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<p>With the rising prevalence of diabetic retinopathy (DR), short videos have become a key source of health information for the public. This study aims to evaluate the quality and interaction performance of DR educational short videos, and explore the impacts of content quality, creator attributes, and platform factors on user interaction. We analyzed 146 DR-themed videos from Douyin and Bilibili, assessed content quality using four international benchmarks (JAMA, mDISCERN, GQS, and PEMAT), and measured interaction via the entropy weight method (EWM). Through non-parametric tests, Spearman correlation analysis, quantile regression, mediation analysis, and moderation analysis, the study found that: overall content quality was moderate, with user interaction indicators showing severe right-skewness; all quality dimensions were significantly positively correlated with each other, while JAMA scores were significantly negatively correlated with the weighted sum of interactions; significant differences existed in multiple indicators across different creator backgrounds, professional titles, and platforms; the impact of quality indicators on interaction was heterogeneous and varied by platform. Conclusions suggest that content creation should be optimized based on platform characteristics, and information seekers should develop habits of rational screening and cross-validation.</p>

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Quality, interaction, and platform-creator heterogeneity of DR short videos on Douyin and Bilibili: a cross-sectional study

  • 期刊论文

  • 出版模式：

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  • 发表日期：

    2026年5月6日

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  • Li Zhong,
  • Qingruo Mao,
  • Siyan Liu,
  • Mengxia Zeng,
  • Jing Yan,
  • Tiancai Wen

摘要

With the rising prevalence of diabetic retinopathy (DR), short videos have become a key source of health information for the public. This study aims to evaluate the quality and interaction performance of DR educational short videos, and explore the impacts of content quality, creator attributes, and platform factors on user interaction. We analyzed 146 DR-themed videos from Douyin and Bilibili, assessed content quality using four international benchmarks (JAMA, mDISCERN, GQS, and PEMAT), and measured interaction via the entropy weight method (EWM). Through non-parametric tests, Spearman correlation analysis, quantile regression, mediation analysis, and moderation analysis, the study found that: overall content quality was moderate, with user interaction indicators showing severe right-skewness; all quality dimensions were significantly positively correlated with each other, while JAMA scores were significantly negatively correlated with the weighted sum of interactions; significant differences existed in multiple indicators across different creator backgrounds, professional titles, and platforms; the impact of quality indicators on interaction was heterogeneous and varied by platform. Conclusions suggest that content creation should be optimized based on platform characteristics, and information seekers should develop habits of rational screening and cross-validation.