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

Theoretical Frameworks and Concepts (252) E-Health / Health Services Research and New Models of Care (517) Theories, Models, and Frameworks in Human Factors (72) Mobile Health (mhealth) (2939) Adoption and Change Management of eHealth Systems (712) Usability of Apps and User Perceptions of mHealth (974)

Published on in Vol 23, No 12 (2021): December

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/28086, first published .
The Mediating Influence of the Unified Theory of Acceptance and Use of Technology on the Relationship Between Internal Health Locus of Control and Mobile Health Adoption: Cross-sectional Study

The Mediating Influence of the Unified Theory of Acceptance and Use of Technology on the Relationship Between Internal Health Locus of Control and Mobile Health Adoption: Cross-sectional Study

The Mediating Influence of the Unified Theory of Acceptance and Use of Technology on the Relationship Between Internal Health Locus of Control and Mobile Health Adoption: Cross-sectional Study

Authors of this article:

Ashraf Sadat Ahadzadeh1 Author Orcid Image ;   Shin Ling Wu2 Author Orcid Image ;   Fon Sim Ong3 Author Orcid Image ;   Ruolan Deng4 Author Orcid Image
Article Authors Cited by (14) Tweetations (3) Metrics

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  2. Mensah I, Zeng G, Mwakapesa D. The behavioral intention to adopt mobile health services: The moderating impact of mobile self-efficacy. Frontiers in Public Health 2022;10 View
  3. Sadat Ahadzadeh A, Wu S, Lee K, Ong F, Deng R. My perfectionism drives me to be a cyborg: moderating role of internal locus of control on propensity towards memory implant. Behaviour & Information Technology 2024;43(5):862 View
  4. Isakadze N, Marvel F. What Are the Features Promoting and Deterring Engagement in Mobile Health Intervention Use. JACC: Advances 2023;2(8):100615 View
  5. Razaghizad A, McKee T, Malhamé I, Friedrich M, Giannetti N, Coristine A, Johnson A, Ashley E, Hershman S, Struck B, Krastev S, Pilat D, Sharma A. Mobile Health Fitness Interventions. JACC: Advances 2023;2(8):100613 View
  6. Shao H, Liu C, Tang L, Wang B, Xie H, Zhang Y. Factors Influencing the Behavioral Intentions and Use Behaviors of Telemedicine in Patients With Diabetes: Web-Based Survey Study. JMIR Human Factors 2023;10:e46624 View
  7. Omar N, Che Zainal C, Abdul Rashid M, Hassan N, Abd Malek S, Abu Bakar A. Framework analysis on the adoption of digital healthcare services among senior citizens by using the extended technology acceptance model (ETAM). F1000Research 2023;12:1551 View
  8. Nabelsi V, Lévesque-Chouinard A. Successful Electronic Consultation Service Initiative in Quebec, Canada With Primary Care Physicians’ and Specialists’ Experiences on Acceptance and Use of Technological Innovation: Cross-Sectional Exploratory Study. JMIR Formative Research 2024;8:e52921 View
  9. Trang T, Chien Thang P, Hai L, Phuong V, Quy T. Understanding the Adoption of Artificial Intelligence in Journalism: An Empirical Study in Vietnam. Sage Open 2024;14(2) View
  10. Kaur J, Saini S, Behl A, Poonia A. Impact of Digital Storytelling on Improving Brand Image Among Consumers. Journal of Promotion Management 2024;30(8):1348 View
  11. Mohd Nawi C, Hussein Z, Mohd Nawi C. Factors Influencing the Acceptance of AI in Mobile Health Apps in Malaysia. Information Management and Business Review 2024;16(3(I)):685 View
  12. He D, Yao J, Qi W, Cao S, Chen Y, Zhu X, Lou X, Chen X, Lin X, Feng Y, Fu X, Ning L, Wang S, Liu Y. Nurses' acceptance of nursing information systems: A multi‐center cross‐sectional study in China. Journal of Clinical Nursing 2024 View
  13. Mozafari S, Yang A, Talaei-Khoei J. Health Locus of Control and Medical Behavioral Interventions: Systematic Review and Recommendations. Interactive Journal of Medical Research 2024;13:e52287 View
  14. Yan T, Yu H, Tang J. The Influence of Multiple Factors on Musicology Doctoral Students’ Academic Performance: An Empirical Study Based in China. Behavioral Sciences 2024;14(11):1073 View