Understanding when and how social features in health tools help — and when they backfire.
Adding social features to digital health interventions can help people access emotional, instrumental, and informational support; strengthen accountability; and create shared experiences. But early commercial implementations of these features often invited people to share in ways that violated social norms, producing awkward interactions and undermining the benefits. Through a series of research prototypes — Three Good Things, GoalPost, GoalLine, Commit to Steps, Crumbs, and Yarn — this body of work identifies design patterns that preserve the benefits of social features while avoiding the pitfalls. Post-doctoral scholar Laura Pina also led investigations into how families share personal tracking data, culminating in the design and deployment of DreamCatcher.
This research was funded by Intel, the Robert Wood Johnson Foundation, the University of Michigan Rackham Graduate School, and the University of Washington Royalty Research Fund.
Sharing data about health behaviors — steps walked, calories eaten, moods tracked — is socially complex in ways that early platforms underestimated. Posting an automatically generated activity update to a social network site exposes people to audiences with different relationships, expectations, and norms. When these posts generate silence, unwanted commentary, or awkward responses, people disengage.
To understand what actually goes wrong, we interviewed people using social network sites for health, identifying the gap between what sharing features afforded and what people actually needed from their social connections. This work surfaced that the problem was not social sharing per se, but the lack of structure, context, and audience control that platforms provided.
Building on this empirical grounding, we developed a design framework for social sharing in personal informatics — characterizing the social contexts in which people share, the goals sharing is meant to serve, and the design strategies most likely to support positive interactions. We then evaluated revised messaging based on this framework.
Alongside this conceptual work, we designed, built, and evaluated a series of research prototypes that tested specific design strategies in deployment.
Happier Together integrated a positive psychology–based wellness journaling application (Three Good Things) into a social network site, allowing friends to share and respond to each other's daily reflections.
GoalPost and GoalLine examined how sharing fitness goals and progress within a structured social context — rather than broadcasting to an undifferentiated feed — changed social interactions around physical activity. Commit to Steps explored the role of public commitment and accountability mechanisms.
Crumbs introduced lightweight daily food challenges as a mechanism for promoting social engagement and mindfulness around eating, avoiding the high disclosure burden of detailed food logging.
Yarn explored how structured storytelling — rather than raw data sharing — could help people create and share meaningful narratives from personal tracking data, giving sharing more communicative purpose and social value.
Alongside purpose-built prototypes, we also examined how people use general-purpose social platforms for health sharing. A study of Instagram as a platform for healthy eating documented how people self-organize around food tracking, support, and accountability — and the social dynamics, norms, and tensions that emerge in those communities.
Social features in health apps represent one form of peer support, but people managing chronic illness also draw on richer, more informal networks of peers — sharing information, coordination strategies, and emotional support. We developed a conceptual model of shared health informatics for chronic illness, grounding the design space for peer support technologies in the lived experience of people with chronic conditions. This work connects to my research on digital mental health, which examines engagement and intervention design in mental health contexts more broadly.
Laura Pina led an extension of this research into family contexts, examining how tracking and data sharing practices play out across generational relationships and household dynamics. A broad interview and diary study characterized how families currently use health monitoring tools, and what they need and want from shared data.
Building on these findings, Laura led the design, development, and deployment of DreamCatcher, a system that supports parents and school-age children in tracking and reviewing sleep information together. The study examined how joint review of shared data changed family conversations about sleep, and the design considerations specific to cross-generational data sharing.
As people accumulate years of personal tracking data, questions arise about what happens to that data over time — and how it can benefit future generations. This line of work examined menopause as a case study in designing for intergenerational data sharing, exploring how people might record and pass on experiences that have historically been underdiscussed and underrepresented in health information resources.