Reliability,quality,and science popularization of diabetes knowledge information in China video sharing platform: A cross-sectional study

Abstract

Objective

More and more diabetes individuals are using internet video platforms for self-management of blood glucose in China. TikTok, WeChat, and Bilibili have gained popularity because of easy access to health information. However, the quality, reliability, and science popularization of health information on these platforms have still not been fully assessed, and studies comparing the three platforms are lacking. A cross-sectional study was established to evaluate the reliability, quality, and science popularization of diabetes health information on Chinese Internet video platforms.

Methods

This study used “diabetes” as a keyword to identify the top 100 videos meeting the specified criteria on each platform, resulting in 300 videos. The modified DISCERN score, the Journal of the American Medical Association Score (JAMA) benchmark criteria, and Global Quality Scores (GQS) were employed to assess the reliability of videos. This study developed criteria to evaluate the science popularization of the platforms. Each video was assessed based on the health information categories recommended by the Chinese Diabetes Guidelines (2024).

Results

Of the videos retrieved, 50.67% (152/300) were posted by certified medical professionals. Patient education was the most frequently discussed topic (120/300, 40.00%), including diet and lifestyle interventions. The median DISCERN score for the 300 videos was 3.00 (interquartile range (IQR): 2.00–4.00). The science dissemination score was 67.00 (IQR: 58.00–74.25), and the median GQS was 3. There was no significant difference in JAMA scores among the three platforms (p = 0.095). Bilibili received the highest science popularization score (median: 70.00, IQR: 63.45–77.00) and guideline score (median: 2.00, IQR: 1.00–4.00). Although healthcare professionals have a higher audience focus, video quality is inferior to non-healthcare professionals.

Conclusion

The results of this cross-sectional study suggest that videos of diabetes information from Internet platforms in China are not satisfactory. Compared with TikTok and WeChat, Bilibili has the highest quality of popular science videos. Health regulatory authorities should improve the enthusiasm of professional medical staff to participate in scientific communication, crack down on false information, and improve the quality of popular science works and public health literacy.

Keywords

Diabetes social media information quality science popularization

What is already known about this topic:

Internet platform information has now become increasingly used by people with diabetes for blood glucose self-management.

The quality, reliability, and science dissemination of health information on these platforms have still not been fully assessed in China.

What this study adds:

This study established a cross-sectional study to evaluate the reliability, quality, and science popularization of diabetes health information in Chinese Internet video platforms. A total of 300 videos were collected on the TikTok, Bilibili, and WeChat platforms in China using the keyword “diabetes.”

Criteria for assessing the science popularization of videos were developed in this study. Each video was evaluated according to the categories of health information recommended by the Chinese Diabetes Guideline (2024).

Diabetes information from Chinese Internet video platforms was unsatisfactory.

The science dissemination of medical professionals was significantly lower than non-medical professionals in China.

How this study might affect research, practice, or policy:

Health regulatory authorities should improve the enthusiasm of professional medical staff to participate in scientific communication, crack down on false information, and improve the quality of popular science works and public health literacy.

High-quality controlled trials should be designed in the future to compare the impact of viewing health videos on patient outcomes.

Introduction

Diabetes has become one of the fastest-growing global health emergencies in the twenty-first century.¹ It is estimated that there are more than 820 million people with diabetes worldwide, and about 3.4 million people die of diabetes each year. China has the largest number of diabetes patients in the world, accounting for approximately 22% of the global diabetes population.² In the past decade, the number of patients has increased by 56%, from 90 million to over 140 million. Notably, the prevalence of diabetes is on the rise among young people,³ with the age-standardized prevalence increasing from 7.53% to 13.67% between 2005 and 2023.

As a chronic metabolic disease with long-term effects, the pathophysiological process of diabetes presents a high degree of complexity. Effective and continuous self-management provides a feasible and essential strategy for disease control.^4,5 Health literacy, defined as the ability to obtain, comprehend, apply health-related knowledge, and exercise appropriate judgments, plays a significant role in the management of patients.⁶ However, Chinese diabetic patients exhibit a low level of health literacy. Estimates suggested that the rates of awareness and treatment were 36.7% and 32.9%,⁷ among diabetic patients in China, respectively. Low health literacy may contribute to poor adherence and glycemic control, leading to unfavorable clinical outcomes.^8–10

Diabetic patients with low health literacy tend to have a large demand for health knowledge.¹¹ Nowadays, Internet platforms have become an important source of health information.¹² Among 1.07 billion Internet users in China, more than 76% have the experience of searching for health information in various Internet information release platforms.¹³ Unlike regulated platforms such as “WeDoctor” and “Ping An Good Doctor,” the open nature of social media allows the public to upload health information freely. This has resulted in the rapid circulation and arbitrary dissemination of poor-quality health information on various publishing platforms. Studies have shown that more than 25% of the most viewed YouTube videos contain misleading information.¹⁴ Misinformation about COVID-19 has caused hundreds of deaths.¹⁵

