ArticleFrontiers in medicine2025
A step toward the future? evaluating GenAI QPR simulation training for mental health gatekeepers.
Article in Frontiers in medicine, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 6 papers.
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Who cites it
6 citing papers in PubMed.
- Generative Large Language Models in Mental Health Care Settings: Systematic Review and Meta-Analysis.JMIR AI · 2026Review
- Variability and Innovation in Faculty Development Models in Emergency Medicine.AEM education and training · 2026Review
- Use of a Conversational Agent for Training Mental Health Professionals in Suicide Safety Planning: Pilot Feasibility and Acceptability Study.JMIR mental health · 2026Article
- Breaking bad news with reflective AI virtual experience (BRAVE): development and evaluation of a generative AI-based simulation tool.Advances in simulation (London, England) · 2026Article
- The effectiveness of multilingual AI-based simulator for suicide risk assessment training in improving self-efficacy among young psychiatrists: a pilot study across twenty languages.BMC psychiatry · 2026Article
- Validating GenAI feedback in suicide prevention training: a mixed-methods study of QPR skill assessment.Frontiers in medicine · 2025Article
Corrections and comments
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Authors and funding
4 authors.
Funding
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Abstract
Background: Suicide remains a leading cause of preventable death, placing a significant burden on healthcare systems worldwide. Effective suicide prevention relies not only on mental health professionals but also on well-trained gatekeepers, including primary care providers, emergency physicians, and community healthcare workers. Traditional training programs, such as Methods: A total of 89 adult participants from the community, all of whom were mental health professionals (including social workers, occupational therapists, speech therapists, and physicians), completed pre- and post-intervention assessments measuring self-efficacy and willingness to support individuals at risk of suicide. Participants engaged in real-time interactions with an AI-powered simulator that mimicked conversations with at-risk individuals, enabling dynamic practice of QPR (Question, Persuade, Refer) skills. Data were collected in June 2024. Quantitative data were analyzed using paired Results: Post-intervention self-efficacy scores showed a significant increase, with a large effect size (Cohen's D = 1.67). Willingness-to-support scores demonstrated a slight but non-significant improvement. Higher QPR self-efficacy correlated positively with increased willingness to support. Qualitative feedback indicated that participants found the simulator realistic and beneficial for skill acquisition, although some expressed concerns regarding the potential reduction of human interaction in mental health training. Conclusion: AI-driven simulators hold promise as scalable, accessible, and clinically relevant tools for suicide prevention training. Their integration into medical education and clinical settings could improve the preparedness of healthcare providers, primary care physicians, and frontline medical staff in identifying and managing suicide risk. These findings support the adoption of digital health innovations to enhance medical training and public health interventions.
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