TikTok, RedNote, and Bilibili as sources of medical information on chronic obstructive pulmonary disease: a cross-platform content analysis

Introduction

Chronic obstructive pulmonary disease (COPD) poses a major public health challenge and is a leading cause of morbidity and mortality worldwide (1). According to global estimates, COPD is currently among the leading causes of death, with its prevalence and mortality continuing to rise. In China, the burden of COPD is particularly pronounced because of high smoking rates, population aging, and widespread exposure to environmental pollutants (2,3). Effective COPD management relies on not only pharmacological treatment but also long-term disease awareness, self-management, lifestyle modifications, and timely engagement with healthcare services (4,5). Therefore, access to accurate, comprehensive, and reliable health information is crucial for patients, caregivers, and the general public.

In recent years, short-video platforms have emerged as important channels for the dissemination of health information (6). Platforms such as TikTok, RedNote, and Bilibili have attracted hundreds of millions of users in China by offering brief, visually engaging content that is easily accessible and highly shareable (7). Short videos are typically concise, visually engaging, and easy to understand, which may lower barriers to information access, particularly for individuals with limited health literacy or those who are reluctant to consult traditional medical resources (8).

Despite these advantages, the increasing reliance on short-video platforms for health information has raised concerns regarding the accuracy, completeness, and reliability of the information provided. Unlike peer-reviewed medical literature or professionally curated health websites, content on short-video platforms is often generated by a diverse range of uploaders, including healthcare professionals, institutions, commercial entities, and members of the general public. The absence of standardized review mechanisms and the dominance of algorithm-driven content recommendation systems may facilitate the rapid spread of misleading, incomplete, or biased information (9).

The quality of online medical information related to various diseases across platforms, including osteoarthritis, laryngeal carcinoma, and cardiovascular conditions, has been previously evaluated (8,10). These studies consistently report substantial variability in content quality, with professionally generated content outperforming that from nonprofessional institutions (8). Nevertheless, evidence specifically focusing on COPD-related short videos remains limited, particularly in the context of Chinese short-video platforms with distinct user demographics and content ecosystems.

Therefore, this study aimed to assess the quality and misinformation status of COPD-related videos across three mainstream platforms and analyze the prevalent clinical inaccuracies and their potential health risks with the intention to offer practical references for standardizing online medical content and reducing any adverse impacts on patient disease management.

Methods

Search strategy and data collection

This observational cross-sectional study used videos collected from the short-video platforms TikTok, Bilibili, and RedNote. On December 15, 2025, searches were conducted using the keyword “chronic obstructive pulmonary disease”. To minimize bias associated with personalized recommendation algorithms, we logged out of all accounts and performed the searches using newly created accounts. Search results on each platform were sorted according to their default ranking algorithms without applying any preset filters. This approach ensured that the collected videos reflected the platforms’ standard ranking criteria. Videos were included if they were related to COPD. The exclusion criteria were as follows: (I) duplicate content and (II) videos containing irrelevant material. Shared videos without original creation or additional professional interpretation were excluded as duplicates or non-original content. For the selected videos, characteristics such as the title, number of likes, comments, favorites, shares, source, information type, and content were recorded and analyzed. The screening and inclusion process is illustrated in Figure 1.

Figure 1 Flowchart depicting the screening process for COPD-related short videos. After removing duplicate, re-posted, and irrelevant videos, 510 videos were included for analysis, including 167 from TikTok, 167 from RedNote, and 176 from Bilibili. COPD, chronic obstructive pulmonary disease.

Video content and uploader types

Based on content, the videos were classified into six distinct categories:

• Disease prevention: content focusing on risk factors and daily preventive behaviors for COPD.
• Disease mechanism: content explaining pathological changes, pathophysiology, lung function decline, and progression of COPD.
• Disease diagnosis: content about clinical manifestations, screening methods, diagnostic criteria, differential diagnosis, and lung function testing for COPD.
• Disease treatment: content introducing pharmacological therapy, non-pharmacological management, and follow-up care for COPD.
• Advertisement: content primarily promoting commercial products with obvious marketing purposes.
• Experience sharing: personal narratives of patients regarding symptoms, treatment experiences, quality of life, or emotional coping.

Videos were categorized into four types according to the uploader’s verified background:

• Professional individual: verified personal accounts of licensed physicians, respiratory therapists, or researchers with formal medical education and qualifications; identity verified via platform certification.
• Non-professional individual: personal accounts without verified medical background, including patients, family members, or ordinary users.
• Professional institution: verified official accounts of tertiary hospitals, respiratory medicine departments, medical universities, or formal medical associations.
• Non-professional institution: verified official accounts of non-medical organizations without formal medical qualification.

