Harnessing Machine Learning in Tackling Domestic Violence—An Integrative Review

Abstract

Domestic violence (DV) is a public health crisis that threatens both the mental and physical health of people. With the unprecedented surge in data available on the internet and electronic health record systems, leveraging machine learning (ML) to detect obscure changes and predict the likelihood of DV from digital text data is a promising area health science research. However, there is a paucity of research discussing and reviewing ML applications in DV research. Methods: We extracted 3588 articles from four databases. Twenty-two articles met the inclusion criteria. Results: Twelve articles used the supervised ML method, seven articles used the unsupervised ML method, and three articles applied both. Most studies were published in Australia (n = 6) and the United States (n = 4). Data sources included social media, professional notes, national databases, surveys, and newspapers. Random forest (n = 9), support vector machine (n = 8), and naïve Bayes (n = 7) were the top three algorithms, while the most used automatic algorithm for unsupervised ML in DV research was latent Dirichlet allocation (LDA) for topic modeling (n = 2). Eight types of outcomes were identified, while three purposes of ML and challenges were delineated and are discussed. Conclusions: Leveraging the ML method to tackle DV holds unprecedented potential, especially in classification, prediction, and exploration tasks, and particularly when using social media data. However, adoption challenges, data source issues, and lengthy data preparation times are the main bottlenecks in this context. To overcome those challenges, early ML algorithms have been developed and evaluated on DV clinical data.

Examining the Supports and Advice That Women With Intimate Partner Violence Experience Received in Online Health Communities: Text Mining Approach

“…Moreover, women should be advised about how to seek help in OHCs effectively by emphasizing the value of choosing a post title with negative connotations and seeking help politely in the initial postings. Furthermore, a recent review discussed how an automated system can assist IPV detection [ 39 ]. Our study is a starting point for developing future IPV automatic system interventions that allow users to search for comparable experiences effectively.…”

Effective Professional Interventions for Protecting Children and Families from Violence in Buraydah, Al Qassim

“…One novel concept is to employ technology to improve intervention and support services. Individuals and families victimized by violence can benefit from mobile applications and online platforms that provide accessible resources, counselling services, and reporting procedures (Hui et al, 2023;Batada & Leon, 2019). A mobile application established in a neighbouring Saudi city, for example, allows users to access information about healthy relationships, parenting ideas, and emergency contacts for instant aid.…”

Harnessing Health Information Technology in Domestic Violence in the United States: A Scoping Review

“…Women could experience emotional breakdown easier or the need to express themselves after traumatic experiences like DV. The anonymity and instant communication facilitated by mobile devices and the Internet, have provided opportunities for women to seek emotional support through texting through online platforms [60,61]. This avenue enables better adaptations and enhances the quality of life following traumatic experiences caused by abusive relationships.…”