Affiliation:
1. School of Population Health, Faculty of Medicine, University of New South Wales, Kensington, Sydney, Australia
Abstract
Abstract
Background and Objectives
The police are often the first to attend domestic violence events in New South Wales (NSW), Australia, recording related details as structured information (e.g., date of the event, type of incident, premises type) and text narratives which contain important information (e.g., mental health status, abuse types) for victims and perpetrators. This study examined the characteristics of victims and persons of interest (POIs) suspected and/or charged with perpetrating a domestic violence-related crime in residential care facilities.
Research Design and Methods
The study employed a text mining method that extracted key information from 700 police-recorded domestic violence events in NSW residential care facilities.
Results
Victims were mostly female (65.4%) and older adults (median age 80.3). POIs were predominantly male (67.0%) and were younger than the victims (median age 57.0). While low rates of mental illnesses were recorded (29.1% in victims; 17.4% in POIs), “dementia” was the most common condition among POIs (55.7%) and victims (73.0%). “Physical abuse” was the most common abuse type (80.2%) with “bruising” the most common injury (36.8%). The most common relationship between perpetrator and victim was “carer” (76.6%).
Discussion and Implications
These findings highlight the opportunity provided by police text-based data to offer insights into elder abuse within residential care facilities.
Funder
Australian Institute of Criminology
Publisher
Oxford University Press (OUP)
Subject
Geriatrics and Gerontology,Gerontology,General Medicine
Reference40 articles.
1. Text mining applications in psychiatry: A systematic literature review;Abbe;International Journal of Methods in Psychiatric Research,2016
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