AI-Mediated Mental Health Disclosure

Youth in the United States are facing a growing mental health crisis [1]. However, many adolescents do not seek timely support due to barriers such as difficulty articulating their emotional experiences, uncertainty about when or how to ask for help, and concerns about social stigma [2]. At the same time, recent studies show that one in eight adolescents use generative AI chatbots (e.g., ChatGPT, Gemini) to seek mental health advice because they are accessible, immediate, and perceived as private [3,4]. Despite this growing use, AI-mediated conversations remain isolated from adolescents’ formal care circle and are vulnerable to hallucinated or potentially harmful guidance [5]. This presents a critical opportunity to design AI systems that act as communication bridges, enabling youth to share mental health concerns with trusted care providers and receive timely support.

Existing research on AI and mental health highlights its potential for screening, psychoeducation, and structured therapeutic interactions [6,7]. However, most work treats AI as a single-user system and pays limited attention to interaction design challenges such as user roles, disclosure boundaries, interaction modalities, and coordination among multiple stakeholders, factors that are critical in collaborative care contexts [8]. As a result, there is limited design knowledge about how AI systems might function as privacy-preserving mediators of mental health disclosure that support user agency, shared understanding, and trust across care networks. This project explores the design space for AI-mediated disclosure of mental health and wellbeing among youth by exploring ways to transform user-AI conversations into collaborative tool empowering users to share their mental health conditions with care providers, for timely care and support.