Videos on Bilibili, TikTok, and Xiaohongshu as Sources of Medical Information on Adenoid Hypertrophy: Cross-Sectional Content Analysis.

Background: The clinical diagnosis rate of adenoid hypertrophy (AH) in children has increased in recent years, drawing growing attention from parents. Short-video platforms such as Bilibili, TikTok, and Xiaohongshu host a large volume of educational content on this condition. However, the quality and reliability of this information remain unclear. Objective: This study aimed to evaluate the completeness, understandability, actionability, reliability, and overall quality of short videos on AH across Bilibili, TikTok, and Xiaohongshu and to explore factors associated with these quality metrics, including uploader characteristics and engagement indicators. Methods: We collected 220 videos (Bilibili: n=90, 40.9%; TikTok: n=63, 28.6%; and Xiaohongshu: n=67, 30.5%) using newly registered accounts. Two independent reviewers evaluated video quality using a 6-item content completeness scale (score range 0-12), the Patient Education Materials Assessment Tool for Audiovisual Materials, the modified DISCERN instrument, and the Global Quality Scale (GQS). Interrater reliability was high (Cohen κ=0.77-0.993). Completeness assessed essential informational components of AH. As data were nonnormally distributed, results are presented as median (IQR). Cross-platform comparisons were conducted using the Kruskal-Wallis H test with post hoc Mann-Whitney U tests (with Bonferroni correction). Spearman correlation was used to explore associations between video characteristics (ie, duration and engagement metrics) and quality outcomes. Stepwise linear regression identified independent predictors of overall quality (GQS). Results: Video duration differed significantly across platforms (Bilibili: median 113.5, IQR 66.5-271.5 seconds; TikTok: median 73, IQR 44-100 seconds; and Xiaohongshu: median 63, IQR 41-127.5 seconds; P<.001). Bilibili videos demonstrated higher completeness than videos on the other 2 platforms (Bilibili: median 2, IQR 1.5-4.0; TikTok: median 1.5, IQR 0.5-2.0; and Xiaohongshu: median 1.5, IQR 0.5-2.8; P<.001); overall differences were observed for understandability and reliability, but pairwise comparisons did not reach statistical significance after Bonferroni correction. Xiaohongshu videos showed greater actionability than TikTok videos (P=.011). Medical professionals (n=158, 71.8%) had higher understandability than nonprofessionals (n=158, 81.8% vs n=62, 66.7%; P=.001). Video duration positively correlated with completeness (ρ=0.64, 95% CI 0.56-0.71; P<.001). Shares showed weak positive correlations with completeness and actionability. Stepwise regression identified understandability (using the Patient Education Materials Assessment Tool-Understandability) as the strongest independent predictor of overall quality (GQS), followed by actionability, video duration, and uploader type; engagement metrics and platform did not enter the final model. Conclusions: The quality of AH-related videos on Chinese short-video platforms is generally suboptimal. Bilibili offers higher completeness, while Xiaohongshu excels in actionability and interactivity. Understandability is the strongest predictor of overall quality, surpassing uploader type and engagement metrics. To improve online health information, platforms should move beyond engagement-based algorithms, and health care professionals should prioritize clear, actionable content.