Published on in Vol 9, No 1 (2022): Jan-Mar

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/34918, first published .
Suitability of the Unified Theory of Acceptance and Use of Technology 2 Model for Predicting mHealth Acceptance Using Diabetes as an Example: Qualitative Methods Triangulation Study

Suitability of the Unified Theory of Acceptance and Use of Technology 2 Model for Predicting mHealth Acceptance Using Diabetes as an Example: Qualitative Methods Triangulation Study

Suitability of the Unified Theory of Acceptance and Use of Technology 2 Model for Predicting mHealth Acceptance Using Diabetes as an Example: Qualitative Methods Triangulation Study

Journals

  1. Schretzlmaier P, Hecker A, Ammenwerth E. Extension of the Unified Theory of Acceptance and Use of Technology 2 model for predicting mHealth acceptance using diabetes as an example: a cross-sectional validation study. BMJ Health & Care Informatics Online 2022;29(1):e100640 View
  2. Alhur M, Alshamari S, Oláh J, Aldreabi H. Unsupervised Machine Learning to Identify Positive and Negative Themes in Jordanian mHealth Apps. International Journal of E-Services and Mobile Applications 2022;14(1):1 View
  3. Thérouanne P, Hayotte M, Halgand F, d'Arripe-Longueville F. The Acceptability of Technology-Based Physical Activity Interventions in Postbariatric Surgery Women: Insights From Qualitative Analysis Using the Unified Theory of Acceptance and Use of Technology 2 Model. JMIR Human Factors 2023;10:e42178 View
  4. Edo O, Ang D, Etu E, Tenebe I, Edo S, Diekola O. Why do healthcare workers adopt digital health technologies - A cross-sectional study integrating the TAM and UTAUT model in a developing economy. International Journal of Information Management Data Insights 2023;3(2):100186 View
  5. Conway A, Ryan A, Harkin D, Mc Cauley C. “It’s Another Feather in My Hat”-Exploring Factors Influencing the Adoption of Apps With People Living With Dementia. Dementia 2023;22(7):1487 View
  6. Jibb L, Sivaratnam S, Hashemi E, Chu C, Nathan P, Chartrand J, Alberts N, Masama T, Pease H, Torres L, Cortes H, Zworth M, Kuczynski S, Fortier M, Ayatollahi H. Parent and clinician perceptions and recommendations on a pediatric cancer pain management app: A qualitative co-design study. PLOS Digital Health 2023;2(11):e0000169 View
  7. Zolfaqari Z, Ayatollahi H, Ranjbar F, Abasi A. Motivating and inhibiting factors influencing the application of mhealth technology in post-abortion care: a review study. BMC Pregnancy and Childbirth 2024;24(1) View