Quality, Reliability, and Dissemination of Oseltamivir-Related Health Information on Chinese Short-Video Platforms: A Cross-Platform Content Analysis of Douyin and Bilibili

Quality, Reliability, and Dissemination of Oseltamivir-Related Health Information on Chinese Short-Video Platforms: A Cross-Platform Content Analysis of Douyin and Bilibili | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Article Quality, Reliability, and Dissemination of Oseltamivir-Related Health Information on Chinese Short-Video Platforms: A Cross-Platform Content Analysis of Douyin and Bilibili Sicong Hu, Yujun Xiong, Qinwen Fei, Tian Lv, Tianjiao Meng This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-9104007/v1 This work is licensed under a CC BY 4.0 License Status: Under Review Version 1 posted 7 You are reading this latest preprint version Abstract Background Oseltamivir, an antiviral for influenza, is frequently discussed on short-video platforms like Douyin and Bilibili, yet the quality of these videos remains unclear. Objective This study evaluated the quality, reliability, and content of oseltamivir-related videos on Douyin and Bilibili, comparing platforms and uploader types. Methods We conducted a cross-sectional analysis of 188 videos (100 from Douyin, 88 from Bilibili). Quality and reliability were assessed using GQS, mDISCERN, JAMA benchmarks, and PEMAT. Video characteristics, uploader types, and engagement metrics were analyzed. Results Douyin had more professional uploaders (83.0% vs. 35.2%). Videos from specialist doctors scored higher across most tools. Douyin videos scored higher in GQS, PEMAT-A, and JAMA, while Bilibili videos scored higher in PEMAT-U. Both platforms focused on basic introductions, neglecting safety and efficacy. Longer videos correlated with higher PEMAT-U scores, but user engagement did not correlate with quality. Conclusions Video quality varies significantly. Professional uploaders, especially doctors, provide higher-quality content. User engagement is not a reliable indicator of information quality, highlighting the need for better oversight. Health sciences/Health care Health sciences/Medical research Oseltamivir Short-video platforms Health information quality Douyin Bilibili Content analysis Figures Figure 1 Figure 2 Figure 3 Figure 4 Figure 5 Figure 6 1. Introduction Short-video platforms have grown quickly. They have changed how people create, share, and get health information. In China, Douyin has 907 million monthly active users. Bilibili has 225 million monthly active users[ 1 ]. These platforms are now key places where the public looks for medical knowledge. This includes information on preventing disease, getting diagnosed, and using medicine [ 2 , 3 ]. Short videos are more engaging and easier to access than traditional text-based health education. They can spread information fast [ 4 – 7 ]. But it is very easy to create content on these platforms. There is no strict peer review. This causes major worries about how accurate, complete, and reliable the health information is [ 8 , 9 ]. Information about medicine is especially at risk for being wrong on short-video platforms. Wrong or incomplete drug information can lead to bad self-medication, delays in seeing a doctor, poor treatment follow-up, and avoidable side effects. Past studies checking health information on social media often find big differences in content quality. Many videos do not use evidence-based references, lack transparency, or are not balanced[ 10 – 12 ]. More people are using short videos to make health decisions. So, from a public health view, it is very important to check the quality of drug-related content. Oseltamivir is a drug that stops the flu virus. It is widely used to treat and prevent influenza. It is recommended in many national and international guidelines[ 13 ]. In China, doctors often prescribe oseltamivir during flu seasons. The drug is also talked about a lot in public media, especially when flu activity is high[ 14 ]. Even though it is common, people often have wrong ideas about when to use it, when to start taking it, the correct dose, how long to take it, and its possible side effects[ 15 , 16 ].Wrong information can lead to incorrect use, make the treatment less effective, and create safety risks. This shows why accurate public education about this drug is important. Douyin and Bilibili are two major but different short-video platforms in China. They have different user groups, content styles, and ways of sharing information. Douyin has a very large user base. It uses algorithms to recommend content and information spreads quickly. Bilibili traditionally has younger, more educated users. It focuses more on longer, explanatory videos[ 17 , 18 ]. Recent studies looking at disease-specific information on these platforms—like for lung cancer, Alzheimer's disease, and stroke—keep finding big differences in video quality. They find a weak link between how much the public engages with a video and how reliable its information is. They also find much room to improve the content's educational value[ 19 – 21 ].These platform features might affect how oseltamivir information is shown and its overall quality and reliability. But direct comparisons of drug-related content across platforms are still rare. So far, most studies checking online health information look at diseases, lifestyle, or general medical topics. There are few systematic checks of medication-specific content on Chinese short-video platforms[ 10 ]. There is especially a lack of analyses that use several proven assessment tools together to check content quality, reliability, transparency, and understandability all at once[ 22 ].Filling this gap is important. It will give useful information to doctors, public health workers, and platform regulators about how drug information is currently shared. Therefore, this study aimed to check the quality, reliability, and educational value of oseltamivir-related videos on Douyin and Bilibili. We used established tools: the Global Quality Score (GQS), the modified DISCERN (mDISCERN) tool, the Journal of the American Medical Association (JAMA) benchmark criteria, and the Patient Education Materials Assessment Tool (PEMAT). We did a cross-platform content analysis. We wanted to find the strong points and weak points in the current video content. Our goal is to give evidence-based suggestions for sharing more accurate and reliable medication information on short-video platforms. 2. Methods 2.1 Study Design We designed this study as a cross-sectional content analysis. Our goal was to evaluate the quality, reliability, and educational features of oseltamivir-related videos on two major Chinese short-video platforms: Douyin and Bilibili. We developed our methods by looking at how earlier studies assessed online health information quality. We also followed standard reporting practices for this type of digital media research. In this cross-sectional investigation, we collected publicly available short videos from Douyin (the Chinese counterpart to TikTok, http://www.douyin.com) and Bilibili (http://www.bilibili.com). A detailed introduction of these two platforms, including their founding dates, positioning, core features, user base, and content ecosystem, is provided in Supplementary Table 1. 2.2 Data Sources and Video Selection 2.2.1 Search Strategy We did a systematic search on both Douyin and Bilibili on December 8, 2025. We used the Chinese keyword “奥司他韦” (oseltamivir). From each platform, we took the top 100 videos that the platform's search ranked as most relevant. To make sure the engagement numbers (like likes and comments) were stable, we only included videos uploaded more than one week before our search date. We wanted to avoid bias from personalized algorithms. So, before searching, we cleared all browser history, cache, cookies, and autofill data. We then used a newly registered account for each platform. Each account used a different, unused mobile phone number. This ensured our past activity did not affect which videos we saw. 2.2.2 Eligibility Criteria (1) Inclusion Criteria: We included videos if they: were in Chinese; focused on oseltamivir health information; were in the top 100 search results for relevance; and were uploaded more than one week before we collected data. (2) Exclusion Criteria: We excluded videos if they: were not about oseltamivir or medication education; were mainly ads or promotions; or were duplicates on or across the platforms. 2.2.3 Video Screening Process We first got 200 videos (100 from each platform).On Douyin, no videos met exclusion criteria, and all 100 videos were retained.On Bilibili, 12 videos were excluded, including 8 duplicated videos, 1 advertisement, and 3 irrelevant videos.After screening, a total of 188 videos were included in the final analysis, comprising 100 Douyin videos and 88 Bilibili videos.The detailed video selection and exclusion process is illustrated in Figure 1 (flowchart). The detailed information of all included videos, including video links and extracted evaluation variables, is provided in the Supplementary Data. 2.3 Data Extraction Two reviewers independently watched all included videos and filled out a standard form to collect data. We extracted the following information: 2.3.1 General Video Characteristics The following general characteristics were extracted for each included video: (1) video duration (in seconds); (2) number of likes; (3) number of favorites (collections); (4) number of shares; (5) number of comments; and (6) video uploader identity. Uploaders were categorized into four groups: individuals (with no medical background), specialist physicians (e.g., from respiratory medicine, infectious diseases, or pediatrics), non-specialist physicians, and news media or organizations. For subgroup analysis, uploaders were further dichotomized into: professional sources (comprising both specialist and non-specialist physicians) and non-professional sources (comprising individuals and media/institutional accounts). The distribution of uploader identities is presented in Figure 2. 2.3.3 Video Content Classification Each video was assessed for the presence or absence of the following content domains related to oseltamivir: (1) General introduction (drug name and therapeutic effects); (2) Usage and contraindications; (3) Safety information, including use in special populations (e.g., children, elderly, pregnant women); (4) Evaluation of drug efficacy; and (5) Pharmacological mechanisms, including comparisons with similar antiviral medications. The frequency of videos covering each content domain on Douyin and Bilibili is summarized in Figure 3. 2.4 Quality and Reliability Assessment Video quality and reliability were evaluated using four validated instruments. 2.4.1 Global Quality Score (GQS) The overall educational quality, flow, and usefulness of the videos for patients were assessed using the Global Quality Scale (GQS)[23]. Videos were rated on a 5-point Likert scale (see Supplementary Table 2 for detailed criteria), with higher scores indicating better overall quality. 