ArticleScientific reports2025
Performance of mental health chatbot agents in detecting and managing suicidal ideation.
Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 23 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
23 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Responsible artificial intelligence integration framework for psychiatric guidelines.The international journal of neuropsychopharmacology · 2026Guideline
- Making medical AI benchmarks clinically interpretable: the case of mental health.BMJ mental health · 2026Article
- Possible Role and Function of AI Conversational Agents in Dialectical Behavior Therapy for Borderline Personality Disorder: Qualitative Interview Study.JMIR mental health · 2026Article
- Preparing AI chatbots to respond to patient distress and suicidality in high-risk healthcare settings.NPJ digital medicine · 2026Article
- Educating minds with generative AI.Communications psychology · 2026Review
- Health Care Professionals' Perspectives on Conversational Mental Health Chatbots: Protocol for a Systematic Review.JMIR research protocols · 2026Article
- Strengths and Potential Pitfalls of the Use of Artificial Intelligence in Psychiatric Education and Practice.Academic psychiatry : the journal of the American Association of Directors of Psychiatric Residency Training and the Association for Academic Psychiatry · 2026Article
- Multiturn Large Language Model-Based Conversational Agents for Patients With Cancer and Caregivers: Scoping Review.JMIR cancer · 2026Article
- Generative AI and exacerbated suicide risk among vulnerable populations.Lancet regional health. Americas · 2026Article
- Ethical Considerations in Personal Health Large Language Models.Journal of medical Internet research · 2026Article
- Characterizing artificial intelligence (AI) psychosis in a large academic medical setting: evidence of the new clinical phenomenon and the vulnerability of those in early phases of psychosis.medRxiv : the preprint server for health sciences · 2026Article
- Mapping Practice-Based Signals of Generative AI in Psychiatric Care: Qualitative Study of Korean Psychiatrists' Experiences, Interpretations, and Implementation Priorities.Journal of medical Internet research · 2026Article
- Safety Mechanisms and Risk Mitigation in Generative AI Mental Health Chatbots: A Systematic Scoping Review.Healthcare (Basel, Switzerland) · 2026Review
- Automated Safety Testing and Reporting Application for Conversational Safety Monitoring of Generative AI Tools for Mental Health: Development and Validation Study.JMIR mental health · 2026Article
- Barriers and Facilitators to the Use of Large Language Model-Based Conversational Agents in Mental Healthcare: A Systematic Review.Healthcare (Basel, Switzerland) · 2026Review
- Bridging Science and Subjectivity: Evolving Evidence, Emerging Technologies and the Call for Personalised Psychotherapy: Créer une passerelle entre la science et la subjectivité : Évolution des données probantes, arrivée de nouvelles technologies et appel à une psychothérapie personnalisée.Canadian journal of psychiatry. Revue canadienne de psychiatrie · 2026Article
- Privacy assurances and professional-boundary warnings in generative AI mental health chatbots: a randomized vignette experiment on calibrated trust, overreliance risk, and professional help-seeking intentions.Frontiers in psychology · 2026Article
- Are artificial intelligence chatbots safe for suicide risk assessment? A narratively synthesized review of current evidence.Global mental health (Cambridge, England) · 2026Review
- Designing AI for distress: an iterative case study of a hierarchical agent for psychosocial support.Frontiers in artificial intelligence · 2026Article
- Molecular pathways linking chronic psychological stress to accelerated aging: mechanisms and interventions.Frontiers in aging · 2026Review
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.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Advances in artificial intelligence (AI) technologies sparked a rapid development of smartphone applications designed to help individuals experiencing mental health problems through an AI-powered chatbot agent. However, the safety of such agents when dealing with individuals experiencing a mental health crisis, including suicidal crisis, has not been evaluated. In this study, we assessed the ability of 29 AI-powered chatbot agents to respond to simulated suicidal risk scenarios. Application repositories were searched and the app descriptions screened in search of apps that claimed to be beneficial when experiencing mental distress and offered an AI-powered chatbot function. All agents were tested with a standardized set of prompts based on the Columbia-Suicide Severity Rating Scale designed to simulate increasing suicidal risk. We assessed the responses according to pre-defined criteria based on the ability to provide emergency contact information and other factors. None of the tested agents satisfied our initial criteria for an adequate response, 51.72% satisfied the relaxed criteria for a marginal response, while 48.28% were deemed inadequate. Common errors included the inability to provide emergency contact information and a lack of contextual understanding. These findings raise concerns about the deployment of AI-powered chatbots in sensitive health contexts without proper clinical validation.
Indexed as
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.