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

Digital Health Reviews (3450) Mobile Health (mhealth) (4969) Human Factors and Usability Case Studies (1257) Usability of Apps and User Perceptions of mHealth (1750)

Published on in Vol 27 (2025)

This is a member publication of Imperial College London (Jisc)

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/66432, first published .
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Improving Acceptability of mHealth Apps—The Use of the Technology Acceptance Model to Assess the Acceptability of mHealth Apps: Systematic Review

Improving Acceptability of mHealth Apps—The Use of the Technology Acceptance Model to Assess the Acceptability of mHealth Apps: Systematic Review

Authors of this article:

Ahmer Adnan1 Author Orcid Image ;   Rebecca Eilish Irvine1 Author Orcid Image ;   Allison Williams2 Author Orcid Image ;   Matthew Harris2 Author Orcid Image ;   Grazia Antonacci2, 3 Author Orcid Image
Article Authors Cited by (31) Tweetations Metrics

Journals

  1. Fritz B, Eppelmann L, Edelmann A, Rohrmann S, Wessa M. How mental health status and attitudes toward mental health shape AI Acceptance in psychosocial care: a cross-sectional analysis. BMC Psychology 2025;13(1) View
  2. Cheney M, Zingg T, Kezbers K, Montgomery A, Bain C, Stanley N, Frank-Pearce S, Kendzor D, Hébert E, Businelle M. A Smartphone Application for People Who are Not Ready to Quit Smoking: A Post-intervention Qualitative Assessment of the Phoenix Project. American Journal of Health Promotion 2026;40(2):174 View
  3. Müller P, Schulze A, Geppert J, Menning A, Brand F, Stehr P, Reifegerste D, Rossmann C. Poisoning accidents in young children—Theory-based evaluation of an mHealth app. DIGITAL HEALTH 2025;11 View
  4. Latorre M, Paggiaro P, Cardini C, Paoletti G, Nappi E, Di Gioacchino M, Heffler E, Blasi F, Canonica G, Puggioni F. Digital Innovation in Asthma Management in Italy: Results From the “Confronting Asthma Survey”. Clinical and Translational Allergy 2025;15(10) View
  5. Hussain S, Nshom E, Jie L. Clicks, trust, and care: Digital health engagement among university students in Pakistan. Telematics and Informatics Reports 2025;20:100264 View
  6. Zhang C, Hong Y, Chen Y, Arbing R, Chen W, Huang F. Effectiveness of nurse-led mHealth interventions on symptom outcomes in adult patients with cancer: a systematic review and meta-analysis. BMC Nursing 2025;24(1) View
  7. Yao J, Wang H, Jia S, Chen W, Hu E. Effects of mobile health technology on physical activity in pregnant women: a systematic review and meta-analysis. BMC Pregnancy and Childbirth 2025;25(1) View
  8. Behera R, Zhang L. Unveiling factors of gamification platforms for tourism marketing: exploring its impact on tourist inspiration and sustainable tourist engagement. Journal of Hospitality and Tourism Insights 2026;9(4):1565 View
  9. Morales-Urrutia D, Yépez-Villacis R, Mantilla-Falcón L. Educational podcasts and student engagement in Ecuadorian higher education: an SEM-based evaluation of the technology acceptance model. Frontiers in Education 2026;10 View
  10. MacAskill W, Gill P, Woloszczuk C, Alam K, Wallis K, McGrail M, Kondalsamy-Chennakesavan S, Nasir B. A systematic review of the scope and impact of rural primary healthcare innovations using digital health technology. BMJ Open 2026;16(1):e097874 View
  11. Zeng Q, Zhu J, Wang Y, Su S, Huang Y. Artificial intelligence self-efficacy and attitudes among nursing students: a multicenter network analysis of educational stratification. BMC Medical Education 2026;26(1) View
  12. Cao X, Lu Y, Li J, Luo X, Zeng Y, Wang S, Gao H. Medical students perceptions and attitudes toward the use of generative artificial intelligence in clinical decision-making: a nationwide cross-sectional survey in China. BMC Medical Education 2026;26(1) View
  13. Berry E, Sculthorpe N, Warner A, Sanal-Hayes N, Hayes L. Designing an mHealth App to Encourage Uptake of Muscle-Strengthening Exercise in Older Adults: Co-Design Focus Group Study. JMIR Aging 2026;9:e87332 View
