.g., gender, postcode, ethnicity), but also in text narratives describing other details such as injuries, substance use, and mental health status. However, the voluminous nature of the narratives has prevented their use for surveillance purposes. We used a validated text mining methodology on 492,393 police-attended domestic violence event narratives from 2005 to 2016 to extract mental health mentions on persons of interest (POIs) (individuals suspected/charged with a domestic violence offense) and victims, abuse types, and victim injuries. A significant increase was observed in events that recorded an injury type (28.3% in 2005 to 35.6% in 2016). The pattern of injury and abuse types differed between male and female victims with male victims more likely to be punched and to experience cuts and bleeding and female victims more likely to be grabbed and pushed and have bruises. The four most common mental illnesses (alcohol abuse, bipolar disorder, depression schizophrenia) were the same in male and female POIs. An increase from 5.0% in 2005 to 24.3% in 2016 was observed in the proportion of events with a reported mental illness with an increase between 2005 and 2016 in depression among female victims. These findings demonstrate that extracting information from police narratives can provide novel insights into domestic violence patterns including confounding factors (e.g., mental illness) and thus enable policy responses to address this significant public health problem.
Highlights
The World Health Organization (WHO) defines public health surveillance as “an ongoing, systematic collection, analysis and interpretation of health-related data” that is essential to the planning, implementation, and evaluation of public health practice [1]
We recently demonstrated the successful application of text mining to a large corpus of police domestic violence event narratives to identify mentions of mental illness, abuse type(s), and victim injuries [16, 17]
The New South Wales Police Force (NSWPF) made available 492,393 police recorded domestic violence event narratives from January 2005 to December 2016 that were flagged in the fixed fields with one of the following tags: “domestic” as the type of offense, “domestic violence related” as the associated factor of the police event; or the relationship status between the victim and the person of interest (POI—an individual suspected/charged with a domestic violence offense) being described as “spouse/partner,” “boy/girlfriend,” “parent/guardian,” “child,” “sibling,” “other member of family,” or “carer.” The dataset contained cases where no crime was committed but the police did attend the event
Summary
The World Health Organization (WHO) defines public health surveillance as “an ongoing, systematic collection, analysis and interpretation of health-related data” that is essential to the planning, implementation, and evaluation of public health practice [1]. Surveillance is undertaken to inform prevention and control measures and can serve as an early warning system, identify public health emergencies, document the impact of an intervention or progress toward the Improving Domestic Violence Surveillance identification of public health targets and goals and contribute to a better understanding of the problem. Domestic violence is recognized as a significant public health problem that mostly affects women. In Australia, the Personal Safety Survey reports that 39% of the population aged more than 15 years have experience physical or sexual violence perpetrated by a current or a former partner [2]. On average one woman per week is murdered by a current or former intimate partner, and 1 in 6 women and 1 in 16 men have been subjected to physical and/or sexual violence by a current or former partner [3]. Reporting on domestic violence in Australia is based mostly on data from hospital presentations, court outcomes (e.g., domestic violence convictions), periodic surveys such as Australian Bureau of Statistics’ Personal Safety Survey, and police records [3]
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