All included videos were independently coded and classified by two trained reviewers using the above operational definitions. Discrepancies were resolved through consensus discussion. Unresolved disagreements were adjudicated by a third senior researcher. Inter-rater reliability for content category and uploader type classification was assessed using Cohen’s kappa coefficient.

Video quality assessment

We used well-established assessment tools to evaluate video quality and reliability, which are widely used to assess the quality of online medical information (11). The Global Quality Scale (GQS), a scoring system designed to evaluate the educational value of online videos, assesses the quality, accessibility, and usability of the information presented in these videos (12). GQS uses a five-point scale, with higher scores indicating better content organization and a greater amount of useful information (Table S1). The reliability of COPD-related videos was assessed using the modified Decision-Making Information Support Criteria for Evaluating the Reliability of Non-randomized Studies (mDISCERN). This five-item tool evaluates clarity of aims, use of reliable sources, balance and impartiality, provision of additional resources, and discussion of uncertainty. Each item was scored as 0 or 1, giving a total score of 0–5, with higher scores indicating greater reliability (Table S2) (13,14).

Statistical analysis

The Shapiro-Wilk test indicated that all continuous variables significantly deviated from normality. Descriptive results are presented as the median and interquartile range for continuous variables and as frequencies and percentages for categorical variables. For between-group comparisons, the Mann-Whitney U test was used to compare continuous variables between two groups, whereas the Kruskal-Wallis H test was used for comparisons among three or more groups. Categorical variables were compared using the chi-square test. Spearman’s rank correlation analysis was applied to quantify associations between variables. A P value of <0.05 was considered statistically significant. All statistical analyses were performed using R, version 4.4.0.

Results

Video characteristics

Table 1 demonstrates the basic characteristics of COPD-related videos across the three platforms. In total, 167, 167, and 176 videos were included from TikTok, RedNote, and Bilibili, respectively. Analysis of general video characteristics revealed statistically significant differences in interaction metrics among the three platforms (P<0.001). TikTok videos showed significantly higher numbers of likes, comments, shares, and favorites than RedNote and Bilibili videos. For quality assessment, both overall GQS and mDISCERN scores were significantly higher for Bilibili videos (P<0.001). Bilibili also outperformed the other platforms consistently across all mDISCERN subdomains (Table S3).

Video content and sources

The kappa values were 0.85 for content categories and 0.88 for uploader types. Regarding video content, TikTok primarily focused on disease prevention (31.6%), whereas RedNote and Bilibili focused on disease treatment (26.5% and 36.4%, respectively) (Figure 2A-2C). In terms of uploader types, TikTok was dominated by professional individuals (63.5%), whereas RedNote and Bilibili were dominated by nonprofessional institutions (60.5% and 73.9%, respectively) (Figure 2D-2F).

Figure 2 Distribution of content categories and uploader types of COPD-related short videos. Content categories on TikTok (A), RedNote (B), and Bilibili (C), respectively. Uploader types on TikTok (D), RedNote (E), and Bilibili (F), respectively. COPD, chronic obstructive pulmonary disease.

Video popularity and quality assessment

Regarding video popularity, TikTok videos demonstrated significantly higher numbers of likes, comments, shares, and favorites than RedNote and Bilibili videos (Figure 3), whereas no significant difference was observed between RedNote and Bilibili. In terms of video quality, at the platform level, Bilibili videos achieved significantly higher GQS and mDISCERN scores than RedNote and TikTok videos (Figure 4A,4B), with no significant difference between RedNote and TikTok. At the uploader level, videos uploaded by institutions received significantly higher GQS and mDISCERN scores than those uploaded by individuals. Videos from professional individuals scored significantly higher on both GQS and mDISCERN than those from nonprofessional individuals (Figure S1A,S1B). At the content level, videos categorized as Advertisement and Experience Sharing scored significantly lower than the other content types. No significant differences were observed among the four content categories of Disease Prevention, Disease Mechanism, Disease Diagnosis, and Disease Treatment (Figure S2A,S2B).

Figure 3 Comparison of the popularity of COPD-related short videos. User engagement indicators, including likes, comments, shares, and favorites/saves, were compared among TikTok, RedNote, and Bilibili. Between-platform differences were assessed using Kruskal-Wallis H tests. ***, P<0.001. COPD, chronic obstructive pulmonary disease.

Figure 4 GQS and mDISCERN scores of COPD-related short videos. (A) GQS scores across platforms; (B) mDISCERN scores across platforms. ***, P<0.001. COPD, chronic obstructive pulmonary disease; GQS, Global Quality Scale; mDISCERN, modified Decision-Making Information Support Criteria for Evaluating the Reliability of Non-randomized Studies.

