Evidence map›Paper›PMID 40811811›Full record

ArticleJMIR mental health2025

An Examination of Generative AI Response to Suicide Inquires: Content Analysis.

Laurie O Campbell, Kathryn Babb, Glenn W Lambie, B Grant Hayes

Abstract read
In one paragraph

Article in JMIR mental health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 21 papers.

0numbers the graph read from it
0cells of the map it votes in
21citing 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

21 citing papers in PubMed.

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  7. CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne · 2026
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  12. Urgent considerations for suicide prevention in the safe and ethical use of artificial intelligence.CMAJ : Canadian Medical Association journal = journal de l'Association medicale canadienne · 2026
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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

4 authors.

Laurie O CampbellLearning Sciences and Educational Research, College of Community Innovation and Education, University of Central Florida, 4000 Central Florida Blvd, Orlando, 32816, United States, 1 407-823-2000, 1 407-823-5651.ORCID 0000-0001-7313-5457
Kathryn BabbCounselor Education and School Psychology, Capella University, Orlando, FL, United States.ORCID 0000-0002-1030-9613
Glenn W LambieCollege of Community Innovation and Education, University of Central Florida, Orlando, FL, United States.ORCID 0000-0003-4181-6201
B Grant HayesCollege of Community Innovation and Education, University of Central Florida, Orlando, FL, United States.ORCID 0009-0000-1064-8618

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Generative artificial intelligence (AI) chatbots are an online source of information consulted by adolescents to gain insight into mental health and wellness behaviors. However, the accuracy and content of generative AI responses to questions related to suicide have not been systematically investigated. Objective: This study aims to investigate general (not counseling-specific) generative AI chatbots' responses to questions regarding suicide. Methods: A content analysis was conducted of the responses of generative AI chatbots to questions about suicide. In phase 1 of the study, generative chatbots examined include: (1) Google Bard or Gemini; (2) Microsoft Bing or CoPilot; (3) ChatGPT 3.5 (OpenAI); and (4) Claude (Anthropic). In phase 2 of the study, additional generative chatbot responses were analyzed, which included Google Gemini, Claude 2 (Anthropic), xAI Grok 2, Mistral AI, and Meta AI (Meta Platforms). The two phases occurred a year apart. Results: Findings included a linguistic analysis of the authenticity and tone within the responses using the Linguistic Inquiry and Word Count program. There was an increase in the depth and accuracy of the responses between phase 1 and phase 2 of the study. There is evidence that the responses by the generative AI chatbots were more comprehensive and responsive during phase 2 than phase 1. Specifically, the responses were found to provide more information regarding all aspects of suicide (eg, signs of suicide, lethality, resources, and ways to support those in crisis). Another difference noted in the responses between the first and second phases was the emphasis on the 988 suicide hotline number. Conclusions: While this dynamic information may be helpful for youth in need, the importance of individuals seeking help from a trained mental health professional remains. Further, generative AI algorithms related to suicide questions should be checked periodically to ensure best practices regarding suicide prevention are being communicated.

Indexed as

Artificial IntelligenceSuicideAdolescentHumansadolescent suicideartificial intelligencechatbotsLinguistic Inquiry and Word CountLIWCschool counseling

Identifiers

PMID40811811
PMCPMC12371289

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.