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

Use and User Demographics of mHealth (335) Adoption and Change Management of eHealth Systems (712)

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

Authors of this article:

Zhaohua Deng1 Author Orcid Image ;   Ziying Hong1 Author Orcid Image ;   Cong Ren2 Author Orcid Image ;   Wei Zhang1 Author Orcid Image ;   Fei Xiang1 Author Orcid Image
Article Authors Cited by (139) Tweetations (4) Metrics

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 2022;62(2):267 View
  23. Moon J, Rigg J, Smith J. Korean American Smokers’ Perspectives on Mobile Smoking Cessation Applications. Tobacco Use Insights 2020;13 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) 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 2022;22(4) 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 2022;24(3):983 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 2022;30(1):37 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;64(5):689 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 2022;30(1):659 View
  41. Kovács B, Szakály Z. Market orientation and corporate performance in the health industry. Management & Marketing. Challenges for the Knowledge Society 2022;17(1):41 View
  42. Dahlhausen F, Zinner M, Bieske L, Ehlers J, Boehme P, Fehring L. Physicians’ Attitudes Toward Prescribable mHealth Apps and Implications for Adoption in Germany: Mixed Methods Study. JMIR mHealth and uHealth 2021;9(11):e33012 View
  43. Palos-Sanchez P, Saura J, Rios Martin M, Aguayo-Camacho M. Toward a Better Understanding of the Intention to Use mHealth Apps: Exploratory Study. JMIR mHealth and uHealth 2021;9(9):e27021 View
  44. Gao Y, Gong L, Liu H, Kong Y, Wu X, Guo Y, Hu D. Research on the influencing factors of users’ information processing in online health communities based on heuristic-systematic model. Frontiers in Psychology 2022;13 View
  45. Liu Y, Lu X, Zhao G, Li C, Shi J. Adoption of mobile health services using the unified theory of acceptance and use of technology model: Self-efficacy and privacy concerns. Frontiers in Psychology 2022;13 View
  46. 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
  47. Li Y, Zhang X, Guo X, Wang L. Underlying Emotional Mechanisms of Routine m-Health Use in Chronically Ill Patients. IEEE Transactions on Engineering Management 2022;69(6):2658 View
  48. Chew E, Teo S, Tang W, Ng D, Koh G, Teo V. Trust and Uncertainty in the Implementation of a Pilot Remote Blood Pressure Monitoring Program in Primary Care: Qualitative Study of Patient and Health Care Professional Views. JMIR Human Factors 2023;10:e36072 View
  49. Pais S, Petrova K, Parry D. Enhancing System Acceptance through User-Centred Design: Integrating Patient Generated Wellness Data. Sensors 2021;22(1):45 View
  50. Klaver N, van de Klundert J, van den Broek R, Askari M. Relationship Between Perceived Risks of Using mHealth Applications and the Intention to Use Them Among Older Adults in the Netherlands: Cross-sectional Study. JMIR mHealth and uHealth 2021;9(8):e26845 View
  51. Alves Bernardes R, Parreira P, Sousa L, Cruz A. Complexity and intention to use an innovative device for post-infarction patients: rehabilitation nurses' perspectives. Central European Journal of Nursing and Midwifery 2022;13(1):595 View
  52. Kang H, Han J, Kwon G. The Acceptance Behavior of Smart Home Health Care Services in South Korea: An Integrated Model of UTAUT and TTF. International Journal of Environmental Research and Public Health 2022;19(20):13279 View
  53. Li C, Li Y. Factors Influencing Public Risk Perception of Emerging Technologies: A Meta-Analysis. Sustainability 2023;15(5):3939 View
  54. Bogale B, Habte A, Haile D, Guteta M, Mohammed N, Gebremichael M. Willingness to Receive mHealth Messages Among Diabetic Patients at Mizan Tepi University Teaching Hospital: Implications for Digital Health. Patient Preference and Adherence 2022;Volume 16:1499 View
