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

Focus Groups and Qualitative Research for Human Factors Research (1220) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1732) Mobile Health (mhealth) (3464) Diabetes (259) Diabetes Self-Management (588) Usability of Apps and User Perceptions of mHealth (1188) Adoption and Change Management of eHealth Systems (894) mHealth for Wellness, Behavior Change and Prevention (3315) Theories, Models, and Frameworks in Human Factors (93)

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

Authors of this article:

Patrik Schretzlmaier1 Author Orcid Image ;   Achim Hecker2, 3 Author Orcid Image ;   Elske Ammenwerth1 Author Orcid Image
Article Authors Cited by (23) Tweetations (2) Metrics

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 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
  8. Huang W, Ong W, Wong M, Ng E, Koh T, Chandramouli C, Ng C, Hummel Y, Huang F, Lam C, Tromp J. Applying the UTAUT2 framework to patients’ attitudes toward healthcare task shifting with artificial intelligence. BMC Health Services Research 2024;24(1) View
  9. Mosleh S, Alsaadi F, Alnaqbi F, Alkhzaimi M, Alnaqbi S, Alsereidi W. Examining the association between emotional intelligence and chatbot utilization in education: A cross-sectional examination of undergraduate students in the UAE. Heliyon 2024;10(11):e31952 View
  10. Roy P. What drives the adoption of data analytics at Australian university libraries in the perspective of UTAUT2?. The Journal of Academic Librarianship 2024;50(5):102927 View
  11. Alviani R, Purwandari B, Eitiveni I, Purwaningsih M. Factors Affecting Adoption of Telemedicine for Virtual Healthcare Services in Indonesia. Journal of Information Systems Engineering and Business Intelligence 2023;9(1):47 View
  12. Kruger S, Deacon E, van Rensburg E, Segal D. Adjustment experiences of adolescents living with well-controlled type 1 diabetes using closed-loop technology. Frontiers in Clinical Diabetes and Healthcare 2024;5 View
  13. Šafran V, Smrke U, Ilijevec B, Horvat S, Flis V, Plohl N, Mlakar I. Feasibility of a computerized clinical decision support system delivered via a socially assistive robot during grand rounds: A pilot study. DIGITAL HEALTH 2025;11 View
  14. Eriksson P, Gabrielsson-Järhult F, Thorold Nylin H, Nilsson E. Patients’ Experiences With Using a Digital Platform for Chat-Based Consultation in Primary Health Care in Sweden: Qualitative Study. Journal of Medical Internet Research 2025;27:e77478 View
  15. Zhang Y, Yang S, Wei W. Reflections of Fitness—Investigating User Acceptance of Smart Fitness Mirrors Based on UTAUT2. IEEE Access 2025;13:126167 View
  16. Mijić M, Ćebić B, Bogdanović V. Predictors of intention to use functional applications for mobile health in the Republic of Serbia using extended UTAUT2 model. Zdravstvena zastita 2025;54(2):36 View
  17. Mutunhu B, Chipangura B, Singh S. Towards a quantified-self technology conceptual framework for monitoring diabetes. Suid-Afrikaanse Tydskrif vir Natuurwetenskap en Tegnologie 2024;43(1):69 View
  18. Tian k, Chen J, Sun X. Investigating the actual usage behavior of Thai traditional craftsmen in adopting AI through a hybrid SEM–ANN approach. Humanities and Social Sciences Communications 2025;12(1) View
  19. Suepiantham S, Katira R. Patient Perspectives Towards Artificial Intelligence in Heart Failure Care. Cureus 2025 View

Books/Policy Documents

  1. Ndlovu B, Chipangura B, Singh S. Proceedings of Ninth International Congress on Information and Communication Technology. View
  2. Quirit R, Himang C. Exploring Technology-Infused Education in the Post-Pandemic Era. View
  3. Marlina E, Purwaningsih M, Siagian A, Al Hakim S, Maryati I. Qualitative Research Methods for Dissertation Research. View

Dissertations

  1. . Factors Influencing User Experience and Consumer Behavioral Intention to Use Visual Analytics Technology. View