This paper is in the following e-collection/theme issue:

Formative Evaluation of Digital Health Interventions (2220) mHealth for Wellness, Behavior Change and Prevention (2752) Wearable Devices and Sensors (822) Prevention and Health Promotion (899)

Published on in Vol 7 (2023)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/42087, first published .
Predicting Habitual Use of Wearable Health Devices Among Middle-aged Individuals With Metabolic Syndrome Risk Factors in South Korea: Cross-sectional Study

Predicting Habitual Use of Wearable Health Devices Among Middle-aged Individuals With Metabolic Syndrome Risk Factors in South Korea: Cross-sectional Study

Predicting Habitual Use of Wearable Health Devices Among Middle-aged Individuals With Metabolic Syndrome Risk Factors in South Korea: Cross-sectional Study

Authors of this article:

Jaeyoung Ha1 Author Orcid Image ;   Jungmi Park1 Author Orcid Image ;   Sangyi Lee1 Author Orcid Image ;   Jeong Lee2 Author Orcid Image ;   Jin-Young Choi1 Author Orcid Image ;   Junhyoung Kim1 Author Orcid Image ;   Sung-il Cho1, 3 Author Orcid Image ;   Gyeong-Suk Jeon4 Author Orcid Image
Article Authors Cited by (4) Tweetations Metrics

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  2. Alanzi T, Alzahrani W, Almoraikhi ‏, Algannas ‏, Alghamdi M, Alzahrani ‏, Abutaleb R, Ba Dughaish ‏, Alotibi N, Alkhalifah S, Alshehri ‏, Alzahrani H, Almahdi ‏, Alanzi N, Farhah ‏. Adoption of Wearable Insulin Biosensors for Diabetes Management: A Cross-Sectional Study. Cureus 2023 View
  3. Choi S, Seo J, Hernandez M, Kitsiou S. Conversational agents in mHealth: use patterns, challenges, and design opportunities for individuals with visual impairments. Journal of Technology in Behavioral Science 2024 View
  4. Min H, Li J, Di M, Huang S, Sun X, Li T, Wu Y. Factors influencing the continuance intention of the women’s health WeChat public account: an integrated model of UTAUT2 and HBM. Frontiers in Public Health 2024;12 View