2.4.2 Modified DISCERN (mDISCERN) The modified DISCERN (mDISCERN)[19,24]tool was applied to evaluate the reliability and credibility of the video content. This tool is specifically designed to assess the trustworthiness of health information by addressing five key yes/no questions: clarity, source credibility, balance, provision of references, and discussion of uncertainties. Each affirmative response was awarded one point, yielding a total score ranging from 0 to 5 (see Supplementary Table 3 for the specific criteria). 2.4.3 JAMA Benchmark Criteria The Journal of the American Medical Association (JAMA)[25-27] benchmark criteria were used to assess the transparency and accountability of the video content by evaluating four key elements: authorship, attribution (source citation), currency (timeliness), and disclosure of conflicts of interest. Each criterion was scored as 1 point if clearly present, yielding a maximum total score of 4 (see Supplementary Table 4 for details). 2.4.4 Patient Education Materials Assessment Tool for Printable Materials (PEMAT-P) Although PEMAT-P[28,29]was originally developed for printable patient education materials, it was applied in this study to evaluate the educational content of health-related videos, with a focus on understandability and actionability rather than audiovisual production quality. This approach has been commonly adopted in previous studies assessing structured health information delivered through digital and social media formats. PEMAT-P is a validated instrument developed by the Agency for Healthcare Research and Quality (AHRQ) and assesses educational quality across two core domains: understandability and actionability. The understandability domain evaluates whether materials are easy to comprehend for individuals with varying levels of health literacy and includes items addressing clarity of purpose, word choice, use of numbers, organization, layout and design, and appropriate use of visual aids (Items 1–19). The actionability domain assesses whether materials clearly identify actions users can take and provide sufficient guidance to support those actions (Items 20–26). Each item was scored using a binary rating system (1 = criterion met; 0 = criterion not met; NA = not applicable) according to the standardized instructions in the PEMAT-P User’s Guide. Domain-specific scores were calculated by dividing the total points earned by the number of applicable items (excluding NA responses) and multiplying by 100. Consistent with established guidance, scores of ≥70% were considered indicative of acceptable educational quality[30]. Detailed scoring criteria are provided in Supplementary Table 5. 2.5 Reviewer Training and Inter-Rater Reliability All videos were independently assessed by two trained reviewers(Tianjiao Meng and Qinwen Fei) with medical backgrounds. Prior to formal evaluation, reviewers underwent calibration sessions to ensure consistent understanding of scoring criteria. Discrepancies were resolved through discussion, and consensus was reached with the involvement of a third reviewer(Tian Lv) when necessary. 2.6 Statistical Analysis Descriptive statistics were used to summarize video characteristics, content domains, and quality scores. Continuous variables were presented as means with standard deviations or medians with interquartile ranges, as appropriate, while categorical variables were expressed as frequencies and percentages. Comparisons of quality and reliability scores among different uploader groups were conducted using non-parametric tests. Correlations between general video engagement metrics and quality or reliability scores were assessed using correlation analyses. Statistical analyses were performed using standard statistical software, with a two-sided P value < 0.05 considered statistically significant. The distribution of quality and reliability scores among uploader categories is illustrated in Figure 4, comparative analyses are shown in Figure 5, and correlations between video engagement metrics and quality or reliability scores are presented as a heatmap in Figure 6. The present study analyzed publicly available videos from Douyin and Bilibili platforms. No human participants were involved, and no identifiable personal information was collected. The study protocol was reviewed and exempted from ethical approval by the Ethics Committee of Zhuji People’s Hospital. Informed consent was waived. 3. Results 3.1 Overall characteristics of videos across platforms Table 1 summarizes the characteristics of oseltamivir-related videos on Douyin and Bilibili, including engagement metrics, uploader types, content quality scores, and content coverage. A total of 188 videos were analyzed, comprising 100 videos from Douyin and 88 from Bilibili. Videos on Douyin demonstrated substantially higher engagement across all interaction metrics, including likes (26,927.48 ± 95,272.25 vs. 1,310.64 ± 4,542.54), collections (14,460.32 ± 43,966.02 vs. 533.35 ± 1,423.97), comments (1,225.04 ± 3,734.08 vs. 198.89 ± 417.90), and shares (24,752.58 ± 103,189.66 vs. 780.45 ± 3,713.77). In contrast, videos on Bilibili were markedly longer in duration, with a mean length of 173.86 ± 168.91 seconds compared with 92.57 ± 55.03 seconds on Douyin. Regarding uploader composition, Douyin featured a significantly higher proportion of professional contributors, particularly professional physicians (47.0% vs. 18.2%). Overall, professional uploaders accounted for 83.0% of videos on Douyin, compared with 35.2% on Bilibili, where individual uploaders constituted the largest group (43.2%). In terms of content quality, videos on Douyin achieved higher mean scores for GQS (2.92 ± 0.66 vs. 2.47 ± 0.90), PEMAT-U (77.49% ± 16.46 vs. 67.74% ± 17.47), PEMAT-A (64.10% ± 20.60 vs. 48.06% ± 24.68), and JAMA criteria (2.04 ± 0.35 vs. 1.57 ± 0.60). In contrast, mDISCERN scores were comparably low across both platforms (2.06 ± 0.42 on Douyin vs. 2.01 ± 0.63 on Bilibili). With respect to content coverage, most videos focused on basic introduction and usage-related information, whereas pharmacological mechanisms, safety considerations, and effect evaluation were less consistently addressed across both platforms (Table 1). 3.2 Platform-level differences in quality scores and uploader characteristics Platform-level differences in uploader composition and video quality are illustrated in Figs. 1 – 3 . Douyin was characterized by a substantially higher proportion of videos uploaded by professional physicians compared with Bilibili, whereas Bilibili featured a larger share of content produced by individual uploaders and media organizations. As shown in Fig. 1 , videos uploaded by specialist physicians consistently demonstrated higher distributions of Global Quality Score (GQS), PEMAT Understandability (PEMAT-U), and PEMAT Actionability (PEMAT-A) compared with other uploader types. In contrast, videos produced by individuals without a medical background exhibited lower score distributions across these domains. Platform-level comparisons of quality and reliability scores are presented in Figs. 2 and 3 . Videos on Douyin achieved significantly higher GQS, PEMAT-A, and JAMA benchmark scores than those on Bilibili, indicating superior overall educational quality, greater actionability, and more complete disclosure practices. However, no significant difference was observed between the two platforms for mDISCERN scores (Fig. 3 ), suggesting that reliability-related criteria—such as source citation, balance of information, and reference to uncertainties—were similarly limited across both platforms. 3.3 Content coverage and video length Analysis of content domains revealed that videos on both platforms predominantly addressed basic introduction and usage-related information, while pharmacological actions, safety considerations, and effect evaluation were less frequently covered (Fig. 4 , Table 1). This pattern was consistent across uploader types and platforms. Videos on Bilibili demonstrated significantly higher PEMAT-U scores, indicating greater understandability for general audiences. This difference corresponded with the longer average video duration observed on Bilibili. As illustrated in Fig. 6 , video length showed a moderate positive correlation with PEMAT-U ( r = 0.64), suggesting that longer videos may facilitate more detailed explanations and clearer presentation of information. 3.4 Platform-level comparison of quality and reliability scores(Figure 5 ) Platform-specific comparisons of video quality and reliability scores are presented in Fig. 5 . Videos on Douyin achieved significantly higher Global Quality Score (GQS), PEMAT Actionability (PEMAT-A), and JAMA benchmark scores than those on Bilibili, whereas videos on Bilibili demonstrated significantly higher PEMAT Understandability (PEMAT-U) scores. No significant difference was observed between the two platforms for mDISCERN scores. 3.5 Associations between engagement metrics and content quality Spearman correlation analyses examining the relationships between video engagement metrics and quality or reliability scores are presented in Fig. 6 . Strong positive intercorrelations were observed among engagement indicators themselves, including likes, comments, shares, and collections (all r > 0.90), indicating that videos performing well on one engagement metric tended to perform similarly on others. In contrast, no significant associations were identified between engagement metrics and core indicators of content quality or reliability, including GQS, mDISCERN, and JAMA benchmark scores. This finding suggests a clear disconnect between user engagement and the educational quality or informational reliability of the videos. Additionally, video length demonstrated weak positive correlations with GQS ( r = 0.26) and mDISCERN ( r = 0.38), as well as a weak negative correlation with JAMA score ( r = − 0.23). 4. Discussion In this study we analyzed oseltamivir-related videos from two Chinese video platforms. We looked at who uploaded the videos, what topics they covered, how good the information was, and how users interacted with them. We found several key things. First, videos made by medical professionals, especially specialist doctors, had much higher educational quality and were more actionable than videos from non-professionals. Second, there were clear differences between Douyin and Bilibili in both style and quality. Third, user popularity metrics like likes did not show a strong link with our measures of information quality and reliability. Our findings show how the person who uploads a video and the platform itself together affect whether the information meets medical standards. 