ArticleJMIR dermatology2025
Perception, Quality, and Accuracy of Sunscreen Content on TikTok: SkinMedia Cross-Sectional Content Analysis.
Article in JMIR dermatology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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
1 citing paper in PubMed.
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: TikTok, with more than 2 billion users worldwide, has become an influential venue for health information, including dermatologic advice. However, concerns remain about the accuracy and impact of sunscreen-related content. Objective: This study aimed to assess the quality, accuracy, and themes of popular TikTok videos about sunscreen; evaluate associations with creator credentials and promotional content; and identify implications for public health. Methods: We conducted a cross-sectional content analysis of the 100 most-liked English-language TikTok videos generated by the search term "sunscreen." Metadata, creator characteristics, Global Quality Score (GQS), accuracy, attitudes, promotional disclosures, and reference use were extracted using a structured codebook. Thematic and statistical analyses (ie, Pearson correlations, χ2, 2-tailed t tests, and ANOVA) were conducted, with significance defined as P<.05. Results: Of the top 100 videos, 74 (74%) expressed a positive attitude toward sunscreen, 35 (35%) were accurate, 57 (57%) were opinion based, and 6 (6%) were inaccurate. None of the videos cited references. GQS ratings were low: 40 (40%) videos were rated poor (score=1), 31 (31%) below average (score=2), and only 2 (2%) excellent (score=5). Promotional content appeared in 27 (27%) videos. Accuracy was negatively correlated with likes (r=-0.229; P=.02) and views (r=-0.242; P=.02), while GQS correlated positively with accuracy (r=0.270; P=.007) but not with engagement. Likes and views were strongly correlated (r=0.726; P<.001). Conclusions: Despite broadly positive sentiment toward sunscreen, misinformation and promotional bias are common in highly engaged TikTok videos, and user engagement is often unrelated to accuracy or educational quality. Dermatologists and public health experts must proactively engage on social platforms to counter misinformation and promote reliable skin health information.
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Identifiers
What OpenQuestion 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 OpenQuestion graph.