Domestic Violence in Residential Care Facilities in New South Wales, Australia: A Text Mining Study

Withall, Adrienne; Karystianis, George; Duncan, D.; Hwang, Ye In; Hagos, Amanuel Kidane; Butler, Tony

doi:10.1093/geront/gnab068

Cited by 8 publications

(6 citation statements)

References 29 publications

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“…Improved training and awareness from attending police officers can assist in the recording of key details of those involved in a domestic violence event beyond routine demographic and spatio-temporal characteristics and potentially capture information for at-risk sub-populations. Examples of this include reports of mental illness in perpetrators and victims, observed injuries not requiring hospitalization, threats, trends in specific abuse types such as non-fatal strangulation and frequency of abuse within a particular setting such as nursing homes (16)(17)(18)(19)(20)(21).…”

Section: Discussionmentioning

confidence: 99%

“…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 ). We also demonstrated that the extracted information can be used to provide insights into domestic violence and mental illness ( 18 ) and in the context specific diagnoses (i.e., autism) ( 19 ), the setting (i.e., nursing homes) ( 20 ), and abuse type (i.e., non-fatal strangulation) ( 21 ).…”

Section: Introductionmentioning

confidence: 99%

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Surveillance of Domestic Violence Using Text Mining Outputs From Australian Police Records

et al. 2022

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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.

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Section: Discussionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Surveillance of Domestic Violence Using Text Mining Outputs From Australian Police Records

et al. 2022

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“…Finally, a number of papers (n = 16) were found to report on the same two broad studies, using similar datasets and models. These were the Karystianis et al papers on the New South Wales Police Force data using a rule-based approach, n = 6 (Adily et al, 2021;Hwang et al, 2020;Karystianis et al, 2019Wilson et al, 2021;Withall et al, 2022), and the Poelmans et al papers on the Amsterdam-Amstelland Police Force Data using an FCA and ESOM based approach, n = 10 (Elzinga, Poelmans, Viaene, & Dedene, 2009;J. Poelmans, Elzinga, & Dedene, 2013;J.…”

Section: Included Studiesmentioning

confidence: 99%

A Systematic Literature Review of the Use of Computational Text Analysis Methods in Intimate Partner Violence Research

et al. 2023

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Purpose Computational text mining methods are proposed as a useful methodological innovation in Intimate Partner Violence (IPV) research. Text mining can offer researchers access to existing or new datasets, sourced from social media or from IPV-related organisations, that would be too large to analyse manually. This article aims to give an overview of current work applying text mining methodologies in the study of IPV, as a starting point for researchers wanting to use such methods in their own work. Methods This article reports the results of a systematic review of academic research using computational text mining to research IPV. A review protocol was developed according to PRISMA guidelines, and a literature search of 8 databases was conducted, identifying 22 unique studies that were included in the review. Results The included studies cover a wide range of methodologies and outcomes. Supervised and unsupervised approaches are represented, including rule-based classification (n = 3), traditional Machine Learning (n = 8), Deep Learning (n = 6) and topic modelling (n = 4) methods. Datasets are mostly sourced from social media (n = 15), with other data being sourced from police forces (n = 3), health or social care providers (n = 3), or litigation texts (n = 1). Evaluation methods mostly used a held-out, labelled test set, or k-fold Cross Validation, with Accuracy and F1 metrics reported. Only a few studies commented on the ethics of computational IPV research. Conclusions Text mining methodologies offer promising data collection and analysis techniques for IPV research. Future work in this space must consider ethical implications of computational approaches.

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“…These text records enable identification of the characteristics of domestic violence perpetrators (hereafter referred to as Persons of Interest (POIs) i.e., individuals involved in an event that have been accused or charged for perpetrating DV related crimes) that can inform further research, clinical screening, and interventions. Police records enable characteristics of DV events to be described ( 19 ) based on the setting (e.g., nursing homes) ( 21 ), specific mental health conditions (e.g., autism) ( 22 ) and abuse types (e.g., non-fatal strangulation, coercive control) ( 23 , 24 ), and population sub-groups ( 25 ).…”

Section: Introductionmentioning

confidence: 99%

Characteristics of domestic violence perpetrators with dementia from police records using text mining

Reutens,

Karystianis,

Withall

et al. 2024

Front. Psychiatry

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AimFew studies have examined the characteristics of domestic violence (DV) committed by people with dementia. We provide an overview of DV perpetrated by people with dementia in the community based on police reports of attendances at DV events.MethodA text mining method was used on 416,441 New South Wales (NSW) police narratives of DV events from January 2005 to December 2016 to extract information for Persons of Interest (POIs) with mentions of dementia.ResultsEvents involving those with dementia accounted for a relatively low proportion of total DV events (<1%). Of the 260 DV events with a dementia mention for the POI, the most common abuse types were assault (49.7%) and verbal abuse (31.6%). Spouses were the largest group of victims (50.8%) followed by children (8.8%). Physical abuse was common, occurring in 82.4% of events, but injuries were relatively mild. Although weapons were infrequently used, they were involved in 5% of events, mostly by POIs aged 75 years and older. Similarly, the POIs were mainly aged 75+ years (60%), however the proportion of those aged <65 was relatively high (20.8%) compared to the reported prevalence of dementia in that age group.ConclusionsThis study demonstrates that some cases of DV perpetrated by people with reported dementia are significant enough to warrant police involvement. This highlights the need to proactively discuss the potential for violence as part of the holistic management and support family members, particularly those caring for people with young-onset dementias.

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Domestic Violence in Residential Care Facilities in New South Wales, Australia: A Text Mining Study

Cited by 8 publications

References 29 publications

Surveillance of Domestic Violence Using Text Mining Outputs From Australian Police Records

Surveillance of Domestic Violence Using Text Mining Outputs From Australian Police Records

A Systematic Literature Review of the Use of Computational Text Analysis Methods in Intimate Partner Violence Research

Characteristics of domestic violence perpetrators with dementia from police records using text mining

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