Cross-sectional study evaluates BPPV-related video quality on TikTok and Bilibili, highlighting low reliability and accuracy.
Background Benign Paroxysmal Positional Vertigo (BPPV) is common with high recurrence. Social media platforms like TikTok and Bilibili offer health-related content, but their quality and reliability remain unclear. Objective This study aims to evaluate the content and quality of BPPV-related videos on TikTok and Bilibili. Methods A total of 199 BPPV-related short videos from TikTok and Bilibili were collected between September 25 and 28, 2025. Video characteristics were extracted, and quality was assessed using the Global Quality Score (GQS) and modified DISCERN scale (mDISCERN). Content accuracy was evaluated based on clinical guidelines. Non-parametric tests and Spearman correlation analysis were used to compare uploader groups and explore the relationship between engagement and video quality. Results The videos had a median duration of 99 seconds. TikTok videos showed significantly higher interaction metrics than those on Bilibili (all P < 0.001). Content primarily covered clinical presentation, diagnosis, and treatment, while epidemiology and prevention were underrepresented. The median GQS was 3.00, and the median mDISCERN score was 2.00, indicating low quality and reliability. Professional videos had significantly higher mDISCERN scores than individual user videos ( P < 0.001), but both groups had low scores. For content accuracy, the lower quartile for professional videos was exceptionally low (Q1 = 0.00), with 25% of these videos containing significant errors or omissions. No significant correlations were found between engagement metrics and quality scores ( r = 0.00-0.11, P > 0.05). Conclusion BPPV-related short videos on TikTok and Bilibili generally have low quality, reliability, and accuracy. While professional videos are more reliable, they lack evidence-based content and omit key information. Strengthening content moderation and increasing professional involvement is crucial for improving digital health education.
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Zheng et al. (2026) studied this question.
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