Abstract
Hypothyroidism is a common endocrine disorder that significantly impacts patients' quality of life. In recent years, short-video platforms have become an important source of health information for the public. This study aimed to evaluate the content, quality, and reliability of hypothyroidism-related videos on TikTok and Bilibili. We searched for videos related to "hypothyroidism" on TikTok and Bilibili and included the top 150 videos based on comprehensive ranking, excluding irrelevant, duplicate, advertisement, and course-related videos. Extracted variables included video duration, number of likes, collections, comments, shares, uploader type, and content themes. The Global Quality Score and modified DISCERN (mDISCERN) tools were used to assess each video. Mann-Whitney U tests and Kruskal-Wallis tests were used to compare differences, and Spearman correlation analysis was performed to examine associations between engagement metrics and video quality. A total of 270 videos were included. Video content primarily focused on treatment (62.2%) and symptoms (60.0%), whereas prevention (7.0%) and epidemiology (4.1%) were notably underrepresented. Videos on Bilibili were longer but had lower engagement (P < .05), while TikTok videos had higher mDISCERN scores. Videos uploaded by specialists received the highest Global Quality Score and mDISCERN scores (P < .05). Engagement metrics were strongly intercorrelated (P < .05), but showed no significant association with video quality (P > .05). Video length demonstrated a weak correlation with quality (P < .05). This study revealed that hypothyroidism-related short videos generally have incomplete content structures, particularly with insufficient coverage of prevention and epidemiology. The overall quality and reliability were suboptimal, with videos by specialists demonstrating higher quality. Future efforts should encourage greater participation of specialists in short-video health education content creation, and platforms should strengthen content oversight and optimize algorithms to enhance the visibility of high-quality video content.