ArticleBMJ health & care informatics2022
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.
Article in BMJ health & care informatics, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers, 1 of them a synthesis that pooled it.
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Who cites it
12 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Determinants of Health Care Technology Adoption Using an Integrated Unified Theory of Acceptance and Use of Technology and Task Technology Fit Model: Systematic Review and Meta-Analysis.Journal of medical Internet research · 2025Pooled it
- Influence of Disease-Related Stigma on Patients' Decisions to Upload Medical Reports to the German Electronic Health Record: Randomized Controlled Trial.JMIR human factors · 2024Trial
- Article
- Thematic analysis of how general practitioners perceive digital social prescribing as an intervention aiming at promoting psychosocial health and wellbeing in older adults.Frontiers in public health · 2026Article
- 'Don't Assume, Ask': A Collaboration With Consumers, Interpreters, Clinicians and Health Service Staff to Increase Video Telehealth in Culturally and Linguistically Diverse Groups.Health expectations : an international journal of public participation in health care and health policy · 2025Article
- Article
- A systematic review of consumers' and healthcare professionals' trust in digital healthcare.NPJ digital medicine · 2025Article
- Factors associated with intention to use an educative mHealth application among high-risk target groups in health prevention.mHealth · 2025Article
- Applying the UTAUT2 framework to patients' attitudes toward healthcare task shifting with artificial intelligence.BMC health services research · 2024Article
- Intention to use personal health record system and its predictors among chronic patients enrolled at public hospitals in Bahir Dar city, northwest Ethiopia: using modified UTAUT2 model.Frontiers in medicine · 2024Article
- Designing and implementing mHealth technology: the challenge of meeting the needs of diverse communities.BMJ health & care informatics · 2023Article
- Pregnant women and mobile apps: Unraveling pregnant women's adoption of mobile pregnancy education apps.Digital healthArticle
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Authors and funding
3 authors.
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Abstract
objectivesMobile health applications are instrumental in the self-management of chronic diseases like diabetes. Technology acceptance models such as Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) have proven essential for predicting the acceptance of information technology. However, earlier research has found that the constructs "perceived disease threat" and "trust" should be added to UTAUT2 in the mHealth acceptance context. This study aims to evaluate the extended UTAUT2 model for predicting mHealth acceptance, represented by behavioral intention, using mobile diabetes applications as an example.
methodsWe extended UTAUT2 with the additional constructs "perceived disease threat" and "trust". We conducted a web-based survey in German-speaking countries focusing on patients with diabetes and their relatives who have been using mobile diabetes applications for at least 3 months. We analysed 413 completed questionnaires by structural equation modelling.
resultsWe could confirm that the newly added constructs "perceived disease threat" and "trust" indeed predict behavioural intention to use mobile diabetes applications. We could also confirm the UTAUT2 constructs "performance expectancy" and "habit" to predict behavioural intention to use mobile diabetes applications. The results show that the extended UTAUT2 model could explain 35.0% of the variance in behavioural intention. DISCUSSION: Even if UTAUT2 is well established in the information technologies sector to predict technology acceptance, our results reveal that the original UTAUT2 should be extended by "perceived disease threat" and "trust" to better predict mHealth acceptance.
conclusionDespite the newly added constructs, UTAUT2 can only partially predict mHealth acceptance. Future research should investigate additional mHealth acceptance factors, including how patients perceive trust in mHealth applications.
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