Quality Analysis of Stroke-Related Videos on Video Platforms: Cross-Sectional Study

Area of Science:

• Public Health
• Digital Health
• Medical Communication

Background:

• Stroke is a major global health concern with high incidence, disability, and mortality.
• TikTok and Bilibili are primary sources of stroke information in China.
• The quality and reliability of stroke videos on these platforms are largely unevaluated.

Purpose of the Study:

• To analyze the content and quality of stroke-related videos on Chinese video-sharing platforms (TikTok and Bilibili).

Main Methods:

• Cross-sectional study of stroke videos retrieved from TikTok and Bilibili in March 2025.
• Video quality assessed using Global Quality Scale (GQS), modified DISCERN (mDISCERN), and Patient Education Materials Assessment Tool (PEMAT).
• Statistical analyses included descriptive statistics, Kruskal-Wallis tests, Spearman's rank correlation, and random forest modeling.

Main Results:

• Popular science education content predominated (66.7%), with TikTok featuring more (93.3%) than Bilibili (52.9%).
• TikTok videos had higher engagement (likes, comments) and shorter durations than Bilibili videos.
• Videos from professional teams and certified physicians/institutions showed higher quality scores (GQS, PEMAT).
• User engagement correlated strongly with itself but weakly with quality; machine learning models indicated duration and subscriber count as weak predictors of quality.

Conclusions:

• Stroke video quality on TikTok and Bilibili is suboptimal.
• Medical authority (verified creators) is a significant indicator of video quality.
• Current engagement metrics are insufficient for quality assessment; future algorithms need content-based features and creator credentials.