Abstract
INTRODUCTION: TikTok has emerged as a popular platform for sharing medical insights, but concerns exist regarding disseminating inaccurate information on medical conditions, potentially harming patient care. This study aims to evaluate the quality and reliability of TikTok videos on uterine fibroid embolization (UFE). It also examines how video engagement and content quality vary based on the uploader type and video style. METHODOLOGY: We selected the top 100 TikTok videos on UFEs based on the number of likes since March 2024. These videos were identified using the hashtag "#UFE." Videos were categorized based on several factors, including the number of likes, comments, shares, upload date, uploader's background (academic, non-healthcare professionals (non-HCPs), non-physician, non-radiologist, and radiologist), and type of content (anecdotal, educational, and procedural). The strength of treatment recommendations was assessed for all videos using the DISCERN instrument (16 to 80), which assesses reliability of treatment information, and the Patient Education Materials Assessment Tool for Audiovisual Materials (PEMAT-A/V), which assesses understandability and actionability via a percentage score. Descriptive and ANOVA analyses were conducted with a statistical significance set at p < 0.05. RESULTS: Of the top 100 TikTok videos related to UFE, 99 were in English and one was in Spanish, which was excluded from our study. A total of 12 videos (12.12%) were uploaded by radiologists, while the majority (66, 66.67%) were created by non-HCPs. Non-radiologist physicians garnered the highest average engagement and quality scores, including the highest DISCERN score (41.07). Academic institutions achieved the highest PEMAT understandability score (80.47%). Non-HCPs ranked second in engagement but had the second-lowest PEMAT understandability score (65.96%), just above non-physician HCPs, who had the lowest score (64.68%). Educational videos (35, 35.35%) outperformed anecdotal ones (59, 59.59%) in quality, achieving higher DISCERN (40.57) and PEMAT understandability (68.85%) scores. While DISCERN scores did not significantly differ by video aim, both PEMAT understandability (p = 0.01763) and DISCERN (p = 0.00166) scores showed significant differences based on the uploader type. DISCUSSION: Our analysis of the top 100 TikTok videos on UFE reveals a landscape dominated by non-physician contributors, with only 12 videos created by radiologists. Despite this, content from non-radiologist physicians garnered the highest engagement and exhibited the highest quality, underscoring the influence of credible medical voices on social media. While anecdotal content prevails, educational videos achieved better quality scores, highlighting the value of evidence-based communication. These findings suggest a critical opportunity for radiologists and other physicians to enhance patient education, counter misinformation, and leverage TikTok as a low-cost, high-impact platform for healthcare communication. However, limitations include a narrow focus on highly liked content and exclusion of TikTok's algorithmic influence.