ArticleScientific reports2026
A cross-sectional analysis of the quality and characteristics of sleep apnea hypopnea syndrome videos on YouTube, Bilibili, and TikTok.
Article in Scientific reports, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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.
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.
Who cites it
3 citing papers in PubMed.
- The quality and reliability of short videos about cervical spondylosis on TikTok and Redbook: a cross-sectional study.BMC musculoskeletal disorders · 2026Article
- Alcohol-related health information on Chinese short-video platforms: a cross-sectional content analysis of Douyin and Bilibili.Scientific reports · 2026Article
- The reliability and quality of short videos as a source of dietary guidance for cardiovascular disease: a cross-sectional study.Frontiers in cardiovascular medicine · 2026Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors.
Funding
Abstract
Sleep Apnea Hypopnea Syndrome (SAHS) is a prevalent sleep disorder associated with substantial health risks, highlighting the need for improved public awareness. This cross-sectional analysis systematically evaluated the quality of SAHS-related videos on YouTube, Bilibili, and TikTok. Of 903 videos initially identified, 227 met the inclusion criteria for analysis. Cross-platform comparisons revealed that long-form platforms hosted higher-quality content, whereas short-form platforms generated greater engagement despite lower informational integrity. This study reveals a structural disconnect between informational quality and audience engagement, consistent with theories of algorithmic filtering. While professional identity remains a reliable predictor of quality, user engagement is largely driven by peripheral cues rather than medical accuracy. This study further contributes to the theoretical understanding of online health communication by situating platform-specific patterns within broader frameworks of algorithmic curation, heuristic processing, and trust formation. By integrating these theoretical perspectives with empirical quality assessments, the study offers a conceptually grounded explanation for why medically accurate content often remains less visible within algorithmic media environments. These findings underscore the need for platform-specific interventions that integrate credibility signals into recommendation algorithms to mitigate the spread of low-quality health information.
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What Socratic holds
Registered trials
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.