The global youth mental health (YMH) crisis demands scalable, effective solutions, yet current care models remain insufficiently engaging and effective. Critical barriers include limited personalisation, reduced youth agency in collaborative decision-making, and poor care continuity. Generative AI has the potential to address these challenges. However, key limitations prevent clinical translation: LLMs cannot reason longitudinally over evolving clinical contexts; lack frameworks for ensuring safety, youth agency, and evidence-informed decision-making; and operate as standalone tools disconnected from face-to-face care. This project will address these limitations through SensAI, a multi-stakeholder AI collaborator that supports young people with depression and anxiety and their clinicians to enhance personalisation, agency, and continuity in YMH. We will: (1) develop novel methods for longitudinal LLM reasoning; (2) produce YMH-specific constitutional principles that enable LLMs to deliver safe, agency-supportive, and evidence-aligned guidance; (3) integrate these methods into SensAI, an AI collaborator that supports young people and clinicians across the care journey; and (4) evaluate SensAI’s feasibility, safety, and preliminary effectiveness of through a pilot randomised controlled trial.
Generative AI
Youth mental health