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KAIST Professor Uichin Lee Receives Distinguished Paper Award from ACM < Photo. Professor Uichin Lee (left) receiving the award > KAIST (President Kwang Hyung Lee) announced on the 25th of October that Professor Uichin Lee’s research team from the School of Computing received the Distinguished Paper Award at the International Joint Conference on Pervasive and Ubiquitous Computing and International Symposium on Wearable Computing (Ubicomp / ISWC) hosted by the Association for Computing Machinery (ACM) in Melbourne, Australia on October 8. The ACM Ubiquitous Computing Conference is the most prestigious international conference where leading universities and global companies from around the world present the latest research results on ubiquitous computing and wearable technologies in the field of human-computer interaction (HCI). The conference program is composed of invited papers published in the Proceedings of the ACM (PACM) on Interactive, Mobile, Wearable and Ubiquitous Technologies (IMWUT), which covers the latest research in the field of ubiquitous and wearable computing. The Distinguished Paper Award Selection Committee selected eight papers among 205 papers published in the seven volumes of the ACM Proceedings (PACM IMWUT) that made outstanding and exemplary contributions to the research community. The committee consists of 16 prominent experts who are current and former members of the journal's editorial board which made the selection after a rigorous review of all papers for a period that stretched over a month. < Figure 1. BeActive mobile app to promote physical activity to form active lifestyle habits > The research that won the Distinguished Paper Award was conducted by Dr. Junyoung Park, a graduate of the KAIST Graduate School of Data Science, as the 1st author, and was titled “Understanding Disengagement in Just-in-Time Mobile Health Interventions” Professor Uichin Lee’s research team proposed ‘Just-in-Time (JIT) Mobile Health Interventions’ that actively provide interventions in optimal situations by utilizing data collected from health management apps, based on the premise that these apps are aptly in use to ensure effectiveness. < Figure 2. Overview of traditional user-requested digital behavioral intervention notifications (Pull) and automatic transmission (Push) for Just-in-Time (JIT) mobile health interventions using smartphone sensing technologies > The research team conducted a systematic analysis of the decline in participation in digital behavior change interventions. They developed the BeActive system, an app that promotes physical activities designed to help forming active lifestyle habits, and systematically analyzed the effects of users’ self-control ability and boredom-proneness on compliance with behavioral interventions. The results of an 8-week empirical experiment revealed that even if JIT interventions are provided according to the user’s situation, it is impossible to avoid a decline in participation. However, for users with high self-control and low boredom tendency, the compliance with JIT interventions delivered through the app was significantly higher than that of users in other groups. In particular, users with high boredom proneness easily got tired of the repeated timely interventions, and their compliance with the app decreased more quickly than in other groups. < Figure 3. JIT Mobile Health Intervention: a demonstrative case of the BeActive system > Professor Uichin Lee explained, “The results of the first study on the participation in digital therapeutics and wellness services utilizing JIT mobile health interventions provide a starting point for exploring ways to increase participation,” and “It will be possible to develop user-centered artificial intelligence technology that increases participation by utilizing large-scale language models (LLMs) and complex situational awareness technologies.” < Figure 4. A conceptual illustration of engagement in digital health apps. Engagement in digital health apps consists of (1) engagement in using digital health apps and (2) engagement in behavioral interventions provided by digital health apps, i.e., compliance with behavioral interventions. Adherence to behavioral interventions recommended by digital health apps can help achieve the ultimate health goals. > This study was conducted with the support of the 2021 Biomedical Technology Development Program and the 2022 Basic Research and Development Program of the National Research Foundation of Korea funded by the Ministry of Science and ICT. < Figure 5. A conceptual illustration of participation and disengagement. It is divided into participation by use of service provided by the app and participation (adherence) for behavioral intervention. The distinction of participation can be explained by dividing it into adoption, abandonment, and attrition. > < Figure 6. Trends of changes in frequency of app usage and adherence to behavioral intervention over 8 weeks, ● SC: Self-Control Ability (High-SC: user group with high self-control, Low-SC: user group with low self-control) ● BD: Boredom-Proneness (High-BD: user group with high boredom-proneness, Low-BD: user group with low boredom-proneness) >
2024.10.25 View 115

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