Correlation analysis of video variables

Spearman’s rank correlation analysis was used to explore the associations between video dissemination metrics and quality assessment scores (Figure 5). The results indicated strong positive correlations among all popularity metrics (likes, comments, shares, and favorites) across all videos. GQS and mDISCERN scores also showed a significant positive correlation, with the strongest correlation observed on the Bilibili platform (ρ =0.75). No other significant correlations were observed among the remaining variables.

Figure 5 Spearman’s rank correlation analysis of different variables for COPD-related short videos. (A) TikTok, (B) RedNote, and (C) Bilibili. Each cell displays Spearman’s rank correlation coefficient (ρ) between two variables. The colored value bars represent the correlation coefficients, with darker red indicating stronger positive correlations and lighter red indicating weaker correlations or values closer to zero. The analysis included popularity metrics, GQS scores, and mDISCERN scores. COPD, chronic obstructive pulmonary disease; GQS, Global Quality Scale; mDISCERN, modified Decision-Making Information Support Criteria for Evaluating the Reliability of Non-randomized Studies.

Qualitative characterization of misinformation themes

Overall, 42.4% (156/368) of videos uploaded by non-professional individual users were identified as containing misinformation. Within these videos, five major misinformation themes were identified: (I) oversimplification of treatment benefits (n=42); (II) misleading claims about alternative remedies as substitutes for standard care (n=35); (III) confusion between symptoms and formal diagnosis (n=34); (IV) underestimation of guideline-based maintenance therapy (n=30); (V) exaggerated risks of inhaled medications (n=15). Details of the themes and their descriptions are presented in Table 2.

Discussion

In this cross-sectional content analysis, we systematically evaluated COPD-related short videos on three major Chinese short-video platforms, focusing on their dissemination characteristics, content types, sources, and information quality. Our findings revealed substantial differences across platforms in popularity metrics and content quality.

Dissemination and user engagement

From a dissemination perspective, TikTok videos exhibited significantly higher levels of user engagement than RedNote and Bilibili videos, as reflected by the number of likes, comments, shares, and saves, which is consistent with TikTok’s algorithm-driven content distribution model and its emphasis on viral reach (15). Notably, higher popularity did not correspond to higher information quality, as TikTok videos achieved lower GQS and mDISCERN scores than Bilibili videos. Algorithmic amplification and user engagement may be driven more by presentation style and accessibility than by informational rigor. A similar phenomenon has been reported in studies evaluating disease-related content on short-video platforms (16,17).

Platform-specific quality and ecosystems

Regarding information quality, Bilibili videos achieved the highest GQS and mDISCERN scores among the three platforms. Bilibili’s user base is characterized by higher educational attainment and a stronger preference for in-depth, explanatory content, which may partially explain the superior quality observed (18). Platform-specific culture and audience expectations may play a critical role in shaping the quality of health information. Bilibili has traditionally been regarded as a content-sharing platform focused on education, knowledge exchange, and longer-form videos (19). Its users are often characterized by higher educational attainment and a stronger interest in detailed explanations, which may encourage content creators to provide more comprehensive and balanced medical information (20). Given the pressure to capture viewers’ attention within a very short period, creators may oversimplify complex disease-related concepts or omit critical details, such as treatment risks or alternative management approaches.

Uploader type was also an important determinant of video quality. Videos uploaded by institutions achieved significantly higher GQS and mDISCERN scores than those uploaded by individuals; professional individuals outperformed nonprofessional individuals. This finding is consistent with previous research and reinforces the importance of medical expertise and institutional oversight in the production of reliable health information (21,22). Professional involvement helps ensure a baseline level of medical accuracy that lay creators often lack (23). Nevertheless, nonprofessional institutions dominated content production on RedNote and Bilibili, indicating a potential gap between content supply and professional involvement that warrants further attention.

Content focus and reliability

Across content categories, videos focusing on disease prevention, mechanisms, diagnosis, and treatment showed comparable quality scores, whereas advertisement and experience-sharing videos scored significantly lower. In addition to these differences in quality, this study identified distinct patterns in content focus and uploader composition across platforms. TikTok videos primarily addressed disease prevention, whereas RedNote and Bilibili focused more heavily on disease treatment. These differences may reveal platform-specific audience preferences and content strategies. Prevention-related content is often easier to present in short, actionable formats and may appeal to a broader audience, whereas treatment-related information typically requires more detailed explanation and context. Although experience-sharing content may provide emotional support and relatability, it often lacks systematic medical information and may introduce anecdotal bias (24). Similarly, advertisement-related videos may selectively emphasize benefits while omitting risks or alternative management options, thereby reducing informational reliability. These findings highlight the need for viewers to critically evaluate the purpose of content and for platforms to strengthen content labeling and review mechanisms (25).

