Evidence map›Paper›PMID 41181547›Full record

ArticleDigital health

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

Ke-Xin Sun, Chen Cui, Fei Mu, Meng Tang, Rui Gong, Zhen Yan, Jin-Yi Zhao, Jing-Wen Wang

Abstract read
In one paragraph

Article in Digital health. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

10 citing papers in PubMed.

  1. Article
  2. Article
  3. Article
  4. Article
  5. Article
  6. Article
  7. Article
  8. Article
  9. Article
  10. Article
4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Ke-Xin SunDepartment of Pharmacy, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Chen CuiDepartment of Pharmacy, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Fei MuDepartment of Pharmacy, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Meng TangDepartment of Pharmacy, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Rui GongDepartment of Pharmacy, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Zhen YanDepartment of Pharmacy, Xijing Hospital, Fourth Military Medical University, Xi'an, China.
Jin-Yi ZhaoDepartment of Pharmacy, Xijing Hospital, Fourth Military Medical University, Xi'an, China.ORCID https://orcid.org/0000-0002-1561-2638
Jing-Wen WangDepartment of Pharmacy, Xijing Hospital, Fourth Military Medical University, Xi'an, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

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 ( 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.

Indexed as

Diabetesinformation qualityscience popularizationsocial media

Identifiers

PMID41181547
PMCPMC12576113

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.