Therefore, an increasing number of researchers are trying to evaluate the quality of online platform health information.¹⁶ Narrative video, compared with graphic information, is easier to understand by patients for better self-management. As the representative of short-form video platforms, TikTok in China has emerged as one of the most popular applications, with more than 800 million daily users by December 2022.¹⁷ Meanwhile, WeChat has been widely utilized for managing chronic diseases such as diabetes in China.¹⁸ A survey of 9000 users in the Health Science Video Insight Report (2019) showed that 92.1% of users had watched health science popularization videos, and WeChat viewing was the main platform. For young users, Bilibili is an important way to receive health knowledge, which is presented in the form of entertaining videos. Bilibili has 368 million active users per month, 82% of whom are adolescents.¹⁹ In summary, Internet-based video platforms have become increasingly popular and significant channels for disseminating health information among Chinese people.²⁰

Currently, the clarity of diabetes health information obtained by Chinese patients remains uncertain. There is a dearth of comprehensive quality evaluations regarding diabetes on all video platforms in China. Although previous studies²¹ have explored the quality of diabetes video information on TikTok, they have certain limitations. On the one hand, TikTok content alone is not comprehensive. Previous Studies have neglected the WeChat platform, which plays a significant role in chronic disease management, with Bilibili in the majority of younger age groups; on the other hand, the commonly used DISCERN approach focuses solely on information reliability and disease treatment. Furthermore, the lack of evaluation criteria regarding diabetes definitions, epidemiology, risk factors, and symptoms made it impossible to assess the accuracy and professionalism of the information. Therefore, this study used Global Quality Scores (GQS) and Journal of the American Medical Association Score (JAMA) scales to supplement the limitations of DISCERN and comprehensively evaluate the video quality. At the same time, the Chinese Guidelines for Prevention and Treatment of Diabetes (2024) were used to evaluate the diagnosis, treatment, and differentiation of the disease. By establishing evaluation criteria, the educational value of videos is scored.

High-quality videos should not only include scientific health information but also be easily understood or have entertainment value.²² Due to the accessibility of health information dissemination on video platforms, the user base extends beyond medical professionals, so the video should be easier to understand. However, the majority of research primarily focuses on video content analysis^23,24 while overlooking the assessment of video popularity. Therefore, this study proposes a novel method for evaluating science popularization. Based on assessing the value of video science, it contains popularity and artistic dimensions.

In summary, this cross-sectional study aimed to assess the reliability, quality, and science popularization of diabetes information across multiple video platforms in China. This study focuses on evaluating the guidance provided by current diabetes-related videos for patients while highlighting their potential value as popular science resources.

Methods

This study was reviewed and granted an exemption from formal approval by the Ethics Review Board of the First Affiliated Hospital of the Air Force Military Medical University, as it involved only the analysis of existing, publicly available, and anonymized data. The cross-sectional study design followed the STROBE Statement (Supplementary File 1). This study utilized publicly accessible data from Bilibili, WeChat, and TikTok. All data were collected from content that was publicly available at the time of retrieval. Data collection and processing strictly adhered to the terms of service for each platform. No personally identifiable information was extracted or disclosed, in accordance with user privacy protection measures.

Study eligibility criteria and searching strategy

TikTok, WeChat, and Bilibili platforms were searched on 10 June 2025 using the Chinese term for “diabetes.” The research activities were performed at the First Affiliated Hospital of the Air Force Military Medical University. Search results were saved locally for further analysis because the search results of the Internet platform change every day. In the case of a video playlist with multiple videos, only the first video in each case is included. We restricted this analysis to the top 100 videos, as several studies have demonstrated that more than 100 videos have no significant effect on the analysis.^25,26 Each video platform was registered and logged in with a new account, and cookies were cleared to eliminate interference. The default algorithmic sorting of each platform was used to identify the video most likely to be presented to a viewer, and all search results were saved locally for subsequent analysis.

Inclusion was limited to videos primarily focused on diabetes, while those covering traditional Chinese medicine treatments, duplicates, advertisements, or unrelated topics were excluded. Consensus was sought between authors if it was uncertain whether a video should be included, and it tended to be included for a comprehensive assessment. Basic information about the included videos was recorded in Excel (Microsoft Corp). The search was performed on a Windows system (Microsoft Windows 11, Lenovo PC) with a newly installed browser (Google Chrome).

Data extraction

Two reviewers independently viewed and analyzed the videos. The following characteristics were collected: video title, upload time, length, upload time, number of praise points, number of collections, number of forwards, and number of comments. Video publishers are divided into certified healthcare professionals, healthcare institutions, non-certified healthcare professionals/institutions, patients/families, popular science users/organizations, news media organizations and health education organizations, and individual users.

