Evidence map›Paper›PMID 40342510›Full record

ArticleFrontiers in public health2025

Hip fractures in Chinese TikTok (Douyin) short videos: an analysis of information quality, content and user comment attitudes.

Zhuoxin Li, Yashi Lin, Kairou Zhang, Ran Li, Mei Ju, Yanhua Chen, Jing Fu, Ruiyu Huang, Ling Zhu, Junjun Sun and 5 more

Abstract read
In one paragraph

Article in Frontiers in public health, 2025. 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.

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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

15 authors.

Zhuoxin LiDepartment of Nursing, The Affiliated Hospital, Southwest Medical University, Luzhou, China.
Yashi LinDepartment of Nursing, The Affiliated Hospital, Southwest Medical University, Luzhou, China.
Kairou ZhangDepartment of Nursing, The Affiliated Hospital, Southwest Medical University, Luzhou, China.
Ran LiDepartment of Nursing, The Affiliated Hospital, Southwest Medical University, Luzhou, China.
Mei JuDepartment of Nursing, The Affiliated Hospital, Southwest Medical University, Luzhou, China.
Yanhua ChenSchool of Nursing, Southwest Medical University, Luzhou, China.
Jing FuSchool of Nursing, Southwest Medical University, Luzhou, China.
Ruiyu HuangSchool of Continuing Education, Guiyang Healthcare Vocational University, Guiyang, China.
Ling ZhuDepartment of Chinese Medicine, Sichuan Provincial People's Hospital, University of Electronic Science and Technology of China, Chengdu, China.
Junjun SunSchool of Nursing, Xinxiang Medical University, Xinxiang, China.
Yanxia GuoFaculty of Nursing and Midwifery, Jiangsu College of Nursing, Huaian, China.
Min GaoSchool of Nursing, Xinxiang Medical University, Xinxiang, China.
Yue HuSchool of Nursing, Southwest Medical University, Luzhou, China.
Gang LiuDepartment of Orthopedics and Center for Orthopedic Diseases Research, Affiliated Traditional Chinese Medicine Hospital of Southwest Medical University, Luzhou, China.
Baolu ZhangSchool of Nursing, Southwest Medical University, Luzhou, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Hip fracture presents a major healthcare challenge globally. While numerous Douyin videos address hip fracture, their information quality and factors affecting user comment attitudes remain uncertain. Objective: This study aims to analyze the content, information quality, and user comment attitudes of videos depicting hip fractures on Chinese TikTok (Douyin). Methods: The search term "hip fracture" was used on Douyin, which resulted in 170 samples being included. Video information quality was assessed using the GQS and PEMAT scales. Video content was analyzed using DivoMiner. User comments were extracted using Gooseeker, and user comment attitudes were interpreted as positive, neutral, or negative using the Weiciyun website. Data analysis was performed using IBM SPSS version 29.0, including non-parametric tests for continuous variables and chi-square tests for categorical variables. The identified factors were then included in a multivariate logistic regression analysis to examine their impact on user comment attitudes. Results: Health professionals were the primary source of videos (136/138, 98.6%). The overall information quality of the videos was moderate (median 3, IQR 2.00-4.00). Douyin videos were relatively high in understandability (median 72.70%, IQR 63.60-81.80%) but low in actionability (median 33.33%, IQR 0-66.67%). Most videos focused on treatment (139/170, 81.8%). Regarding user comment attitudes, the majority of videos were received with positive comments (113/170, 66.5%), followed by negative comments (39/170, 22.9%) and neutral comments (18/170, 10.6%). The multivariate logistic regression analysis revealed three factors influencing positive attitudes: the GQS score (OR 13.824, 95% CI 6.033-31.676), understandability (OR 2.281, 95% CI 1.542-5.163) and not mentioning risk factors in videos (OR 0.291, 95%CI 0.091-0.931). Conclusion: The majority of hip fracture videos on Douyin were created by health professionals and had intermediate information quality, with user comment attitudes remaining positive. However, these videos often lacked actionability and had insufficient mention of prevention and rehabilitation content. Videos with higher information quality that addressed hip fracture risk factors received more positive user comments. This study suggests that publishers of hip fracture-related videos should improve actionability while simultaneously paying attention to both prevention and rehabilitation content to enhance the educational value of these videos.

Indexed as

Hip FracturesSocial MediaVideo RecordingAdultChinaEast Asian PeopleFemaleHumansMaleMiddle AgedDouyinhip fracturesinformation qualityshort videouser comment attitudes

Identifiers

PMID40342510
PMCPMC12058786

What OpenQuestion holds

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LicenceCC BY
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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.