  55. Cao J, Kurata K, Lim Y, Sengoku S, Kodama K. Social Acceptance of Mobile Health among Young Adults in Japan: An Extension of the UTAUT Model. International Journal of Environmental Research and Public Health 2022;19(22):15156 View
  56. Zhang J, Luximon Y, Li Q. Seeking medical advice in mobile applications: How social cue design and privacy concerns influence trust and behavioral intention in impersonal patient–physician interactions. Computers in Human Behavior 2022;130:107178 View
  57. Bian D, Xiao Y, Song K, Dong M, Li L, Millar R, Shi C, Li G. Determinants Influencing the Adoption of Internet Health Care Technology Among Chinese Health Care Professionals: Extension of the Value-Based Adoption Model With Burnout Theory. Journal of Medical Internet Research 2023;25:e37671 View
  58. Kaium M, Bao Y, Alam M, Hasan N, Hoque M. Understanding the insight of factors affecting mHealth adoption. International Journal of Research in Business and Social Science (2147- 4478) 2019;8(6):181 View
  59. Kaur A, Ahuja P, Jain J, Singh S, Garg A. Is Youth Ready for the Looming Technology Frontier in Healthcare? Examining Intentions and Adoption of Mobile Health (mHealth). Business Perspectives and Research 2023;11(1):63 View
  60. Guazzini A, Fiorenza M, Panerai G, Duradoni M. What Went Wrong? Predictors of Contact Tracing Adoption in Italy during COVID-19 Pandemic. Future Internet 2021;13(11):286 View
  61. Mensah I. Understanding the Drivers of Ghanaian Citizens' Adoption Intentions of Mobile Health Services. Frontiers in Public Health 2022;10 View
  62. Yao J, Pang Q, Zhang B, Wang L, Huang Y. Public Health and Online MICE Technology During the COVID-19 Pandemic: The Role of Health Beliefs and Technology Innovation. Frontiers in Public Health 2021;9 View
  63. Pan J, Dong H, Bryan-Kinns N. Perception and Initial Adoption of Mobile Health Services of Older Adults in London: Mixed Methods Investigation. JMIR Aging 2021;4(4):e30420 View
  64. Hu X, Fang H, Wang P. Factors affecting doctor’s recommendation for mobile health services. DIGITAL HEALTH 2022;8:205520762211259 View
  65. Zahed K, Smith A, McDonald A, Sasangohar F. The Effects of Drowsiness Detection Technology and Education on Nurses’ Beliefs and Attitudes toward Drowsy Driving. IISE Transactions on Occupational Ergonomics and Human Factors 2022;10(2):104 View
  66. Gamor N, Dzansi G, Konlan K, Abdulai E. Exploring social media adoption by nurses for nursing practice in rural Volta, Ghana. Nursing Open 2023;10(7):4432 View
  67. Wang H, Zhang J, Luximon Y, Qin M, Geng P, Tao D. The Determinants of User Acceptance of Mobile Medical Platforms: An Investigation Integrating the TPB, TAM, and Patient-Centered Factors. International Journal of Environmental Research and Public Health 2022;19(17):10758 View
  68. Pannard M, Leroy T, Escriva-Boulley G, Bernetière C, Desfriches O, Paquienséguy F, Préau M. Rôle des émotions et représentations dans le recours à la m-health chez les membres d’une communauté d’intérêt en ligne en lien avec le cancer, les Seintinelles. Bulletin du Cancer 2022;109(10):1040 View
  69. Bahanan L, Alsharif M. Factors affecting the acceptance of teledentistry determined using the technology acceptance model: A cross-sectional study. DIGITAL HEALTH 2023;9 View
  70. Talukder M, Aroos-Sheriffdeen S, Khan M, Quazi A, Abdullah A. Usage behavior of mHealth service users in Australia: do user demographics matter?. Journal of Services Marketing 2023;37(7):801 View
  71. 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
  72. Said G. Factors Affecting mHealth Technology Adoption in Developing Countries: The Case of Egypt. Computers 2022;12(1):9 View
  73. Meng F, Guo X, Peng Z, Zhang X, Lai K. Understanding the Antecedents of the Routine Use of Mobile Health Services: A Person–Technology–Health Framework. Frontiers in Psychology 2022;13 View
  74. Ge F, Qian H, Lei J, Ni Y, Li Q, Wang S, Ding K. Experiences and Challenges of Emerging Online Health Services Combating COVID-19 in China: Retrospective, Cross-Sectional Study of Internet Hospitals. JMIR Medical Informatics 2022;10(6):e37042 View
