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

Web-based and Mobile Health Interventions (4018) Innovations and Technology for Healthy Eating Education (487) Innovations and Technology for Physical Activity Education (926) mHealth for Wellness, Behavior Change and Prevention (3315) Behavior Change (863) Parent and Child Education on Healthy Eating and Nutrition (214)

Published on in Vol 22, No 7 (2020): July

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/17031, first published .
Effects of the e-Motivate4Change Program on Metabolic Syndrome in Young Adults Using Health Apps and Wearable Devices: Quasi-Experimental Study

Effects of the e-Motivate4Change Program on Metabolic Syndrome in Young Adults Using Health Apps and Wearable Devices: Quasi-Experimental Study

Effects of the e-Motivate4Change Program on Metabolic Syndrome in Young Adults Using Health Apps and Wearable Devices: Quasi-Experimental Study

Authors of this article:

Ji-Soo Lee1 Author Orcid Image ;   Min-Ah Kang1, 2 Author Orcid Image ;   Soo-Kyoung Lee1 Author Orcid Image
Article Authors Cited by (18) Tweetations (3) Metrics

Journals

  1. Kim G, Lee J, Lee S. A Technology-Mediated Interventional Approach to the Prevention of Metabolic Syndrome: A Systematic Review and Meta-Analysis. International Journal of Environmental Research and Public Health 2021;18(2):512 View
  2. Cilli E, Ranieri J, Guerra F, Ferri C, Di Giacomo D. Naturalizing digital and quality of life in chronic diseases: Systematic review to research perspective into technological advancing and personalized medicine. DIGITAL HEALTH 2022;8:205520762211448 View
  3. Edney S, Chua X, Müller A, Kui K, Müller‐Riemenschneider F. mHealth interventions targeting movement behaviors in Asia: A scoping review. Obesity Reviews 2022;23(4) View
  4. Ju H, Kang E, Kim Y, Ko H, Cho B. The Effectiveness of a Mobile Health Care App and Human Coaching Program in Primary Care Clinics: Pilot Multicenter Real-World Study. JMIR mHealth and uHealth 2022;10(5):e34531 View
  5. Kim H, Lee K, Lee J, Youk H, Lee H. The Effect of a Mobile and Wearable Device Intervention on Increased Physical Activity to Prevent Metabolic Syndrome: Observational Study. JMIR mHealth and uHealth 2022;10(2):e34059 View
  6. Thomas J, Patel A, Das Sivadasan S, Sreevallabhan S, Illathu Madhavamenon K, Mohanan R. Clove bud (Syzygium aromaticum L.) polyphenol helps to mitigate metabolic syndrome by establishing intracellular redox homeostasis and glucose metabolism: A randomized, double-blinded, active-controlled comparative study. Journal of Functional Foods 2022;98:105273 View
  7. Gonzalez-Fimbres R. Diferencias de género en uso de aplicaciones móviles de ejercicio en alumnos de Entrenamiento Deportivo. Revista de Ciencias del Ejercicio FOD 2022;17(1) View
  8. Wang W, Cheng J, Song W, Shen Y. The Effectiveness of Wearable Devices as Physical Activity Interventions for Preventing and Treating Obesity in Children and Adolescents: Systematic Review and Meta-analysis. JMIR mHealth and uHealth 2022;10(4):e32435 View
  9. Ha J, Park J, Lee S, Lee J, Choi J, Kim J, Cho S, Jeon G. Predicting Habitual Use of Wearable Health Devices Among Middle-aged Individuals With Metabolic Syndrome Risk Factors in South Korea: Cross-sectional Study. JMIR Formative Research 2023;7:e42087 View
  10. Lee J, Lee S. Identification of Risk Groups for and Factors Affecting Metabolic Syndrome in South Korean Single-Person Households Using Latent Class Analysis and Machine Learning Techniques: Secondary Analysis Study. JMIR Formative Research 2023;7:e42756 View
  11. Anisha S, Sen A, Bain C. Evaluating the Potential and Pitfalls of AI-Powered Conversational Agents as Humanlike Virtual Health Carers in the Remote Management of Noncommunicable Diseases: Scoping Review. Journal of Medical Internet Research 2024;26:e56114 View
  12. Dominguez Miranda S, Rodriguez Aguilar R. Machine learning models in health prevention and promotion and labor productivity: A co-word analysis. Iberoamerican Journal of Science Measurement and Communication 2024;4(1):1 View
  13. Alharbi H, Alsulami R, Alsuhaibani R, Muthaffar A, Alsulami T, Alzobaidi A, Al-Amer E, Alismail F, Alnughaymishi M, Aldakhil L, Aldanyowi S. Assessing the Impact of Digital Programmes and Applications on Patients with Metabolic Syndrome: An Updated Meta-analysis. Journal of Advanced Trends in Medical Research 2024;1(4):1147 View
  14. Abdelqader E, Mahmoud W, Gebreel H, Kamel M, Abu-Elghait M. Correlation between gut microbiota dysbiosis, metabolic syndrome and breast cancer. Scientific Reports 2025;15(1) View
  15. Yang J, Casey A, Cale L. The role of healthy lifestyle technologies in supporting young adults’ healthy active lifestyles. Sport, Education and Society 2025:1 View
  16. Madsong C, Lininger J, Terathongkum S. The effectiveness of a self-efficacy enhancement program on health behaviors and clinical outcomes in people with metabolic syndrome: A quasi-experimental study in Thailand. Belitung Nursing Journal 2025;11(4):432 View
  17. Shaluhiyah Z, Qatrannada S, Kusumawati A, Miah M. The effect of digital health intervention in promoting healthy behavior: A systematic scoping review on strategies to prevent non-communicable diseases. Dialogues in Health 2025;7:100258 View

Books/Policy Documents

  1. Domínguez-Miranda S, Rodríguez-Aguilar R. Computer Science and Engineering in Health Services. View