The video content is divided into the following categories: disease science popularization, clinical manifestations and diagnosis, pathogenesis, patient education, diabetes medication, treatment, complications, and patient reports.

Quality evaluation

The modified DISCERN, the JAMA benchmark criteria,²⁷ and GQS were employed to assess the reliability of videos. The DISCERN score²⁸ is used to evaluate the quality of information about treatment options in videos, including five aspects: clarity, reliability, bias, reference supplementation, and areas of uncertainty (Supplementary File 2, Table 1). Compared to the original version, the mDISCERN significantly enhances operability and efficiency in evaluating video materials while retaining the core elements of assessment. Each criterion met earns one point, with a maximum of five points indicating the highest level of reliability. The JAMA benchmark criteria²⁹ evaluated the quality of health information on the Internet based on four criteria: authorship, attribution, currency, and disclosure, with a range from 1.00 to 4.00 (Supplementary File 2, Table 2). The GQS scale^30,31 serves as a tool for assessing the overall quality of videos, with a range from 1 to 5. A maximum score of 5 indicates exceptional quality (Supplementary File 2, Table 3).

This study developed a set of criteria for assessing the scientific rigor, dissemination, and artistic quality of videos (Supplementary File 2, Table 4). A total of nine criteria were used, with different scales of scores to make a total of 100 points. Higher scores indicate better scientific dissemination.

Additionally, each video was also evaluated based on the categories of health information recommended by the Chinese diabetes guidelines,³² including epidemiology, pathogenesis, clinical presentation, diagnosis/testing, prevention, screening, self-management, medication, complications, and risk factors of diabetes. Each category is assigned a score of 1 point for a total score of 10 points. The characteristic and quality evaluation was also performed according to whether or not the publisher was a medical professional.

Statistical analysis

Analyses were performed using Python 3.8.8 (Python Software Foundation, DE, USA). Data are presented as median and interquartile range (IQR). Data collected by two researchers were tested with Kendall's W concordance test. Categorical data were presented as frequencies and rates (%) using the Kruskal–Wallis H test for three or more groups and the Mann–Whitney method for two groups. p < 0.05 was considered statistically significant.

Results

Characteristics of video

After applying the inclusion and exclusion criteria, a total of 300 videos from three platforms were included. The video screening process is shown in Figure 1. As shown in Table 1, Bilibili uploaded the longest video duration of 531 s, and TikTok obtained the highest praise, forwarding, comments, and collections (p < 0.05). The recommended dates of the videos from WeChat were relatively new, ranging from 13 April 2022, to the day of retrieval.

Figure 1.

Flowchart of diabetes-related video screening for analysis. A final cohort of 300 videos was selected.

Table 1.

Characteristics of 300 videos on the three internet platforms.

	Bilibili (n = 100)	TikTok (n = 100)	WeChat (n = 100)
Video duration (s)*, mean (range)	531 (47–2229)	149 (8–1344)	95 (6–504)
Likes, mean (range)*	5890 (1–130,000)	77,201 (969–614,000)	10,580 (1–1154)
Save, mean (range)*	2648 (2–57,000)	29,107 (125–335,000)	8871 (5–100,000)
share, mean (range)*	1289 (0–21,000)	49,478 (159–502,000)	1–1154 (25,135)
Comments, mean (range)*	449 (0–4530)	4052 (18–55,000)	1483 (0–100,000)
Content category (n)
Patient education	19	42	59
Lifestyle intervention	3	5	4
Diet	9	16	27
Others	7	21	28
Complications	5	12	11
Clinical presentation & diagnosis	17	10	12
Pathogenesis	8	11	1
Patient reporting	17	11	3
Disease basics	26	5	3
Medication knowledge	7	3	2
Treatment strategies	1	6	9
Publisher type (n)
Certified medical professionals	8	75	69
Uncertified medical health personnel/institution	12	0	9
Patient/Patient's family member	1	0	0
Medical institution/organization	1	3	1
Science popularization user/ organization	30	7	1
News media/organization	3	3	20
Individual user	45	12	0

*p < 0.05. Baseline characteristics of included videos, highlighting distinct differences in video format and publisher type across platforms.

Results of content analysis

Of the videos retrieved, 50.67% (152/300) were posted by certified medical professionals, followed by individual users (19.00%, 57/300). Five videos were released by healthcare institutions/organizations, accounting for 1.67% of the total videos. TikTok (25%, 75/300) and WeChat (23%, 69/300) had the highest number of videos posted by certified medical professionals. Bilibili was mostly posted by individual users (15%, 45/300).

