Published on in Vol 24, No 1 (2022): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/31920, first published .
Design of an Integrated Acceptance Framework for Older Users and eHealth: Influential Factor Analysis

Design of an Integrated Acceptance Framework for Older Users and eHealth: Influential Factor Analysis

Design of an Integrated Acceptance Framework for Older Users and eHealth: Influential Factor Analysis

Journals

  1. 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
  2. Östlund B, Malvezzi M, Frennert S, Funk M, Gonzalez-Vargas J, Baur K, Alimisis D, Thorsteinsson F, Alonso-Cepeda A, Fau G, Haufe F, Di Pardo M, Moreno J. Interactive robots for health in Europe: Technology readiness and adoption potential. Frontiers in Public Health 2023;11 View
  3. Yuen K, Chua J, Li X, Wang X. The determinants of users’ intention to adopt telehealth: Health belief, perceived value and self-determination perspectives. Journal of Retailing and Consumer Services 2023;73:103346 View
  4. Lu C, Tsai-Lin T. Are Older Adults Special in Adopting Public eHealth Service Initiatives? The Modified Model of UTAUT. SAGE Open 2024;14(1) View
  5. Cao X, Zhang H, Zhou B, Wang D, Cui C, Bai X. Factors influencing older adults’ acceptance of voice assistants. Frontiers in Psychology 2024;15 View
  6. Al-Adwan A, Alsoud M, Li N, Majali T, Smedley J, Habibi A. Unlocking future learning: Exploring higher education students' intention to adopt meta-education. Heliyon 2024;10(9):e29544 View
  7. Felber N, Alavi H, Mugellini E, Wangmo T. The smart home, a true home? How new technologies disrupt the experience of home for older persons. Universal Access in the Information Society 2024 View