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Abstract

Objective

This study aims to systematically assess the content characteristics and information quality of knee arthroplasty-related videos on TikTok and Bilibili, in order to provide evidence to support the optimization of health science communication.

Methods

On February 13, 2025, we searched for “膝关节置换” (knee arthroplasty in Chinese) on TikTok and Bilibili, and initially collected 100 videos from each platform according to the default sorting order, which were then subjected to further screening. Videos containing irrelevant content, lacking audio, being non-original reposts, or intended for advertising and marketing purposes were excluded. The quality and reliability of the included videos were assessed by applying four validated instruments: the modified version of DISCERN (mDISCERN), the Global Quality Score (GQS), the Video Information and Quality Index (VIQI), and the Patient Education Materials Assessment Tool (PEMAT). Interplatform variations and correlations between quality and user interactions were analyzed via Mann‒Whitney U and chi-square tests.

Results

A total of 162 knee arthroplasty related videos were analyzed, including 88 from TikTok and 74 from Bilibili. TikTok videos demonstrated higher engagement and more certified uploaders, whereas Bilibili featured more diverse professional backgrounds. Bilibili emphasizing anatomy using PPT/class based, animation/ motion and television program/documentary styles. TikTok focusing on examination/diagnosis, and treatment delivered through solo narrative and Questions and Answers (Q&A). TikTok videos achieved higher scores across all quality assessment tools. Professionally generated content consistently outperformed nonprofessional content across most quality metrics, whereas no significant difference was observed for mDISCERN. Correlation analysis showed that engagement was strongly associated with VIQI on both platforms, with additional moderate associations for GQS and PEMAT only on TikTok, while mDISCERN showed no significant correlation.

Conclusions

TikTok favors high user engagement, whereas Bilibili provides more structured educational content. Professional involvement is essential to ensure information quality and effective medical communication.

Keywords

Bilibili health science information quality knee arthroplasty short video platforms TikTok

Introduction

Knee arthroplasty is the mainstream treatment for end-stage knee osteoarthritis.¹ The global annual surgical volume continues to increase, exceeding 200 procedures per 100,000 population in some high income countries^.² Although the procedure is generally safe and effective, postoperative complications such as deep vein thrombosis remain common, and the mortality rate is still approximately 0.2%–0.4%.³ These risks, combined with frequent misunderstandings about the surgery among patients and their families, suggest the need to popularize the science of knee arthroplasty surgery to aid patient-doctor communication and promote their postoperative recovery.^4,5

Online video platforms have become important channels for the public to access medical information.⁶ Digital health communication has reshaped the doctor-patient interaction model, and patients can significantly improve their participation in preoperative decision-making and postoperative self-management by actively learning about surgical principles and rehabilitation.⁷ However, the quality of information on current video platforms varies, which may lead to cognitive bias or delays in standardized treatment.^8,9 A growing proportion of health information in such videos relies on on-screen text and subtitles, underscoring the need for health education materials to be clear, accurate, and easy to understand, as recommended by major health authorities such as the National Institutes of Health, the U.S. Department of Health and Human Services, and the American Medical Association.¹⁰ Therefore, regulating such videos’ scientific validity and credibility is crucial for optimizing treatment outcomes and enhancing public health awareness.¹¹

TikTok and Bilibili are two of China's most popular online video platforms.^12,13 Among them, TikTok is a representative short-video platform that can achieve accurate access to medical content through intelligent algorithms.¹⁴ BiliBili, as a comprehensive video-sharing platform popular among China's younger generations, has built an in-depth health knowledge dissemination scenario through its professional community attributes.¹⁵ It is known that approximately half of the adult population consults the internet for health-related information.¹⁶ There are many videos related to knee arthroplasty on the above platforms, but there is a lack of quality assessment for these videos.

Therefore, this study systematically examines the types and quality of information presented in knee arthroplasty related videos on Bilibili and TikTok, with the aim of helping viewers identify reliable information and promoting informed understanding of knee arthroplasty.

