Labor induction and social media influence: An analytical video-based cross-sectional study to assess quality, reliability, and accuracy of related content on TikTok

BACKGROUND: TikTok pregnancy-related information content has not yet been investigated. OBJECTIVE: To assess the quality, reliability, and misinformation on TikTok videos regarding induction of labor (IOL). STUDY DESIGN: A cross-sectional analysis of TikTok videos, employing the "Induction of Labor" keyword, was conducted on the 13th of January 2025. All videos retrieved under this search term were evaluated. The TikTok materials were compared between patients and healthcare with the following tools: Patient Education Materials Assessment Tool (PEMAT A/V), the modified Development of a Quality Index for Health Information (mDISCERN), global quality scale (GQS), and video information and quality index (VIQI). RESULTS: One hundred fifty TikTok videos were examined. The contents were created mainly from patients 52 % (78/150), 39 % from healthcare (59/150), and 9 % (13/150) from other sources. Healthcare content showed a higher PEMAT A/V for actionability and understandability median score, 81.8 % and 66.7 %, respectively, compared to the patient-generated content median score of 75.0 %, and 33.3 % (P = 0.01 and P < 0.001). On VIQI, healthcare videos outperformed patients' content, in information accuracy (4.0 vs 2.5), precision (4.0 vs 2.5), and total VIQI score (14.0 vs. 10.0; all P < 0.001). Healthcare and other sources had a median of 2.0 for mDISCERN reliability (P < 0.001). GQS showed a median of 4.0 for healthcare content versus 2.5 median for patients' content (P < 0.001). CONCLUSION: Patients' TikTok content reporting low scores on all validated assessment tools. Healthcare videos reported a higher score of understandability, actionability, and accuracy. These findings suggest that obstetric healthcare content on social media are probably necessary to offer IOL evidence-based information.