Evidence map›Paper›PMID 42659509›Full record

ArticleRevista brasileira de enfermagem2026

Artificial Intelligence in Addressing Interpersonal Violence Against Vulnerable Populations: A Scoping Review.

Hallessa de Fátima da Silva Pimentel, Julia Sunmy Aguni Chunga, Ana Maria José Garcia João Pascoal, Dulce Aparecida Barbosa, Claudia Galindo Novoa, Hugo Fernandes

Abstract readScoping Review
In one paragraph

Article in Revista brasileira de enfermagem, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from 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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Hallessa de Fátima da Silva PimentelUniversidade Federal de São Paulo. São Paulo, São Paulo, Brazil.ORCID http://orcid.org/0000-0002-0910-4717
Julia Sunmy Aguni ChungaUniversidade Federal de São Paulo. São Paulo, São Paulo, Brazil.ORCID http://orcid.org/0009-0004-5286-5345
Ana Maria José Garcia João PascoalUniversidade Agostinho Neto. Talatona, Angola.ORCID http://orcid.org/0009-0007-1258-2967
Dulce Aparecida BarbosaUniversidade Federal de São Paulo. São Paulo, São Paulo, Brazil.ORCID http://orcid.org/0000-0002-9912-4446
Claudia Galindo NovoaUniversidade Federal de São Paulo. São Paulo, São Paulo, Brazil.ORCID http://orcid.org/0000-0002-7861-3216
Hugo FernandesUniversidade Federal de São Paulo. São Paulo, São Paulo, Brazil.ORCID http://orcid.org/0000-0003-2380-2914

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectivesto map and summarize the main applications of artificial intelligence in addressing interpersonal violence against vulnerable populations.

methodsa scoping review was conducted between December 2024 and February 2025 in the PubMed, Web of Science, Embase, PsycINFO, and CINAHL databases, as well as grey matter databases. Editorials, retractions, and studies of self-inflicted violence were excluded.

results750 texts were found. After applying the eligibility criteria, a sample of ten materials was obtained. The studies were grouped into the categories "Prediction and automated monitoring of violence", "Decision support, technological innovation in health and social protection" and "Ethics, security, and social impact of artificial intelligence in vulnerable contexts".

conclusionsartificial intelligence models for addressing violence against vulnerable populations require verification, data protection, social governance and testing with a high level of evidence.

Indexed as

Artificial IntelligenceViolenceVulnerable PopulationsHumans

Identifiers

PMID42659509
PMCPMC13505558

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.