Materials and methods

Study design

This study was designed as a cross-sectional content analysis. The initial data collection was conducted on February 13, 2025, at the Henan Province Hospital of Traditional Chinese Medicine (The Second Affiliated Hospital of Henan University of Chinese Medicine) by the research team. The hospital serves as a clinical teaching and research institution affiliated with the Henan University of Chinese Medicine, ensuring close integration between clinical practice and academic research. Following data acquisition, systematic screening, coding, and statistical processing were performed between February 13 and March 1, 2025, to ensure the accuracy of the dataset. resolved by a third author. All the information is derived from publicly posted Bilibili and TikTok videos and does not involve personal privacy data, so no ethical scrutiny is needed.

Video collection and review

On February 13, 2025, a search was performed on Bilibili and TikTok with the keywords“膝关节置换”(Knee arthroplasty in Chinese). Two authors independently reviewed all retrieved videos and excluded those containing irrelevant content, lacking audio, being non-original reposts, or intended for advertising and marketing purposes. Direct reprints, translations, or rough versions of videos are not considered original videos.

Video characteristics

The system automatically recorded multiple video engagement metrics, including the numbers of likes, favorites, comments, shares, views, and bullet-screen messages. The authentication status of each uploader account was first identified. Among certified accounts, uploaders were categorized into doctors, other health workers or students, hospitals, departments, or associations (nonprofit organizations), and for-profit companies. The subject of the videos was categorized into anatomy, etiology/prevention, pathology, epidemiology, symptoms, examination/diagnosis, treatment, and prognosis. Video shooting styles are categorized as solo narrative, question and answer (Q&A), PPT/class, animation/motion, medical scene, and television programs/documentaries. In addition, the inclusion of knowledge related to Traditional Chinese Medicine was extracted as one of the video characteristics.

Quality assessment

The quality and reliability of the included videos were assessed by applying four validated instruments: the modified version of DISCERN (mDISCERN),¹⁷ the Global Quality Score (GQS),¹⁸ the Video Information and Quality Index (VIQI)^,¹⁹ and the Patient Education Materials Assessment Tool (PEMAT).²⁰

The mDISCERN consists of five related questions. Each question has a “yes” score of 1 and a “no” score of 0. The higher the score is, the more reliable the corresponding video (Supplementary material 1).

The GQS measures whether the information is clear, accurate, and reliable and provides valuable health guidance to viewers. Scores range from 1 to 5, with higher scores indicating higher quality and credibility of the content; conversely, they indicate that the content may be one-sided, inaccurate, or lacking scientific support (Supplementary material 2).

The VIQI consists of four dimensions: information fluency, accuracy, quality, and precision, denoted by VIQI-1, VIQI-2, VIQI-3, and VIQI-4, respectively. Higher scores indicate better quality (Supplementary material 3).

The PEMAT assesses the understandability and ability of patient education materials. We score each item on a scale of “Agree = 1, Disagree = 0, N/A (not applicable).” The total score (PEMAT-T), understandability (PEMAT-U), and actionability (PEMAT-A) were calculated as (actual score/maximum possible score) × 100. Higher final scores indicate better quality and applicability of the video (Supplementary material 4).

Statistical analysis

The data were statistically analyzed via SPSS 25.0 software. The Shapiro–Wilk test was used to assess the normality of continuous variables. Continuous variables that did not conform to a normal distribution are presented as the median and interquartile range (M [P25, P75]). We used the Mann-Whitney U test to compare continuous variables that did not fit the normal distribution, reporting them as numbers and ratios. The chi-square test and continuity correction were used to compare categorical variables to elucidate the differences between the two platforms, TikTok and Bilibili. Correlation analysis was performed via Spearman's method to assess the relationship between viewer interaction and video quality, where r > 0 indicates a positive correlation and r < 0 indicates a negative correlation. The strength of the correlation was categorized as follows: |r| ≤ 2 indicates no correlation; 0.2 < |r| ≤ 0.4 indicates a weak correlation; 0.4 < |r| ≤ 0.6 indicates a moderate correlation; and 0.6 < |r| ≤ 0.8 indicates a strong correlation, with a p-value of < 0.05 considered statistically significant.