Information quality and engagement correlation

Correlation analysis provided important insights into the association between dissemination metrics and information quality. No significant correlation was identified between engagement indicators and GQS or mDISCERN scores. This finding suggests a disconnect between user engagement and the quality of medical information. The absence of an association between quality and engagement has important public health implications, as low-quality information may achieve widespread dissemination and influence patient perceptions and behaviors (14). Without deliberate intervention, high-quality content produced by professional individuals may struggle to compete with more sensationalized or simplified videos (26,27).

Misinformation and clinical implications

Nearly half of the videos uploaded by non-professional individuals (42.4%) contained misinformation, most frequently involving overly optimistic treatment claims, unproven therapies, and alternative remedies presented as substitutes for guideline-based care. Low-quality videos often failed to address several clinically important issues, including adherence to long-acting bronchodilators such as long-acting muscarinic antagonist/long-acting beta-agonist (LAMA/LABA) therapy, correct inhaler technique, recognition of acute exacerbations, and regular follow-up. Some videos also placed disproportionate emphasis on symptomatic relief or non-standard remedies while providing limited discussion of evidence-based maintenance treatment. Given that COPD management depends on sustained, individualized, and evidence-based interventions, such misinformation may have clinically meaningful consequences (28,29). Patients exposed to these narratives may develop unrealistic expectations, underestimate the importance of long-term treatment, delay medical consultation during exacerbations, or become reluctant to follow recommended therapeutic strategies (30,31).

Several factors may contribute to the dissemination of inaccurate COPD-related information on short-video platforms. These include the absence of rigorous pre-publication review mechanisms, algorithmic systems that prioritize engagement over accuracy, and the tendency of lay creators to generalize personal experiences into broad medical advice (32). Beyond misinformation, COPD-related videos also showed broader structural limitations, including inconsistent quality, a disconnect between popularity and credibility, and substantial involvement of non-specialist creators. Platforms should strengthen medical content oversight and promote professionally produced videos (33). Respiratory professionals should create concise, accessible, and scientifically rigorous educational content that directly addresses common misconceptions (34). Patients should be equipped with practical skills to critically appraise online content, such as verifying creator credentials, approaching absolute claims such as “complete cure” with caution (35).

This study provides evidence to support the optimization of COPD-related digital health communication strategies on short-video platforms. However, several limitations should be acknowledged. First, the cross-sectional design captured video content at a single time point and therefore could not reflect temporal changes in content quality and dissemination. Second, quality assessment using the GQS and mDISCERN instruments involves an inevitable degree of subjective judgment. Third, platform algorithms that prioritize highly interactive content may exclude low-popularity but high-quality videos, resulting in potential sampling bias. Despite these limitations, this study provides a comprehensive comparative evaluation of COPD-related short videos across major Chinese platforms.

Conclusions

In conclusion, content reliability varies distinctly by platform and uploader background, and video popularity fails to reflect factual accuracy. Widespread medical misconceptions pose tangible risks to standardized disease care. Strengthened professional participation and platform supervision are essential to optimize online COPD health education.

Acknowledgments

None.

Footnote

Peer Review File: Available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-0907/prf

Funding: This study was supported by the Key Support Project of the Regional Innovation and Development Joint Fund of the National Natural Science Foundation of China (No. U20A20398), the General Program of the National Natural Science Foundation of China (No. 82374399), the Anhui Provincial High-Level Traditional Chinese Medicine Inheritance Talent Development Project in 2024 (No. 2024sjzyfzzxgspccrcxm20240066), and Natural Science Foundation Doctoral Special Project of the Anhui Provincial Department of Education (No. 2025AHGXZK50104). The funders of the study did not have any involvement in the design of this study, data collection, analysis, interpretation, or writing the report.

Conflicts of Interest: All authors have completed the ICMJE uniform disclosure form (available at https://jtd.amegroups.com/article/view/10.21037/jtd-2026-0907/coif). The authors have no conflicts of interest to declare.

Ethical Statement: The authors are accountable for all aspects of the work in ensuring that questions related to the accuracy or integrity of any part of the work are appropriately investigated and resolved.

Open Access Statement: This is an Open Access article distributed in accordance with the Creative Commons Attribution-NonCommercial-NoDerivs 4.0 International License (CC BY-NC-ND 4.0), which permits the non-commercial replication and distribution of the article with the strict proviso that no changes or edits are made and the original work is properly cited (including links to both the formal publication through the relevant DOI and the license). See: https://creativecommons.org/licenses/by-nc-nd/4.0/.

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