Each platform included at least 7 types of videos (Figure 2). Among these 300 videos, patient education was the most frequently discussed topic (40.00%, 120/300), followed by clinical presentation and diagnosis. Bilibili had a more comprehensive distribution of content types. Of note, 13 videos mentioned diabetes reversal (4.33%).

Figure 2.

Distribution of publisher types (a) and content types (b) across platforms. Patient education was the predominant topic.

Results of video quality evaluation

Among the 300 videos analyzed, the median DISCERN score was 3.00 (IQR: 2.00–4.00), which is a fairly reliable quality. The overall score of science popularization was 67.00 (IQR: 58.00–74.25). The median JAMA score was 2.00 (IQR 2.00–3.00), with no significant difference (p = 0.095).

Figure 3 shows that the DISCERN scores for the three platforms are evenly distributed. A very high level of agreement was found for the DISCERN score, as evidenced by a Kendall's W of 0.909 (p < 0.001), reflecting strong consensus among the evaluators. The lowest scoring items were references and sources of video content. The overall assessment yielded unsatisfactory video quality ratings. Of the 300 videos, the clarity domain scored the highest, while only 59 videos mentioned other sources with the lowest scores, as shown in Table 2.

Figure 3.

DISCERN score and JAMA score comparison of videos. JAMA: Journal of the American Medical Association Score.

Table 2.

Results of video quality information evaluation.

	Bilibili (n = 100)	TikTok (n = 100)	WeChat (n = 100)	Total	P-value
DISCERN score, median (IQR)	3.00 (2.00–3.00)	3.00 (3.00–4.00)	3.00 (2.00–4.00)	3.00 (2.00–4.00)	<0.001
Clarity (n)	100	100	100	300
Reliable source of information (n)	69	84	64	217
Lack of bias (n)	61	56	36	153
Reference supplementation (n)	27	19	13	59
Mention of uncertainty (n)	11	54	73	138
JAMA score, median (IQR)	3.00 (2.00–3.00)	2.00 (2.00–3.00)	2.00 (2.00–3.00)	2.00 (2.00–3.00)	0.095
Authorship (n)	49	99	99	247
Attribution (n)	40	26	27	93
Currency (n)	100	100	100	300
Disclosure (n)	92	24	0	116
Science popularization, median (IQR)	70.00 (63.45–77.00)	65.50 (56.75–73.50)	63.00 (56.75–72.00)	67.00 (58.00–74.25)	<0.001
Scientific rigor	24.00 (20.75–26.00)	23.50 (20.00–25)	21.50 (17.00–25.00)	23.00 (19.00–25.00)
Popularity	23.00 (18.00–26.00)	21.00 (17.75–24.00)	20.00 (18.00–24.00)	21.00 (18.00–24.00)
Artistic quality	24.00 (22.00–27.00)	21.50 (20.00–25.00)	22.00 (20.00–25.00)	23.00 (20.00–16.00)
Guideline score, median (IQR)	2.00 (1.00–4.00)	1.00 (1.00–2.00)	1.00 (1.00–2.00)	1.00 (1.00–2.00)	<0.001

JAMA: Journal of the American Medical Association Score; IQR: interquartile range.

Bilibili achieved the highest JAMA score (3.00, 2.00–3.00) compared to TikTok (2.00, 2.00–3.00) and WeChat (2.00, 2.00–3.00). WeChat had the lowest JAMA score, with none of the videos reaching 4.00. All 300 videos indicated the date of upload. However, only 93 videos listed references and content sources. The inter-rater reliability for the JAMA score was statistically significant with a Kendall's W of 0.614 (p = 0.004), indicating moderate agreement among the raters.

The median GQS score for all three platforms is 3 (Figure 4). Bilibili has 15 top-quality videos, and WeChat has the least, with only 1. The distribution of ratings for TikTok is relatively more concentrated in the middle to high range, with a lower percentage of low scores (≤2) than the other two platforms.

Figure 4.

Comparison of GQS scores highlights distinct platform strengths. GQS: Global Quality Scores.

Assessment of science popularization

This study evaluated the science popularization of each video, rating its scientific rigor, popularity, and artistic quality. Bilibili (median 70.00, IQR: 63.45–77.00) was higher than TikTok (median 65.50, IQR: 56.75–73.50) and WeChat (median 63.00, IQR: 56.75–72.00).

All three platforms covered epidemiology, pathogenesis, clinical presentation, diagnosis/detection, prevention, screening, self-management, medication, complications, and diabetes risk factors (Supplementary Figure 1). The highest median diabetes guideline score was found in Bilibili (median 2.00, IQR: 1.00–4.00), above TikTok (median 1.00, IQR: 1.00–2.00) and WeChat (median 1.00, IQR: 1.00–2.00). Of all 300 videos, only 36 (12.00%) provided information about medication for diabetes, while 13 mentioned medication dosage, and 23 dealt with precautions for medication use. The assessment of the science popularization score demonstrated strong inter-rater reliability, with a Kendall's W value of 0.734 (p < 0.001). For the Guideline score, the Kendall's W coefficient was 0.683 (p < 0.001), signifying a moderate to strong degree of consistency between the raters.

