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AI-Driven Innovation in Suicide Prevention: Evidence, Implementation, and Ethics

Digitalization has long been an important theme in suicide prevention, and the rapid development of AI has accelerated its potential. Patients are already using chatbots as add-ons to therapy, and significant others are turning to AI for guidance on supporting a suicidal loved one. These developments bring both promise and concern - particularly around safety, clinical accountability, and privacy.This Research Topic aims to bring together empirical studies - qualitative, quantitative, or mixed-methods - examining the development, use, and impact of AI-driven digital tools in the field of suicide prevention and treatment. We are especially interested in work that grounds AI applications in clinical or lived-experience contexts, and that speaks to researchers, health professionals, and policymakers working in this space.Topics within scope include:• Development, evaluation, or effectiveness of chatbots and conversational agents for suicide prevention or treatment• Integration of large language models (LLMs) into apps, serious games, or digital interventions for suicide prevention• AI-supported tools for training professionals and gatekeepers• Digital phenotyping or ecological momentary assessment approaches applied to suicidality• Impact of AI tools on patients, carers, and significant others• Safety, privacy, and ethical considerations in AI-driven suicide preventionPlease note: submissions focusing on AI or LLM methodology without a substantive clinical or applied mental health focus are outside the scope of this section. Topic editors: Derek De Beurs, Eva De Jaegere, Michelle Tye Source: https://www.frontiersin.org/research-topics/82733/ai-driven-innovation-in-suicide-prevention-evidence-implementation-and-ethics

Open for submissionsHosted by Frontiers in Psychiatry
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