Smartphone Apps for Domestic Violence Prevention: A Systematic Review
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Sumra, Mehreen; Asghar, Sohail; Saeed Khan, Khalid; Fernández Luna, Juan Manuel; Huete Guadix, Juan Francisco; Bueno Cavanillas, AuroraEditorial
MDPI
Materia
Domestic violence Violence prevention Smartphone apps
Date
2023-03-03Referencia bibliográfica
Sumra, M.; Asghar, S.; Khan, K.S.; Fernández-Luna, J.M.; Huete, J.F.; Bueno-Cavanillas, A. Smartphone Apps for Domestic Violence Prevention: A Systematic Review. Int. J. Environ. Res. Public Health 2023, 20, 5246. https://doi.org/10.3390/ijerph20075246
Abstract
Smartphone applications or apps are increasingly being produced to help with protection
against the risk of domestic violence. There is a need to formally evaluate their features. Objective:
This study systematically reviewed app-based interventions for domestic violence prevention, which
will be helpful for app developers. Methods: We overviewed all apps concerning domestic violence
awareness and prevention without language restrictions, collating information about features and
limitations. We conducted searches in Google, the Google Play Store, and the App Store (iOS)
covering a 10-year time period (2012–2022). We collected data related to the apps from the developers’
descriptions, peer reviewed research articles, critical reviews in blogs, news articles, and other
online sources. Results: The search identified 621 potentially relevant apps of which 136 were
selected for review. There were five app categories: emergency assistance (n = 61, 44.9%), avoidance
(n = 29, 21.3%), informative (n = 29, 21.3%), legal information (n = 10, 7.4%), and self-assessment
(n = 7, 5.1%). Over half the apps (n = 97, 71%) were released in 2020–22. Around a half were from
north-east America (n = 63, 46.3%). Where emergency alerts existed, they required triggering by
the potential victim. There was no automation. Content analysis showed 20 apps with unique
features, including geo-fences, accelerometer-based alert, shake-based alert, functionality under low
resources, alert auto-cancellation, anonymous communication, and data encryption. None of the
apps deployed artificial intelligence to assist the potential victims. Conclusions: Apps currently
have many limitations. Future apps should focus on automation, making better use of artificial
intelligence deploying multimedia (voice, video, image capture, text and sentiment analysis), speech
recognition, and pitch detection to aid in live analysis of the situation and for accurately generating
emergency alerts.