Results

Video characteristics

Among the 200 videos obtained, 162 (81%) valid videos were finally obtained for inclusion in this study (Figure 1), including 88 TikTok videos and 74 Bilibili videos used to analyze the dissemination characteristics of knee arthroplasty-related content (Table 1). The number of thumbs up and comments on TikTok videos was significantly greater than that on Bilibili videos (P < 0.001).

Figure 1.

Search strategy for videos on knee arthroplasty.

Table 1.

Characteristics of videos about knee arthroplasty on TikTok and Bilibili.

Subject	TikTok (N1 = 88)			Bilibili (N2 = 74)			P value
	M	Min–Max	P25-P75	M	Min–Max	P25-P75	P value
Thumbs up	227	15–15546	81.75–732.75	19.5	0–2727	4–70	<0.001 ^a
Favorites	27.5	0–5651	10.25–181.25	25.5	0–1908	6.75–98.5	0.181^a
Comments	13	1–3545	5–70	2	0–749	0–8	<0.001^a
Shares	13	0–7610	3.25–85	-	-	-	-
Views	-	-	-	1152	28–313073	392–5444.5	-
Bullet screen	-	-	-	0	0–225	0–1	-

Mann‒Whitney U test.

-indicates that no corresponding data were available on the platform.

Uploader characteristics

There were 88 TikTok uploaders and 74 Bilibili uploaders (Table 2). aRegarding whether they were certified and the type of certification, TikTok had the highest percentage of certified uploaders, 93.2%, and 92.0% were certified as doctors (P < 0.001).

Table 2.

Characteristics of video uploaders on TikTok and Bilibili concerning knee arthroplasty.

Subject	TikTok (N1 = 88)	Bilibili (N2 = 74)	P value
Certification, n (%)	82 (93.2%)	35 (47.3%)	<0.001^b
Type of certified uploader, n (%)
Doctor	81 (92.0%)	33 (44.6%)	<0.001^b
Other health workers/students	0	0	-
Hospitals/departments/associations (also considered nonprofit organizations)	1 (1.1%)	1 (1.4%)	＞0.999^c
For-profit company	0	1 (1.4%)	0.457^c
Official and self-published media	0	0	-
Non-certified	6 (6.8%)	39 (52.7%)	<0.001^b

Chi-Square test.

Fisher's exact test.

Video categorization

Subject categorization differed between platforms, with Bilibili emphasizing anatomy (P < 0.001) and TikTok emphasizing examination/diagnosis (P = 0.022) and treatment (P = 0.010) (Table 3). Video shooting style categorization differed between platforms, with TikTok favoring solo narrative (P < 0.001) and questions and answers (Q&A) (P = 0.001), and Bilibili favoring PPT/class based (P < 0.001), animation/ motion (P < 0.001) and television program/documentary styles (P = 0.011). In addition, 6.8% of Bilibili videos incorporate knowledge of traditional Chinese medicine, whereas TikTok has no such content.

Table 3.

Categorization of videos about knee arthroplasty on TikTok and Bilibili.

Subject, n (%)	TikTok (N₁ = 88)	Bilibili (N₂ = 74)	P value
Anatomy	0	20 (27.0%)	<0.001^b
Etiology/Prevention	4 (4.5%)	2 (2.7%)	0.531^d
Pathology	0	1 (1.4%)	0.457^c
Epidemiology	0	0	-
Symptoms	0	1 (1.4%)	0.457^c
Examination/Diagnosis	11 (12.5%)	2 (2.7%)	0.022^b
Treatment	37 (42.0%)	17 (23.0%)	0.010^b
Prognosis	43 (48.9%)	31 (41.9%)	0.375^b
Video shooting style, n (%)
Solo narrative	42 (47.7%)	9 (12.2%)	<0.001^b
Questions and Answers (Q&A)	8 (9.1%)	0	0.001^d
PPT/classes	0	7 (9.5%)	<0.001^d
Animation/Motion	4 (4.5%)	33 (44.6%)	<0.001^b
Medical Scenarios	34 (38.6%)	21 (28.4%)	0.170^b
Television programs/documentaries	0	4 (5.4%)	0.011^d
Whether knowledge of Traditional Chinese Medicine is included, n (%)
Yes	0	5 (6.8%)	-
No	88 (100%)	69 (93.2%)	-

Chi-Square test.

