ArticleFrontiers in public health2025
Reveal the dynamics of mobile health services continuance intention: effects of expectation, confirmation, and chronic disease.
Article in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Who cites it
2 citing papers in PubMed.
- Digital Dental Triage and Access to Care: A Qualitative Study of Experiences in a Teaching Hospital.Dentistry journal · 2026Article
- Intention to continue using corporate wellness mHealth apps in Thailand: A health belief model approach.Digital healthArticle
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: The sustainable development of mobile health (mHealth) services relies on the continuous use by users. Most studies consider users' intention to continue using mHealth services as a static measure rather than one that changes dynamically over time, often neglecting the impact of individual differences, such as the presence of chronic disease, on usage patterns. Methods: Drawing on the expectation-confirmation model, this study investigates the dynamic nature of the intention to continue using mHealth services, with a particular focus on the role of chronic disease. Conducting a longitudinal study with three rounds of online survey, we analyzed data collected from 236 completed respondents using a latent growth model. Results: The results indicate that users' intention to continue using mHealth services is not static and tends to decrease over time. Expectation accelerates the descent, while confirmation mitigates it. Furthermore, expectation shows a stronger impact on users without chronic disease compared to those with chronic conditions. Discussion: This study advances the understanding of the continuous use of mHealth services by incorporating time-based dynamics and the influence of chronic disease. This study also extends the traditional expectation-confirmation model into a dynamic framework.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.