While prior research has focused on providers, caregivers, and adult patients, little is known about adolescents’ perceptions of AI in health learning and management. Utilizing design fiction and co-design methods, we conducted seven workshops with 23 adolescents (aged 14-17) to understand how they anticipate using health AI in the context of a family celiac diagnosis. Our findings reveal that adolescents have four main envisioned roles of health AI: enhancing health understanding and help-seeking, reducing cognitive burden, supporting family health management, and providing guidance while respecting their autonomy. We also identified nuanced trust and a divided view toward emotional support from health AI. These findings suggest that adolescents perceive AI’s value as a tool that moves them from efficiency to meaning–one that creates time for valued activities. We discuss opportunities for future health AI systems to be designed to encourage adolescent autonomy and reflection, while also supporting meaningful, dialectical activities.

We investigate the role of large language models (LLMs) in supporting mental health by analyzing Reddit posts and comments about mental health conversations with ChatGPT. Our findings reveal that users value ChatGPT as a safe, non-judgmental space, often favoring it over human support due to its accessibility, availability, and knowledgeable responses. ChatGPT provides a range of support, including actionable advice, emotional support, and validation, while helping users better understand their mental states. Additionally, we found that ChatGPT offers innovative support for individuals facing mental health challenges, such as assistance in navigating difficult conversations, preparing for therapy sessions, and exploring therapeutic interventions. However, users also voiced potential risks, including the spread of incorrect health advice, ChatGPT's overly validating nature, and privacy concerns. We discuss the implications of LLMs as tools for mental health support in both everyday health and clinical therapy settings and suggest strategies to mitigate risks in LLM-powered interactions.

Mobile dating apps are now used for a wide range of networking opportunities beyond romantic relationships. However, previous studies on mobile dating apps have not fully taken into account the multiple motivations that users may have. This study aimed to address this gap by conducting semi-structured interviews with 12 Tinder users in South Korea, who reported having multiple motivations for using mobile dating apps. We discovered that participants' motivations using Tinder became gradually expanded but clarified over time. Furthermore, we found that participants rarely disclosed their motivations on their profiles, but heavily relied on implicit cues from other profiles to guess the motivations of others. Based on these findings, we propose design suggestions for improving the design of dating apps to better support users' multi-faceted and variable motivations using mobile dating apps.

Role-playing can be an effective method for disability awareness education (DAE), and the immersive nature of virtual reality (VR) holds promise for enhancing DAE experiences. However, existing VR applications for DAE often pay less attention to the social aspects of disabilities, resulting in a lack of ability to simulate implicit social discrimination experienced by individuals with disabilities. To bridge this gap, we developed DiVRsity, a customizable VR group role-playing platform for DAE. To identify design requirements for DiVRsity, we conducted a formative study with VR and DAE experts. In an evaluation study, 28 participants engaged in role-playing exercises using DiVRsity, simulating discriminatory interpersonal situations experienced by individuals with vision impairments. Findings revealed that participants’ disability awareness significantly increased after engaging in role-playing activities using DiVRsity compared to before. We discuss the potential of VR as a role-playing platform for DAE and provide design implications for future VR-based DAE tools.