ArticleJMIR mHealth and uHealth2020
Adoption of Mobile Health Apps in Dietetic Practice: Case Study of Diyetkolik.
Article in JMIR mHealth and uHealth, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 17 papers, 1 of them a synthesis that pooled it.
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Who cites it
17 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Improving Acceptability of mHealth Apps-The Use of the Technology Acceptance Model to Assess the Acceptability of mHealth Apps: Systematic Review.Journal of medical Internet research · 2025Pooled it
- Establishing a usability cut-point for the health information technology usability evaluation scale (Health-ITUES).International journal of medical informatics · 2022Trial
- Physician-Patient Communication and Physicians' Acceptance of a Tailored Digital Health Information Service: Quantitative Online Survey.JMIR human factors · 2026Article
- Why health apps fail: the role of smartphone proficiency in mHealth resistance.Frontiers in public health · 2026Article
- A systematic review of consumers' and healthcare professionals' trust in digital healthcare.NPJ digital medicine · 2025Article
- Personal Goals, User Engagement, and Meal Adherence within a Personalised AI-Based Mobile Application for Nutrition and Physical Activity.Life (Basel, Switzerland) · 2024Article
- Understanding the Role of Technology Anxiety in the Adoption of Digital Health Technologies (DHTs) by Older Adults with Chronic Diseases in Shanghai: An Extension of the Unified Theory of Acceptance and Use of Technology (UTAUT) Model.Healthcare (Basel, Switzerland) · 2024Article
- Exploring dietitians' views on digital nutrition educational tools in Malaysia: a qualitative study.Nutrition research and practice · 2024Article
- Mapping Theories, Models, and Frameworks to Evaluate Digital Health Interventions: Scoping Review.Journal of medical Internet research · 2024Article
- The Nutritional Content of Meal Images in Free-Living Conditions-Automatic Assessment with goFOODNutrients · 2023Article
- Exploring Functions and Predictors of Digital Health Engagement Among German Internet Users: Survey Study.Journal of medical Internet research · 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
- The Acceptance Behavior of Smart Home Health Care Services in South Korea: An Integrated Model of UTAUT and TTF.International journal of environmental research and public health · 2022Article
- Users' Perspective on the AI-Based Smartphone PROTEIN App for Personalized Nutrition and Healthy Living: A Modified Technology Acceptance Model (mTAM) Approach.Frontiers in nutrition · 2022Article
- Toward a Better Understanding of the Intention to Use mHealth Apps: Exploratory Study.JMIR mHealth and uHealth · 2021Article
- Challenges of Implementing an mHealth Application for Personalized Physical Activity Counselling in Primary Health Care: A Qualitative Study.International journal of general medicine · 2021Article
- Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundDietetics mobile health apps provide lifestyle tracking and support on demand. Mobile health has become a new trend for health service providers through which they have been shifting their services from clinical consultations to online apps. These apps usually offer basic features at no cost and charge a premium for advanced features. Although diet apps are now more common and have a larger user base, in general, there is a gap in literature addressing why users intend to use diet apps. We used Diyetkolik, Turkey's most widely used online dietetics platform for 7 years, as a case study to understand the behavioral intentions of users.
objectiveThe aim of this study was to investigate the factors that influence the behavioral intentions of users to adopt and use mobile health apps. We used the Technology Acceptance Model and extended it by exploring other factors such as price-value, perceived risk, and trust factors in order to assess the technology acceptance of users.
methodsWe conducted quantitative research on the Diyetkolik app users by using random sampling. Valid data samples gathered from 658 app users were analyzed statistically by applying structural equation modeling.
resultsStatistical findings suggested that perceived usefulness (P<.001), perceived ease of use (P<.001), trust (P<.001), and price-value (P<.001) had significant relationships with behavioral intention to use. However, no relationship between perceived risk and behavioral intention was found (P=.99). Additionally, there was no statistical significance for age (P=.09), gender (P=.98), or previous app use experience (P=.14) on the intention to use the app.
conclusionsThis research is an invaluable addition to Technology Acceptance Model literature. The results indicated that 2 external factors (trust and price-value) in addition to Technology Acceptance Model factors showed statistical relevance with behavioral intention to use and improved our understanding of user acceptance of a mobile health app. The third external factor (perceived risk) did not show any statistical relevance regarding behavioral intention to use. Most users of the Diyetkolik dietetics app were hesitant in purchasing dietitian services online. Users should be frequently reassured about the security of the platform and the authenticity of the platform's dietitians to ensure that users' interactions with the dietitians are based on trust for the platform and the brand.
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