4.1 Influence of Uploader Professional Background on Video Quality We found that the uploader's professional background is very important. Videos from specialist doctors got higher scores for GQS, PEMAT-A, and PEMAT-U. This means their videos had better structure, clearer explanations, and more useful advice. Videos from people without a medical background scored much lower. This matches what other studies have found for many other health topics. Those studies also show that videos from doctors are usually more accurate, complete, and useful for education[ 31 – 35 ]. Specialist doctors know more about the topic. They also know more about clinical guidelines and real-world prescribing. However, scores for mDISCERN and JAMA benchmarks were not very different between uploader types. This means all uploaders, including professionals, did not do enough to show their sources, name the author, or declare conflicts of interest. Other studies about stroke information online have found the same transparency problem [ 36 ].This seems to be a common problem on social media, not just for one group. Official guidelines say trustworthy health information must be transparent and use clear, evidence-based sources[ 37 , 38 ]. Our finding shows a big gap between these rules and what happens on short-video platforms. This gap matters for public health. If a video is not transparent, viewers cannot judge if it is credible. This is especially risky during flu season when many people look for antiviral drug information. Different uploader groups play different roles online. Professional doctors often share standard, guideline-based knowledge. Non-professional creators often share personal stories, give emotional support, or simplify messages. These roles can work together. But if being easy to understand is more important than being accurate, it can lead to wrong risk perceptions and poor medication decisions by the public. 4.2 Platform-Specific Differences in Quality and Communication Style We found clear quality differences between Douyin and Bilibili. Douyin videos had higher Global Quality Scores, PEMAT Actionability scores, and JAMA benchmark scores. This means Douyin content often gives clearer, more direct advice and better disclosure. One reason might be Douyin's own rules for medical content, which were updated in 2025[ 39 ]. Also, many more videos on Douyin came from professional doctors compared to Bilibili (84% vs 38%). This likely helps Douyin videos be more actionable. Other studies also find that videos by medical professionals are usually higher quality[ 40 , 41 ]. On the other hand, Bilibili videos had much higher PEMAT Understandability scores. This means Bilibili content may be easier for regular people to understand. One reason is that Bilibili videos are longer on average than Douyin videos (173.86 seconds vs. 92.57 seconds). Longer videos allow for more detailed explanations. Our analysis also showed a link between video length and understandability scores (r = 0.64). These differences come from the platforms themselves. Douyin is for short videos and uses algorithms. This encourages short, direct messages with clear advice. Bilibili allows longer videos. This encourages storytelling and step-by-step explanations, which makes content easier to understand. However, being easy to understand does not always mean the information is more reliable or complete. We need to check online medical content on many quality points. The mDISCERN scores were not different between the two platforms. This means both platforms did about the same on reliability. This finding shows that platform features alone cannot ensure good medical information. We need clear quality control and standard reporting practices on all social media. 4.3 Content Coverage Patterns and Educational Gaps On both platforms, most videos talked about basic introductions and how to use the drug. They talked much less about how the drug works, safety issues, or how well it works. Basic information is important. But not talking enough about safety and evidence can stop viewers from making fully informed choices about antiviral therapy. Other studies about online health content for medicines and diseases find the same pattern. Simple information is common, but complex, important topics are not [ 21 , 42 ].Videos about other conditions like cryptorchidism and stroke also often lack complete information. This gap might happen because videos are short, or because creators think viewers will not watch technical content. 4.4 Disconnection Between User Engagement and Information Quality In our study, user engagement numbers like likes and comments were not linked to core quality scores like GQS, mDISCERN, or JAMA. This disconnect is not unique. A study on gallstone videos on TikTok also found that more likes and collections were linked to lower video quality[ 32 ]. This means a popular video is not always an educational one. Studies on other platforms agree. For example, a study on eczema videos on YouTube found no link between video quality and view counts[ 43 ]. This happens because the public often prefers simple, immediate, and emotional content. Professional medical standards are different. Engagement is likely driven by how a video looks, its story, or platform algorithms, not by how accurate or complete its information is. So, using popularity alone to judge credibility is risky. This is especially true for medicine information, where wrong information can lead to bad treatment decisions. 4.5 Implications for Public Health and Medical Communication Our findings show the good and bad sides of short-video platforms for sharing drug information. Videos from medical professionals are usually better for education. But sometimes, a professional title makes information seem trustworthy even when the evidence is weak, as other studies note[ 44 ].Also, user engagement numbers cannot replace a real check of content quality. We need better content moderation, more professionals making videos, and teaching the public how to judge online health information. To improve medication videos, we need to work on several things. We should get more specialist doctors to make videos. Platforms should put quality scores into their recommendation systems. We should also promote standards for transparency. Doing these things together can make health information on short-video platforms more reliable and valuable. 4.6 Limitations Our study has some limits. First, it was a cross-sectional study. We cannot see how content quality changes over time. Second, we only looked at two Chinese platforms. Our results may not apply to other social media. Third, we used validated tools to score videos, but some scoring is always subjective. Finally, we did not check every single claim in the videos for factual accuracy. This is important for future research to do. 5. Conclusion In summary, the quality of oseltamivir videos on major Chinese video platforms varies a lot. This mainly depends on who made the video and which platform it is on. User numbers like likes and comments do not show good information quality or reliability. Our results show we should support medical content made by professionals. This content should be transparent and based on evidence. This will help the public make better health decisions. Declarations Acknowledgments The authors would like to thank all individuals who contributed to data collection, video screening, and methodological discussions during the study. Data Availability All data analyzed in this study were derived from publicly accessible videos on Douyin and Bilibili. The list of included videos, video links, and extracted evaluation data are provided in the Supplementary Data (Excel file). Due to the dynamic nature of online platforms, the availability of individual videos may change over time. Funding This research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors. Conflict of Interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper. Ethical Approval The study analyzed publicly available videos from Douyin and Bilibili platforms. No human participants were involved, and no identifiable personal information was collected. The study protocol was reviewed and exempted from ethical approval by the Ethics Committee of Zhuji People’s Hospital. Informed consent was obtained from all reviewers involved in the assessment of the videos. References QuestMobile. *QuestMobile 2025 New Media Ecosystem Review: Five Major Platforms Reach 1.149 Billion MAUs, Diversified Content and Algorithm Technology Differentiate Competition, Young Users Prefer Cross-Platform* [Report in Chinese]. QuestMobile. 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BiliBili, Douyin and Xiaohongshu as health information platforms for stroke: evaluating information quality and content. Sci. Rep. 15 10.1038/s41598-025-21535-z (2025). PMID: 41152378; PMCID: PMC12568935. Alhlayl, A. S. & Alzghaibi, H. A. Evaluating the effectiveness and limitations of online health information tools in assessing the quality of medication-related content. Front. Public. Health . 13 10.3389/fpubh.2025.1460202 (2025). PMID: 40066011; PMCID: PMC11891361. Bernard, A. et al. S. Asystematic review of patient inflammatory bowel disease information resources on the World Wide Web. Am J Gastroenterol. 102,2070–2077(2007). 10.1111/j.1572-0241.2007.01325.x . Epub 2007 May 19. PMID: 17511753. Jung, M. J. & Seo, M. S. Assessment of reliability and information quality of YouTube videos about root canal treatment after 2016. BMC Oral Health . 22 10.1186/s12903-022-02540-4 (2022). PMID: 36384745; PMCID: PMC9670470. Silberg, W. M., Lundberg, G. D. & Musacchio, R. A. Assessing, controlling, and assuring the quality of medical information on the Internet: Caveant lector et viewor–Let the reader and viewer beware. JAMA. 277,1244–1245 PMID: 9103351. (1997). Kyarunts, M., Mansukhani, M. P., Loukianova, L. L. & Kolla, B. P. Assessing the quality of publicly available videos on MDMA-assisted psychotherapy for PTSD. Am. J. Addict. 31 , 502–507. 10.1111/ajad.13325 (2022). Epub 2022 Aug 24. PMID: 36000281. Rothrock, S. G. et al. Trustworthiness, Readability, and Accuracy of Medical Information Regarding Common Pediatric Emergency Medicine-Related Complaints on the Web. J. Emerg. Med. 57 , 469–477. 10.1016/j.jemermed.2019.06.043 (2019). Epub 2019 Sep 24. PMID: 31561928. The patient education materials assessment tool (PEMAT). and user’s guide Available at: https://www.ahrq.gov/health-literacy/patient-education/pemat.html Shoemaker, S. J., Wolf, M. S. & Brach, C. Development of the Patient Education Materials Assessment Tool (PEMAT): a new measure of understandability and actionability for print and audiovisual patient information. Patient Educ. Couns. 96 , 395–403. 10.1016/j.pec.2014.05.027 (2014). Epub 2014 Jun 12. PMID: 24973195; PMCID: PMC5085258. Mak, W. N., Kaur, S. & Meade, M. J. A Cross-Sectional Study of the Quality of Online Information on Periodontal Surgery. Clin Exp Dent Res. 11,e70195 (2025). 10.1002/cre2.70195 . PMID: 40762531; PMCID: PMC12323047. Zheng, S. et al. Quality and Reliability of Liver Cancer-Related Short Chinese Videos on TikTok and Bilibili: Cross-Sectional Content Analysis Study. J. Med. Internet Res. 25 , e47210. 