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

Health Services Research (495) Adoption and Change Management of eHealth Systems (731) Wearable Devices and Sensors (903)

Published on in Vol 9, No 3 (2020): Jul-Sep

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/19776, first published .
Exploring the Usage Intentions of Wearable Medical Devices: A Demonstration Study

Exploring the Usage Intentions of Wearable Medical Devices: A Demonstration Study

Exploring the Usage Intentions of Wearable Medical Devices: A Demonstration Study

Authors of this article:

Chiao-Chen Chang1 Author Orcid Image
Article Authors Cited by (20) Tweetations (3) Metrics

Journals

  1. Yang Q, Al Mamun A, Hayat N, Salleh M, Jingzu G, Zainol N, Lavorgna L. Modelling the mass adoption potential of wearable medical devices. PLOS ONE 2022;17(6):e0269256 View
  2. Hayat N, Zainol N, Salameh A, Al Mamun A, Yang Q, Md Salleh M. How health motivation moderates the effect of intention and usage of wearable medical devices? An empirical study in Malaysia. Frontiers in Public Health 2022;10 View
  3. Bube B, Zanón B, Lara Palma A, Klocke H. Wearable Devices in Diving: Scoping Review. JMIR mHealth and uHealth 2022;10(9):e35727 View
  4. Calegari L, Tortorella G, Fettermann D. Getting Connected to M-Health Technologies through a Meta-Analysis. International Journal of Environmental Research and Public Health 2023;20(5):4369 View
  5. Chen J, Li T, You H, Wang J, Peng X, Chen B. Behavioral Interpretation of Willingness to Use Wearable Health Devices in Community Residents: A Cross-Sectional Study. International Journal of Environmental Research and Public Health 2023;20(4):3247 View
  6. Hayat N, Salameh A, Malik H, Yaacob M. Exploring the adoption of wearable healthcare devices among the Pakistani adults with dual analysis techniques. Technology in Society 2022;70:102015 View
  7. Zhang Q, Khan S, Khan S, Khan I. Assessing the older population acceptance of healthcare wearable in a developing Country: an extended PMT model. Journal of Data, Information and Management 2023;5(1-2):39 View
  8. Zhang Z, Xia E, Huang J. Impact of the Moderating Effect of National Culture on Adoption Intention in Wearable Health Care Devices: Meta-analysis. JMIR mHealth and uHealth 2022;10(6):e30960 View
  9. Calegari L, R.D. B, Fettermann D. A meta-analysis of a comprehensive m-health technology acceptance. International Journal of Lean Six Sigma 2024;15(1):1 View
  10. Graeber J, Warmerdam E, Aufenberg S, Bull C, Davies K, Dixon J, Emmert K, Judd C, Maetzler C, Reilmann R, Ng W, Macrae V, Maetzler W, Kaduszkiewicz H. Technology acceptance of digital devices for home use: Qualitative results of a mixed methods study. DIGITAL HEALTH 2023;9 View
  11. Hayat N, Salameh A, Mamun A, Alam S, Zainol N. Exploring the mass adoption potential of wearable fitness devices in Malaysia. DIGITAL HEALTH 2023;9 View
  12. 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
  13. Hayat N, Al Mamun A, Gao J, Yang Q, Hussain W. Envisaging the intention and adoption of electronic health applications among middle-aged and older adults: Evidence from an emerging economy. DIGITAL HEALTH 2024;10 View
  14. Thomas M, Boursalie O, Samavi R, Doyle T. Data-driven approach to quantify trust in medical devices using Bayesian networks. Experimental Biology and Medicine 2023;248(24):2578 View
  15. Zhang M, Cai A, Jin K, Huang J, Li D, He M, Gao R. Scientific epistemology beliefs and acceptance of Traditional Chinese Medicine: A multigroup analysis based on the UTAUT model in Southern China. Heliyon 2024;10(12):e33136 View
  16. Song L, Li B, Wu H, Wu C, Zhang X, Yu Z. Understanding the factors of wearable devices among the patients with thyroid cancer: A modified UTAUT2 model. PLOS ONE 2024;19(7):e0305944 View
  17. Kruger S, Deacon E, van Rensburg E, Segal D. Adjustment experiences of adolescents living with well-controlled type 1 diabetes using closed-loop technology. Frontiers in Clinical Diabetes and Healthcare 2024;5 View

Books/Policy Documents

  1. Nguyen T, Tran K, Raza A, Nguyen Q, Bui H, Tran K. Artificial Intelligence for Smart Manufacturing. View