Medical vs. non-medical professionals

The results showed significant differences between medical and non-medical professionals (Supplement Table 5). Non-medical professionals’ videos lasted longer. Video content posted by medical professionals was significantly better (p < 0.05) than non-medical professionals in terms of user interaction data, with better likes, favorites, retweets, and comments. Medical professionals had lower median JAMA scores (2.00, 2.00–3.00) than non-medical professionals (3.00, 2.00–3.00). Despite having better communication, medical professionals were less artistic, had lower scores for popularization of science, and contained lower guideline information (1.00 vs 2.00).

Discussion

This is the first cross-sectional study to comprehensively analyze diabetes-related videos on three representative Chinese video-sharing platforms. A total of 300 eligible videos were included from 13 April 2022 to 10 June 2025. The median DISCERN score for the 300 videos was 3.00 (IQR: 2.00–4.00), with the lowest quality being from other sources (59/300, 19.67%). The science score was 67.00 (IQR: 58.00–74.25), the median GQS score was grade 3, and the median JAMA score was 2.00 (IQR: 2.00–3.00). Overall, video quality was unsatisfactory. Despite having higher viewer interaction data, medical professionals had significantly lower JAMA scores (2.00 vs 3.00) and scientific popularization than non-medical professionals (65.00 vs 70.00).

The difference in JAMA scores among the three platforms was not statistically significant (p = 0.095), and the GQS scores were all 3, but there was a greater distribution of high scores in TikTok. Bilibili received the highest popularity of science scores (median: 70.00, IQR: 63.45–77.00), guideline scores (median: 2.00, IQR: 1.00–4.00), and JAMA scores of 3.00 (2.00–3.00). Based on the results combined with the distribution of ratings, the quality of the Bilibili platform was considered superior to that of TikTok and WeChat.

This study evaluated the diabetes guideline information and medication information contained in each video. The most frequently mentioned aspect was diabetes self-management, especially dietary management. According to the Chinese Guidelines for the Food and Nutrition of Adults with Diabetes (2024), a well-balanced diet plays a crucial role in preventing and controlling diabetes and achieving good control of blood glucose. However, in most videos, food recommendations did not indicate a source of evidence. Therefore, dietary recommendations made by publishers in videos should be viewed with caution.

In this study, 13 videos (4.33%) involved the content of diabetes reversal and aroused the attention of viewers. All videos on diabetes reversal suggested that dietary and lifestyle interventions could reverse diabetes. Many publishers have named themselves the title of “experts in diabetes reversal.” In actuality, the term “diabetes remission” is a more precise descriptor than “reversal.” In 2022, the American Diabetes Association and the European Diabetes Association jointly released an expert consensus on the definition and interpretation of remission in type 2 diabetes. Diabetes remission is defined as achieving hemoglobin A1c < 6.5% for at least 3 months after discontinuation of glucose-lowering medications. Studies have shown^33,34 that intensive lifestyle intervention, drug therapy, and metabolic surgery can relieve some type 2 diabetes.

In March 2025, the American College of Lifestyle Medicine released the first Diabetes Remission guidelines, which recognize lifestyle interventions as the foundation of T2D and prediabetes management, rather than medications.³⁵ The guideline suggests that the process of remission needs to take place with the intervention of a clinician or healthcare professional. And there is a lack of evidence to support long-term remission. Patients may develop a false sense of cure during remission, which can lead to the recurrence of hyperglycemia due to relaxed lifestyle choices.³⁶

Only 36 (12.00%) provided information on diabetes medications. The lack of drug-specific information probably results from several contributing factors. First, video creators, particularly those without medical credentials, often refrain from providing specific medication instructions. Such advice could be construed as an unlicensed medical recommendation, which carries regulatory and legal risks from platforms. Second, pharmacotherapy for diabetes is highly individualized. It is difficult to generalize in public videos due to many factors such as blood glucose level, complications, liver and kidney function of patients. Omitting such information, however, can prove counterproductive. Research³⁷ indicates that individuals with diabetes frequently manage a diverse array of medications, spanning from common biguanides and sulfonylureas to drugs addressing comorbidities affecting the digestive, cardiovascular, and hematological systems. This complexity underscores a substantial patient need for reliable information concerning drug interactions, adverse effects, and proper dosing. In the absence of authoritative sources, patients often resort to informal channels for answers, potentially compromising medication safety.

