Published on in Vol 6, No 8 (2018): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/9316, first published .
What Predicts Patients’ Adoption Intention Toward mHealth Services in China: Empirical Study

What Predicts Patients’ Adoption Intention Toward mHealth Services in China: Empirical Study

What Predicts Patients’ Adoption Intention Toward mHealth Services in China: Empirical Study

Journals

  1. Zhang Y, Liu C, Luo S, Xie Y, Liu F, Li X, Zhou Z. Factors Influencing Patients’ Intentions to Use Diabetes Management Apps Based on an Extended Unified Theory of Acceptance and Use of Technology Model: Web-Based Survey. Journal of Medical Internet Research 2019;21(8):e15023 View
  2. Zhang Y, Liu C, Luo S, Huang J, Li X, Zhou Z. Effectiveness of Lilly Connected Care Program (LCCP) App-Based Diabetes Education for Patients With Type 2 Diabetes Treated With Insulin: Retrospective Real-World Study. JMIR mHealth and uHealth 2020;8(3):e17455 View
  3. Rossmann C, Riesmeyer C, Brew-Sam N, Karnowski V, Joeckel S, Chib A, Ling R. Appropriation of Mobile Health for Diabetes Self-Management: Lessons From Two Qualitative Studies. JMIR Diabetes 2019;4(1):e10271 View
  4. Mensah I, Chuanyong L, Zeng G. Factors Determining the Continued Intention to Use Mobile Money Transfer Services (MMTS) Among University Students in Ghana. International Journal of Mobile Human Computer Interaction 2020;12(1):1 View
  5. Meng F, Zhang X, Guo X, Lai K, Zhao X. How Do Patients with Chronic Diseases Make Usage Decisions regarding Mobile Health Monitoring Service?. Journal of Healthcare Engineering 2019;2019:1 View
  6. Liang D, Fan G. Social Support and User Characteristics in Online Diabetes Communities: An In-Depth Survey of a Large-Scale Chinese Population. International Journal of Environmental Research and Public Health 2020;17(8):2806 View
  7. Sittig S, Hauff C, Graves R, Williams S, McDermott R, Fruh S, Hall H, Campbell M, Swanzy D, Wright T, Hudson G. Characteristics of and Factors Influencing College Nursing Students' Willingness to Utilize mHealth for Health Promotion. CIN: Computers, Informatics, Nursing 2020;38(5):246 View
  8. Hu G, Han X, Zhou H, Liu Y. Public Perception on Healthcare Services: Evidence from Social Media Platforms in China. International Journal of Environmental Research and Public Health 2019;16(7):1273 View
  9. Apolinário-Hagen J, Hennemann S, Fritsche L, Drüge M, Breil B. Determinant Factors of Public Acceptance of Stress Management Apps: Survey Study. JMIR Mental Health 2019;6(11):e15373 View
  10. Meng F, Guo X, Peng Z, Zhang X, Vogel D. The routine use of mobile health services in the presence of health consciousness. Electronic Commerce Research and Applications 2019;35:100847 View
  11. Ramdani B, Duan B, Berrou I. Exploring the Determinants of Mobile Health Adoption by Hospitals in China: Empirical Study. JMIR Medical Informatics 2020;8(7):e14795 View
  12. Shan W, Wang Y, Luan J, Tang P. The Influence of Physician Information on Patients’ Choice of Physician in mHealth Services Using China’s Chunyu Doctor App: Eye-Tracking and Questionnaire Study. JMIR mHealth and uHealth 2019;7(10):e15544 View
  13. Park H, Kim K, Soh J, Hyun Y, Jang S, Lee S, Hwang G, Kim H. Factors Influencing Acceptance of Personal Health Record Apps for Workplace Health Promotion: Cross-Sectional Questionnaire Study. JMIR mHealth and uHealth 2020;8(6):e16723 View
  14. Akdur G, Aydin M, Akdur G. Adoption of Mobile Health Apps in Dietetic Practice: Case Study of Diyetkolik. JMIR mHealth and uHealth 2020;8(10):e16911 View
  15. Balapour A, Reychav I, Sabherwal R, Azuri J. Mobile technology identity and self-efficacy: Implications for the adoption of clinically supported mobile health apps. International Journal of Information Management 2019;49:58 View
  16. Galvin H, DeMuro P. Developments in Privacy and Data Ownership in Mobile Health Technologies, 2016-2019. Yearbook of Medical Informatics 2020;29(01):032 View
  17. Kamal S, Shafiq M, Kakria P. Investigating acceptance of telemedicine services through an extended technology acceptance model (TAM). Technology in Society 2020;60:101212 View
  18. Zhu P, Shen J, Xu M. Patients’ Willingness to Share Information in Online Patient Communities: Questionnaire Study. Journal of Medical Internet Research 2020;22(4):e16546 View
  19. Alsisi E, Al-Ashaab A, Abualfaraa W. The Development of a Smart Health Awareness Message Framework Based on the Use of Social Media: Quantitative Study. Journal of Medical Internet Research 2020;22(7):e16212 View
  20. Meng F, Guo X, Peng Z, Lai K, Zhao X. Investigating the Adoption of Mobile Health Services by Elderly Users: Trust Transfer Model and Survey Study. JMIR mHealth and uHealth 2019;7(1):e12269 View
