Published on in Vol 7, No 9 (2019): September

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/13127, first published .
Using the Unified Theory of Acceptance and Use of Technology (UTAUT) to Investigate the Intention to Use Physical Activity Apps: Cross-Sectional Survey

Using the Unified Theory of Acceptance and Use of Technology (UTAUT) to Investigate the Intention to Use Physical Activity Apps: Cross-Sectional Survey

Using the Unified Theory of Acceptance and Use of Technology (UTAUT) to Investigate the Intention to Use Physical Activity Apps: Cross-Sectional Survey

Journals

  1. Alabdullah J, Van Lunen B, Claiborne D, Daniel S, Yen C, Gustin T. Application of the unified theory of acceptance and use of technology model to predict dental students’ behavioral intention to use teledentistry. Journal of Dental Education 2020;84(11):1262 View
  2. Park H, Kim K, Soh J, Hyun Y, Jang S, Lee S, Hwang G, Kim H. Factors Influencing Acceptance of Personal Health Record Apps for Workplace Health Promotion: Cross-Sectional Questionnaire Study. JMIR mHealth and uHealth 2020;8(6):e16723 View
  3. González Bravo L, Fernández Sagredo M, Torres Martínez P, Barrios Penna C, Fonseca Molina J, Stanciu I, Nistor N. Psychometric analysis of a measure of acceptance of new technologies (UTAUT), applied to the use of haptic virtual simulators in dental students. European Journal of Dental Education 2020;24(4):706 View
  4. Erlita U, Priyanto . Analysis of Acceptance of Vocational High School e-Report in Temanggung District Using the UTAUT Model (Unified Theory of Acceptance and Use of Technology). Journal of Physics: Conference Series 2021;1737(1):012023 View
  5. Vinnikova A, Lu L, Wei J, Fang G, Yan J. The Use of Smartphone Fitness Applications: The Role of Self-Efficacy and Self-Regulation. International Journal of Environmental Research and Public Health 2020;17(20):7639 View
  6. Azizi S, Roozbahani N, Khatony A. Factors affecting the acceptance of blended learning in medical education: application of UTAUT2 model. BMC Medical Education 2020;20(1) View
  7. Chayomchai A. The Online Technology Acceptance Model of Generation-Z People in Thailand during COVID-19 Crisis. Management & Marketing. Challenges for the Knowledge Society 2020;15(s1):496 View
  8. Ferreira Barbosa H, García-Fernández J, Pedragosa V, Cepeda-Carrion G. The use of fitness centre apps and its relation to customer satisfaction: a UTAUT2 perspective. International Journal of Sports Marketing and Sponsorship 2022;23(5):966 View
  9. Mitchell K, Holtz B, McCarroll A. Assessing College Students' Perceptions of and Intentions to Use a Mobile App for Mental Health. Telemedicine and e-Health 2022;28(4):566 View
  10. Yang Y, Koenigstorfer J. Determinants of Fitness App Usage and Moderating Impacts of Education-, Motivation-, and Gamification-Related App Features on Physical Activity Intentions: Cross-sectional Survey Study. Journal of Medical Internet Research 2021;23(7):e26063 View
  11. Olamijuwon E, Odimegwu C. Sexuality Education in the Digital Age: Modelling the Predictors of Acceptance and Behavioural Intention to Access and Interact with Sexuality Information on Social Media. Sexuality Research and Social Policy 2022;19(3):1241 View
  12. van der Waal N, de Wit J, Bol N, Ebbers W, Hooft L, Metting E, van der Laan L. Predictors of contact tracing app adoption: Integrating the UTAUT, HBM and contextual factors. Technology in Society 2022;71:102101 View
  13. Alwahaishi S. Student Use of E-Learning During the Coronavirus Pandemic. International Journal of Distance Education Technologies 2021;19(4):72 View
  14. Yang Y, Yu Z. Examining Users' Sustained Attention to Online Learning by Modifying a UTAUT Model of Rain Classroom. International Journal of Online Pedagogy and Course Design 2022;12(1):1 View
  15. Baer N, Vietzke J, Schenk L, Jutai J. Middle-aged and older adults’ acceptance of mobile nutrition and fitness apps: A systematic mixed studies review. PLOS ONE 2022;17(12):e0278879 View
  16. Fossouo Tagne J, Yakob R, Mcdonald R, Wickramasinghe N. Linking Activity Theory Within User-Centered Design: Novel Framework to Inform Design and Evaluation of Adverse Drug Reaction Reporting Systems in Pharmacy. JMIR Human Factors 2023;10:e43529 View
  17. Guo J, Chupradit S. Influencing Factors of College Students’ Use of Sports Apps in Mandatory Situations: Based on UTAUT and SDT. BioMed Research International 2022;2022:1 View
