Evidence map›Paper›PMID 39913422›Full record

ArticlePloS one2025

Quality of information in gestational diabetes mellitus videos on TikTok: Cross-sectional study.

Genyan Jiang, Lei Chen, Lan Geng, Yuhan Zhang, Zhiqi Chen, Yaqi Zhu, Shuangshuang Ma, Mei Zhao

Expression of concernAbstract read
In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. It carries an expression of concern. Cited by 8 papers.

0numbers the graph read from it
0cells of the map it votes in
8citing 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

8 citing papers in PubMed.

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4 · The record

Corrections and comments

5 · Who and what money

Authors and funding

8 authors.

Genyan JiangSchool of Nursing, Anhui Medical University, Hefei, China.ORCID 0009-0007-6139-0574
Lei ChenSchool of Nursing, Anhui Medical University, Hefei, China.
Lan GengSchool of Nursing, Anhui Medical University, Hefei, China.
Yuhan ZhangSchool of Nursing, Anhui Medical University, Hefei, China.
Zhiqi ChenSchool of Nursing, Anhui Medical University, Hefei, China.
Yaqi ZhuSchool of Nursing, Anhui Medical University, Hefei, China.
Shuangshuang MaSchool of Nursing, Anhui Medical University, Hefei, China.
Mei ZhaoSchool of Nursing, Anhui Medical University, Hefei, China.ORCID 0000-0003-3530-0233

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundTikTok is an important channel for consumers to obtain and adopt health information. However, misinformation on TikTok could potentially impact public health. Currently, the quality of content related to GDM on TikTok has not been thoroughly reviewed.

objectiveThis study aims to explore the information quality of GDM videos on TikTok.

methodsA comprehensive cross-sectional study was conducted on TikTok videos related to GDM. The quality of the videos was assessed using three standardized evaluation tools: DISCERN, the Journal of the American Medical Association (JAMA) benchmarks, and the Global Quality Scale (GQS). The comprehensiveness of the content was evaluated through six questions covering definitions, signs/symptoms, risk factors, evaluation, management, and outcomes. Additionally, a correlational analysis was conducted between video quality and the characteristics of the uploaders and the videos themselves.

resultsA total of 216 videos were included in the final analysis, with 162 uploaded by health professionals, 40 by general users, and the remaining videos contributed by individual science communicators, for-profit organizations, and news agencies. The average DISCERN, JAMA, and GQS scores for all videos were 48.87, 1.86, and 2.06, respectively. The videos uploaded by health professionals scored the highest in DISCERN, while the videos uploaded by individual science communicators scored significantly higher in JAMA and GQS than those from other sources. Correlation analysis between video quality and video features showed DISCERN scores, JAMA scores and GQS scores were positively correlated with video duration (P<0.001). Content scores were positively correlated with the number of comments (P<0.05), the number of shares (P<0.001), and video duration (P<0.001).

conclusionWe found that the quality of GDM video on TikTok is poor and lack of relevant information, highlighting the potential risks of using TikTok as a source of health information. Patients should pay attention to identifying health-related information on TikTok.

Indexed as

Diabetes, GestationalSocial MediaVideo RecordingCross-Sectional StudiesFemaleHumansPregnancy

Identifiers

PMID39913422
PMCPMC11801523

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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.