10.2196/47210 (2023). PMID: 37405825; PMCID: PMC10357314. Sun, F., Zheng, S. & Wu, J. Quality of Information in Gallstone Disease Videos on TikTok: Cross-sectional Study. J Med Internet Res. 25,e39162 (2023). 10.2196/39162 . PMID: 36753307; PMCID: PMC9947761. Zhang, R. et al. Analyzing dissemination, quality, and reliability of Chinese brain tumor-related short videos on TikTok and Bilibili: a cross-sectional study. Front. Neurol. 15 10.3389/fneur.2024.1404038 (2024). PMID: 39494168; PMCID: PMC11527622. Shi, A. et al. Mpox (monkeypox) information on TikTok: analysis of quality and audience engagement. BMJ Glob Health . 8 , e011138. 10.1136/bmjgh-2022-011138 (2023). PMID: 36918216; PMCID: PMC10016284. Lukić, S. & Petrović, J. The quality of information provided by the most popular dementia videos on TikTok. Front Public Health. 11,1266415 (2023). 10.3389/fpubh.2023.1266415 . PMID: 38089039; PMCID: PMC10713706. Lobo, E. H. et al. Utilization of social media communities for caregiver information support in stroke recovery: An analysis of content and interactions. PLoS One. 17,e0262919 (2022). 10.1371/journal.pone.0262919 . PMID: 35081150; PMCID: PMC8791510. Kington, R. S. et al. Identifying Credible Sources of Health Information in Social Media: Principles and Attributes. NAM Perspect 10.31478/202107a(2021 ). doi: 10.31478/202107a. PMID: 34611600; PMCID: PMC8486420. MedlinePlus. Evaluating health information [Internet]. Bethesda (MD): National Library of Medicine (US); Last updated February 26, 2024[cited 2026 Jan 11]. Available from: https://medlineplus.gov/evaluatinghealthinformation.html Douyin, D. [updated 2025; cited 2026 Jan 11]. (2021). Available from: https://www.douyin.com/rule/policy?activeId=medical_convention Dimitroyannis, R. et al. A Social Media Quality Review of Popular Sinusitis Videos on TikTok. Otolaryngol Head Neck Surg. 170,1456–1466 (2024). 10.1002/ohn.688 . Epub 2024 Mar 3. PMID: 38431902. Hu, R. H. et al. Quality and accuracy of gastric cancer related videos in social media videos platforms. BMC Public Health. 22,2025(2022). 10.1186/s12889-022-14417-w . PMID: 36335401; PMCID: PMC9636631. Sun, Y., Liu, X., Zhang, X., Xu, Q. & Li, A. Health information analysis of cryptorchidism-related short videos: Analyzing quality and reliability. Digit Health. 11,20552076251317578(2025). 10.1177/20552076251317578 . PMID: 39877853; PMCID: PMC11773521. Mueller, S. M. et al. Fiction, Falsehoods, and Few Facts: Cross-Sectional Study on the Content-Related Quality of Atopic Eczema-Related Videos on YouTube. J Med Internet Res .22,e15599 (2020). 10.2196/15599 . PMID: 32329744; PMCID: PMC7210495. Kang, E., Lee, H., Choi, J. & Ju, H. The Quality of Evidence of and Engagement With Video Medical Claims. JAMA Netw. Open. 9 , e2552106 (2026). Tables Table 1 is available in the Supplementary Files section. Additional Declarations No competing interests reported. Supplementary Files Table1andSupplementaryTable1.pdf Cite Share Download PDF Status: Under Review Version 1 posted Reviewers agreed at journal 06 May, 2026 Reviewers agreed at journal 22 Apr, 2026 Reviewers invited by journal 20 Apr, 2026 Editor assigned by journal 20 Apr, 2026 Editor invited by journal 31 Mar, 2026 Submission checks completed at journal 27 Mar, 2026 First submitted to journal 27 Mar, 2026 You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. We do this by developing innovative software and high quality services for the global research community. Our growing team is made up of researchers and industry professionals working together to solve the most critical problems facing scientific publishing. Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-9104007","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Article","associatedPublications":[],"authors":[{"id":629663557,"identity":"b135e064-02be-48cb-b700-a59f81aabfcc","order_by":0,"name":"Sicong Hu","email":"","orcid":"","institution":"The Affiliated Lihuili Hospital of Ningbo University","correspondingAuthor":false,"prefix":"","firstName":"Sicong","middleName":"","lastName":"Hu","suffix":""},{"id":629663558,"identity":"d7c73bab-2075-4f22-924f-a213bb36c971","order_by":1,"name":"Yujun Xiong","email":"","orcid":"","institution":"Beijing Hospital","correspondingAuthor":false,"prefix":"","firstName":"Yujun","middleName":"","lastName":"Xiong","suffix":""},{"id":629663559,"identity":"d6e40862-3545-4861-bd9b-1fe9c0fbc7aa","order_by":2,"name":"Qinwen Fei","email":"","orcid":"","institution":"Zhuji Affiliated Hospital of Wenzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Qinwen","middleName":"","lastName":"Fei","suffix":""},{"id":629663560,"identity":"39a32838-66df-48d1-9cd7-9b35681b33be","order_by":3,"name":"Tian Lv","email":"","orcid":"","institution":"Zhuji Affiliated Hospital of Wenzhou Medical University","correspondingAuthor":false,"prefix":"","firstName":"Tian","middleName":"","lastName":"Lv","suffix":""},{"id":629663561,"identity":"b89bf690-2e94-40bc-8049-ec02168636ea","order_by":4,"name":"Tianjiao Meng","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA1ElEQVRIiWNgGAWjYBACNmaG5Acf//yXsz/MfIA4LXzsDc8MZzYwGzMcb0sgToscz8EH0pwNzIkNZ84YEOkwieQEY8YdbIyNM3I+3njDYCen20BQS1rC48IzPMzMErmbLecwJBubHSCoJSfBeAabBBubRO42aR6GA4nbCGvJ/yDNw2bAwyOR84xILTwHEqR52xIkJHjOsBGphb0hzXDGmQMGBuxtxpZzDIjwi3wzMCo/VByo38DM/PDGmwo7OYJaUIAED5FRg6yFVB2jYBSMglEwIgAADb1AxRQsKLcAAAAASUVORK5CYII=","orcid":"","institution":"Zhuji Affiliated Hospital of Wenzhou Medical University","correspondingAuthor":true,"prefix":"","firstName":"Tianjiao","middleName":"","lastName":"Meng","suffix":""}],"badges":[],"createdAt":"2026-03-12 11:09:03","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-9104007/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-9104007/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":108182951,"identity":"9bcd433b-7f27-4efb-8e68-13abc42b9534","added_by":"auto","created_at":"2026-04-30 08:59:42","extension":"jpeg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":193373,"visible":true,"origin":"","legend":"\u003cp\u003eFlowchart of Video Selection and Screening Process for the Cross-Sectional Content Analysis.\u003c/p\u003e\n\u003cp\u003eThis flowchart details the systematic identification and screening of videos for analysis. A search was conducted on TikTok and Bilibili on December 8, 2025, using the Chinese keyword for \"Oseltamivir.\" To minimize the impact of newly released content, only videos uploaded more than one week prior to the search date (i.e., before December 1, 2025) were considered eligible. From this temporally filtered pool on each platform, the top 100 videos sorted by platform-defined relevance were retrieved (initial n=200). After applying further exclusion criteria (duplicates, advertisements, irrelevance), 12 videos were removed from the Bilibili sample. No videos were excluded from the TikTok sample. Consequently, 188 videos (100 from TikTok, 88 from Bilibili) were included for final analysis.\u003c/p\u003e","description":"","filename":"floatimage1.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9104007/v1/94082a2caecc7a444fbdf5ca.jpeg"},{"id":108111747,"identity":"fbef4bb6-47ad-4357-b3ae-1c1ac6f76576","added_by":"auto","created_at":"2026-04-29 13:05:56","extension":"png","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":97028,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of uploader types for oseltamivir-related videos on TikTok and Bilibili.\u003c/p\u003e\n\u003cp\u003e(A) Overall distribution of uploader categories among all included videos (n = 188), classified as individuals (non-medical background), news media or organizations, non-specialist physicians, and specialist physicians.\u003c/p\u003e\n\u003cp\u003e(B) Platform-specific distribution of uploader categories on TikTok and Bilibili.\u003c/p\u003e\n\u003cp\u003e(C) Overall distribution of videos according to uploader professionalism, categorized as professional (specialist physicians and non-specialist physicians) and non-professional sources (individuals and news media or organizations).\u003c/p\u003e\n\u003cp\u003e(D) Platform-specific distribution of professional versus non-professional uploaders on TikTok and Bilibili. Percentages represent the proportion of videos within each category.\u003c/p\u003e","description":"","filename":"floatimage2.png","url":"https://assets-eu.researchsquare.com/files/rs-9104007/v1/eebe8d15ef031b4563f5719b.png"},{"id":108182313,"identity":"dc3cca08-4975-4aab-bdc7-6c775c619e97","added_by":"auto","created_at":"2026-04-30 08:59:18","extension":"jpeg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":205662,"visible":true,"origin":"","legend":"\u003cp\u003eContent coverage of oseltamivir-related videos on TikTok and Bilibili.\u003c/p\u003e\n\u003cp\u003eThe bar chart illustrates the number of videos covering five predefined content domains: effect evaluation, basic introduction, pharmacological actions, safety information, and usage and contraindications. Values indicate the absolute number of videos addressing each content category on TikTok (n = 100) and Bilibili (n = 88). One video could cover more than one content domain.\u003c/p\u003e","description":"","filename":"floatimage3.jpeg","url":"https://assets-eu.researchsquare.com/files/rs-9104007/v1/4660985348d644f43b9e7ed4.jpeg"},{"id":108182095,"identity":"a7c90fa7-bfa2-4b74-8b84-269898f35e3e","added_by":"auto","created_at":"2026-04-30 08:59:08","extension":"png","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":167241,"visible":true,"origin":"","legend":"\u003cp\u003eDistribution of quality and reliability scores of oseltamivir-related videos by uploader type.\u003c/p\u003e\n\u003cp\u003eCaption: Panels A–E display the kernel density distributions of five assessment tools across four uploader categories: individuals (non-medical background), news media or organizations, non-specialist physicians, and specialist physicians.\u003c/p\u003e\n\u003cp\u003e(A) Global Quality Score (GQS);\u003c/p\u003e\n\u003cp\u003e(B) modified DISCERN score (mDISCERN);\u003c/p\u003e\n\u003cp\u003e(C) PEMAT Understandability (PEMAT-U);\u003c/p\u003e\n\u003cp\u003e(D) PEMAT Actionability (PEMAT-A);\u003c/p\u003e\n\u003cp\u003e(E) JAMA benchmark criteria score.\u003c/p\u003e\n\u003cp\u003eHigher values indicate better overall quality, reliability, understandability, or actionability, depending on the assessment tool. The distributions illustrate heterogeneity in video quality across uploader types, with professional physician–uploaded videos generally demonstrating higher score concentrations in overall quality and educational domains, while transparency-related criteria (JAMA) show limited differentiation among uploader categories.\u003c/p\u003e","description":"","filename":"floatimage4.png","url":"https://assets-eu.researchsquare.com/files/rs-9104007/v1/2d6c8a8fe1015dcf8db916eb.png"},{"id":108111750,"identity":"4b9969c9-d106-4cff-92dd-264480d945f5","added_by":"auto","created_at":"2026-04-29 13:05:56","extension":"png","order_by":5,"title":"Figure 5","display":"","copyAsset":false,"role":"figure","size":117705,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of Quality and Reliability Scores Between TikTok and Bilibili Across Five Evaluation Tools.