TY - JOUR
T1 - Designing intelligent self-checkup based technologies for everyday healthy living
AU - Jiang, Yanqi
AU - Ding, Xianghua
AU - Liu, Di
AU - Gui, Xinning
AU - Zhang, Wenqiang
AU - Zhang, Wei
N1 - Funding Information:
We would like to thank our participants for sharing their experiences, and the anonymous reviewers for their insightful and constructive comments. This work was supported by the National Natural Science Foundation of China (NSFC) [grant number 61672167 ].
Publisher Copyright:
© 2022 Elsevier Ltd
PY - 2022/10
Y1 - 2022/10
N2 - Recent years have seen increasing interest in health promotion or disease prevention, rather than disease treatment/management, as a more cost-effective approach towards healthcare. Technologies designed to help build healthy habits, or lifestyle technologies, have important roles to play in that respect. However, so far, they are mainly explored without considering individual health statuses, which may lead to people's excessive pursuit of quantified goals and cause negative health outcomes. In addition, while AI-powered health checkup technologies have become available for consumers to assess health on their own, they are mainly disease-oriented, and their potential for preventive health – everyday health assessment and early interventions through lifestyle changes – has been largely under-explored. This paper attempts to combine intelligent self-checkup and personalized lifestyle technologies so as to provide suggestions based on personal health status, as a potentially more effective approach to support preventive health in everyday life, or everyday healthy living as we call it in this paper. In particular, we present the iterative design process of a mobile application which supports AI-powered everyday health assessment based on face examination and adaptive inquiry, and provides personalized and adaptive lifestyle advice. Design improvements were made based on the first pilot study, and a 4-week field trial of the final design prototype reveals a number of design implications for intelligent health technologies to better support everyday healthy living.
AB - Recent years have seen increasing interest in health promotion or disease prevention, rather than disease treatment/management, as a more cost-effective approach towards healthcare. Technologies designed to help build healthy habits, or lifestyle technologies, have important roles to play in that respect. However, so far, they are mainly explored without considering individual health statuses, which may lead to people's excessive pursuit of quantified goals and cause negative health outcomes. In addition, while AI-powered health checkup technologies have become available for consumers to assess health on their own, they are mainly disease-oriented, and their potential for preventive health – everyday health assessment and early interventions through lifestyle changes – has been largely under-explored. This paper attempts to combine intelligent self-checkup and personalized lifestyle technologies so as to provide suggestions based on personal health status, as a potentially more effective approach to support preventive health in everyday life, or everyday healthy living as we call it in this paper. In particular, we present the iterative design process of a mobile application which supports AI-powered everyday health assessment based on face examination and adaptive inquiry, and provides personalized and adaptive lifestyle advice. Design improvements were made based on the first pilot study, and a 4-week field trial of the final design prototype reveals a number of design implications for intelligent health technologies to better support everyday healthy living.
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U2 - 10.1016/j.ijhcs.2022.102866
DO - 10.1016/j.ijhcs.2022.102866
M3 - Article
AN - SCOPUS:85131425053
SN - 1071-5819
VL - 166
JO - International Journal of Human Computer Studies
JF - International Journal of Human Computer Studies
M1 - 102866
ER -