Fisher's exact test.

Continuity correction.

Video quality

Video quality assessment revealed consistently higher scores for TikTok than for Bilibili on mDISCERN (P < 0.001), GQS (P = 0.006), VIQI (P < 0.001), PEMAT-U (P < 0.001), PEMAT-A (P = 0.042) and PEMAT-T (P < 0.001) (Table 4).

Table 4.

Quality assessment of videos about knee arthroplasty on TikTok and Bilibili.

Subject	TikTok (N₁ = 88)			Bilibili (N₂ = 74)			P value
Subject	M	Min–Max	P25-P75	M	Min–Max	P25-P75	P value
mDISCERN-1	71 (80.7%)			69 (93.2%)			0.020^b
mDISCERN-2	14 (15.9%)			52 (70.3%)			<0.001^b
mDISCERN-3	83 (94.3%)			73 (98.6%)			0.300 ^d
mDISCERN-4	14 (15.9%)			13 (17.6%)			0.778^b
mDISCERN-5	1 (1.1%)			14 (18.9%)			<0.001^b
mDISCERN-sum	8	6–9	8–8	7	5–9	7–8	<0.001^a
GQS	3	2–5	3–4	3	2–4	3–3.25	0.006^a
VIQI-1	3	2–5	2–3	2	1–4	1–2.25	<0.001^a
VIQI-2	4	2–5	3–4	3	1–4	2–3	<0.001^a
VIQI-3	3	2–5	3–4	3	2–4	2–3	<0.001^a
VIQI-4	4	3–5	4–4.75	3	2–5	3–4	<0.001^a
VIQI-sum	14	11–20	12.25–15.75	11	7–15	10–12	<0.001^a
PEMAT-U	9	6–13	9–11	7.5	5–11	7–8	<0.001^a
PEMAT-A	3	2–4	2–3	2	1–3	2–3	0.042^a
PEMAT-T	12	8–17	11–13.75	10	7–14	9–11	<0.001^a

Mann‒Whitney U test.

Chi-Square test.

Continuity correction.

Video quality assessment showed that professional generated videos scored higher than non-professional generated videos in GQS (P < 0.001), VIQI (P < 0.001), PEMAT-U (P < 0.001), PEMAT-A (P < 0.001), and PEMAT-T (P < 0.001) (Table 5).

Table 5.

Comparison of video quality between professionals and non-professionals.

Subject	Professionals (N = 116)			Non-Professionals (N = 46)			P value
Subject	M	Min–Max	P25-P75	M	Min–Max	P25-P75	P value
mDISCERN-1	100 (86.2%)			40 (87.0%)			0.900^b
mDISCERN-2	48 (41.4%)			18 (39.1%)			0.793^b
mDISCERN-3	114 (98.3%)			42 (91.3%)			0.097^d
mDISCERN-4	20 (17.2%)			7 (15.2%)			0.755^b
mDISCERN-5	7 (6.0%)			8 (17.4%)			0.051^d
mDISCERN-sum	8	5–9	7–8	8	5–9	7–8	0.834^a
GQS	3	2–5	3–4	3	2–4	2.75–3	<0.001^a
VIQI-1	3	1–5	2–3	2	1–3	1–3	<0.001^a
VIQI-2	4	1–5	3–4	3	2–4	2–3	<0.001^a
VIQI-3	3	2–5	3–4	3	2–4	2–3	0.031^a
VIQI-4	4	3–5	4–4	3	2–5	3–4	<0.001^a
VIQI-sum	13	8–20	11–15	11	7–15	9.75–12	<0.001^a
PEMAT-U	9	6–13	8–10	7	5–10	6–8	<0.001^a
PEMAT-A	3	2–4	2–3	2	1–3	2–3	<0.001^a
PEMAT-T	12	8–17	10.25–13	9	7–13	8–10	<0.001^a

Professionals: physicians, other healthcare workers/students, hospitals/departments/associations, for-profit healthcare companies, official media.

