Cross-sectional analysis of the reliability and engagement metrics of YouTube videos on semaglutide for weight loss.
Medicine (Baltimore) · 2026
Last updated 2026-07-22| Journal | Medicine (Baltimore), 2026 |
|---|---|
| Citations | 0 |
| Molecules | semaglutide |
Abstract
This study aimed to assess the quality and reliability of health information in the 100 most-viewed YouTube videos related to semaglutide for weight loss, as of December 2024. The study also explored the relationship between engagement metrics and content quality, with attention to the prevalence of misinformation. A cross-sectional evaluation was conducted in December 2024. The top 100 English-language YouTube videos retrieved using the search term "semaglutide weight loss" were analyzed. Each video was assessed using 2 validated tools: the Global Quality Score and the Modified DISCERN (quality assessment tool for consumer health information) instrument. Viewer engagement data - including likes, comments, and views - were recorded. Statistical analyses included descriptive statistics and multiple linear regression to examine relationships between engagement metrics and content quality. Videos from academic and healthcare-affiliated sources generally scored higher in quality assessments, while those produced by individual users tended to lack source citations and balanced information. Although certain engagement metrics, such as the number of likes and comments, showed modest associations with higher Global Quality Scores, view count did not consistently predict quality. A notable portion of user-generated videos lacked discussion of semaglutide's risks and contraindications. The study highlights the variability in quality among semaglutide-related videos on YouTube. Engagement does not necessarily reflect the reliability of content, underscoring the importance of guiding viewers toward credible health sources. Enhancing digital health literacy and promoting greater visibility of evidence-based content may help improve the quality of health information encountered on widely used digital platforms.
Verbatim abstract via PubMed 42260873 ↗
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