ArticleJMIR human factors2022
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.
Article in JMIR human factors, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 16 papers.
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16 citing papers in PubMed.
- Evaluating a Digital Chronic Condition Prevention Intervention (THRIVE) in Australian General Practice: Protocol for a Mixed Methods Feasibility Study (ePREVENT-360).JMIR research protocols · 2026Article
- Technology Acceptance of 2 mHealth Apps During an Observational Technology Evaluation Study: Qualitative Results of a Mixed Methods Study.JMIR human factors · 2026Observational
- The Role of Digital Media in Chronic Disease Self-Management: Protocol for a Multimethod Study of the DISELMA Research Consortium.JMIR research protocols · 2026Article
- Validation of a novel patient-reported measure of the burden of digital care in diabetes.BMC medicine · 2025Article
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- Patients' Experiences With Using a Digital Platform for Chat-Based Consultation in Primary Health Care in Sweden: Qualitative Study.Journal of medical Internet research · 2025Article
- Article
- Applying the UTAUT2 framework to patients' attitudes toward healthcare task shifting with artificial intelligence.BMC health services research · 2024Article
- Motivating and inhibiting factors influencing the application of mhealth technology in post-abortion care: a review study.BMC pregnancy and childbirth · 2024Review
- Adjustment experiences of adolescents living with well-controlled type 1 diabetes using closed-loop technology.Frontiers in clinical diabetes and healthcare · 2024Article
- Parent and clinician perceptions and recommendations on a pediatric cancer pain management app: A qualitative co-design study.PLOS digital health · 2023Article
- "It's Another Feather in My Hat"-Exploring Factors Influencing the Adoption of Apps With People Living With Dementia.Dementia (London, England) · 2023Article
- 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 · 2023Article
- 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 · 2022Article
- Article
- Both sides of the screen: A dual-sided model of telemedicine adoption through extended UTAUT2.Digital healthArticle
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Abstract
backgroundIn recent years, the use of mobile health (mHealth) apps to manage chronic diseases has increased significantly. Although mHealth apps have many benefits, their acceptance is still low in certain areas and groups. Most mHealth acceptance studies are based on technology acceptance models. In particular, the Unified Theory of Acceptance and Use of Technology 2 (UTAUT2) model was developed to predict technology acceptance in a consumer context. However, to date, only a few studies have used the UTAUT2 model to predict mHealth acceptance and confirm its suitability for the health sector. Thus, it is unclear whether the UTAUT2 model is suitable for predicting mHealth acceptance and whether essential variables for a health-related context are missing.
objectiveThis study aims to validate the suitability of UTAUT2 for predicting mHealth acceptance.
methodsIn this study, diabetes was used as an example as mHealth apps are a significant element of diabetes self-management. In addition, diabetes is one of the most common chronic diseases affecting young and older people worldwide. An explorative literature review and guided interviews with 11 mHealth or technology acceptance experts and 8 mHealth users in Austria and Germany were triangulated to identify all relevant constructs for predicting mHealth acceptance. The interview participants were recruited by purposive sampling until theoretical saturation was reached. Data were analyzed using structured content analysis based on inductive and deductive approaches.
resultsThis study was able to confirm the relevance of all exogenous UTAUT2 constructs. However, it revealed two additional constructs that may also need to be considered to better predict mHealth acceptance: trust and perceived disease threat.
conclusionsThis study showed that the UTAUT2 model is suitable for predicting mHealth acceptance. However, the model should be extended to include 2 additional constructs for use in the mHealth context.
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