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

Usability of Apps and User Perceptions of mHealth (902) mHealth for Wellness, Behavior Change and Prevention (2754) mHealth for Symptom and Disease Monitoring, Chronic Disease Management (1317) Ethics, Privacy, and Legal Issues (458) Quality/Credibility of eHealth Information and Trust Issues (492) Mobile Health (mhealth) (2777)

Published on in Vol 10, No 1 (2022): January

Preprints (earlier versions) of this paper are available at https://preprints.jmir.org/preprint/27095, first published .
Applying an Extended UTAUT2 Model to Explain User Acceptance of Lifestyle and Therapy Mobile Health Apps: Survey Study

Applying an Extended UTAUT2 Model to Explain User Acceptance of Lifestyle and Therapy Mobile Health Apps: Survey Study

Applying an Extended UTAUT2 Model to Explain User Acceptance of Lifestyle and Therapy Mobile Health Apps: Survey Study

Authors of this article:

Eva-Maria Schomakers1 Author Orcid Image ;   Chantal Lidynia1 Author Orcid Image ;   Luisa Sophie Vervier1 Author Orcid Image ;   André Calero Valdez1 Author Orcid Image ;   Martina Ziefle1 Author Orcid Image
Article Authors Cited by (40) Tweetations (4) Metrics

Journals

  1. Ong A, Kurata Y, Castro S, De Leon J, Dela Rosa H, Tomines A. Factors influencing the acceptance of telemedicine in the Philippines. Technology in Society 2022;70:102040 View
  2. Wang X, Wu Y, Meng Z, Li J, Xu L, Sun X, Zang S. Willingness to Use Mobile Health Devices in the Post–COVID-19 Era: Nationwide Cross-sectional Study in China. Journal of Medical Internet Research 2023;25:e44225 View
  3. Bai B, Guo Z. Understanding Users’ Continuance Usage Behavior Towards Digital Health Information System Driven by the Digital Revolution Under COVID-19 Context: An Extended UTAUT Model. Psychology Research and Behavior Management 2022;Volume 15:2831 View
  4. Jezrawi R, Balakumar S, Masud R, Gabizon I, Bhagirath V, Varughese J, Brown M, Trottier D, Schwalm J, McGillion M, Alvarez E, Lokker C. Patient and physician perspectives on the use and outcome measures of mHealth apps: Exploratory survey and focus group study. DIGITAL HEALTH 2022;8:205520762211027 View
  5. 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
  6. Gil‐Cordero E, Ledesma‐Chaves P, Baena‐Luna P. Acceptance factors of Zara's shopping app among fashion consumers during COVID‐19. Journal of Consumer Behaviour 2023;22(4):955 View
  7. Gaber H, Hassan L. Using mobile health apps during the Covid-19 pandemic in a developing country for business sustainability. Cogent Business & Management 2022;9(1) View
  8. Antunes E, Alcaire R, Amaral I. Wellbeing and (Mental) Health: A Quantitative Exploration of Portuguese Young Adults’ Uses of M-Apps from a Gender Perspective. Social Sciences 2022;12(1):3 View
  9. Uncovska M, Freitag B, Meister S, Fehring L. Patient Acceptance of Prescribed and Fully Reimbursed mHealth Apps in Germany: An UTAUT2-based Online Survey Study. Journal of Medical Systems 2023;47(1) View
  10. Korn S, Böttcher M, Busse T, Kernebeck S, Breucha M, Ehlers J, Kahlert C, Weitz J, Bork U. Use and Perception of Digital Health Technologies by Surgical Patients in Germany in the Pre–COVID-19 Era: Survey Study. JMIR Formative Research 2022;6(5):e33985 View
  11. 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
  12. Olugboyega O, Ilesanmi K, Oseghale G, Aigbavboa C. The link between construction apps’ acceptance and digital attributes of construction professionals: perspectives from digital competence model. Construction Innovation 2024;24(4):912 View
  13. Cao J, Kurata K, Lim Y, Sengoku S, Kodama K. Social Acceptance of Mobile Health among Young Adults in Japan: An Extension of the UTAUT Model. International Journal of Environmental Research and Public Health 2022;19(22):15156 View
  14. Kamaruzaman K, Hussein Z, Fikry A. Factors Affecting Behavioural Intention to Use Mobile Health Applications among Obese People in Malaysia. European Journal of Business Science and Technology 2023;9(1):92 View
  15. Liew T, Tan S, Sung J, Gan C, Lee Y. Love is in the cloud: Uncovering the factors driving continuous use intention of online dating applications. Cogent Social Sciences 2023;9(1) View
  16. Angosto S, García-Fernández J, Grimaldi-Puyana M. A systematic review of intention to use fitness apps (2020–2023). Humanities and Social Sciences Communications 2023;10(1) View
  17. Memenga P, Baumann E, Luetke Lanfer H, Reifegerste D, Geulen J, Weber W, Hahne A, Müller A, Weg-Remers S. Intentions of Patients With Cancer and Their Relatives to Use a Live Chat on Familial Cancer Risk: Results From a Cross-Sectional Web-Based Survey. Journal of Medical Internet Research 2023;25:e45198 View
