Previously submitted to: JMIR Medical Informatics (no longer under consideration since Nov 08, 2026)
Date Submitted: Nov 7, 2026
Open Peer Review Period: Nov 8, 2026 - Nov 8, 2026
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Quality and Reliability of Perimenopausal Syndrome-Related Short Videos on Douyin and Bilibili: A Cross-Sectional Study
ABSTRACT
Background:
In recent years, short video platforms represented by Douyin and Bilibili have risen rapidly, becoming important channels for the public to access health information .Perimenopausal women, as active users of short videos, increasingly rely on platform content to understand their health status and coping strategies . However, health-related information on short video platforms lacks a unified professional review mechanism, with uneven information quality that makes it difficult for users to distinguish scientific accuracy and reliability. Some videos contain exaggerated claims of efficacy, concealed risks, and dissemination of pseudoscience, which may adversely affect the health decisions of perimenopausal women.
Objective:
To evaluate the quality, reliability, and characteristics of short videos on perimenopausal syndrome on Bilibili and Douyin.
Methods:
A cross-sectional study analyzed 179 top-ranked videos retrieved using the keyword "Perimenopausal syndrome in Chinese". Quality and reliability were assessed using the Global Quality Score (GQS) and Modified DISCERN (mDISCERN). Engagement metrics were collected, and statistical analyses were performed.
Results:
Overall quality was low (median GQS 3.00, mDISCERN 2.00), with poor evidence quality. Bilibili had higher GQS scores than Douyin (P=0.049), while Douyin showed higher engagement. Professionally certified creators produced significantly higher-quality content than non-professionals. Video duration positively correlated with quality (r=0.486), but engagement metrics did not, indicating a "quality-traffic decoupling" phenomenon.
Conclusions:
Short videos on perimenopausal syndrome are generally of low quality. Professional certification and longer durations predict better quality, whereas high traffic does not. Platforms should strengthen professional reviews and optimize algorithms.
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