\u003c/p\u003e\n\u003cp\u003eCaption: Violin plots comparing the distribution of scores for oseltamivir-related videos from TikTok and Bilibili across five standardized assessment tools. Panels display: (A) Global Quality Score (GQS), (B) Modified DISCERN (mDISCERN), (C) PEMAT Understandability (PEMAT-U) scores (%), (D) PEMAT Actionability (PEMAT-A) scores (%), and (E) JAMA Benchmark Criteria score. Platforms are color-coded: TikTok (red) and Bilibili (blue). Key observations: Videos on TikTok demonstrated significantly higher median scores in overall quality (GQS), actionability (PEMAT-A), and transparency (JAMA) (indicated by *** and ****), suggesting platform-specific differences in these dimensions. In contrast, Bilibili videos achieved notably higher scores in understandability (PEMAT-U) and a marginally better reliability score (mDISCERN), highlighting its content's enhanced clarity and patient-centered utility.\u003c/p\u003e","description":"","filename":"floatimage5.png","url":"https://assets-eu.researchsquare.com/files/rs-9104007/v1/2ee179b86d4e65667b8d26fe.png"},{"id":108182480,"identity":"55e72b20-deb3-4de7-95f4-26ec6039aa5c","added_by":"auto","created_at":"2026-04-30 08:59:23","extension":"png","order_by":6,"title":"Figure 6","display":"","copyAsset":false,"role":"figure","size":286232,"visible":true,"origin":"","legend":"\u003cp\u003eCorrelation Heatmap Between Video Engagement Metrics and Quality/Reliability Scores.\u003c/p\u003e\n\u003cp\u003eCaption: Heatmap illustrating Spearman correlation coefficients between video engagement metrics (likes, collections, comments, shares, and video length) and quality/reliability assessment scores (GQS, mDISCERN, PEMAT-U, PEMAT-A, and JAMA). Color intensity indicates the strength and direction of correlations, with red representing positive correlations and blue representing negative correlations, while lighter shades indicate weaker associations. Strong positive correlations were observed among engagement metrics (all r \u0026gt;= 0.89), suggesting high internal consistency across different measures of user interaction. Moderate correlations were identified between PEMAT-A and PEMAT-U, as well as between GQS, mDISCERN, and PEMAT scores, indicating partial agreement among different quality assessment tools. Video length showed weak positive correlations with mDISCERN and GQS scores, and a weak negative correlation with JAMA scores. Overall, engagement metrics demonstrated limited correlations with core quality and reliability scores, indicating that video popularity does not necessarily reflect the informational quality or reliability of the content.\u003c/p\u003e","description":"","filename":"floatimage6.png","url":"https://assets-eu.researchsquare.com/files/rs-9104007/v1/9ffbda5708e0b6b762b85de8.png"},{"id":108976821,"identity":"27ccacf7-6144-42b5-a30d-957f594e09cd","added_by":"auto","created_at":"2026-05-11 11:28:58","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1242139,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9104007/v1/c15a5e5f-82cc-4521-a714-fa2514f59cdf.pdf"},{"id":108111746,"identity":"8381c8f9-bd8e-4e82-b204-c20c7b94a4d1","added_by":"auto","created_at":"2026-04-29 13:05:55","extension":"pdf","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":86143,"visible":true,"origin":"","legend":"","description":"","filename":"Table1andSupplementaryTable1.pdf","url":"https://assets-eu.researchsquare.com/files/rs-9104007/v1/1c3cbf40fa60b359e081ab72.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Quality, Reliability, and Dissemination of Oseltamivir-Related Health Information on Chinese Short-Video Platforms: A Cross-Platform Content Analysis of Douyin and Bilibili","fulltext":[{"header":"1. Introduction","content":"\u003cp\u003eShort-video platforms have grown quickly. They have changed how people create, share, and get health information. In China, Douyin has 907\u0026nbsp;million monthly active users. Bilibili has 225\u0026nbsp;million monthly active users[\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. These platforms are now key places where the public looks for medical knowledge. This includes information on preventing disease, getting diagnosed, and using medicine [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eShort videos are more engaging and easier to access than traditional text-based health education. They can spread information fast [\u003cspan additionalcitationids=\"CR5 CR6\" citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e]. But it is very easy to create content on these platforms. There is no strict peer review. This causes major worries about how accurate, complete, and reliable the health information is [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e, \u003cspan citationid=\"CR9\" class=\"CitationRef\"\u003e9\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eInformation about medicine is especially at risk for being wrong on short-video platforms. Wrong or incomplete drug information can lead to bad self-medication, delays in seeing a doctor, poor treatment follow-up, and avoidable side effects. Past studies checking health information on social media often find big differences in content quality. Many videos do not use evidence-based references, lack transparency, or are not balanced[\u003cspan additionalcitationids=\"CR11\" citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e]. More people are using short videos to make health decisions. So, from a public health view, it is very important to check the quality of drug-related content.\u003c/p\u003e \u003cp\u003eOseltamivir is a drug that stops the flu virus. It is widely used to treat and prevent influenza. It is recommended in many national and international guidelines[\u003cspan citationid=\"CR13\" class=\"CitationRef\"\u003e13\u003c/span\u003e]. In China, doctors often prescribe oseltamivir during flu seasons. The drug is also talked about a lot in public media, especially when flu activity is high[\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e]. Even though it is common, people often have wrong ideas about when to use it, when to start taking it, the correct dose, how long to take it, and its possible side effects[\u003cspan citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e, \u003cspan citationid=\"CR16\" class=\"CitationRef\"\u003e16\u003c/span\u003e].Wrong information can lead to incorrect use, make the treatment less effective, and create safety risks. This shows why accurate public education about this drug is important.\u003c/p\u003e \u003cp\u003eDouyin and Bilibili are two major but different short-video platforms in China. They have different user groups, content styles, and ways of sharing information. Douyin has a very large user base. It uses algorithms to recommend content and information spreads quickly. Bilibili traditionally has younger, more educated users. It focuses more on longer, explanatory videos[\u003cspan citationid=\"CR17\" class=\"CitationRef\"\u003e17\u003c/span\u003e, \u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e]. Recent studies looking at disease-specific information on these platforms\u0026mdash;like for lung cancer, Alzheimer's disease, and stroke\u0026mdash;keep finding big differences in video quality. They find a weak link between how much the public engages with a video and how reliable its information is. They also find much room to improve the content's educational value[\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e].These platform features might affect how oseltamivir information is shown and its overall quality and reliability. But direct comparisons of drug-related content across platforms are still rare.\u003c/p\u003e \u003cp\u003eSo far, most studies checking online health information look at diseases, lifestyle, or general medical topics. There are few systematic checks of medication-specific content on Chinese short-video platforms[\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e]. There is especially a lack of analyses that use several proven assessment tools together to check content quality, reliability, transparency, and understandability all at once[\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e].Filling this gap is important. It will give useful information to doctors, public health workers, and platform regulators about how drug information is currently shared.\u003c/p\u003e \u003cp\u003eTherefore, this study aimed to check the quality, reliability, and educational value of oseltamivir-related videos on Douyin and Bilibili. We used established tools: the Global Quality Score (GQS), the modified DISCERN (mDISCERN) tool, the Journal of the American Medical Association (JAMA) benchmark criteria, and the Patient Education Materials Assessment Tool (PEMAT). We did a cross-platform content analysis. We wanted to find the strong points and weak points in the current video content. Our goal is to give evidence-based suggestions for sharing more accurate and reliable medication information on short-video platforms.\u003c/p\u003e"},{"header":"2. Methods","content":"\u003cp\u003e2.1 Study Design\u003c/p\u003e\n\u003cp\u003eWe designed this study as a cross-sectional content analysis. Our goal was to evaluate the quality, reliability, and educational features of oseltamivir-related videos on two major Chinese short-video platforms: Douyin and Bilibili. We developed our methods by looking at how earlier studies assessed online health information quality. We also followed standard reporting practices for this type of digital media research.\u003c/p\u003e\n\u003cp\u003eIn this cross-sectional investigation, we collected publicly available short videos from Douyin (the Chinese counterpart to TikTok, http://www.douyin.com) and Bilibili (http://www.bilibili.com). A detailed introduction of these two platforms, including their founding dates, positioning, core features, user base, and content ecosystem, is provided in Supplementary Table 1.\u003c/p\u003e\n\u003cp\u003e2.2 Data Sources and Video Selection\u003c/p\u003e\n\u003cp\u003e2.2.1 Search Strategy\u003c/p\u003e\n\u003cp\u003eWe did a systematic search on both Douyin and Bilibili on December 8, 2025. We used the Chinese keyword \u0026ldquo;奥司他韦\u0026rdquo;\u0026nbsp;(oseltamivir). From each platform, we took the top 100 videos that the platform\u0026apos;s search ranked as most relevant. To make sure the engagement numbers (like likes and comments) were stable, we only included videos uploaded more than one week before our search date.\u003c/p\u003e\n\u003cp\u003eWe wanted to avoid bias from personalized algorithms. So, before searching, we cleared all browser history, cache, cookies, and autofill data. We then used a newly registered account for each platform. Each account used a different, unused mobile phone number. This ensured our past activity did not affect which videos we saw.