ReviewInquiry : a journal of medical care organization, provision and financing
The Impact of Narrative Reviews on Patient E-doctor Choice in Online Health Communities.
Review in Inquiry : a journal of medical care organization, provision and financing. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
- Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
5 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
As online health communities (OHCs) continue to proliferate, narrative reviews on doctors have become a vital reference source for patients when choosing online health services. However, the potential value of subjective information reflecting patient experiences in OHCs has not been fully explored. The present study seeks to investigate the impact of narrative reviews on patients' selection of e-doctors and the extent to which such reviews are moderated by doctors' specialties. This paper collected data from 747 doctors and 105 032 reviews from WeDoctor, one of China's most popular OHCs, in 2019. We employed Latent Dirichlet Allocation topic modeling to extract 3 topics and analyzed their effects on patient e-doctor choice using a multiple regression method. Our findings indicate that Topic 1, clinical skills and effects, had a positive impact on patient choice in OHCs (
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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.