Authors
Abby Shah, Aleezay Khan, Alexander Schafer, Abriel Reister, Jared Bengston, Nour Rammal, Nicholas Mulder, Coby Fan, Jeffrey S Jones
Published in
The American journal of emergency medicine. Aug 15, 2026. Epub Aug 15, 2026.
Abstract
TikTok is a major platform for hazardous user-generated content involving adolescents and young adults. Hazardous videos extend beyond named challenges to include stunts, dares, and copycat behaviors that may encourage imitation through algorithmic promotion and peer engagement. This study characterized hazardous TikTok videos, identified their mechanisms and clinical consequences, explored why adolescents and young adults engage with them, and examined the social network and algorithmic features that accelerate their spread.
This descriptive qualitative content analysis examined public TikTok videos depicting potentially hazardous behaviors among adolescents and young adults. Videos were identified through direct TikTok searches and supplemented by media, regulatory, and toxicology sources. They were then archived, transcribed, and coded using a standardized abstraction form. Qualitative thematic analysis examined motives for participation and dissemination mechanisms, while physician review assessed medical risk and misinformation or disinformation.
Sixty-nine videos met inclusion criteria; 55 (79.7%) addressed highly prevalent youth challenges and had more than 30,000 views. Twenty-eight videos (40.6%) were associated with challenge types with documented fatalities, and all identified behaviors were deemed medically dangerous. Medical misinformation or disinformation was present in 62 of 69 videos (90.0%). Dissemination was facilitated by recommendation-feed amplification, shared audiovisual templates, hashtag aggregation, social proof, behavioral reinforcement, and moderation evasion through re-uploads, altered hashtags, or coded language. Interrater reliability was substantial (Kappa = 0.80).
Hazardous TikTok videos are widely disseminated, medically serious, and shaped by misinformation, peer influence, and algorithmic amplification. These findings are relevant to clinicians and public health professionals seeking to recognize, document, and prevent social media-related injuries.
PMID:
42618391
Bibliographic data and abstract were imported from PubMed on 20 Aug 2026.
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