Accessibility settings

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

eHealth Literacy / Digital Literacy (572) Demographics of Users, Social & Digital Divide (971) Personal Health Records, Patient-Accessible Electronic Health Records, Patient Portals (716) Adoption and Change Management of eHealth Systems (954) Theoretical Frameworks and Concepts (374) Electronic Health Records (1378)

Published on in Vol 27 (2025)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/79595, first published .
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

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 (4) Tweetations (1) 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 2026:1 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