Beyond virality: evaluating evidence-based content delivery in social media-based pediatric orthodontic education.

BACKGROUND: Malocclusion, affecting over 260 million Chinese children, demands early orthodontic intervention to address both physiological and psychosocial impacts. While social media platforms have become primary sources of health guidance for parents, their algorithm-driven ecosystems often prioritize engagement over scientific rigor. Content creators, including unqualified influencers, frequently disseminate unverified claims about treatment timing, methods, and outcomes. Such misinformation may exacerbate parental anxiety, or promote non-evidence-based interventions. This study evaluates the quality of high-engagement videos across platforms, identifies systemic gaps enabling misinformation proliferation, and proposes safeguards to align content dissemination with evidence-based practices. METHODS: A cross-sectional analysis was conducted on 200 top-viewed videos (100 per platform) retrieved via keyword searches on TikTok and Rednote. Videos were assessed using three validated tools: Global Quality Score (GQS), JAMA benchmark criteria, and a Modified DISCERN score. Statistical analyses included Mann-Whitney U tests, Spearman correlations, and inter-rater reliability assessments. RESULTS: TikTok videos exhibited significantly higher engagement (likes, shares) and superior quality scores (GQS: 2.89 vs. 2.32; mDISCERN: 1.75 vs. 1.20) compared to Rednote (all P < 0.01). Orthodontist-produced content scored higher in JAMA and mDISCERN across both platforms (P < 0.01). On Rednote, quality metrics (GQS, mDISCERN) correlated positively with user engagement and video duration (R: 0.27–0.49, P < 0.01), whereas TikTok showed inverse trends between quality and engagement (R: -0.23 to -0.35, P < 0.05). Inter-rater reliability was excellent (ICC: 0.780–1.000). CONCLUSIONS: Despite higher engagement metrics, TikTok demonstrated superior video quality compared to Rednote, yet both platforms exhibited concerning inconsistencies in orthodontic information accuracy, a reflection of systemic algorithm-driven health misinformation risks. Content from credentialed professionals consistently outperformed non-expert sources in reliability, underscoring the public health dangers of prioritizing influencer-generated material lacking scientific validation. Strategic integration of medical expertise into content algorithms, standardization of quality verification frameworks, and enhanced public health literacy are imperative to counteract misinformation propagation and align social media’s educational potential with evidence-based orthodontic care.