ArticleFrontiers in public health2025
How is patient trust transferred from online medical platforms to offline?
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.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
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.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
2 citing papers in PubMed.
- Unconsummated marriage: etiology and treatment of erectile dysfunction in newlywed men-a narrative review with a focus on China.Translational andrology and urology · 2026Review
- Trust transfer in digital healthcare: The role of self-service systems in reducing patient treatment barriers.Digital healthArticle
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
1 author.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: The function of the internet medical platform has expanded from online consultation to offline diagnosis and treatment appointment, forming a complete service process combining online and offline, improving the patient's medical experience and promoting the transfer of online trust to offline. However, the existing studies pay insufficient attention to the dynamic and multi-stage characteristics of online medical trust, especially the lack of in-depth discussion on the trust transfer of patients from online to offline. Methods: This study builds a patient trust transfer model based on relevant theories, and analyzes the influence mechanism of online reputation feedback on patients' online and offline trust combined with text mining technologies such as sentiment analysis. The research adopts the multi-dimensional analysis method, comprehensively considers the online and offline scenarios, and reveals the key drivers of trust transfer through large-scale data analysis. Results: The study found that doctors' online reputation feedback and interaction quality were important factors affecting patients' trust transfer. Positive online interaction and high-quality reputation feedback significantly enhanced patient trust and promoted the transfer of online trust to offline. The trust transfer process is dynamic and multi-stage, and the influencing factors of different stages are different. The study also revealed the significant difference in trust mechanism between online medicine and traditional medicine. Discussion: This study revealed the formation and transfer mechanism of trust in online health care by building a trust transfer model, filling the gap in related research. The results provide practical guidance for the online medical platform to optimize the service process and enhance the trust of patients. In the future, we can further explore the trust transfer mechanism under different cultural backgrounds to promote the globalization of Internet medicine.
Indexed as
Identifiers
What OpenQuestion holds
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.