Evidence map›Paper›PMID 40604608›Full record

ArticleBMC public health2025

Crisis-line workers' perspectives on AI in suicide prevention: a qualitative exploration of risk and opportunity.

Jacob Greaves, Erminia Colucci

Abstract read
In one paragraph

Article in BMC public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. Article
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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

2 authors.

Jacob GreavesMiddlesex University, London, UK. jake.greaves@pm.me.
Erminia ColucciMiddlesex University, London, UK.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundCrisis support services offer crucial intervention for individuals in acute distress, providing timely access to trained volunteers whose human connection is key to the effectiveness of these services. However, there are significant disparities in who utilises these services. Recent advancements in artificial intelligence (AI) present new possibilities for crisis intervention in the form of AI-powered conversational partners. Yet, there is little guidance on how AI might be used in this context; and the risks and opportunities remain largely unexplored. This study aims to explore the risks and opportunities of integrating artificial volunteers (AVs) into crisis support, focusing on meeting the needs of those at risk of suicide. It collects the perspectives of crisis service volunteers to contemplate an AVs potential effect on the quality and effectiveness of support provided in crisis situations.

methodsA thematic analysis was used to interpret 13 semi-structured, exploratory qualitative interviews of an UK-based crisis service volunteers.

resultsThree concerns were identified regarding perceived inflexibility and inauthenticity of AI, and the potential for dehumanisation of texters, aligning with factors influencing suicidal behaviour, such as perceived rejection and feelings of entrapment. Despite these concerns, the study found potential advantages, including reduced perceived burden on texters, enhanced confidentiality, and consistent, impartial responses. Recommendations for potential implementations suggest a cautious yet open-minded approach to integrating AI into crisis support, emphasising the need for transparency, accountability, and clarity on the role of human oversight.

conclusionsAI could complement rather than replace human support in the form of an AV, offering a differentiated, accessible avenue for those who might prefer or benefit from non-human interaction.

Indexed as

Artificial IntelligenceCrisis InterventionHotlinesSuicide PreventionVolunteersAdultFemaleHumansInterviews as TopicMaleMiddle AgedQualitative ResearchUnited KingdomAIArtificial intelligenceCrisisInternetSuicideTechnologyVolunteers

Identifiers

PMID40604608
PMCPMC12220356

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LicenceCC BY
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Registered trials

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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.