  14. Chen S, Mohamad E, Azlan A, Zhao X. Instant messaging-based digital health interventions for diabetes management: a domain-structured systematic review and meta-analysis of randomized controlled trials. Frontiers in Public Health 2026;14 View
  15. Liu J, Guo Y, Wu Y, Jin N, Dong Y, Zhao X, Chen X. The intervention effect of internet-based cognitive behavioral therapy on anxiety, depression, and stress in college students: a systematic review and meta-analysis based on randomized controlled trials. Frontiers in Psychology 2026;17 View
  16. Wongsapai M, Wudtijureepun K, Suthachai T, Tamdee D, Ittichaicharoen J, Wuttisarnwattana P, Suebnukarn S. A Community-Based Usability Study of an AI-Enabled Oral Cancer Screening App Operated by Village Health Volunteers: Mixed Methods Study. JMIR mHealth and uHealth 2026;14:e83738 View
  17. He Y, Gong J, Li S, Zhang L. Perceptions and feasibility of augmented reality for pressure injury care among healthcare professionals and caregivers: A qualitative study. DIGITAL HEALTH 2026;12 View
  18. González-Velázquez S, Molina A, González I, Lacave C, Mondéjar T, Nugent C. StopMiedo: a technology-assisted intervention system for the treatment of amaxophobia. Universal Access in the Information Society 2026;25(2) View
  19. Najsrova A, Banikova S, Szegedi I, Horakova N, Hotkova D, Vitova K, Fiedorova I, Trda J, Volny O. Patient Attitudes Toward Virtual Reality Telerehabilitation After Subacute Stroke: A Follow-Up Study. Bratislava Medical Journal 2026 View
  20. Aovare P, Chilunga F, Hayfron-Benjamin C, Laar A, Moens N, Moll van Charante E, Agyemang C. Impact of an interactive smartphone application on glycaemic and blood pressure control among diabetes and hypertension patients in Ghana: A quasi-experimental study. Heliyon 2026;12(10):e45003 View
  21. Jung F, Luppa M, Reusche M, Wirkner K, Eberl M, Dietz Y, Engel C, Riedel-Heller S. Digital Health Literacy, Technology Acceptance, and Competence Among Older Adults Aged ≥65 Years: Cross-Sectional Study Investigating Differences Between Women and Men. Journal of Medical Internet Research 2026;28:e85846 View
  22. Han Q, Zhao C. Trust, perceived accuracy, and continued use of patient–facing symptom monitoring applications: Cross-sectional study. DIGITAL HEALTH 2026;12 View
  23. Shekhar A, Mitonga-Monga J. A bridge, not a destination: YouTube viewer perspectives on AI mental health support and human therapy. Frontiers in Digital Health 2026;8 View
  24. van Asselt A, Roke Y, van Antwerpen T, Reekers D, Salawanbessie-Nieuwenhuizen I, Begeer S, Scheeren A. User Experiences of the Mobile Stress Autism Mate (SAM) Junior Application for Autistic Adolescents: A Qualitative Study. Advances in Neurodevelopmental Disorders 2026 View
  25. Muriithi G, Arasa R, Mutetei T. Implementation process and acceptability of the electronic community health information system among community health workers in Kenya. Frontiers in Health Services 2026;6 View
  26. Jagemann I, Hegner S, Hirschfeld G. The Role of Rating Valence in AI Skin Cancer App Acceptance: Eye-Tracking and Questionnaire Study. JMIR Human Factors 2026;13:e93489 View
  27. Johnson D. Teaching Family Medicine Residents to Appraise Digital Behavioral Health Tools: An Early-Phase Mixed-Methods Evaluation of a Longitudinal Curriculum. Journal of Technology in Behavioral Science 2026 View
  28. Podkamien Y, Perez D, Stockheim I. Evolving ease: the dynamic moderating role of perceived ease of use in the technology acceptance model. Innovation & Management Review 2026;23:85 View

Books/Policy Documents

  1. Hauser M, Hudecek M. Human and Smart Marketing. View

Conference Proceedings

  1. Rosyifah H, Arzeta R, Thennida S, Wiryawan D. 2025 International Conference on Computer, Control, Informatics and its Applications (IC3INA). The Use Of Digital Technologies Feature in Enhancing Efficiency and Accessibility of Mobile-Based Healthcare Application View
  2. Hariprasad T, Harshini , Dhanuka D, Shivalingaiah K, P P, Llantuy N. 2026 13th International Conference on Computing for Sustainable Global Development (INDIACom). Application of SEM and Multi-Machine Learning Sentiment Analysis for Identification of Factors Influencing UPI Adoption View