Non-professionals: self-publishers, nonaccredited people.

Mann‒Whitney U test.

Chi-Square test.

Continuity correction.

Correlation analysis

Correlation analysis revealed platform specific patterns (Table 6). On TikTok, VIQI was strongly correlated with all engagement metrics, GQS and PEMAT were moderately correlated, and mDISCERN was not significantly associated. On Bilibili, significant correlations were limited to VIQI, which showed strong associations with Thumbs up and Views, and moderate associations with Favorites, Comments, and Bullet screen.

Table 6.

Correlation analysis between video quality and viewer interaction on TikTok and Bilibili.

r	TikTok (N₁ = 88)				Bilibili (N₂ = 74)
P value	mDISCERN	GQS	VIQI	PEMAT	mDISCERN	GQS	VIQI	PEMAT
Thumbs up	0.118	0.545	0.730	0.521	0.062	0.025	0.678	0.147
Thumbs up	0.274	<0.001	<0.001	<0.001	0.598	0.830	<0.001	0.210
Favorites	0.138	0.499	0.658	0.498	0.193	−0.024	0.576	−0.012
Favorites	0.200	<0.001	<0.001	<0.001	0.100	0.836	<0.001	0.917
Comments	0.121	0.502	0.658	0.473	0.024	−0.101	0.506	0.093
Comments	0.261	<0.001	<0.001	<0.001	0.836	0.390	<0.001	0.430
Shares	0.142	0.535	0.660	0.492	-	-	-	-
Shares	0.186	<0.001	<0.001	<0.001	-	-	-	-
Views	-	-	-	-	0.036	0.013	0.607	0.041
Views	-	-	-	-	0.764	0.912	<0.001	0.729
Bullet screen	-	-	-	-	0.021	−0.108	0.408	−0.019
Bullet screen	-	-	-	-	0.858	0.359	<0.001	0.876

|r|≤ 2 uncorrelated; 0.2< |r|≤ 0.4 weakly correlated; 0.4< |r|≤ 0.6 moderately correlated; 0.6< |r|≤ 0.8 strongly correlated.

-indicates that at least one variable is constant and cannot be calculated.

Discussion

As an important tool for public health education, social media has developed rapidly in recent years because of its ability to overcome geographical limitations and enhance the accessibility of medical information.²¹ Digital video has become a central vehicle for patients to access health information, and its dynamic visualization features help popularize complex medical concepts such as surgical procedures and rehabilitation training.¹¹ This study is the first to systematically assess the characteristics of knee arthroplasty-related videos on the TikTok and Bilibili platforms.

Video characteristics

The results suggest that knee arthroplasty videos on TikTok demonstrate better interactivity, as evidenced by higher numbers of thumbs up and comments. The high interaction rate of TikTok is closely related to its algorithmic mechanism of prioritizing short-duration and high-engagement content.²² These kinds of algorithms tend to highlight content that makes people feel strongly, and even if the medical information isn't very detailed, it may still get to a lot of people quickly.²³ In contrast, Bilibili emphasizes content completeness and structured presentation, which is associated with lower immediate interaction but greater informational density.^24,25 Because of this, platform algorithm optimization needs to find a balance between focusing on popular topics and screening professional content.²⁶ Future dissemination strategies should align content presentation with platform specific interaction mechanisms. On TikTok, concise and visually engaging videos can be used to enhance interaction while maintaining informational accuracy. On Bilibili, optimizing engagement strategies within structured educational content may improve interaction without reducing content depth.

