ArticleDigital health
Online health community-An empirical analysis based on grounded theory and entropy weight TOPSIS method to evaluate the service quality.
Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 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
3 citing papers in PubMed.
- Construction of an evaluation index system for user satisfaction with immersive virtual reality exergaming.Frontiers in psychology · 2026Article
- Sustainable service quality assessment of Chinese healthcare e-government: a multi-criteria decision framework based on SERVQUAL model and entropy-weight TOPSIS method.Frontiers in digital health · 2025Article
- Health system efficiency and equity in ASEAN: an empirical investigation.Cost effectiveness and resource allocation : C/E · 2024Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Introduction: With the enhancement of people's health awareness and the impact of the coronavirus pandemic in recent years, people's demand for online health information continues to expand, and online health communities (OHCs) have developed rapidly. However, the service quality of OHCs is uneven, and problems such as content quality, privacy disclosure are increasingly prominent. It's of great significance to establish normalized OHC service quality evaluation standards and develop effective evaluation tools and methods for the improvement of OHC service quality. Material and Methods: Based on the grounded theory, the raw materials obtained from semi-structured interviews were coded in three stages to construct a service quality evaluation system for OHC. Through empirical analysis, the rationality and effectiveness of the evaluation system were verified. Then six representative Chinese OHCs were selected and their service quality was evaluated by the entropy weight TOPSIS method. Results: The service quality evaluation system of OHC was constructed which includes 4 first-level indicators and 16 second-level indicators. The weights of the first-level indicators from large to small are content quality, emotional experience quality, interaction quality and function quality. Among the second-level indicator weights, the top three are perceived cost reasonableness, content professionalism and effectiveness of interactive content. Conclusions: The indicator system is reasonable and effective and the evaluation method has strong applicability and operability. This study will provide theoretical guidance for community platform operators and relevant departments to design effective evaluation mechanism of OHC service quality, offering a reference for decisions and policymakers.
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.