Evidence mapPaperPMID 41278376Full record

ArticleDigital health

Quality and reliability of Alzheimer's disease videos on Douyin and Bilibili: A cross-sectional content analysis study.

Jingyu Li, Jingshu Zhang, Xinyi Xu, Lu Xiao, Yanjun Ling, Shuzhen Liu, Ying Gao, Lan Zhao, Hui Jia

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 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing 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

7 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

9 authors.

Jingyu LiFirst Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China.ORCID https://orcid.org/0000-0003-3507-1231
Jingshu ZhangFirst Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China.ORCID https://orcid.org/0009-0008-0475-6098
Xinyi XuFirst Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China.ORCID https://orcid.org/0009-0002-7459-350X
Lu XiaoFirst Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China.ORCID https://orcid.org/0000-0003-2158-7667
Yanjun LingKey Laboratory of Stem Cells and Tissue Engineering (Ministry of Education), Zhongshan School of Medicine, Sun Yat-Sen University, Guangzhou, China.ORCID https://orcid.org/0009-0001-0048-213X
Shuzhen LiuFirst Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China.ORCID https://orcid.org/0009-0009-4735-3456
Ying GaoFirst Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China.ORCID https://orcid.org/0009-0000-7517-1347
Lan ZhaoFirst Teaching Hospital of Tianjin University of Traditional Chinese Medicine, Tianjin, China.ORCID https://orcid.org/0000-0002-7449-2947
Hui JiaQingdao Traditional Chinese Medicine Hospital, Qingdao Hiser Hospital Affiliated of Qingdao University, Shandong, China.ORCID https://orcid.org/0009-0001-3699-1497

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Alzheimer's disease (AD) poses a significant public health challenge to China's aging population. Patients and their families increasingly turn to short-video platforms such as Douyin and Bilibili for information. However, there is currently a lack of systematic analysis regarding the quality and reliability of advertising content on these platforms, creating a critical gap in understanding this emerging information ecosystem. Aim: Systematically evaluate the quality and reliability of videos on Douyin and Bilibili, analyzing the relationship between content themes, upload sources, and user engagement metrics. Methods: Using "Alzheimer's disease" as the keyword, we retrieved the top 100 videos from multiple platforms. Videos were categorized by uploader type and content. Two qualified researchers assessed their reliability and quality using the JAMA, the modified DISCERN instrument (mDISCERN), and Global Quality Score (GQS) scale. Data analysis employed nonparametric statistical methods. Apply relevance and logistic regression analysis to discuss factors that may influence video quality. Results: This study analyzed a total of 171 videos. Results indicate that compared to Douyin, videos on the Bilibili platform scored higher across multiple quality evaluation metrics (GQS: 2.0(1.0-2.0) vs 1.0(1.0-2.0); mDISCERN: 2.0(2.0-2.0) vs. 2.0(2.0-2.0); JAMA: 2.0(1.0-2.0) vs. 1.0 (1.0-2.0); Conclusion: This study reveals a pronounced "quality-dissemination paradox" in AD content across mainstream short-video platforms: While scientifically rigorous content published by medical professionals receives high quality ratings, it significantly underperforms in user engagement metrics compared to nonprofessional content centered on patient narratives and lived experiences. This highlights a severe disconnect between scientific rigor and public participation within algorithmic dissemination ecosystems. To address this, platforms should optimize algorithms to enhance the visibility of authoritative content, encourage collaboration between professional and nonprofessional creators to boost content appeal, and strengthen health media literacy education for the public-particularly older adults-to improve their ability to discern information.

Indexed as

Alzheimer's diseaseBilibilicross-sectional studyPublic healthshort videos

Identifiers

PMID41278376
PMCPMC12638718

What Socratic 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 Socratic graph.