Uploader characteristics

The present study found that TikTok had a significantly higher proportion of certified uploaders, predominantly doctors, in contrast to Bilibili, where certified uploaders represented more heterogeneous professional categories. The diversity in the types of uploaders on the platforms is attributed mainly to the differences in the platforms’ authentication policies.²³ TikTok adopts a profession oriented certification system that emphasizes medical credentials, enhancing the visibility and credibility of physician generated content.^27,28 In contrast, Bilibili applies a more inclusive authentication framework that allows diverse professional and institutional identities, resulting in greater heterogeneity among certified uploaders.²⁹ Future platform governance should balance professional authority with interdisciplinary participation. TikTok could broaden certification to other qualified health professionals and institutions while maintaining medical accuracy, whereas Bilibili should strengthen the identification of medical credentials within its diverse system to improve content credibility and patient recognition of authoritative information.

Video categorization

Clear differences were observed in both subject categorization and shooting style between platforms. Bilibili's significant dominance in anatomical topics is closely related to its animation- or motion-driven creation style, which, through 3D model disassembling and surgical simulation, can effectively reduce the complexity of medical knowledge and the threshold of understanding.³⁰ On the other hand, TikTok's creative style of solo narrative and medical scenarios is more suitable for the demand for short videos for emotional resonance and immediate information transfer. However, excessive reliance on personal narratives may lead to fragmentation of information, especially in treatment and prognosis topics, and the subjectivity of patient experiences may weaken the authority of clinical guidelines.³¹ Notably, 6.8% of videos in Bilibili integrated knowledge of postoperative traditional Chinese medicine conditioning. In contrast, TikTok did not involve such content at all, reflecting the limitations of short video platforms in disseminating diverse medical perspectives. Future content development should adopt platform specific strategies. TikTok should enhance the structural organization of solo narrative and scenario based videos, particularly for treatment and prognosis topics, by incorporating standardized and guideline oriented information to reduce fragmentation. Bilibili should further leverage animation driven strengths to expand content beyond anatomy into perioperative management and rehabilitation, including evidence based postoperative traditional Chinese medicine conditioning, thereby improving both educational depth and accessibility.

Video quality

This study showed that TikTok videos consistently achieved higher scores across all video quality assessment tools, including mDISCERN, GQS, VIQI, and PEMAT, compared with Bilibili. In addition, videos generated by professionals scored significantly higher than those generated by non professionals across multiple quality metrics. This finding reflects the inherently high level of specialized medical knowledge required for knee arthroplasty related content, which encompasses complex surgical indications, perioperative management, postoperative rehabilitation, and risk communication.³² Accurate presentation of such information relies heavily on formal medical training and clinical experience, thereby conferring a clear advantage to professionally generated videos in terms of reliability, clarity, and actionability.³³ The consistently higher video quality scores observed on TikTok further correspond to the greater representation of certified medical professionals on the platform.³⁴ Professional creators are more likely to structure content in accordance with clinical guidelines and patient education principles, resulting in improved understandability and educational effectiveness across multiple assessment tools.³⁵ These findings underscore the necessity of professional involvement in the dissemination of knee arthroplasty related information to ensure the delivery of accurate and high-quality health education⁹. Future efforts should focus on platform optimization, with Bilibili introducing more professional teams to improve production standards, TikTok strengthening content auditing to ensure informational rigor, and both platforms enhancing mechanisms for conflict of interest disclosure to increase the credibility of medical science content.

