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

eHealth Literacy / Digital Literacy (908) Personal Health Records, Patient-Accessible Electronic Health Records, Patient Portals (1036) Demographics of Users, Social & Digital Divide (1317) Adoption and Change Management of eHealth Systems (1147) Theoretical Frameworks and Concepts (576) Electronic Health Records (1773)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/79595, first published .
Young woman in a wheelchair working on a laptop at a desk

Using a Technology Acceptance Model to Explore the Intention to Use Digital Health Technologies Among People With Disabilities: Cross-Sectional Survey Study

Using a Technology Acceptance Model to Explore the Intention to Use Digital Health Technologies Among People With Disabilities: Cross-Sectional Survey Study

Authors of this article:

Jae-Hak Kim1 Author Orcid Image ;   Janghyeon Kim2, 3 Author Orcid Image ;   Bo-Young Youn3 Author Orcid Image
Article Authors Cited by (13) Tweetations Metrics

Journals

  1. Jin K, Zhong X, Jiang Q, Xu W, Zhou S, Shao Y. Adoption intentions and barriers to emerging technologies among people with disabilities: a systematic review of attitudes, accessibility, and inclusion. Disability and Rehabilitation: Assistive Technology 2026;21(4):1079 View
  2. Țuclea C, Poenaru L. Generation Z Employees’ Acceptance and AI Use Intensity: A Moderated Mediation Model of Psychological Safety, Technostress, and Trust. Merits 2026;6(1):7 View
  3. Mousa M, Rashed A, Akaileh M, Zamil A, Ahmed H, Abdelghani A. Artificial Intelligence Marketing Technologies and Consumer Purchasing Decisions: The Moderating Role of Virtual Customer Experience and Implications for Sustainable Consumption in Telecommunications Service Environments. Sustainability 2026;18(6):2674 View
  4. Chellappa V. Safety professionals’ acceptance of artificial intelligence in the construction industry: an extended technology acceptance model. Safety Science 2026;199:107194 View
  5. Park J, Lee H, Kwon Y, Cho G, Yun J. Factors Associated with the Intention to Adopt Digital Health Technologies for Physical Activity Among People with Disabilities: An Integrated Technology Acceptance Model–Theory of Planned Behavior Framework. Healthcare 2026;14(10):1344 View
  6. Ebner F, Schneider U, Schneider C, Trukeschitz B. User Acceptance of Remote Care Assist, a Telecare System for Home Care Among Care and Nursing Staff: Cross-Sectional Pilot Study. JMIR Rehabilitation and Assistive Technologies 2026;13:e80514 View
  7. Sun T, Chuang S. Determinants of Patients’ Intention to Use Remote Monitoring Service for Cardiac Implantable Electronic Devices: An Extended Technology Acceptance Model Study in Taiwan. Healthcare 2026;14(12):1802 View
  8. Chowdhury S, Ferdousi F, Jisun T. Determinants of Behavioral Intention to Use Digital Healthcare Services: A Cross‐Sectional PLS‐SEM Study on the Shukhee App in Bangladesh. Health Science Reports 2026;9(9) View
  9. Tanouri A, Bayat A, Stephenson M, Shafei A, Shabahang R. Immersive Technologies in Manufacturing Training and Education in Australia. Journal of Manufacturing and Materials Processing 2026;10(9):356 View
  10. Yuan X, Zhao X, Zhang M, Duan Y, Shui Y. Dynamics of Digital Support Platform Use Among Family Caregivers of Children With Disabilities: Longitudinal Study. JMIR mHealth and uHealth 2026;14:e92481 View
  11. Bagadood N. Cross-time associations among technology acceptance, disability-related attitudes, and social problem-solving in university students with learning disabilities. Scientific Reports 2026;16(1) View
  12. Chang W, Jung Y, Choi J, Kim W, Sohn M, Jee S, Shin Y, Ko S, Paik N. Usability and Satisfaction of a Multi-Domain ICT-Based Rehabilitation Management Program in Patients With Post-Acute Stroke: Multicenter Formative Evaluation (Preprint). JMIR Rehabilitation and Assistive Technologies 2026 View

Conference Proceedings

  1. Viriyaputta J, Kurniawan R. 2026 13th International Conference on ICT for Smart Society (ICISS). Factors Influencing Perceived Benefits of AI-Assisted Healthcare Systems in Indonesia View