  75. Mensah I, Zeng G, Mwakapesa D. Understanding the drivers of the public value of e-government: Validation of a public value e-government adoption model. Frontiers in Psychology 2022;13 View
  76. 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
  77. Wang Y, Li S, Gong J, Cao L, Xu D, Yu Q, Wang X, Chen Y. Perceived Stigma and Self-Efficacy of Patients With Inflammatory Bowel Disease-Related Stoma in China: A Cross-Sectional Study. Frontiers in Medicine 2022;9 View
  78. Paschalie L, Santoso A. Cryptocurrencies as Investment Instrument: A Social Commerce and Subscription-Based Service Perspective. Journal of Business and Economic Analysis 2020;03(02):106 View
  79. Breil B, Salewski C, Apolinário-Hagen J. Comparing the Acceptance of Mobile Hypertension Apps for Disease Management Among Patients Versus Clinical Use Among Physicians: Cross-sectional Survey. JMIR Cardio 2022;6(1):e31617 View
  80. LeRouge C, Durneva P, Lyon V, Thompson M. Health Consumer Engagement, Enablement, and Empowerment in Smartphone-Enabled Home-Based Diagnostic Testing for Viral Infections: Mixed Methods Study. JMIR mHealth and uHealth 2022;10(6):e34685 View
  81. Wu S, Ma E, Wang J, Li D. Experience with Travel Mobile Apps and Travel Intentions—The Case of University Students in China. Sustainability 2022;14(19):12603 View
  82. Chen P, Shen Y, Li Z, Sun X, Feng X, Fisher E. What Factors Predict the Adoption of Type 2 Diabetes Patients to Wearable Activity Trackers—Application of Diffusion of Innovation Theory. Frontiers in Public Health 2022;9 View
  83. Alsyouf A, Lutfi A, Al-Bsheish M, Jarrar M, Al-Mugheed K, Almaiah M, Alhazmi F, Masa’deh R, Anshasi R, Ashour A. Exposure Detection Applications Acceptance: The Case of COVID-19. International Journal of Environmental Research and Public Health 2022;19(12):7307 View
  84. Pan J, Dong H. mHealth Adoption Among Older Chinese Adults: A Conceptual Model With Design Suggestions. International Journal of Human–Computer Interaction 2023;39(5):1072 View
  85. Zahed K, Fields S, Sasangohar F. Investigating the Efficacy of Behavioral Models to Predict Use of Health Technology: A Scoping Review. Proceedings of the Human Factors and Ergonomics Society Annual Meeting 2022;66(1):2172 View
  86. Tran C, Nguyen T. Health vs. privacy? The risk-risk tradeoff in using COVID-19 contact-tracing apps. Technology in Society 2021;67:101755 View
  87. 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
  88. Alsyouf A, Masa’deh R, Albugami M, Al-Bsheish M, Lutfi A, Alsubahi N. Risk of Fear and Anxiety in Utilising Health App Surveillance Due to COVID-19: Gender Differences Analysis. Risks 2021;9(10):179 View
  89. Dash A, Sahoo A. Physician’s perception of E-consultation adoption amid of COVID-19 pandemic. VINE Journal of Information and Knowledge Management Systems 2023;53(6):1271 View
  90. Dash A, Sahoo A. Moderating effect of gender on adoption of digital health consultation: a patient perspective study. International Journal of Pharmaceutical and Healthcare Marketing 2021;15(4):598 View
  91. Alkhalifah T. A Structural Equation Modelling of Governing Factors Influencing Patient Acceptance of Mobile Health in Saudi Arabia. International Journal of E-Services and Mobile Applications 2022;14(1):1 View
  92. Cui W, Zhu W, Li X, Wu D, He P, Yu G. Attitudes and perspectives of 534 Chinese pediatricians toward internet hospitals. Frontiers in Pediatrics 2022;10 View
  93. Al-Dhaen F, Hou J, Rana N, Weerakkody V. Advancing the Understanding of the Role of Responsible AI in the Continued Use of IoMT in Healthcare. Information Systems Frontiers 2023;25(6):2159 View
  94. Schomakers E, Lidynia C, Vervier L, Calero Valdez A, Ziefle M. Applying an Extended UTAUT2 Model to Explain User Acceptance of Lifestyle and Therapy Mobile Health Apps: Survey Study. JMIR mHealth and uHealth 2022;10(1):e27095 View
  95. Paschalie L, Santoso A. Cryptocurrencies as Investment Instrument: A Social Commerce and Subscription-Based Service Perspective. Journal of Business and Economic Analysis 2020;03(02):106 View