Correlation analysis

Correlation analysis showed that engagement was strongly associated with VIQI on both platforms, while GQS and PEMAT were moderately correlated only on TikTok and mDISCERN showed no significant association, with Bilibili displaying significant correlations exclusively for VIQI. This pattern indicates that user engagement on both platforms is primarily driven by visual presentation quality rather than information reliability, as visually appealing and well structured content directly captures audience attention, whereas the accuracy and completeness of medical information alone do not translate into interactive behaviors.^36,37 Consistent with previous studies,^15,24 some users cannot discern the quality of health-related videos. Importantly, given the widespread reliance on online health information, evidence suggests that information and communication technology–based patient education can promote self-management and behavioral change in some diseases.³⁸ Accordingly, platforms should move beyond engagement-based metrics alone and collaborate with medical professionals to strengthen content review and ensure adequate readability and understandability, thereby reducing misunderstanding and improving educational value.³⁹

Limitations

Previous studies on orthopedic related social media content have mainly focused on other joint diseases and Western platforms, with limited differentiation between professional and nonprofessional creators.^40–42 Building on this literature, the present study systematically evaluated knee arthroplasty related videos on TikTok and Bilibili using a cross platform comparative design and multiple validated assessment tools, including mDISCERN, GQS, VIQI, and PEMAT. This integrated approach enabled a multidimensional assessment of medical information that captured not only content reliability but also visual presentation and educational effectiveness. In addition, the inclusion of uploader verification status and the inclusion of traditional Chinese medicine related content allowed for a more nuanced examination of platform specific and cultural influences on medical content creation. Together, these methodological and contextual considerations enhance the interpretability and practical relevance of the findings for patient education, content optimization, and platform governance.

Despite the above strengths, several limitations should be considered when interpreting the findings of this study. First, although multidimensional assessment tools were applied and independently scored by medical experts, the evaluation framework did not fully incorporate platform specific and culturally differentiated indicators, which may have introduced systematic bias. Second, restrictions in platform data availability limited the inclusion of certain engagement indicators. For example, TikTok does not disclose video play counts, and neither platform provides a dislike or negative feedback mechanism. Third, the analysis was restricted to knee arthroplasty related content within the Chinese context, and multilingual or cross-cultural comparisons were not included, which may limit the generalizability of the findings. In addition, video affiliated textual information was not analyzed, potentially omitting supplementary quality cues. Finally, the study was based on a cross-sectional snapshot of data collected in 2025, and ongoing changes in social media algorithms and user behavior may affect the temporal validity of the results. Future research should incorporate longitudinal designs and dynamic monitoring frameworks, including multimodal data mining and natural language processing techniques, to better capture the evolving landscape of medical information dissemination.

Conclusion

This study systematically reveals the differentiated characteristics of TikTok and Bilibili in disseminating videos related to knee arthroplasty. TikTok emphasizes interactivity and emotional narratives, enabling rapid dissemination of patient experiences and high user engagement, while offering opportunities to enhance informational depth through more structured medical messaging. In contrast, Bilibili prioritizes systematic knowledge delivery through structured formats such as animation and PPT, providing strong educational value, and may further improve its impact by optimizing engagement strategies for long-form medical content. The study further shows that videos produced by professionally certified creators outperform those by nonprofessionals in information accuracy and actionability, highlighting the importance of professional involvement. Looking ahead, platforms should optimize algorithmic weighting to incorporate scientific communication indicators, creators should develop hybrid narratives integrating animation and clinical scenarios, and regulators should establish cross platform auditing frameworks to support accurate medical information dissemination and the enhancement of public health literacy.

Supplemental Material

sj-docx-1-dhj-10.1177_20552076261421072 - Supplemental material for A comparative study of medical information quality and dissemination efficacy of knee arthroplasty videos in Bilibili/TikTok short video platforms

Supplemental material, sj-docx-1-dhj-10.1177_20552076261421072 for A comparative study of medical information quality and dissemination efficacy of knee arthroplasty videos in Bilibili/TikTok short video platforms by Bingqi Wei, Xinyue Zhang, Liu Chen, Xingyue Ren, Yijing Li, Feiyang Chen, Luwei Zhang, Yunfang Fan, Zimeng Xie, Jiarong Li, Yueyang Chen and Shangzeng Wang in DIGITAL HEALTH

Supplemental Material

sj-docx-2-dhj-10.1177_20552076261421072 - Supplemental material for A comparative study of medical information quality and dissemination efficacy of knee arthroplasty videos in Bilibili/TikTok short video platforms