\u003c/p\u003e\n\u003cp\u003e2.2.2 Eligibility Criteria\u003c/p\u003e\n\u003cp\u003e(1) Inclusion Criteria:\u003c/p\u003e\n\u003cp\u003eWe included videos if they: were in Chinese; focused on oseltamivir health information; were in the top 100 search results for relevance; and were uploaded more than one week before we collected data.\u003c/p\u003e\n\u003cp\u003e(2) Exclusion Criteria:\u003c/p\u003e\n\u003cp\u003eWe excluded videos if they: were not about oseltamivir or medication education; were mainly ads or promotions; or were duplicates on or across the platforms.\u003c/p\u003e\n\u003cp\u003e2.2.3 Video Screening Process\u003c/p\u003e\n\u003cp\u003eWe first got 200 videos (100 from each platform).On Douyin, no videos met exclusion criteria, and all 100 videos were retained.On Bilibili, 12 videos were excluded, including 8 duplicated videos, 1 advertisement, and 3 irrelevant videos.After screening, a total of 188 videos were included in the final analysis, comprising 100 Douyin videos and 88 Bilibili videos.The detailed video selection and exclusion process is illustrated in Figure 1 (flowchart).\u003c/p\u003e\n\u003cp\u003eThe detailed information of all included videos, including video links and extracted evaluation variables, is provided in the Supplementary Data.\u003c/p\u003e\n\u003cp\u003e2.3 Data Extraction\u003c/p\u003e\n\u003cp\u003eTwo reviewers independently watched all included videos and filled out a standard form to collect data. We extracted the following information:\u003c/p\u003e\n\u003cp\u003e2.3.1 General Video Characteristics\u003c/p\u003e\n\u003cp\u003eThe following general characteristics were extracted for each included video: (1) video duration (in seconds); (2) number of likes; (3) number of favorites (collections); (4) number of shares; (5) number of comments; and (6) video uploader identity.\u003c/p\u003e\n\u003cp\u003eUploaders were categorized into four groups: individuals (with no medical background), specialist physicians (e.g., from respiratory medicine, infectious diseases, or pediatrics), non-specialist physicians, and news media or organizations. For subgroup analysis, uploaders were further dichotomized into: professional sources (comprising both specialist and non-specialist physicians) and non-professional sources (comprising individuals and media/institutional accounts). The distribution of uploader identities is presented in Figure 2.\u003c/p\u003e\n\u003cp\u003e2.3.3 Video Content Classification\u003c/p\u003e\n\u003cp\u003eEach video was assessed for the presence or absence of the following content domains related to oseltamivir: (1) General introduction (drug name and therapeutic effects); (2) Usage and contraindications; (3) Safety information, including use in special populations (e.g., children, elderly, pregnant women); (4) Evaluation of drug efficacy; and (5) Pharmacological mechanisms, including comparisons with similar antiviral medications. The frequency of videos covering each content domain on Douyin and Bilibili is summarized in Figure 3.\u003c/p\u003e\n\u003cp\u003e2.4 Quality and Reliability Assessment\u003c/p\u003e\n\u003cp\u003eVideo quality and reliability were evaluated using four validated instruments.\u003c/p\u003e\n\u003cp\u003e2.4.1 Global Quality Score (GQS)\u003c/p\u003e\n\u003cp\u003eThe overall educational quality, flow, and usefulness of the videos for patients were assessed using the Global Quality Scale (GQS)[23].\u0026nbsp;Videos were rated on a 5-point Likert scale (see Supplementary Table 2 for detailed criteria), with higher scores indicating better overall quality.\u003c/p\u003e\n\u003cp\u003e2.4.2 Modified DISCERN (mDISCERN)\u003c/p\u003e\n\u003cp\u003eThe modified DISCERN (mDISCERN)[19,24]tool was applied to evaluate the reliability and credibility of the video content. This tool is specifically designed to assess the trustworthiness of health information by addressing five key yes/no questions: clarity, source credibility, balance, provision of references, and discussion of uncertainties. Each affirmative response was awarded one point, yielding a total score ranging from 0 to 5 (see Supplementary Table 3 for the specific criteria).\u003c/p\u003e\n\u003cp\u003e2.4.3 JAMA Benchmark Criteria\u003c/p\u003e\n\u003cp\u003eThe Journal of the American Medical Association (JAMA)[25-27] benchmark criteria were used to assess the transparency and accountability of the video content by evaluating four key elements: authorship, attribution (source citation), currency (timeliness), and disclosure of conflicts of interest. Each criterion was scored as 1 point if clearly present, yielding a maximum total score of 4 (see Supplementary Table 4 for details).\u003c/p\u003e\n\u003cp\u003e2.4.4 Patient Education Materials Assessment Tool for Printable Materials (PEMAT-P)\u003c/p\u003e\n\u003cp\u003eAlthough PEMAT-P[28,29]was originally developed for printable patient education materials, it was applied in this study to evaluate the educational content of health-related videos, with a focus on understandability and actionability rather than audiovisual production quality. This approach has been commonly adopted in previous studies assessing structured health information delivered through digital and social media formats.\u003c/p\u003e\n\u003cp\u003ePEMAT-P is a validated instrument developed by the Agency for Healthcare Research and Quality (AHRQ) and assesses educational quality across two core domains: understandability and actionability. The understandability domain evaluates whether materials are easy to comprehend for individuals with varying levels of health literacy and includes items addressing clarity of purpose, word choice, use of numbers, organization, layout and design, and appropriate use of visual aids (Items 1\u0026ndash;19). The actionability domain assesses whether materials clearly identify actions users can take and provide sufficient guidance to support those actions (Items 20\u0026ndash;26).\u003c/p\u003e\n\u003cp\u003eEach item was scored using a binary rating system (1 = criterion met; 0 = criterion not met; NA = not applicable) according to the standardized instructions in the PEMAT-P User\u0026rsquo;s Guide. Domain-specific scores were calculated by dividing the total points earned by the number of applicable items (excluding NA responses) and multiplying by 100. Consistent with established guidance, scores of \u0026ge;70% were considered indicative of acceptable educational quality[30]. Detailed scoring criteria are provided in Supplementary Table 5.\u003c/p\u003e\n\u003cp\u003e2.5 Reviewer Training and Inter-Rater Reliability\u003c/p\u003e\n\u003cp\u003eAll videos were independently assessed by two trained reviewers(Tianjiao Meng and Qinwen Fei) with medical backgrounds. Prior to formal evaluation, reviewers underwent calibration sessions to ensure consistent understanding of scoring criteria. Discrepancies were resolved through discussion, and consensus was reached with the involvement of a third reviewer(Tian Lv) when necessary.\u003c/p\u003e\n\u003cp\u003e2.6 Statistical Analysis\u003c/p\u003e\n\u003cp\u003eDescriptive statistics were used to summarize video characteristics, content domains, and quality scores. Continuous variables were presented as means with standard deviations or medians with interquartile ranges, as appropriate, while categorical variables were expressed as frequencies and percentages.\u003c/p\u003e\n\u003cp\u003eComparisons of quality and reliability scores among different uploader groups were conducted using non-parametric tests. Correlations between general video engagement metrics and quality or reliability scores were assessed using correlation analyses.\u003c/p\u003e\n\u003cp\u003eStatistical analyses were performed using standard statistical software, with a two-sided P value \u0026lt; 0.05 considered statistically significant.\u003c/p\u003e\n\u003cp\u003eThe distribution of quality and reliability scores among uploader categories is illustrated in Figure 4, comparative analyses are shown in Figure 5, and correlations between video engagement metrics and quality or reliability scores are presented as a heatmap in Figure 6.\u003c/p\u003e\n\u003cp\u003eThe present study analyzed publicly available videos from Douyin and Bilibili platforms. No human participants were involved, and no identifiable personal information was collected. The study protocol was reviewed and exempted from ethical approval by the Ethics Committee of Zhuji People\u0026rsquo;s Hospital. Informed consent was waived.\u003c/p\u003e"},{"header":"3. Results","content":"\u003cdiv id=\"Sec19\" class=\"Section2\"\u003e \u003ch2\u003e3.1 Overall characteristics of videos across platforms\u003c/h2\u003e \u003cp\u003eTable\u0026nbsp;1 summarizes the characteristics of oseltamivir-related videos on Douyin and Bilibili, including engagement metrics, uploader types, content quality scores, and content coverage. A total of 188 videos were analyzed, comprising 100 videos from Douyin and 88 from Bilibili.\u003c/p\u003e \u003cp\u003eVideos on Douyin demonstrated substantially higher engagement across all interaction metrics, including likes (26,927.48\u0026thinsp;\u0026plusmn;\u0026thinsp;95,272.25 vs. 1,310.64\u0026thinsp;\u0026plusmn;\u0026thinsp;4,542.54), collections (14,460.32\u0026thinsp;\u0026plusmn;\u0026thinsp;43,966.02 vs. 533.35\u0026thinsp;\u0026plusmn;\u0026thinsp;1,423.97), comments (1,225.04\u0026thinsp;\u0026plusmn;\u0026thinsp;3,734.08 vs. 198.89\u0026thinsp;\u0026plusmn;\u0026thinsp;417.90), and shares (24,752.58\u0026thinsp;\u0026plusmn;\u0026thinsp;103,189.66 vs. 780.45\u0026thinsp;\u0026plusmn;\u0026thinsp;3,713.77). In contrast, videos on Bilibili were markedly longer in duration, with a mean length of 173.86\u0026thinsp;\u0026plusmn;\u0026thinsp;168.91 seconds compared with 92.57\u0026thinsp;\u0026plusmn;\u0026thinsp;55.03 seconds on Douyin.\u003c/p\u003e \u003cp\u003eRegarding uploader composition, Douyin featured a significantly higher proportion of professional contributors, particularly professional physicians (47.0% vs. 18.2%). Overall, professional uploaders accounted for 83.0% of videos on Douyin, compared with 35.2% on Bilibili, where individual uploaders constituted the largest group (43.2%).\u003c/p\u003e \u003cp\u003eIn terms of content quality, videos on Douyin achieved higher mean scores for GQS (2.92\u0026thinsp;\u0026plusmn;\u0026thinsp;0.66 vs. 2.47\u0026thinsp;\u0026plusmn;\u0026thinsp;0.90), PEMAT-U (77.49% \u0026plusmn; 16.46 vs. 67.74% \u0026plusmn; 17.47), PEMAT-A (64.10% \u0026plusmn; 20.60 vs. 48.06% \u0026plusmn; 24.68), and JAMA criteria (2.04\u0026thinsp;\u0026plusmn;\u0026thinsp;0.35 vs. 1.57\u0026thinsp;\u0026plusmn;\u0026thinsp;0.60). In contrast, mDISCERN scores were comparably low across both platforms (2.06\u0026thinsp;\u0026plusmn;\u0026thinsp;0.42 on Douyin vs. 2.01\u0026thinsp;\u0026plusmn;\u0026thinsp;0.63 on Bilibili).