Assessment of the reliability and quality of breast cancer related videos on TikTok and Bilibili: cross-sectional study in China

BackgroundAs the most common malignant tumor in the world, breast cancer also brings a huge disease burden to China. Ordinary people are increasingly inclined to use the Internet, especially video social platforms, as a source of health information. Educating the public to obtain correct information is important to reduce the incidence of breast cancer and improve the prognosis. However, the quality and reliability of breast cancer-related video content have not been fully studied.ObjectiveThis study aims to evaluate the quality of the information of breast cancer-related videos on TikTok and Bilibili video sharing platforms and factors related to video quality.MethodsWe collected the top 100 videos about breast cancer on TikTok and Bilibili, respectively. Categorize videos according to video source and video content. Video quality and reliability were assessed using Global Quality Score (GQS) and modified DISCERN (mDISCERN) tools. We also analyzed the correlation between video quality and video likes, comments, saves, and shares.ResultsAlthough the quality and reliability of Bilibili’s breast cancer videos were higher than TikTok (p = 0.002 and p = 0.001, respectively), the video quality of both video sharing platforms was not satisfactory, with a median GQS scores of 2.00 and 3.00 and mDISCERN scores of 1.00 and 2.00, respectively. In general, the quality and reliability of videos released by medical practitioners were higher than those of non-medical practitioners, and the quality and reliability of videos covering disease-related knowledge were higher than those of news reports (all p < 0.001). Among medical practitioners, the quality of videos uploaded by doctors in breast disease was significantly lower than that of doctors in other areas (p < 0.05). There was a significant positive correlation between video quality and duration (r = 0.240, p < 0.001), a weak negative correlation between video quality and likes (r = 0.191, p < 0.01), video quality and comments (r = 0.256, p < 0.001), video ...