Supplemental material, sj-docx-2-dhj-10.1177_20552076261421072 for A comparative study of medical information quality and dissemination efficacy of knee arthroplasty videos in Bilibili/TikTok short video platforms by Bingqi Wei, Xinyue Zhang, Liu Chen, Xingyue Ren, Yijing Li, Feiyang Chen, Luwei Zhang, Yunfang Fan, Zimeng Xie, Jiarong Li, Yueyang Chen and Shangzeng Wang in DIGITAL HEALTH

Supplemental Material

sj-docx-3-dhj-10.1177_20552076261421072 - Supplemental material for A comparative study of medical information quality and dissemination efficacy of knee arthroplasty videos in Bilibili/TikTok short video platforms

Supplemental material, sj-docx-3-dhj-10.1177_20552076261421072 for A comparative study of medical information quality and dissemination efficacy of knee arthroplasty videos in Bilibili/TikTok short video platforms by Bingqi Wei, Xinyue Zhang, Liu Chen, Xingyue Ren, Yijing Li, Feiyang Chen, Luwei Zhang, Yunfang Fan, Zimeng Xie, Jiarong Li, Yueyang Chen and Shangzeng Wang in DIGITAL HEALTH

Supplemental Material

sj-pdf-4-dhj-10.1177_20552076261421072 - Supplemental material for A comparative study of medical information quality and dissemination efficacy of knee arthroplasty videos in Bilibili/TikTok short video platforms

Supplemental material, sj-pdf-4-dhj-10.1177_20552076261421072 for A comparative study of medical information quality and dissemination efficacy of knee arthroplasty videos in Bilibili/TikTok short video platforms by Bingqi Wei, Xinyue Zhang, Liu Chen, Xingyue Ren, Yijing Li, Feiyang Chen, Luwei Zhang, Yunfang Fan, Zimeng Xie, Jiarong Li, Yueyang Chen and Shangzeng Wang in DIGITAL HEALTH

Footnotes

Abbreviations

Acknowledgments

NA.

ORCID iDs

Bingqi Wei

Liu Chen

Xingyue Ren

Yijing Li

Yunfang Fan

Luwei Zhang

Shangzeng Wang

Yueyang Chen

Ethical considerations

Not applicable.

Author contributions

BQ.W. conceived and designed the study, defined the research questions, and established the methodological framework. XY.Z. wrote the original draft, structured the manuscript, and drafted the initial version. L.C. reviewed, edited, and revised the manuscript for clarity, coherence, and academic rigor. XY.R. and YJ.L. performed the statistical analysis, interpreted the data, and prepared the results. FY.C., LW.Z. and YF.F. collected the top 100 videos from each platform and extracted video and uploader characteristics. ZM.X., JR.L., and YY.C. were responsible for video screening, categorization, and quality scoring using the mDISCERN, GQS, VIQI, and PEMAT tools. SZ.W. critically revised the manuscript for intellectual content, provided funding, and supervised the research process. All authors contributed to manuscript writing, editing, and approved the final version for submission.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was supported by the National Natural Science Foundation of China (82374490), the Natural Science Foundation of He'nan Province of China (222300420486), He'nan Province University Science and Technology Innovation Team (24IRTSTHN040), the Scientific Research Project of Traditional Chinese Medicine in He'nan Province (2023ZYZD06ZD06), the Scientific Research Project of Traditional Chinese Medicine in He'nan Province (2023ZYZD06, 2021ZY2010, 2019ZY2035), Zhengzhou Science and Technology Benefit to the People's Planning Project (2023KJHM0009), He'nan Province Key Research and Development Special Projects (241111311700), and He'nan Province Young and Middle-aged Health Science and Technology Innovation Leading Talents (LJRC2024020), Henan Students’ innovation training program (202410471006, 202510471007, 202510471049).

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Data availability

The datasets generated during and/or analyzed during this study are available from the corresponding author upon reasonable request.

Supplemental material

Supplemental material for this article is available online.

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Supplementary Material

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