This study established criteria to evaluate the science popularization of videos for the first time. Unlike GQS and DISCERN scores that focus more on external features (structural versus overall credibility), science reviews focus more on the internal characteristics (content quality) of health information in videos. Scientificity is a necessary prerequisite for the evaluation of popular science works. Popularity and artistry are the conditions for the work to stimulate the interest of the audience and to acquire scientific knowledge. The results showed that the Bilibili Platform received the highest score (median: 70.00, IQR: 63.45–77.00). This may be related to the long video time on the Bilibili Platform, which can cover more information. However, results in Shusen Zheng³⁸ suggested that the video quality on Bilibili appeared to be comparatively lower than that on TikTok. This difference may be attributed to the fact that Shusen Zheng's study included a higher percentage of news reports (40/100), which may have an impact on the quality of videos.

Although TikTok (n = 75) and WeChat (n = 69) publishers account for the largest proportion of certified medical professionals, the video quality remains lower than Bilibili, which is consistent with Gaochen Bai et al.²⁰ In addition, the science popularization of medical professionals was significantly lower than non-medical professionals (65.00 vs 70.00). Our researchers discovered that the videos released by the experts were more prone to split themes, shorter in length, and single in form. Most of the videos uploaded by medical professionals are only in the form of language narration with subtitles and music, which is seriously homogenized. Some videos used encompassed extensive professional vocabulary, while lacking proper referencing.

In 2019, the Healthy China Action (2019–2030) was released, mandating tertiary hospitals to create a new media science popularization platform and a health science popularization team. Documents were released by many provincial healthcare committees to encourage physicians to conduct popular science and to incorporate their accomplishments in this area into their performance reviews.³⁹ As a result, stricter guidelines have been proposed for medical staff members’ efforts to popularize health sciences. The government should establish and cultivate high-quality popular science teams to improve the participation and activity of popular science for professional medical personnel.⁴⁰

The extensive development of social media platforms such as TikTok, WeChat, and Bilibili has made health information sharing more convenient and has become the most direct and extensive approach to health communication. However, the commercialized environment for social media reduces the credibility of health science messages. Some misleading information is also very easy to be reprinted by friends to expand the spread of information.⁴¹ Certification standards on social media are easier than “WeDoctor” and “Ping An Good Doctor,” which also contribute to the widespread practice of impersonating medical professionals. Careful identification of the audience is required.

At present, digital technology is more and more widely used and has more and has a significant impact on the healthcare industry. However, the results of this study showed that the construction of health information standards is not fully established at present. Therefore, it is necessary to establish a high-quality team of science dissemination talents. At the same time, the Internet science popularization system should be actively constructed. Establish popular science review standards concurrently to guarantee the caliber of popular science and advance the 14th Five-Year Plan's goal of digitizing health information.

Strengths and limitations

This study has several advantages: first, our study is the first comprehensive research of diabetes-related videos across three representative Chinese Internet platforms (Bilibili, TikTok, and WeChat). Multi-platform assessments reduce the limitations of using a single platform. Second, our research team has developed criteria to assess both the scientific rigor and popularity of health videos for the first time. These findings provide valuable evidence to support the production of diabetes health videos, which promote health education dissemination.

There are several limitations to this study. First, the reproducibility of this study remains limited by the opacity of algorithms for social media platforms, despite standardization of data collection protocols. Second, the study was limited by the sample size of 100 videos per platform, which may not fully represent the vast and dynamic content available on each platform. Third, the assessment of science popularization developed in this study is an initial exploratory tool. As such, it must be validated to establish its reliability and validity, which is essential for creating a standardized assessment system. Fourth, although we conducted a detailed analysis of video quality, the content of the comments was not analyzed. Finally, this study did not explore viewers’ behavior after watching the video. Future studies should analyze larger video datasets and incorporate surveys of audience attitudes. In addition, it is crucial to validate scales of science popularization more rigorously by assessing internal consistency, inter-rater reliability, and construct validity. Ultimately, exploring the actual impact of diabetes health information on audience behavior remains an important direction for future research.

Conclusion

The results of this cross-sectional study showed that diabetes information from Chinese Internet video platforms was unsatisfactory, with a median DISCERN score of 3.00 (2.00–4.00). Bilibili received the highest scientific popularization score (median: 70.00, IQR: 63.45–77.00) and guideline score (median: 2.00, IQR: 1.00–4.00). Medical professionals had significantly lower scientific literacy than non-medical professionals. Health regulators should increase the motivation of medical professionals to participate in science communication, combat disinformation, and improve the quality of scientific works and public health literacy. In the future, high-quality controlled trials should be designed to compare the effects of viewing health videos on future patient outcomes.

