Evidence map›Paper›PMID 42918787›Full record

ArticleNPJ primary care respiratory medicine2026

Evaluating influenza-related short videos on Chinese platforms: information quality, user engagement, and public health implications.

Xinlei Zhang, Chunyuan Zhou, Yuyang Hu, Junchao Yang

Abstract read
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In one paragraph

Article in NPJ primary care respiratory medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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

0 citing papers in PubMed.

No citing paper in PubMed yet.

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

4 authors.

Xinlei ZhangDepartment of Pulmonary and Critical Care Medicine, The Third Affiliated Hospital of Zhejiang Chinese Medical University, 219 Moganshan Road, Xihu District, Hangzhou, Zhejiang, 310005, China.
Chunyuan ZhouDepartment of Pulmonary and Critical Care Medicine, The Third Affiliated Hospital of Zhejiang Chinese Medical University, 219 Moganshan Road, Xihu District, Hangzhou, Zhejiang, 310005, China.
Yuyang HuDepartment of Pulmonary and Critical Care Medicine, The Third Affiliated Hospital of Zhejiang Chinese Medical University, 219 Moganshan Road, Xihu District, Hangzhou, Zhejiang, 310005, China.
Junchao YangDepartment of Pulmonary and Critical Care Medicine, The Third Affiliated Hospital of Zhejiang Chinese Medical University, 219 Moganshan Road, Xihu District, Hangzhou, Zhejiang, 310005, China. yangjunchaozj@zcmu.edu.cn.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Influenza-related short videos have become an important source of health information on Chinese social media. In an ongoing "information disorder" environment, where digital misinformation is known to cause health harms, their information quality and influenza-specific public health implications on major short-video platforms remain insufficiently characterized. On October 7, 2025, new accounts were registered to search for short videos on TikTok and Bilibili using the keywords "" (influenza) and "" (influenza) respectively. Basic information was extracted from each video, and quality was assessed using JAMA, GQS, modified DISCERN, and PEMAT, which do not verify factual accuracy. Statistical analysis was performed using SPSS software. A total of 229 influenza-related short videos were included, primarily uploaded by doctors (n = 73, 31.9%) and non-professional individuals (n = 88, 38.4%). Disease knowledge constituted the main video content (n = 176, 76.9%), with treatment being the primary video theme(n = 85, 37.12%), and monologue the predominant video format (n = 84, 36.68%). Compared to Bilibili, TikTok videos featured shorter lengths, more recent upload dates, higher counts of likes, comments, and shares, and were posted by creators with larger fans counts (all P < 0.001). Bilibili scored significantly higher than TikTok on both JAMA (2.5 (2, 3)) and GQS (4 (4, 4)) scales (both P < 0.001); while TikTok scored higher on PEMAT comprehensibility (100 (82, 100)) and executability (67 (0, 67)) (both P < 0.001). Videos from physicians, news agencies, and non-profit organizations, and those focusing on treatment or diagnosis, generally showed higher quality. The four quality scales were positively correlated(all P < 0.05), while correlations between quality scores and engagement metrics were weak. In the context of ongoing information disorder, influenza-related short videos have become a major channel for public health information access, yet the overall quality of this content remains suboptimal, with deficiencies in key clinical and preventive points. Improving short-form science communication will require higher-quality content, stronger platform governance, and enhanced public media literacy.

Indexed as

Influenza, HumanPublic HealthSocial MediaVideo RecordingChinaDigital MediaHumans

Identifiers

PMID42918787

What OpenQuestion holds

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Registered trials

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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.