ArticleHeliyon2023
A systematic review of ethical challenges and opportunities of addressing domestic violence with AI-technologies and online tools.
Article in Heliyon, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 5 papers, 1 of them a synthesis that pooled it.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
5 citing papers in PubMed, 1 synthesis or guideline pooled it, 20 citations in OpenAlex.
- The Role of Artificial Intelligence for Intimate Partner Violence Prevention: A Systematic Review.Journal of clinical nursing · 2026Pooled it
- AI-Enabled First-Response Support After Sexual and Gender-Based Violence: A PRISMA-ScR Scoping Review.Healthcare (Basel, Switzerland) · 2026Review
- From needs assessment to usability testing: evaluating the AinoAid™ chatbot for domestic violence support.BMC women's health · 2025Article
- Violence against women and girls research: Leveraging gains across disciplines.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Sufficiency for PSS tracking gait disorders in multiple sclerosis: A managerial perspective.Heliyon · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors at 1 institution in 3 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Domestic violence remains a pressing complex social problem of people of any gender, age, socio-economic status, and ethno-cultural background, an issue that worsened worldwide during the COVID-19 pandemic. Digital, online, or artificial intelligence-based smart technological services, applications, and tools provide novel approaches in addressing domestic violence, including intimate partner violence. This systematic literature review analyses the ethical challenges and opportunities these (protective) digital and smart technologies provide to the stakeholders involved. Our results highlight that the public health and societal issue are the leading narratives of domestic violence, which is predominantly interpreted as gender-based violence. The review highlights an emerging trend of the role of machine learning- and artificial intelligence-based approaches in identifying and preventing domestic violence. However, we argue that little recommendation is available to professionals about how to use these approaches in a responsible way, and that the smartness of high-tech technologies is often challenged by basic-level technologies from perpetrators, creating an imbalance that also limits an impactful development of a comprehensive socio-technical regime that serves the safety and resilience of families in their communal setting.
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.