Supplemental Material

sj-docx-1-dhj-10.1177_20552076251393298 - Supplemental material for Reliability, quality, and science popularization of diabetes knowledge information in China video sharing platform: A cross-sectional study

Supplemental material, sj-docx-1-dhj-10.1177_20552076251393298 for Reliability, quality, and science popularization of diabetes knowledge information in China video sharing platform: A cross-sectional study by Ke-Xin Sun, Chen Cui, Fei Mu, Meng Tang, Rui Gong, Zhen Yan, Jin-Yi Zhao and Jing-Wen Wang in DIGITAL HEALTH

Supplemental Material

sj-docx-2-dhj-10.1177_20552076251393298 - Supplemental material for Reliability, quality, and science popularization of diabetes knowledge information in China video sharing platform: A cross-sectional study

Supplemental material, sj-docx-2-dhj-10.1177_20552076251393298 for Reliability, quality, and science popularization of diabetes knowledge information in China video sharing platform: A cross-sectional study by Ke-Xin Sun, Chen Cui, Fei Mu, Meng Tang, Rui Gong, Zhen Yan, Jin-Yi Zhao and Jing-Wen Wang in DIGITAL HEALTH

Footnotes

Acknowledgment

The authors would like to express their gratitude to the participants in the study.

ORCID iD

Jin-Yi Zhao

Ethical considerations

Consent for publication

Not applicable.

Author contributions

JYZ and KXS conceived and designed the study; CC, TM, and KXS collected the data and analyzed it; ZY and FM rigorously revised the manuscript; JWW and RG supervised the study. JYZ and JWW made identical contributions to this manuscript as co-corresponding authors.

Funding

The authors disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This study was supported by the National Nature Science Foundation of China (82203190, 72074218, 82400418), the Innovative Talent Promotion Project of Shaanxi Province (2023-CX-TD-76), and the Shaanxi Provincial Health Research Innovation Capacity Enhancement Program (2023 PT-10).

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

Data were derived from public domain resources. The data that support the findings of this study are available from the corresponding author upon reasonable request.

Guarantor

KXS and JYZ

Supplemental material

Supplemental material for this article is available online.

References

Worldwide trends in diabetes prevalence and treatment from 1990 to 2022: a pooled analysis of 1108 population-representative studies with 141 million participants. Lancet (London, England) 2024; 404: 2077–2093.

, et al. Diabetes in China part 1: epidemiology and risk factors. Lancet Public Health 2024; 9: e1089–e1097.

Zhou

Liu

Zhao

, et al. The national and provincial prevalence and non-fatal burdens of diabetes in China from 2005 to 2023 with projections of prevalence to 2050. Mil Med Res 2025; 12: 28.

Aleppo

Gal

Raghinaru

, et al. Comprehensive telehealth model to support diabetes self-management. JAMA Network Open 2023; 6: e2336876.

Ginoux

Ruskeepää

Perc

, et al.

Is type 1 diabetes a chaotic phenomenon?

Chaos, Solitons Fractals 2018; 111: 198–205.

Chakkalakal

Venkatraman

White

, et al. Validating health literacy and numeracy measures in minority groups. Health Lit Res Pract 2017; 1: e23–e30.

Wang

Peng

Zhao

, et al. Prevalence and treatment of diabetes in China, 2013-2018. Jama 2021; 326: 2498–2506.

Gomes

Muniz

Melo

LGN

, et al. Health literacy and glycemic control in patients with diabetes: a tertiary care center study in Brazil. Diabetol Metab Syndr 2020; 12: 11.

Rahman

Nakamura

Hasan

SMM

, et al. Mediators of the association between low socioeconomic status and poor glycemic control among type 2 diabetics in Bangladesh. Sci Rep 2020; 10: 6690.

10.

Yoon

Kwan

, et al. Healthcare professionals’ views of factors influencing diabetes self-management and the utility of a mHealth application and its features to support self-care. Front Endocrinol (Lausanne) 2022; 13: 793473.

11.

Weymann

Härter

Dirmaier

. Information and decision support needs in patients with type 2 diabetes. Health Informatics J 2016; 22: 46–59.

12.

Barak

Boniel-Nissim

Suler

JJCHB

. Fostering empowerment in online support groups. Comput Hum Behav 2008; 24: 1867–1883.

13.

Center CINI. The 51st Statistical Report on China's Internet Development.

14.

Sun

Zheng

. Quality of information in gallstone disease videos on TikTok: cross-sectional study. J Med Internet Res 2023; 25: e39162.

15.

A. C. ‘Hundreds dead’ because of Covid-19 misinformation. BBC News. 2020. Aug 12, [2021-01-31]. https://www.bbc.co.uk/news/world-53755067.

16.

Moon

Lee

. Evaluation of Korean-language COVID-19-related medical information on YouTube: cross-sectional infodemiology study. J Med Internet Res 2020; 22: e20775.

17.

Lin

Zhou

, et al. Effect of teach-back and Douyin platform short video health education in women receiving infertility treatment. Digit Health 2023; 9: 20552076231203560.