  18. Larnyo E, Dai B, Larnyo A, Nutakor J, Ampon-Wireko S, Nkrumah E, Appiah R. Impact of Actual Use Behavior of Healthcare Wearable Devices on Quality of Life: A Cross-Sectional Survey of People with Dementia and Their Caregivers in Ghana. Healthcare 2022;10(2):275 View
  19. Gulec H, Smahel D. Individual and Parental Factors of Adolescents’ mHealth App Use: Nationally Representative Cross-sectional Study. JMIR mHealth and uHealth 2022;10(12):e40340 View
  20. Stephen Addai-Dansoh , Dr. Ebenezer Larnyo1 , Francisca Arboh , Dr. Jonathan Aseye Nutakor , Jeremiah Osei-Kwakye , Priscilla Yeboah Boahemaa . Understanding the Predictors of Actual Use Behavior of Medical Devices among Kenyans post-COVID-19. The Moderating Effects of Technology Anxiety and Resistance to Change. International Journal of Scientific Research in Science, Engineering and Technology 2022:114 View
  21. Xu L, Li P, Hou X, Yu H, Tang T, Liu T, Xiang S, Wu X, Huang C. Middle-aged and elderly users’ continuous usage intention of health maintenance-oriented WeChat official accounts: empirical study based on a hybrid model in China. BMC Medical Informatics and Decision Making 2021;21(1) View
  22. Wu W, Zhang B, Li S, Liu H. Exploring Factors of the Willingness to Accept AI-Assisted Learning Environments: An Empirical Investigation Based on the UTAUT Model and Perceived Risk Theory. Frontiers in Psychology 2022;13 View
  23. Baysari M, Dort B, Zheng W, Li L, Hilmer S, Westbrook J, Day R. Prescribers’ reported acceptance and use of drug-drug interaction alerts: An Australian survey. Health Informatics Journal 2022;28(2):146045822211006 View
  24. Wang C, Wu G, Zhou X, Lv Y. An Empirical Study of the Factors Influencing User Behavior of Fitness Software in College Students Based on UTAUT. Sustainability 2022;14(15):9720 View
  25. Zha H, Liu K, Tang T, Yin Y, Dou B, Jiang L, Yan H, Tian X, Wang R, Xie W. Acceptance of clinical decision support system to prevent venous thromboembolism among nurses: an extension of the UTAUT model. BMC Medical Informatics and Decision Making 2022;22(1) View
  26. Bäuerle A, Frewer A, Rentrop V, Schüren L, Niedergethmann M, Lortz J, Skoda E, Teufel M. Determinants of Acceptance of Weight Management Applications in Overweight and Obese Individuals: Using an Extended Unified Theory of Acceptance and Use of Technology Model. Nutrients 2022;14(9):1968 View
  27. Ma Y, Zhou M, Yu W, Zou Z, Ge P, Ma Z, Tong Y, Li W, Li Q, Li Y, Zhu S, Sun X, Wu Y. Using the Unified Theory of Acceptance and Use of Technology (UTAUT) and e-health literacy(e-HL) to investigate the tobacco control intentions and behaviors of non-smoking college students in China: a cross-sectional investigation. BMC Public Health 2023;23(1) View
  28. Koo J, Park Y, Kang D. Factors Predicting Older People’s Acceptance of a Personalized Health Care Service App and the Effect of Chronic Disease: Cross-Sectional Questionnaire Study. JMIR Aging 2023;6:e41429 View
  29. Stehr P, Ermel L, Rossmann C, Reifegerste D, Lindemann A, Schulze A. A Mobile Health Information Behavior Model: Theoretical Development and Mixed-Method Testing in the Context of Mobile Apps on Child Poisoning Prevention. Journal of Health Communication 2023;28(10):648 View
  30. Pedersen K, Schlichter B. Improving Predictability and Effectiveness in Preventive Digital Health Interventions: Scoping Review. Interactive Journal of Medical Research 2023;12:e40205 View
  31. Aydin G. Increasing mobile health application usage among Generation Z members: evidence from the UTAUT model. International Journal of Pharmaceutical and Healthcare Marketing 2023;17(3):353 View
  32. López-Sánchez J, Patiño-Vanegas J, Valencia-Arias A, Valencia J. Use and adoption of ICTs oriented to university student learning: Systematic review using PRISMA methodology. Cogent Education 2023;10(2) View
  33. Amorim P, Paiva J, Silva de Lima J, Portugal da Fonseca L, Martins H, Silva P. Lessons learned from investigating patients’ and physiotherapists’ perspectives on the design of a telerehabilitation platform. Disability and Rehabilitation: Assistive Technology 2023:1 View

Books/Policy Documents

  1. Nordin N, Nordin N, Nordin N, Nordin N, Ewan E. Financial Technology (FinTech), Entrepreneurship, and Business Development. View
  2. Tirosh O, Zelcer J, Wickramasinghe N. Digital Disruption in Health Care. View