Evidence map›Paper›PMID 40295710›Full record

ArticleScientific reports2025

Assessing the content and quality of GI bleeding information on Bilibili, TikTok, and YouTube: a cross-sectional study.

Jingsong Wang, Bingxi Liu, Guang Yang, Yixing Luo, Nonghua Lv, Xu Shu, Zhenhua Zhu, Linlin Liu

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Scientific reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 28 papers.

0numbers the graph read from it
0cells of the map it votes in
28citing 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

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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

28 citing papers in PubMed.

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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

8 authors.

Jingsong Wang *Department of Gastroenterology, Jiangxi Provincial Key Laboratory of Digestive Diseases, Jiangxi Clinical Research Center for Gastroenterology, Digestive Disease Hospital, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.
Bingxi Liu *School of Medicine, Jianghan University, Wuhan, 430056, China.
Guang Yang *Department of Gastroenterology, South China Hospital, Medical School, Shenzhen University, Shenzhen, 518116, P. R. China.
Yixing LuoDepartment of Gastroenterology, Jiangxi Provincial Key Laboratory of Digestive Diseases, Jiangxi Clinical Research Center for Gastroenterology, Digestive Disease Hospital, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.
Nonghua LvDepartment of Gastroenterology, Jiangxi Provincial Key Laboratory of Digestive Diseases, Jiangxi Clinical Research Center for Gastroenterology, Digestive Disease Hospital, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.
Xu ShuDepartment of Gastroenterology, Jiangxi Provincial Key Laboratory of Digestive Diseases, Jiangxi Clinical Research Center for Gastroenterology, Digestive Disease Hospital, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China.
Zhenhua ZhuDepartment of Gastroenterology, Jiangxi Provincial Key Laboratory of Digestive Diseases, Jiangxi Clinical Research Center for Gastroenterology, Digestive Disease Hospital, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China. zhuzhenhua19820122@163.com.
Linlin LiuDepartment of Gastroenterology, Jiangxi Provincial Key Laboratory of Digestive Diseases, Jiangxi Clinical Research Center for Gastroenterology, Digestive Disease Hospital, The First Affiliated Hospital, Jiangxi Medical College, Nanchang University, Nanchang, Jiangxi, China. 251503712@qq.com.

Funding

National Natural Science Foundation of China 82360110Natural Science Foundation of Jiangxi Province 20224BAB206073
6 · The paper itself

Abstract

Gastrointestinal (GI) bleeding is a significant clinical issue that is commonly discussed on social media platforms. Despite the widespread availability of health information videos, the quality and comprehensiveness of these videos vary greatly, posing potential risks to public health. This study evaluates the content and quality of GI bleeding-related videos on TikTok, Bilibili, and YouTube. A total of 300 GI bleeding-related videos were collected and analyzed from TikTok, Bilibili, and YouTube. The videos were categorized based on the uploader's background (health professionals vs. non-health professionals). Key metrics such as likes, comments, video duration, and quality scores (GQS, JAMA, and modified DISCERN) were compared. Simultaneously, the content of the videos was analyzed across six aspects: definition, symptoms, risk factors, tests, treatment, and outcomes. A total of 300 GI bleeding-related videos were analyzed, with 196 (65.3%) uploaded by health professionals and 104 (34.7%) by non-health professionals. TikTok videos received significantly more likes and comments but were shorter in duration compared to those on Bilibili and YouTube (p < 0.05). The overall quality and reliability of the videos were relatively low, with median DISCERN and GQS scores of 2 (IQR: 2-3) and 3 (IQR: 2-3), respectively. Videos from health professionals exhibited higher reliability and quality, with median DISCERN scores of 3 (IQR: 3-4) and GQS scores of 3 (IQR: 3-4). The overall quality and comprehensiveness of GI bleeding-related videos on social media platforms are unsatisfactory, with many low-quality videos still prevalent. Although videos from health professionals score higher in quality and reliability, their content comprehensiveness is not significantly better than those from non-health professionals. Efforts should be intensified to improve the content and quality of GI bleeding videos, raise public awareness, and promote patient self-management.

Indexed as

Gastrointestinal HemorrhageSocial MediaVideo RecordingCross-Sectional StudiesHumansInformation DisseminationBilibiliGastrointestinal bleedingHealth informationOnline videoTikTokYouTube

Identifiers

PMID40295710
PMCPMC12038001

What OpenQuestion holds

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Registered trials

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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.