Published on in Vol 9, No 8 (2021): August

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/30214, first published .
Predicting Patients’ Intention to Use a Personal Health Record Using an Adapted Unified Theory of Acceptance and Use of Technology Model: Secondary Data Analysis

Predicting Patients’ Intention to Use a Personal Health Record Using an Adapted Unified Theory of Acceptance and Use of Technology Model: Secondary Data Analysis

Predicting Patients’ Intention to Use a Personal Health Record Using an Adapted Unified Theory of Acceptance and Use of Technology Model: Secondary Data Analysis

Journals

  1. Yousef C, Salgado T, Farooq A, Burnett K, McClelland L, Abu Esba L, Alhamdan H, Khoshhal S, Aldossary I, Alyas O, DeShazo J. Health Care Providers’ Acceptance of a Personal Health Record: Cross-sectional Study. Journal of Medical Internet Research 2021;23(10):e31582 View
  2. Fakhfakh M, Blanchette V, Plourde K, Gadio S, Elf M, Jones C, Meijering L, Giguère A, Légaré F. Canadian Older Adults’ Intention to Use an Electronic Decision Aid for Housing Decisions: Cross-sectional Web-Based Survey. JMIR Aging 2023;6:e43106 View
  3. Yousef C, Salgado T, Burnett K, McClelland L, Alhamdan H, Khoshhal S, Aldossary I, Alyas O, DeShazo J. Perceived barriers and enablers of a personal health record from the healthcare provider perspective. Health Informatics Journal 2023;29(1):146045822311521 View
  4. Alsyouf A, Lutfi A, Alsubahi N, Alhazmi F, Al-Mugheed K, Anshasi R, Alharbi N, Albugami M. The Use of a Technology Acceptance Model (TAM) to Predict Patients’ Usage of a Personal Health Record System: The Role of Security, Privacy, and Usability. International Journal of Environmental Research and Public Health 2023;20(2):1347 View
  5. Yousef C, Salgado T, Farooq A, Burnett K, McClelland L, Abu Esba L, Alhamdan H, Khoshhal S, Aldossary I, Alyas O, DeShazo J. Predicting Health Care Providers' Acceptance of a Personal Health Record Secure Messaging Feature. Applied Clinical Informatics 2022;13(01):148 View
  6. Wei S, Ge P, Zhang J, Xu S, Wang Y, Li Q, Feng B, Yu W, Suo B, Zhang Y, Wang M, Sun X, Song Z, Wu Y. Exploring factors that influence the behavioural intention of medical students to use 3D gastroscopic model to learn how to operate gastroscope using UTAUT Model. BMC Medical Education 2023;23(1) View
  7. Assiri G, Alabdulkarim D, Alanazi A, Altamimi S, Alanazi N, Khawagi W. Description of patient characteristics and medication adherence among medication access mobile application users and nonusers: a single-center questionnaire-based cross-sectional study. BMC Digital Health 2023;1(1) View
  8. Cobelli N, Blasioli E. To be or not to be digital? A bibliometric analysis of adoption of eHealth services. The TQM Journal 2023;35(9):299 View
  9. Wang M, Chen H, Gong C, Peng X, Zhong Y, Wu C, Luo Y, Wu Y. Understanding the use intention and influencing factors of telerehabilitation in people with rehabilitation needs: a cross-sectional survey. Frontiers in Public Health 2023;11 View
  10. Xiao J, Kopycka-Kedzierawski D, Ragusa P, Mendez Chagoya L, Funkhouser K, Lischka T, Wu T, Fiscella K, Kar K, Al Jallad N, Rashwan N, Ren J, Meyerowitz C. Acceptance and Usability of an Innovative mDentistry eHygiene Model Amid the COVID-19 Pandemic Within the US National Dental Practice-Based Research Network: Mixed Methods Study. JMIR Human Factors 2023;10:e45418 View