  96. El Said G. Antecedents of Trust in Mobile-Health Applications: A Human-Computer Interaction Perspective for the Egyptian Users. SSRN Electronic Journal 2022 View
  97. Bakker C, Wyatt T, Breth M, Gao G, Janeway L, Lee M, Martin C, Tiase V. Nurses’ Roles in mHealth App Development: Scoping Review. JMIR Nursing 2023;6:e46058 View
  98. Xu F, Zhang Z, Liu D. Factors Influencing Behavioral Intention for Mobile Applications of Health Care Escort Service. Journal of Multimedia Information System 2023;10(2):179 View
  99. Stehr P, Ermel L, Rossmann C, Reifegerste D, Lindemann A, Schulze A. A Mobile Health Information Behavior Model: Theoretical Development and Mixed-Method Testing in the Context of Mobile Apps on Child Poisoning Prevention. Journal of Health Communication 2023;28(10):648 View
  100. Kuen L, Schürmann F, Westmattelmann D, Hartwig S, Tzafrir S, Schewe G. Trust transfer effects and associated risks in telemedicine adoption. Electronic Markets 2023;33(1) View
  101. Demirci H, Yardan E. Data management in the digital health environment scale development study*. BMC Health Services Research 2023;23(1) View
  102. Yang Toh S, Lee S, Kosasih F, Lim J, Sündermann O. Preliminary effectiveness of an evidence-based mobile application to promote resilience among working adults in Singapore and Hong Kong: Intensive longitudinal study. DIGITAL HEALTH 2023;9 View
  103. Tandon U, Ertz M, Shashi . Continued Intention of mHealth Care Applications among the Elderly: An Enabler and Inhibitor Perspective. International Journal of Human–Computer Interaction 2024;40(18):5026 View
  104. 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
  105. Chudhery M, Safdar S, Huo J, Rehman H, Rafique R. Proposing and Empirically Investigating a Mobile-Based Outpatient Healthcare Service Delivery Framework Using Stimulus–Organism–Response Theory. IEEE Transactions on Engineering Management 2023;70(8):2668 View
  106. Luo Z, Tan X, He M, Wu X. The seewo interactive whiteboard (IWB) for ESL teaching: How useful it is?. Heliyon 2023;9(10):e20424 View
  107. Schroeder T, Haug M, Georgiou A, Seaman K, Gewald H. Evidence of How Physicians and Their Patients Adopt mHealth Apps in Germany: Exploratory Qualitative Study. JMIR mHealth and uHealth 2024;12:e48345 View
  108. Atinafu W, Tilahun K, Yilma T, Mekonnen Z, Walle A, Adem J. Intention to use a mobile phone to receive mental health support and its predicting factors among women attending antenatal care at public health facilities in Ambo town, West Shoa zone, Ethiopia 2022. BMC Health Services Research 2023;23(1) View
  109. Walle A, Ferede T, Shibabaw A, Wubante S, Guadie H, Yehula C, Demsash A. Willingness of diabetes mellitus patients to use mHealth applications and its associated factors for self-care management in a low-income country: an input for digital health implementation. BMJ Health & Care Informatics 2023;30(1):e100761 View
  110. Wang Q, Ma Y, Mao J, Song J, Xiao M, Zhao Q, Yuan F, Hu L. Driving the implementation of hospital examination reservation system through hospital management. BMC Health Services Research 2024;24(1) View
  111. Haverinen J, Harju T, Mikkonen H, Liljamo P, Turpeinen M, Reponen J. Digital Care Pathway for Patients With Sleep Apnea in Specialized Care: Mixed Methods Study. JMIR Human Factors 2024;11:e47809 View
  112. Luo Z. Factors contributing to teachers’ acceptance intention to gamified EFL tools: a scale development study. Educational technology research and development 2024;72(2):447 View
  113. Yang H, Cho Y, Han S. Understanding user perceptions toward marketing in the metaverse. Kybernetes 2024 View
  114. Chen H, Li H, Li L, Zhang X, Gu J, Wang Q, Wu C, Wu Y. Factors Associated with Intention to Use Telerehabilitation for Children with Special Needs: A Cross-Sectional Study. Telemedicine and e-Health 2024;30(5):1425 View
  115. Mittiga S, Freeman N, Furlonger B, Chan P, Leif E. A Content and Quality Evaluation of Mobile Classroom Behavior Management Applications. Journal of Positive Behavior Interventions 2024 View
