Evidence map›Paper›PMID 42512690›Full record

ReviewHealthcare (Basel, Switzerland)2026

AI-Enabled First-Response Support After Sexual and Gender-Based Violence: A PRISMA-ScR Scoping Review.

Paolo Bailo, Chiara Carsana, Maria Garreffa, Anna Carannante, Marco Giustini, Cecilia Fazio, Loredana Falzano, Andrea Piccinini, Simona Gaudi

Abstract readReview
In one paragraph

Review in Healthcare (Basel, Switzerland), 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

9 authors.

Paolo BailoSection of Legal Medicine, School of Law, University of Camerino, 62032 Camerino, Italy.
Chiara CarsanaSection of Legal Medicine and Insurance Medicine, Department of Biomedical Sciences for Health, University of Milan, 20122 Milan, Italy.ORCID 0009-0001-3339-6502
Maria GarreffaSection of Legal Medicine and Insurance Medicine, Department of Biomedical Sciences for Health, University of Milan, 20122 Milan, Italy.
Anna CarannanteDepartment of Environment and Health, Italian Institute of Health, 00161 Rome, Italy.
Marco GiustiniDepartment of Environment and Health, Italian Institute of Health, 00161 Rome, Italy.
Cecilia FazioDepartment of Environment and Health, Italian Institute of Health, 00161 Rome, Italy.
Loredana FalzanoNational Centre for Global Health, Italian Institute of Health, 00161 Rome, Italy.
Andrea PiccininiSection of Legal Medicine and Insurance Medicine, Department of Biomedical Sciences for Health, University of Milan, 20122 Milan, Italy.ORCID 0000-0001-8017-7065
Simona GaudiDepartment of Environment and Health, Italian Institute of Health, 00161 Rome, Italy.ORCID 0000-0001-6079-6942

Funding

Ministry of Health I85E23001150005
6 · The paper itself

Abstract

backgroundArtificial intelligence (AI) is increasingly proposed to augment early-stage assistance for survivors of sexual and gender-based violence (GBV), including intimate partner and domestic violence, across crisis hotlines, specialist services, digital reporting channels, legal support tools and healthcare pathways. However, the scope, maturity and evaluative strength of the peer-reviewed evidence remain uncertain. We aimed to map the application domains, evaluative maturity, and implementation and safety gaps of this evidence base.

methodsWe conducted a scoping review reported according to the PRISMA Extension for Scoping Reviews (PRISMA-ScR), using a Population-Concept-Context framework focused on AI-enabled first-response and early support. Searches in Scopus, Web of Science Core Collection and PubMed were supplemented by targeted searches of IEEE Xplore and ACM Digital Library. Records were screened against predefined criteria, charted using a structured form and synthesised descriptively.

resultsOriginal searches yielded 187 records and 21 included sources of evidence. The supplementary search identified 539 records/candidates; 27 full texts were assessed and 6 additional sources met eligibility criteria, yielding 27 included sources of evidence. Evidence covered survivor-facing conversational support; screening and triage in emergency and specialist services; social-triage and online disclosure models; survivor-informed help-seeking and chatbot design; legal/support routing; and enabling modalities such as speech-based approaches. Most sources reported technical performance, usability, acceptability or systems-audit findings, while no workflow-integrated evaluation was identified and survivor-centred effectiveness outcomes, service uptake and adverse-event monitoring were rarely reported.

conclusionsThe evidence remains heterogeneous and early-stage, with limited support for service-integrated effectiveness or safety. Included sources more often assessed models, interfaces or prototypes than downstream pathway outcomes. The findings support cautious, pathway-aware interpretation and identify recurring concerns regarding escalation, accountability, equity, digital trace safety and human handover. The proposed practice considerations and outcome domains are author-informed priorities for future pilot and implementation studies, not validated guidelines.

Indexed as

artificial intelligencechatbotscrisis hotlinesdomestic violencegender-based violenceintimate partner violencescoping reviewsexual violencetriage

Identifiers

PMID42512690
PMCPMC13410215

What OpenQuestion holds

Textmetadata
LicenceCC BY
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.