Medicine (Baltimore). 2026 Jun 12;105(24):e49308. doi: 10.1097/MD.0000000000049308.
ABSTRACT
Diabetic nephropathy (DN) is a common, life-threatening complication of diabetes, contributing to the global disease burden. With the advent of video platforms, health information is being more widely disseminated. However, the quality of such content varies widely, which may influence the public’s perception. This study aimed to evaluate the upload sources, content, and characteristics of DN-related videos on TikTok and Bilibili and to explore descriptive associations between video quality scores and selected video characteristics. This cross-sectional content analysis included 166 DN-related videos. Video quality was assessed using the Global Quality Scale (GQS), modified DISCERN (mDISCERN), and Journal of the American Medical Association (JAMA) benchmark criteria. Descriptive subgroup and correlation analyses were performed to examine cross-sectional associations between video quality scores and selected video attributes. No multivariable adjustment was performed. In unadjusted cross-sectional comparisons, TikTok videos showed higher observed engagement counts at the time of data collection than Bilibili videos, whereas no statistically significant differences were observed in video duration or quality indicators after correction for multiple comparisons. In unadjusted descriptive subgroup comparisons, videos uploaded by experts showed more favorable results in selected quality-related measures, particularly GQS and JAMA, than videos uploaded by individual users. No clear association was observed between video quality and snapshot engagement metrics recorded at the time of retrieval. This study identified descriptive differences in the presentation and dissemination patterns of DN-related health information across TikTok and Bilibili. Because the analyses were observational, cross-sectional, and unadjusted for potential confounders such as video length and content type, the observed differences between platforms and uploader types should be interpreted as descriptive associations only rather than independent effects.
PMID:42299601 | DOI:10.1097/MD.0000000000049308