\u003c/p\u003e \u003cp\u003eWith respect to content coverage, most videos focused on basic introduction and usage-related information, whereas pharmacological mechanisms, safety considerations, and effect evaluation were less consistently addressed across both platforms (Table\u0026nbsp;1).\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec20\" class=\"Section2\"\u003e \u003ch2\u003e3.2 Platform-level differences in quality scores and uploader characteristics\u003c/h2\u003e \u003cp\u003ePlatform-level differences in uploader composition and video quality are illustrated in Figs.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e\u0026ndash;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Douyin was characterized by a substantially higher proportion of videos uploaded by professional physicians compared with Bilibili, whereas Bilibili featured a larger share of content produced by individual uploaders and media organizations.\u003c/p\u003e \u003cp\u003eAs shown in Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e, videos uploaded by specialist physicians consistently demonstrated higher distributions of Global Quality Score (GQS), PEMAT Understandability (PEMAT-U), and PEMAT Actionability (PEMAT-A) compared with other uploader types. In contrast, videos produced by individuals without a medical background exhibited lower score distributions across these domains.\u003c/p\u003e \u003cp\u003ePlatform-level comparisons of quality and reliability scores are presented in Figs.\u0026nbsp;\u003cspan refid=\"Fig2\" class=\"InternalRef\"\u003e2\u003c/span\u003e and \u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e. Videos on Douyin achieved significantly higher GQS, PEMAT-A, and JAMA benchmark scores than those on Bilibili, indicating superior overall educational quality, greater actionability, and more complete disclosure practices. However, no significant difference was observed between the two platforms for mDISCERN scores (Fig.\u0026nbsp;\u003cspan refid=\"Fig3\" class=\"InternalRef\"\u003e3\u003c/span\u003e), suggesting that reliability-related criteria\u0026mdash;such as source citation, balance of information, and reference to uncertainties\u0026mdash;were similarly limited across both platforms.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec21\" class=\"Section2\"\u003e \u003ch2\u003e3.3 Content coverage and video length\u003c/h2\u003e \u003cp\u003eAnalysis of content domains revealed that videos on both platforms predominantly addressed basic introduction and usage-related information, while pharmacological actions, safety considerations, and effect evaluation were less frequently covered (Fig.\u0026nbsp;\u003cspan refid=\"Fig4\" class=\"InternalRef\"\u003e4\u003c/span\u003e, Table\u0026nbsp;1). This pattern was consistent across uploader types and platforms.\u003c/p\u003e \u003cp\u003eVideos on Bilibili demonstrated significantly higher PEMAT-U scores, indicating greater understandability for general audiences. This difference corresponded with the longer average video duration observed on Bilibili. As illustrated in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e, video length showed a moderate positive correlation with PEMAT-U (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.64), suggesting that longer videos may facilitate more detailed explanations and clearer presentation of information.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec22\" class=\"Section2\"\u003e \u003ch2\u003e3.4 Platform-level comparison of quality and reliability scores(Figure \u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e)\u003c/h2\u003e \u003cp\u003ePlatform-specific comparisons of video quality and reliability scores are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig5\" class=\"InternalRef\"\u003e5\u003c/span\u003e.\u003c/p\u003e \u003cp\u003eVideos on Douyin achieved significantly higher Global Quality Score (GQS), PEMAT Actionability (PEMAT-A), and JAMA benchmark scores than those on Bilibili, whereas videos on Bilibili demonstrated significantly higher PEMAT Understandability (PEMAT-U) scores.\u003c/p\u003e \u003cp\u003eNo significant difference was observed between the two platforms for mDISCERN scores.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec23\" class=\"Section2\"\u003e \u003ch2\u003e3.5 Associations between engagement metrics and content quality\u003c/h2\u003e \u003cp\u003eSpearman correlation analyses examining the relationships between video engagement metrics and quality or reliability scores are presented in Fig.\u0026nbsp;\u003cspan refid=\"Fig6\" class=\"InternalRef\"\u003e6\u003c/span\u003e. Strong positive intercorrelations were observed among engagement indicators themselves, including likes, comments, shares, and collections (all \u003cem\u003er\u003c/em\u003e\u0026thinsp;\u0026gt;\u0026thinsp;0.90), indicating that videos performing well on one engagement metric tended to perform similarly on others.\u003c/p\u003e \u003cp\u003eIn contrast, no significant associations were identified between engagement metrics and core indicators of content quality or reliability, including GQS, mDISCERN, and JAMA benchmark scores. This finding suggests a clear disconnect between user engagement and the educational quality or informational reliability of the videos. Additionally, video length demonstrated weak positive correlations with GQS (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.26) and mDISCERN (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;0.38), as well as a weak negative correlation with JAMA score (\u003cem\u003er\u003c/em\u003e\u0026thinsp;=\u0026thinsp;\u0026minus;\u0026thinsp;0.23).\u003c/p\u003e \u003c/div\u003e"},{"header":"4. Discussion","content":"\u003cp\u003eIn this study we analyzed oseltamivir-related videos from two Chinese video platforms. We looked at who uploaded the videos, what topics they covered, how good the information was, and how users interacted with them. We found several key things.\u003c/p\u003e \u003cp\u003eFirst, videos made by medical professionals, especially specialist doctors, had much higher educational quality and were more actionable than videos from non-professionals. Second, there were clear differences between Douyin and Bilibili in both style and quality. Third, user popularity metrics like likes did not show a strong link with our measures of information quality and reliability. Our findings show how the person who uploads a video and the platform itself together affect whether the information meets medical standards.\u003c/p\u003e \u003cdiv id=\"Sec25\" class=\"Section2\"\u003e \u003ch2\u003e4.1 Influence of Uploader Professional Background on Video Quality\u003c/h2\u003e \u003cp\u003eWe found that the uploader's professional background is very important. Videos from specialist doctors got higher scores for GQS, PEMAT-A, and PEMAT-U. This means their videos had better structure, clearer explanations, and more useful advice. Videos from people without a medical background scored much lower.\u003c/p\u003e \u003cp\u003eThis matches what other studies have found for many other health topics. Those studies also show that videos from doctors are usually more accurate, complete, and useful for education[\u003cspan additionalcitationids=\"CR32 CR33 CR34\" citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e]. Specialist doctors know more about the topic. They also know more about clinical guidelines and real-world prescribing.\u003c/p\u003e \u003cp\u003eHowever, scores for mDISCERN and JAMA benchmarks were not very different between uploader types. This means all uploaders, including professionals, did not do enough to show their sources, name the author, or declare conflicts of interest. Other studies about stroke information online have found the same transparency problem [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e].This seems to be a common problem on social media, not just for one group.\u003c/p\u003e \u003cp\u003eOfficial guidelines say trustworthy health information must be transparent and use clear, evidence-based sources[\u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e, \u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e]. Our finding shows a big gap between these rules and what happens on short-video platforms. This gap matters for public health. If a video is not transparent, viewers cannot judge if it is credible. This is especially risky during flu season when many people look for antiviral drug information.\u003c/p\u003e \u003cp\u003eDifferent uploader groups play different roles online. Professional doctors often share standard, guideline-based knowledge. Non-professional creators often share personal stories, give emotional support, or simplify messages. These roles can work together. But if being easy to understand is more important than being accurate, it can lead to wrong risk perceptions and poor medication decisions by the public.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec26\" class=\"Section2\"\u003e \u003ch2\u003e4.2 Platform-Specific Differences in Quality and Communication Style\u003c/h2\u003e \u003cp\u003eWe found clear quality differences between Douyin and Bilibili. Douyin videos had higher Global Quality Scores, PEMAT Actionability scores, and JAMA benchmark scores. This means Douyin content often gives clearer, more direct advice and better disclosure. One reason might be Douyin's own rules for medical content, which were updated in 2025[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]. Also, many more videos on Douyin came from professional doctors compared to Bilibili (84% vs 38%). This likely helps Douyin videos be more actionable. Other studies also find that videos by medical professionals are usually higher quality[\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eOn the other hand, Bilibili videos had much higher PEMAT Understandability scores. This means Bilibili content may be easier for regular people to understand. One reason is that Bilibili videos are longer on average than Douyin videos (173.86 seconds vs. 92.57 seconds). Longer videos allow for more detailed explanations. Our analysis also showed a link between video length and understandability scores (r\u0026thinsp;=\u0026thinsp;0.64).\u003c/p\u003e \u003cp\u003eThese differences come from the platforms themselves. Douyin is for short videos and uses algorithms. This encourages short, direct messages with clear advice. Bilibili allows longer videos. This encourages storytelling and step-by-step explanations, which makes content easier to understand. However, being easy to understand does not always mean the information is more reliable or complete. We need to check online medical content on many quality points.\u003c/p\u003e \u003cp\u003eThe mDISCERN scores were not different between the two platforms. This means both platforms did about the same on reliability. This finding shows that platform features alone cannot ensure good medical information. We need clear quality control and standard reporting practices on all social media.