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 prevention



Please note: submissions focusing on AI or LLM methodology without a substantive clinical or applied mental health focus are outside the scope of this section.

Article types and fees

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Classification
• Clinical Trial
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• ... View all formats

Articles that are accepted for publication by our external editors following rigorous peer review incur a publishing fee charged to Authors, institutions, or funders.

Article types

This Research Topic accepts the following article types, unless otherwise specified in the Research Topic description:

• Brief Research Report
• Classification
• Clinical Trial
• Data Report
• Editorial
• FAIR² Data
• General Commentary
• Hypothesis and Theory
• Methods
• Mini Review
• Opinion
• Original Research
• Perspective
• Policy and Practice Reviews
• Policy Brief
• Review
• Study Protocol
• Systematic Review
• Technology and Code

Keywords: Suicide prevention, artificial intelligence, large language models, chatbot, digital mental health, mental health apps, crisis intervention, digital intervention, gatekeeper training, serious games, ethics, natural language processing

Important note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.