CAREER: HCC: Advancing Personal Wellbeing through Everyday Meaningful Self-Tracking Experiences

Self-tracking technologies like digital pedometers, food journaling apps, and mood-monitoring apps make up a nearly $20 billion industry in the U.S., with over 40% of U.S. adults having used one and half of primary care providers recommending one. However, people often fail to benefit from the health and wellbeing data collected from these technologies. One reason is that people find the design of these technologies ignores the realities of their everyday lives, in terms of what they can realistically undertake and what resources they have available to them. To help researchers and industry better align the design of self-tracking technology with people's realities, this project will establish deeper understanding of how self-tracking technology can support more meaningful engagement to help people improve their wellbeing. Grounded in theories of meaningfulness, the research team will design, create, and deploy three novel applications that address three aspects of meaningfulness that are understudied in personal informatics: connectedness, resonance, and significance. The first is a webapp for creating customizable representations of physical activity data on watch faces, to promote deeper personal connection between people's values, interests, and their data. The research team will further utilize the webapp in a high school summer program for historically underrepresented groups in computing to introduce students to computing, design, and self-tracking around wellbeing. The second is a communal digital display surfacing shared eating experiences in families, to enhance bonding and resonance among family members. The third involves annotation tools for validated scales used in mental health treatment, to allow people to communicate the significance of the data they collect as part of their care. Informed by people's lived experiences with these approaches, the research team will synthesize the results of these studies to create an empirically validated framework describing how to design meaningful self-tracking interactions. This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.