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec27\" class=\"Section2\"\u003e \u003ch2\u003e4.3 Content Coverage Patterns and Educational Gaps\u003c/h2\u003e \u003cp\u003eOn both platforms, most videos talked about basic introductions and how to use the drug. They talked much less about how the drug works, safety issues, or how well it works. Basic information is important. But not talking enough about safety and evidence can stop viewers from making fully informed choices about antiviral therapy.\u003c/p\u003e \u003cp\u003eOther studies about online health content for medicines and diseases find the same pattern. Simple information is common, but complex, important topics are not [\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e, \u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e].Videos about other conditions like cryptorchidism and stroke also often lack complete information. This gap might happen because videos are short, or because creators think viewers will not watch technical content.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec28\" class=\"Section2\"\u003e \u003ch2\u003e4.4 Disconnection Between User Engagement and Information Quality\u003c/h2\u003e \u003cp\u003eIn our study, user engagement numbers like likes and comments were not linked to core quality scores like GQS, mDISCERN, or JAMA. This disconnect is not unique. A study on gallstone videos on TikTok also found that more likes and collections were linked to lower video quality[\u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e]. This means a popular video is not always an educational one.\u003c/p\u003e \u003cp\u003eStudies on other platforms agree. For example, a study on eczema videos on YouTube found no link between video quality and view counts[\u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThis happens because the public often prefers simple, immediate, and emotional content. Professional medical standards are different. Engagement is likely driven by how a video looks, its story, or platform algorithms, not by how accurate or complete its information is. So, using popularity alone to judge credibility is risky. This is especially true for medicine information, where wrong information can lead to bad treatment decisions.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec29\" class=\"Section2\"\u003e \u003ch2\u003e4.5 Implications for Public Health and Medical Communication\u003c/h2\u003e \u003cp\u003eOur findings show the good and bad sides of short-video platforms for sharing drug information. Videos from medical professionals are usually better for education. But sometimes, a professional title makes information seem trustworthy even when the evidence is weak, as other studies note[\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e].Also, user engagement numbers cannot replace a real check of content quality. We need better content moderation, more professionals making videos, and teaching the public how to judge online health information.\u003c/p\u003e \u003cp\u003eTo improve medication videos, we need to work on several things. We should get more specialist doctors to make videos. Platforms should put quality scores into their recommendation systems. We should also promote standards for transparency. Doing these things together can make health information on short-video platforms more reliable and valuable.\u003c/p\u003e \u003c/div\u003e \u003cdiv id=\"Sec30\" class=\"Section2\"\u003e \u003ch2\u003e4.6 Limitations\u003c/h2\u003e \u003cp\u003eOur study has some limits. First, it was a cross-sectional study. We cannot see how content quality changes over time. Second, we only looked at two Chinese platforms. Our results may not apply to other social media. Third, we used validated tools to score videos, but some scoring is always subjective. Finally, we did not check every single claim in the videos for factual accuracy. This is important for future research to do.\u003c/p\u003e \u003c/div\u003e"},{"header":"5. Conclusion","content":"\u003cp\u003eIn summary, the quality of oseltamivir videos on major Chinese video platforms varies a lot. This mainly depends on who made the video and which platform it is on. User numbers like likes and comments do not show good information quality or reliability. Our results show we should support medical content made by professionals. This content should be transparent and based on evidence. This will help the public make better health decisions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors would like to thank all individuals who contributed to data collection, video screening, and methodological discussions during the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData Availability\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eAll data analyzed in this study were derived from publicly accessible videos on Douyin and Bilibili. The list of included videos, video links, and extracted evaluation data are provided in the Supplementary Data (Excel file). Due to the dynamic nature of online platforms, the availability of individual videos may change over time.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis research did not receive any specific grant from funding agencies in the public, commercial, or not-for-profit sectors.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflict of Interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe study analyzed publicly available videos from Douyin and Bilibili platforms. No human participants were involved, and no identifiable personal information was collected. The study protocol was reviewed and exempted from ethical approval by the Ethics Committee of Zhuji People\u0026rsquo;s Hospital.\u003c/p\u003e\n\u003cp\u003eInformed consent was obtained from all reviewers involved in the assessment of the videos.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eQuestMobile. *QuestMobile 2025 New Media Ecosystem Review: Five Major Platforms Reach 1.149 Billion MAUs, Diversified Content and Algorithm Technology Differentiate Competition, Young Users Prefer Cross-Platform* [Report in Chinese]. QuestMobile. 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Fiction, Falsehoods, and Few Facts: Cross-Sectional Study on the Content-Related Quality of Atopic Eczema-Related Videos on YouTube. \u003cem\u003eJ Med Internet Res\u003c/em\u003e.22,e15599 (2020). \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.2196/15599\u003c/span\u003e\u003cspan address=\"10.2196/15599\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. PMID: 32329744; PMCID: PMC7210495.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKang, E., Lee, H., Choi, J. \u0026amp; Ju, H. The Quality of Evidence of and Engagement With Video Medical Claims. \u003cem\u003eJAMA Netw. Open.\u003c/em\u003e \u003cb\u003e9\u003c/b\u003e, e2552106 (2026).\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Tables","content":"\u003cp\u003eTable 1 is available in the Supplementary Files section.\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"Oseltamivir, Short-video platforms, Health information quality, Douyin, Bilibili, Content analysis","lastPublishedDoi":"10.21203/rs.3.rs-9104007/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-9104007/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003e\u003cstrong\u003eBackground \u003c/strong\u003eOseltamivir, an antiviral for influenza, is frequently discussed on short-video platforms like Douyin and Bilibili, yet the quality of these videos remains unclear.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eObjective \u003c/strong\u003eThis study evaluated the quality, reliability, and content of oseltamivir-related videos on Douyin and Bilibili, comparing platforms and uploader types.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMethods \u003c/strong\u003eWe conducted a cross-sectional analysis of 188 videos (100 from Douyin, 88 from Bilibili). Quality and reliability were assessed using GQS, mDISCERN, JAMA benchmarks, and PEMAT. Video characteristics, uploader types, and engagement metrics were analyzed.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eResults \u003c/strong\u003eDouyin had more professional uploaders (83.0% vs. 35.2%). Videos from specialist doctors scored higher across most tools. Douyin videos scored higher in GQS, PEMAT-A, and JAMA, while Bilibili videos scored higher in PEMAT-U. Both platforms focused on basic introductions, neglecting safety and efficacy. Longer videos correlated with higher PEMAT-U scores, but user engagement did not correlate with quality.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConclusions \u003c/strong\u003eVideo quality varies significantly. Professional uploaders, especially doctors, provide higher-quality content. User engagement is not a reliable indicator of information quality, highlighting the need for better oversight.\u003c/p\u003e","manuscriptTitle":"Quality, Reliability, and Dissemination of Oseltamivir-Related Health Information on Chinese Short-Video Platforms: A Cross-Platform Content Analysis of Douyin and Bilibili","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-04-29 13:05:46","doi":"10.21203/rs.3.rs-9104007/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"reviewerAgreed","content":"202167931914568997625514257037557554160","date":"2026-05-07T02:23:49+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"188174671163744460915544956630246885490","date":"2026-04-22T16:02:13+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-04-21T01:48:51+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-04-20T15:18:49+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-03-31T13:20:25+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-03-28T02:20:14+00:00","index":"","fulltext":""},{"type":"submitted","content":"Scientific Reports","date":"2026-03-28T02:15:33+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"scientific-reports","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"scirep","sideBox":"Learn more about [Scientific Reports](http://www.nature.com/srep/)","snPcode":"","submissionUrl":"","title":"Scientific Reports","twitterHandle":"","acdcEnabled":true,"dfaEnabled":true,"editorialSystem":"stoa","reportingPortfolio":"Scientific Reports","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"634a0fed-6fe4-4271-939b-70f099460ccb","owner":[],"postedDate":"April 29th, 2026","published":true,"recentEditorialEvents":[{"type":"reviewerAgreed","content":"202167931914568997625514257037557554160","date":"2026-05-07T02:23:49+00:00","index":163,"fulltext":""}],"rejectedJournal":[],"revision":"","amendment":"","status":"under-review","subjectAreas":[{"id":67020565,"name":"Health sciences/Health care"},{"id":67020566,"name":"Health sciences/Medical research"}],"tags":[],"updatedAt":"2026-04-29T13:05:46+00:00","versionOfRecord":[],"versionCreatedAt":"2026-04-29 13:05:46","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-9104007","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-9104007","identity":"rs-9104007","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}