2026-09-20T15:27:28Zhttps://digital.lib.washington.edu/server/oai/request

oai:digital.lib.washington.edu:1773/485192026-02-15T22:27:02Zcom_1773_4888col_1773_4933

Spiro, Emma Zeng, Li 2022-04-19T23:46:01Z 2022-04-19T23:46:01Z 2022-04-19 2022 Zeng_washington_0250E_23951.pdf http://hdl.handle.net/1773/48519 Thesis (Ph.D.)--University of Washington, 2022 Physical activity provides wide-ranging physical and mental health benefits. However, a large proportion of the population fails to achieve recommended levels of physical activity. With the development of pervasive technology such as smartphones and wearable devices, increasing attention has been paid to promoting positive fitness behaviors through self-tracking and participation in online communities. Fitness-based applications allow users to log and share activity-related data, providing opportunities to observe, analyze and reflect on performance and goals. They also serve as a social network that connects users, promoting social interaction features as a means towards behavioral change and healthy life-style promotion. However, limited work has comprehensively investigated these networks; their structural features and association with behavior (and behavior change) may reveal important dimensions of social exercise and its impacts on participants. These platforms capture information on physical activities as well as peer-to-peer interactions at large scale and low cost, allowing researchers to observe how individuals really engage in physical activity and social interaction, rather than how they report on their participation (e.g. in traditional surveys). Utilizing large-scale behavioral traces collected using novel sampling methods, this dissertation aims to advance our understanding of online social interaction in a fitness community, and how it is associated with fitness behaviors. This work provides new insights into pathways for health promotion and the possibility for network-based health interventions. application/pdf en_US none behavioral traces fitness behavior online fitness communities self-tracking social interaction social support Information science Information science Social Support on Fitness Behavior in an Online Fitness Community Thesis Open Access open.access