  116. Tu J, Jia X. A Study on Immersion and Intention to Pay in AR Broadcasting: Validating and Expanding the Hedonic Motivation System Adoption Mode. Sustainability 2024;16(5):2040 View
  117. Mohammed A, Rozsa Z. Consumers’ intentions to utilize smartphone diet applications: an integration of the privacy calculus model with self-efficacy, trust and experience. British Food Journal 2024;126(6):2416 View
  118. Zou X, Na Y, Lai K, Liu G. Unpacking public resistance to health Chatbots: a parallel mediation analysis. Frontiers in Psychology 2024;15 View
  119. Jafrin N, Akhter H, Saif A, Said F, Ghosh D. Investigating the antecedents of mHealth adoption by older adults in a lower-middle income country: The PLS-MGA approach. Educational Gerontology 2024;50(9):845 View
  120. Luo Z, Li H. The Involvement of Academic and Emotional Support for Sustainable Use of MOOCs. Behavioral Sciences 2024;14(6):461 View
  121. Kanungo R, Liu R, Gupta S. Cognitive analytics enabled responsible artificial intelligence for business model innovation: A multilayer perceptron neural networks estimation. Journal of Business Research 2024;182:114788 View
  122. Goel A, Singh A, Taneja U, Jain S. Consumer adoption of digital health services: A systematic literature review and research agenda. International Journal of Consumer Studies 2024;48(4) View
  123. Harun Z, Muhammad N, Hussein Z, Fikri A, Abdul A. Factors influencing patients’ intention to use the Health Clinic Online Appointment System app. Information Management and Business Review 2024;16(2(I)):53 View
  124. Abdissa H, Duguma G, Ababulgu F, Lemu Y, Gerbaba M, Noll J, Sori D, Koricha Z. Pregnant mother’s intention to use mobile phone-based messaging interventions for improving maternal and newborn health practices in Jimma Zone, Ethiopia. BMC Digital Health 2024;2(1) View
  125. Luo Z, Cao L. Understanding factors influencing ESL student teachers’ adoption of classroom response systems: an integration of TAM and AOI theory. Interactive Learning Environments 2024:1 View
  126. Wang N, Zhou S, Liu Z, Han Y. Perceptions and Satisfaction With the Use of Digital Medical Services in Urban Older Adults of China: Mixed Methods Study. Journal of Medical Internet Research 2024;26:e48654 View
  127. Feng H, Niwa M, Cao J, Kurata K, Zhang S, Lim Y, Kim T, Guo X, Kageyama I, Kodama K. Promoting the social implementation of digital and mobile health: effects of regulation on user and non-user behavior in East Asia. Drug Discovery Today 2024;29(10):104136 View
  128. Yan C, Cao R, Hu X, Hu Y, Liu H. A longitudinal study of a mHealth app and regional policies on the uptake of postpartum depression referral after positive screening in Shenzhen. BMC Pregnancy and Childbirth 2024;24(1) View
  129. Alsahli S, Hor S. The adoption of mobile health applications by physicians during the COVID-19 pandemic in developing countries: The case of Saudi Arabia. International Journal of Information Management Data Insights 2024;4(2):100289 View
  130. Shin D, Jo H. Adoption and Continuance in the Metaverse. Electronics 2024;13(19):3917 View
  131. Wang H, Hu Y, Li J, Liu S, Feng X. What Determines Healthcare Workers to Seek Professional Psychological Support? A Cross‐Sectional Study. Journal of Advanced Nursing 2024 View
  132. Krishnan G, J.N.V. R. Exploring diabetic patients’ intention to switch POCT self-monitoring glucose devices: investigating influence of perceived usefulness and perceived ease of use. International Journal of Pharmaceutical and Healthcare Marketing 2024 View
  133. Wang L, Zhang Y, Li Z, Pang X, Zhang Y, Zou M. Analysis of willingness to use health management APP for female college students: application of UTAUT model based on Fogg theory. Frontiers in Psychology 2024;15 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
  3. Mouloudj K, Bouarar A, Asanza D, Saadaoui L, Mouloudj S, Njoku A, Evans M, Bouarar A. Integrating Digital Health Strategies for Effective Administration. View
  4. Haverinen J, Suominen J, Kaksonen R, Veikkolainen P, Voutilainen M, Reponen J, Röning J, Falkenbach P. Digital Health and Wireless Solutions. View