Paper Type
Complete
Paper Number
PACIS2025-1380
Description
The impacts of sleep tracking have drawn considerable scholarly attention in recent years. However, why and how people use sleep-tracking technology is less well understood. To address this question, we conducted in-depth interviews among 38 Oura smart ring users. Guided by self-determination theory, we identified satisfaction and frustration of autonomy, competence, and relatedness in the sleep-tracking context. Thereafter, guided by the needs-affordances-features perspective, we mapped these needs to their corresponding affordances and features. Finally, we outlined three key findings unique to sleep tracking: personalized features and suggestions with a guidance-flexibility balance are important for autonomy satisfaction; competence satisfaction is central and benefits from appropriate goals and positive feedback; and relatedness is less central due to the personal nature of health data. Our findings contribute to IS research and practice by providing new insights into the needs of sleep-tracking users and offering guidance for designing technology that effectively meets these needs.
Recommended Citation
Feng, Shan and Mäntymäki, Matti, "Sleep Tracking with a Smart Ring: A Needs-Affordances-Features Perspective" (2025). PACIS 2025 Proceedings. 7.
https://aisel.aisnet.org/pacis2025/hci/hci/7
Sleep Tracking with a Smart Ring: A Needs-Affordances-Features Perspective
The impacts of sleep tracking have drawn considerable scholarly attention in recent years. However, why and how people use sleep-tracking technology is less well understood. To address this question, we conducted in-depth interviews among 38 Oura smart ring users. Guided by self-determination theory, we identified satisfaction and frustration of autonomy, competence, and relatedness in the sleep-tracking context. Thereafter, guided by the needs-affordances-features perspective, we mapped these needs to their corresponding affordances and features. Finally, we outlined three key findings unique to sleep tracking: personalized features and suggestions with a guidance-flexibility balance are important for autonomy satisfaction; competence satisfaction is central and benefits from appropriate goals and positive feedback; and relatedness is less central due to the personal nature of health data. Our findings contribute to IS research and practice by providing new insights into the needs of sleep-tracking users and offering guidance for designing technology that effectively meets these needs.
Comments
HCI