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        <datestamp>2026-09-28T15:30:26Z</datestamp>
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          <dc:title>Table 2_Public health communication and information quality of knee osteoarthritis–related short videos on TikTok, Kwai, and Bilibili: a cross-sectional study.xlsx</dc:title>
          <dc:creator>Yundong Xu (23618407)</dc:creator>
          <dc:creator>Qianqian Yang (203850)</dc:creator>
          <dc:creator>Jian Zhang (1682)</dc:creator>
          <dc:creator>Jin Xu (31283)</dc:creator>
          <dc:creator>Niqin Xiao (23618398)</dc:creator>
          <dc:creator>Heguo Yan (20687687)</dc:creator>
          <dc:creator>Sanjin Zeng (23618401)</dc:creator>
          <dc:creator>Shengyi Zhao (24201552)</dc:creator>
          <dc:creator>Rong Wang (59795)</dc:creator>
          <dc:creator>Zhaohu Xie (23618410)</dc:creator>
          <dc:creator>Zhaofu Li (1431001)</dc:creator>
          <dc:subject>Health Informatics</dc:subject>
          <dc:subject>China</dc:subject>
          <dc:subject>health communication</dc:subject>
          <dc:subject>information dissemination</dc:subject>
          <dc:subject>knee osteoarthritis</dc:subject>
          <dc:subject>social media</dc:subject>
          <dc:subject>video recording</dc:subject>
          <dc:description>Background&lt;p&gt;Knee osteoarthritis (KOA) is a prevalent musculoskeletal disorder and a major cause of pain and disability. As short-video platforms increasingly shape how the public accesses health information, concerns have grown regarding the quality, reliability, and completeness of KOA-related content. This study evaluated KOA-related videos on three major Chinese short-video platforms, TikTok, Kwai, and Bilibili, to compare information quality, user engagement, and implications for digital public health communication.&lt;/p&gt;Methods&lt;p&gt;In this cross-sectional study, standardized Chinese keywords were used to retrieve KOA-related videos from TikTok, Kwai, and Bilibili on December 24, 2025. After deduplication and screening, 300 videos were included, 100 from each platform. Video characteristics and engagement indicators were recorded. Information quality was assessed using the DISCERN reliability section, Global Quality Score (GQS), content completeness score (CS, range 0–10), and engagement score (ES, range 0–4). Uploaders were categorized by source type. Statistical analyses included the Kruskal–Wallis H test, chi-square test, and Spearman correlation analysis.&lt;/p&gt;Results&lt;p&gt;Substantial cross-platform differences were identified. Bilibili videos had the longest duration (median 402 s) and the highest information quality, with superior DISCERN scores (median 32), GQS (mean 4.3), and CS (mean 7), and had the highest proportion of certified medical professionals among uploaders (38.0%). TikTok videos were the shortest (median 86 s) but showed the highest user engagement, including likes, comments, shares, and the highest ES (median 3.6). TikTok and Kwai videos were generally less complete, focusing mainly on symptoms and treatment while providing limited information on etiology and prognosis. Correlation analysis showed that higher information quality and completeness were negatively associated with user interaction metrics, whereas ES was positively associated with engagement.&lt;/p&gt;Conclusions&lt;p&gt;The three major short-video platforms in China represent distinct digital health information ecosystems for KOA, revealing a consistent trade-off between scientific rigor and audience engagement. Platform recommendation mechanisms may may preferentially surface content that is more attractive and interactive rather than more accurate and comprehensive. These findings highlight an important public health challenge in the governance of online health information and suggest that improving chronic disease communication on social media will require both stronger platform-level quality prioritization and more engaging evidence-based content produced by health professionals.&lt;/p&gt;</dc:description>
          <dc:date>2026-09-28T15:30:26Z</dc:date>
          <dc:type>Dataset</dc:type>
          <dc:type>Dataset</dc:type>
          <dc:identifier>10.3389/fdgth.2026.1868584.s002</dc:identifier>
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          <dc:rights>CC BY 4.0</dc:rights>
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