The pivotal role of video duration in health science popularization: A mixed-methods analysis integrating machine learning and fuzzy-set qualitative comparative analysis

Background Short video platforms have become important channels for the public to obtain health information, but the quality of health science popularization content varies greatly. Existing studies lack a comprehensive exploration of the determinants of video quality and their interaction mechanisms. Objective This study aimed to identify the key features influencing the quality of cerebrovascular disease health science popularization short videos and clarify their configurational effects. Methods Python web-crawling technology was used to collect health science popularization short videos on TikTok related to cerebrovascular diseases over the past year, and the video quality was evaluated using the Grade Quality Score (GQS) tool by two medical professionals. Eight machine learning models were constructed to identify key quality-related features. The joint effect of six features was analyzed for necessity and sufficiency by using the fuzzy set qualitative comparative analysis (fsQCA) method. Finally, the Kruskal-Wallis H test was employed to evaluate differences in quality among videos of varying duration. Results A total of 541 valid videos were collected. Most videos were posted by medical staff (77.27%), among which high-quality videos (with GQS > 3) accounted for 14.42%. The importance of video duration reached 30.5%, making it the most crucial feature affecting video quality. The fsQCA results indicated that short duration was one of the conditions for high-quality videos, with the optimal duration being 3 to 5 minutes. Conclusions Video duration was the main determinant of the quality of cerebrovascular disease health science popularization short videos. Improving the short-video communication skills of medical professionals and optimizing video duration are effective ways to enhance the quality of health science popularization content.