Evidence map›Paper›PMID 42718831›Full record

ArticleFrontiers in digital health2026

A comparative study on the credibility of ischemic stroke treatment information on social media platforms: evidence from Weibo and REDnote.

Jiayan Gu, Zihan Li, Jiajun Yang, Sen Miao, Juan Li, Lijuan Gu

Abstract read
In one paragraph

Article in Frontiers in digital health, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
0citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors.

Jiayan Gu *Central Laboratory, Renmin Hospital of Wuhan University, Wuhan, China.
Zihan Li *Hubei Province Key Laboratory of Traditional Chinese Medicine Resource and Chemistry, College of Pharmacy, Hubei University of Chinese Medicine, Wuhan, China.
Jiajun YangCentral Laboratory, Renmin Hospital of Wuhan University, Wuhan, China.
Sen MiaoCentral Laboratory, Renmin Hospital of Wuhan University, Wuhan, China.
Juan LiHubei Province Key Laboratory of Traditional Chinese Medicine Resource and Chemistry, College of Pharmacy, Hubei University of Chinese Medicine, Wuhan, China.
Lijuan GuCentral Laboratory, Renmin Hospital of Wuhan University, Wuhan, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Social media is a key channel for public health information, but its open nature leads to mixed quality of information regarding Ischemic Stroke (IS) treatment, which may mislead patient decisions. This study aimed to systematically compare IS treatment information published by professional and lay sources on two major Chinese social media platforms, Weibo and REDnote, in terms of content, engagement, and quality. Methods: This study employed computational social science and Natural Language Processing (NLP) techniques to analyze posts from four sources (Weibo-Pro, Weibo-Lay, REDnote-Pro, REDnote-Lay). We used topic modeling and co-occurrence networks to analyze content features and developed an automated scoring system based on a Large Language Model (LLM) to quantitatively evaluate information quality on two dimensions: "linguistic features" and "evidence-based medical content". Results: Lay-sourced content exceeded professional-sourced content in both volume and user engagement. Content and quality patterns differed across the two platforms: on Weibo, the evidence-based quality of professional content was significantly higher than that of lay content ( Conclusion: Distinct platform- and source-related patterns were observed across four "discursive communities." On REDnote, professional- and lay-sourced posts showed similar evidence-based quality in this sample. These findings support further investigation of platform-specific communication environments and may inform cautious, context-sensitive approaches for patients, clinicians, and platform managers.

Indexed as

health informationischemic strokelarge language models (LLMs)REDnoteWeibo

Identifiers

PMID42718831
PMCPMC13553954

What OpenQuestion holds

Textmetadata
Read underepoch 390

Registered trials

None linked

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.