Published on in Vol 8, No 6 (2020): June

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/16723, first published .
Factors Influencing Acceptance of Personal Health Record Apps for Workplace Health Promotion: Cross-Sectional Questionnaire Study

Factors Influencing Acceptance of Personal Health Record Apps for Workplace Health Promotion: Cross-Sectional Questionnaire Study

Factors Influencing Acceptance of Personal Health Record Apps for Workplace Health Promotion: Cross-Sectional Questionnaire Study

Journals

  1. Park H, Kim K, Soh J, Hyun Y, Lee B, Lee J, Jo J, Lee H, Kim H. Development and Operation of a Video Teleconsultation System Using Integrated Medical Equipment Gateway: a National Project for Workers in Underserved Areas. Journal of Medical Systems 2020;44(11) View
  2. Yousef C, Salgado T, Farooq A, Burnett K, McClelland L, Abu Esba L, Alhamdan H, Khoshhal S, Aldossary I, Alyas O, DeShazo J. Health Care Providers’ Acceptance of a Personal Health Record: Cross-sectional Study. Journal of Medical Internet Research 2021;23(10):e31582 View
  3. Xu L, Li P, Hou X, Yu H, Tang T, Liu T, Xiang S, Wu X, Huang C. Middle-aged and elderly users’ continuous usage intention of health maintenance-oriented WeChat official accounts: empirical study based on a hybrid model in China. BMC Medical Informatics and Decision Making 2021;21(1) View
  4. Li C, Li Y. Factors Influencing Public Risk Perception of Emerging Technologies: A Meta-Analysis. Sustainability 2023;15(5):3939 View
  5. Paganin G, Simbula S. New Technologies in the Workplace: Can Personal and Organizational Variables Affect the Employees’ Intention to Use a Work-Stress Management App?. International Journal of Environmental Research and Public Health 2021;18(17):9366 View
  6. Chin W, Kurowski A, Gore R, Chen G, Punnett L. Use of a Mobile App for the Process Evaluation of an Intervention in Health Care: Development and Usability Study. JMIR Formative Research 2021;5(10):e20739 View
  7. Alzahrani A, Al-Samarraie H, Eldenfria A, Dodoo J, Zhou X, Alalwan N. COVID-19 and people's continued trust in eHealth systems: a new perspective. Behaviour & Information Technology 2023;42(9):1294 View
  8. Park H, Jeong S, Chung H, Soh J, Hyun Y, Bang S, Kim H. Use of video-based telehealth services using a mobile app for workers in underserved areas during the COVID-19 pandemic: A prospective observational study. International Journal of Medical Informatics 2022;166:104844 View
  9. Junker M, Böhm M, Franz M, Fritsch T, Krcmar H. Value of normative belief in intention to use workplace health promotion apps. BMC Medical Informatics and Decision Making 2022;22(1) View
  10. Choi W, Chang S, Yang Y, Jung S, Lee S, Chun J, Kim D, Lee W, Choi I. Study of the factors influencing the use of MyData platform based on personal health record data sharing system. BMC Medical Informatics and Decision Making 2022;22(1) View
  11. Yousef C, Salgado T, Farooq A, Burnett K, McClelland L, Abu Esba L, Alhamdan H, Khoshhal S, Aldossary I, Alyas O, DeShazo J. Predicting Health Care Providers' Acceptance of a Personal Health Record Secure Messaging Feature. Applied Clinical Informatics 2022;13(01):148 View
  12. Koo J, Park Y, Kang D. Factors Predicting Older People’s Acceptance of a Personalized Health Care Service App and the Effect of Chronic Disease: Cross-Sectional Questionnaire Study. JMIR Aging 2023;6:e41429 View
  13. Hosseini A, Emami H, Sadat Y, Paydar S. Integrated personal health record (PHR) security: requirements and mechanisms. BMC Medical Informatics and Decision Making 2023;23(1) View
  14. Wei X, Cao Y, Peng X, Prybutok V. A meta-analysis of technology acceptance in healthcare from the consumer’s perspective. Health Marketing Quarterly 2024;41(2):192 View
  15. Kokila , Jain R, Munde A, Ansari Z. Determinants of Adoption of Mobile Health Applications: A Machine Learning Approach. Procedia Computer Science 2024;235:1568 View