Using GenAI to train mental health professionals in suicide risk assessment: Preliminary findings

Background Suicide risk assessment is a critical skill for mental health professionals (MHPs), yet traditional training in this area is often limited. This study examined the potential of generative artificial intelligence (GenAI)-based simulator to enhance self- efficacy in suicide risk assessment among MHPs. Method A quasi-experimental study was conducted with 43 MHPs from Israel. Participants attended an online seminar and interacted with a GenAI-powered suicide risk assessment simulator. They completed pre- and post-intervention questionnaires measuring suicide risk assessment self-efficacy and willingness to treat suicidal patients. Qualitative data on user experience were collected. Results We found a significant increase in self-efficacy scores following the intervention. Willingness to treat patients presenting suicide risk increased slightly but did not reach significance. Qualitative feedback indicated that participants found the simulator engaging and valuable for professional development. However, participants raised concerns about over-reliance on AI and the need for human supervision during training. Conclusion This preliminary study suggests that GenAI-based simulators hold promise as a tool to enhance MHPs’ competence in suicide risk assessment. However, further research with larger samples and control groups is needed to confirm these findings and address ethical considerations surrounding AI use in suicide risk assessment training. AI-powered simulation tools have the potential to democratize access to high-quality training in mental health, potentially contributing to global suicide prevention efforts. However, their implementation should be carefully considered to ensure they complement rather than replace human expertise.