18.

Chen

Zhou

, et al. The value of WeChat application in chronic diseases management in China. Comput Methods Programs Biomed 2020; 196: 105710.

19.

Bilibili. Investor home. Available from: https://ir.bilibili.com/ (accessed 4 May 2022)

20.

Bai

, et al. Quality of internet videos related to pediatric urology in mainland China: a cross-sectional study. Front Public Health 2022; 10: 924748.

21.

Kong

Song

Zhao

, et al. Tiktok as a health information source: assessment of the quality of information in diabetes-related videos. J Med Internet Res 2021; 23: e30409.

22.

Lara

García-Avilés

Revuelta

. Online video on climate change: a comparison between television and web formats. 2017.

23.

Sylvia Chou

Gaysynsky

Cappella

. Where we go from here: health misinformation on social Media. Am J Public Health 2020; 110: S273–s275.

24.

Walsh-Buhi

. Social media and cancer misinformation: additional platforms to explore. Am J Public Health 2020; 110: S292–s293.

25.

Zheng

Tong

Wan

, 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 2023; 25: e47210.

26.

Ferhatoglu

Kartal

Ekici

, et al. Evaluation of the reliability, utility, and quality of the information in sleeve gastrectomy videos shared on open access video sharing platform YouTube. Obes Surg 2019; 29: 1477–1484.

27.

Singh

. YouTube for information on rheumatoid arthritis–a wakeup call? J Rheumatol 2012; 39: 899–903.

28.

Rees

Ford

Sheard

. Evaluating the reliability of DISCERN: a tool for assessing the quality of written patient information on treatment choices. Patient Educ Couns 2002; 47: 273–275.

29.

Silberg

Lundberg

Musacchio

. Assessing, controlling, and assuring the quality of medical information on the internet: caveant lector et viewor–let the reader and viewer beware. Jama 1997; 277: 1244–1245.

30.

Oremule

Patel

Orekoya

, et al. Quality and reliability of YouTube videos as a source of patient information on rhinoplasty. JAMA Otolaryngol Head Neck Surg 2019; 145: 282–283.

31.

Bernard

Langille

Hughes

, et al. A systematic review of patient inflammatory bowel disease information resources on the world wide web. Am J Gastroenterol 2007; 102: 2070–2077.

32.

Chinese Diabetes society, guideline for the prevention and treatment of type 2 diabetes mellitus in China (2020 edition). Chin J Endocrinol Metab 2021; 37: 311–398.

33.

Lean

MEJ

Leslie

Barnes

, et al. Durability of a primary care-led weight-management intervention for remission of type 2 diabetes: 2-year results of the DiRECT open-label, cluster-randomised trial. Lancet Diabetes Endocrinol 2019; 7: 344–355.

34.

Schauer

Bhatt

Kirwan

, et al. Bariatric surgery versus intensive medical therapy for diabetes - 5-year outcomes. N Engl J Med 2017; 376: 641–651.

35.

Rosenfeld

Grega

Gulati

. Lifestyle interventions for treatment and remission of type 2 diabetes and prediabetes in adults: implications for clinicians. Am J Lifestyle Med 2025: 15598276251325802. doi:10.1177/15598276251325802

36.

Sarathi

. Letter to the editor from Sarathi: “Consensus report: definition and interpretation of remission in type 2 diabetes”. J Clin Endocrinol Metab 2022; 107: e2644–e2645.

37.

Markovič

Grubelnik

Završnik

, et al. Profiling of patients with type 2 diabetes based on medication adherence data. Front Public Health 2023; 11: 1209809.

38.

Zheng

Tong

Wan

, 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 2023; 25: e47210. Accessed 2023/07. http://europepmc.org/abstract/MED/37405825, https://www.jmir.org/2023/1/e47210/PDF, https://europepmc.org/articles/PMC10357314

39.

Liu

Wang

Jiang

. The impact of popular science articles by physicians on their performance on online medical platforms. Healthcare 2022; 10: 2432.

40.

Wang

Zhao

, et al. Knowledge, attitude, and practice of medication among Haikou residents. Ann Palliat Med 2021; 10: 6883–6891.

41.

Lundin

Jonsson

Wahlgren

, et al. Young adults’ perceptions of living with atopic dermatitis in relation to the concept of self-management: a qualitative study. BMJ open 2021; 11: e044777.

Supplementary Material

Please find the following supplemental material available below.

For Open Access articles published under a Creative Commons License, all supplemental material carries the same license as the article it is associated with.

For non-Open Access articles published, all supplemental material carries a non-exclusive license, and permission requests for re-use of supplemental material or any part of supplemental material shall be sent directly to the copyright owner as specified in the copyright notice associated with the article.

0.00 MB

0.03 MB

0.09 MB