  21. Saheb T. An empirical investigation of the adoption of mobile health applications: integrating big data and social media services. Health and Technology 2020;10(5):1063 View
  22. Mathai N, McGill T, Toohey D. Factors Influencing Consumer Adoption of Electronic Health Records. Journal of Computer Information Systems 2020:1 View
  23. Moon J, Rigg J, Smith J. Korean American Smokers’ Perspectives on Mobile Smoking Cessation Applications. Tobacco Use Insights 2020;13:1179173X2097238 View
  24. An M, You S, Park R, Lee S. Using an Extended Technology Acceptance Model to Understand the Factors Influencing Telehealth Utilization After Flattening the COVID-19 Curve in South Korea: Cross-sectional Survey Study. JMIR Medical Informatics 2021;9(1):e25435 View
  25. Binyamin S, Zafar B. Proposing a mobile apps acceptance model for users in the health area: A systematic literature review and meta-analysis. Health Informatics Journal 2021;27(1):146045822097673 View
  26. Al Aufa B, Renindra I, Putri J, Nurmansyah M. An application of the Unified Theory of Acceptance and Use of Technology (UTAUT) model for understanding patient perceptions on using hospital mobile application. Enfermería Clínica 2020;30:110 View
  27. Aboelmaged M, Hashem G, Mouakket S. Predicting subjective well-being among mHealth users: a readiness – value model. International Journal of Information Management 2021;56:102247 View
  28. Li D, Hu Y, Pfaff H, Wang L, Deng L, Lu C, Xia S, Cheng S, Zhu X, Wu X. Determinants of Patients’ Intention to Use the Online Inquiry Services Provided by Internet Hospitals: Empirical Evidence From China. Journal of Medical Internet Research 2020;22(10):e22716 View
  29. Binyamin S, Hoque M. Understanding the Drivers of Wearable Health Monitoring Technology: An Extension of the Unified Theory of Acceptance and Use of Technology. Sustainability 2020;12(22):9605 View
  30. Dang Y, Guo S, Guo X, Wang M, Xie K. Privacy Concerns About Health Information Disclosure in Mobile Health: Questionnaire Study Investigating the Moderation Effect of Social Support. JMIR mHealth and uHealth 2021;9(2):e19594 View
  31. Mekonnen Z, Gelaye K, Were M, Tilahun B. Mothers intention and preference to use mobile phone text message reminders for child vaccination in Northwest Ethiopia. BMJ Health & Care Informatics 2021;28(1):e100193 View
  32. Khan T, Khan K, Azhar M, Shah S, Uddin M, Khan T. Mobile health services and the elderly: Assessing the determinants of technology adoption readiness in Pakistan. Journal of Public Affairs 2021 View
  33. Salvi D, Poffley E, Tarassenko L, Orchard E. App-Based Versus Standard Six-Minute Walk Test in Pulmonary Hypertension: Mixed Methods Study. JMIR mHealth and uHealth 2021;9(6):e22748 View
  34. Yang M, Jiang J, Kiang M, Yuan F. Re-Examining the Impact of Multidimensional Trust on Patients’ Online Medical Consultation Service Continuance Decision. Information Systems Frontiers 2021 View
  35. Octavius G, Antonio F, Colloc J. Antecedents of Intention to Adopt Mobile Health (mHealth) Application and Its Impact on Intention to Recommend: An Evidence from Indonesian Customers. International Journal of Telemedicine and Applications 2021;2021:1 View
  36. Handayani P, Indriani R, Pinem A. Mobile health readiness factors: From the perspectives of mobile health users in Indonesia. Informatics in Medicine Unlocked 2021;24:100590 View
  37. Li P, Xu L, Tang T, Wu X, Huang C. Willingness to Adopt Health Information Among Social Question-and-Answer Community Users in China: Cross-sectional Survey Study. Journal of Medical Internet Research 2021;23(5):e27811 View
  38. Jusob F, George C, Mapp G. A new privacy framework for the management of chronic diseases via mHealth in a post-Covid-19 world. Journal of Public Health 2021 View
  39. Chow J, Elizabeth Pathak L, Yeh S. Using mobile apps in social work behavioral health care service: The case for China. International Social Work 2021:002087282110319 View
  40. Lee M, Kang D, Kim S, Lim J, Yoon J, Kim Y, Shim S, Kang E, Ahn J, Cho J, Shin S, Oh D. Who is more likely to adopt and comply with the electronic patient-reported outcome measure (ePROM) mobile application? A real-world study with cancer patients undergoing active treatment. Supportive Care in Cancer 2021 View

Books/Policy Documents

  1. Schomakers E, Vervier L, Ziefle M. Human Aspects of IT for the Aged Population. Healthy and Active Aging. View
  2. Sampat B, Sharma A, Prabhakar B. Re-imagining Diffusion and Adoption of Information Technology and Systems: A Continuing Conversation. View