Evidence map›Paper›PMID 41800149›Full record

ArticleDigital health

Does popularity reflect quality? A study on the reliability and quality of CAR-T videos on Chinese short-video platforms.

Simeng Gao, Jingru Han, Yan Zhang, Jie Liao, Jiayi Yang, Yang Zhao, Linhao Xie, Min Su, Jianfu Zhao

Abstract read
In one paragraph

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.

0numbers the graph read from it
0cells of the map it votes in
3citing 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

3 citing papers in PubMed.

  1. When sleep advice goes viral: medical reliability of insomnia content on TikTok.Journal of clinical sleep medicine : JCSM : official publication of the American Academy of Sleep Medicine · 2026
    Article
  2. Article
  3. Article
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

9 authors.

Simeng GaoResearch Center of Cancer Diagnosis and Therapy, Department of Oncology, The First Affiliated Hospital of Jinan University, Guangzhou, China.
Jingru HanResearch Center of Cancer Diagnosis and Therapy, Department of Oncology, The First Affiliated Hospital of Jinan University, Guangzhou, China.ORCID https://orcid.org/0000-0002-2705-678X
Yan ZhangResearch Center of Cancer Diagnosis and Therapy, Department of Oncology, The First Affiliated Hospital of Jinan University, Guangzhou, China.
Jie LiaoResearch Center of Cancer Diagnosis and Therapy, Department of Oncology, The First Affiliated Hospital of Jinan University, Guangzhou, China.
Jiayi YangResearch Center of Cancer Diagnosis and Therapy, Department of Oncology, The First Affiliated Hospital of Jinan University, Guangzhou, China.
Yang ZhaoResearch Center of Cancer Diagnosis and Therapy, Department of Oncology, The First Affiliated Hospital of Jinan University, Guangzhou, China.
Linhao XieResearch Center of Cancer Diagnosis and Therapy, Department of Oncology, The First Affiliated Hospital of Jinan University, Guangzhou, China.
Min SuResearch Center of Cancer Diagnosis and Therapy, Department of Oncology, The First Affiliated Hospital of Jinan University, Guangzhou, China.
Jianfu ZhaoResearch Center of Cancer Diagnosis and Therapy, Department of Oncology, The First Affiliated Hospital of Jinan University, Guangzhou, China.ORCID https://orcid.org/0000-0001-6130-7266

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Chimeric antigen receptor T-cell (CAR-T) therapy represents a transformative advancement in cancer treatment. While public interest in CAR-T has surged, particularly through short-video platforms like TikTok and Bilibili in China, concerns remain regarding the reliability and quality of health information disseminated through such media. Objective: This study aimed to systematically evaluate the content quality, scientific integrity, and user engagement of CAR-T-related videos on Bilibili and TikTok, and to assess whether high traffic equates to high information quality. Methods: A total of 200 Chinese-language videos (100 per platform) were identified using the keyword "CAR-T." Videos were evaluated using three scoring tools: the DISCERN instrument for reliability, the Global Quality Score (GQS), and a novel CAR-T-specific checklist assessing 12 core domains. Content characteristics, source types, and engagement metrics (likes, comments, shares, and saves) were also extracted and compared across platforms and content types. Results: TikTok videos demonstrated significantly higher user engagement but poorer structure and lower DISCERN scores than Bilibili ( Conclusion: CAR-T-related content on Chinese short-video platforms is characterized by a disconnect between popularity and information quality. Effective science communication strategies and platform-level interventions are needed to mitigate misinformation risks and improve the dissemination of high-quality medical content.

Indexed as

BilibiliCAR-T therapycontent qualityDISCERNGlobal Quality Scorehealth communicationshort-video platformsTikTok

Identifiers

PMID41800149
PMCPMC12961123

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
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.