  18. Liu K, Tan W, Saari E. Effects of pervasive game on behavioral intention towards fitness among older adults in Henan: An empirical study. Educational Gerontology 2024;50(3):187 View
  19. von Kalckreuth N, Feufel M. Extending the Privacy Calculus to the mHealth Domain: Survey Study on the Intention to Use mHealth Apps in Germany. JMIR Human Factors 2023;10:e45503 View
  20. Busch-Casler J, Radic M. Trust and Health Information Exchanges: Qualitative Analysis of the Intent to Share Personal Health Information. Journal of Medical Internet Research 2023;25:e41635 View
  21. Khashan M, Elsotouhy M, Alasker T, Ghonim M. Investigating retailing customers' adoption of augmented reality apps: integrating the unified theory of acceptance and use of technology (UTAUT2) and task-technology fit (TTF). Marketing Intelligence & Planning 2023;41(5):613 View
  22. Maican C, Sumedrea S, Tecau A, Nichifor E, Chitu I, Lixandroiu R, Bratucu G. Factors Influencing the Behavioural Intention to Use AI-Generated Images in Business. Journal of Organizational and End User Computing 2023;35(1):1 View
  23. Rohowsky A, Offermann J, Ziefle M. Everybody hurts sometimes: perceptions of benefits and barriers in telemedical consultations. Frontiers in Public Health 2023;11 View
  24. Simões R, Amaral I, Flores A, Antunes E. Scripted Gender Practices: Young Adults’ Social Media App Uses in Portugal. Social Media + Society 2023;9(3) View
  25. Chew H, Achananuparp P, Dalakoti M, Chew N, Chin Y, Gao Y, So B, Shabbir A, Peng L, Ngiam K. Public acceptance of using artificial intelligence-assisted weight management apps in high-income southeast Asian adults with overweight and obesity: a cross-sectional study. Frontiers in Nutrition 2024;11 View
  26. von Kalckreuth N, Feufel M. Influence of Disease-Related Stigma on Patients’ Decisions to Upload Medical Reports to the German Electronic Health Record: Randomized Controlled Trial. JMIR Human Factors 2024;11:e52625 View
  27. Mohammed A, Rozsa Z. Consumers’ intentions to utilize smartphone diet applications: an integration of the privacy calculus model with self-efficacy, trust and experience. British Food Journal 2024;126(6):2416 View
  28. 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
  29. Nyagango A, Sife A, Kazungu I. Factors influencing Satisfaction with mobile phone use for Accessing Agricultural Marketing Information by grape smallholder farmers in Dodoma, Tanzania. Global Knowledge, Memory and Communication 2024 View
  30. Nabelsi V, Lévesque-Chouinard A. Successful Electronic Consultation Service Initiative in Quebec, Canada With Primary Care Physicians’ and Specialists’ Experiences on Acceptance and Use of Technological Innovation: Cross-Sectional Exploratory Study. JMIR Formative Research 2024;8:e52921 View
  31. Huang Y, Lin C, Wang T. Benefits of Give Circle: Exploring the impact of collaborative redistribution platforms on user willingness to donate to charity and tendency towards consumer minimalism. Computers in Human Behavior Reports 2024;14:100421 View
  32. Guste R, Ong A. Machine Learning Decision System on the Empirical Analysis of the Actual Usage of Interactive Entertainment: A Perspective of Sustainable Innovative Technology. Computers 2024;13(6):128 View
  33. Kumari N, Biswas A. Money at my Fingertips: Decoding the Role of Referent Network Size and Financial Knowledge in Reinforcing Continuance Intention of m-Payment Services. Journal of Organizational Computing and Electronic Commerce 2024:1 View
  34. Min H, Li J, Di M, Huang S, Sun X, Li T, Wu Y. Factors influencing the continuance intention of the women’s health WeChat public account: an integrated model of UTAUT2 and HBM. Frontiers in Public Health 2024;12 View
  35. Engström E, Vartanova I, Viberg Johansson J, Persson M, Strimling P. Comparing and modeling the use of online recommender systems. Computers in Human Behavior Reports 2024;15:100449 View
  36. Wu T, Cai X, Fan B, Li R, Wang Q, Deng Z. Community Health Workers’ Continuance of Mobile Health Applications: An Extended Expectation Confirmation Model. Information & Management 2024:104008 View
  37. Xu F, Hu J, Liu D, Zhou C. Towards Sustainable Healthcare: Exploring Factors Influencing Use of Mobile Applications for Medical Escort Services. Sustainability 2024;16(14):6058 View

Books/Policy Documents

  1. Rashed A, Al-Emran M. Proceedings of the 2nd International Conference on Emerging Technologies and Intelligent Systems. View
  2. Burbach L, Ganser R, Vervier L, Ziefle M, Calero Valdez A. Digital Human Modeling and Applications in Health, Safety, Ergonomics and Risk Management. View