Evidence map›Paper›PMID 40815350›Full record

ArticleArchives of osteoporosis2025

Quality of information in osteoporosis videos on TikTok: a cross-sectional study.

Huipin Zhang, Chaomei Zhang, Jing Mo, Wenyan Wang, Zhishui Wu

Abstract read
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In one paragraph

Article in Archives of osteoporosis, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 12 papers.

0numbers the graph read from it
0cells of the map it votes in
12citing 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

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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

12 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

5 authors.

Huipin ZhangDepartment of Neurology, The Third Affiliated Hospital of Soochow University, Changzhou, 213000, Jiangsu, China.
Chaomei ZhangDepartment of Spine Surgery, The Third Affiliated Hospital of Soochow University, Changzhou, 213000, Jiangsu, China.
Jing MoDepartment of Spine Surgery, Northern Jiangsu People's Hospital, Yangzhou, 225000, Jiangsu, China.
Wenyan WangDepartment of Minimally Invasive Spine Surgery, The First Affiliated Hospital of Shandong Second Medical University, Weifang, 261000, Shandong, China.
Zhishui WuDepartment of Spine Surgery, The Third Affiliated Hospital of Soochow University, Changzhou, 213000, Jiangsu, China. zhishuiwu@czfph.com.ORCID 0000-0003-1312-9770

Funding

the Changzhou Health Commission, specifically the Changzhou Health Commission Youth Science and Technology Project No. QN202216the Changzhou Health Youth Talent Cultivation Project No. CZQM2020057
6 · The paper itself

Abstract

This study evaluated the quality of osteoporosis videos on TikTok, finding that while most are by doctors, the information quality is low. Longer videos tend to have better quality but receive less engagement, highlighting concerns about the suitability of TikTok for medical education.

backgroundTikTok has become a significant channel for the general public to access and adopt health information. However, the quality of health content about osteoporosis on TikTok remains underexplored.

objectiveThis study aimed to investigate the information quality of osteoporosis videos on TikTok.

methodsWe analyzed the first 200 videos related to osteoporosis on TikTok, focusing on 128 videos that met our criteria. The quality of these videos was evaluated using quantitative scoring tools such as the DISCERN instrument and Content Integrity Assessment. Additionally, the correlation between video quality and characteristics, including duration, likes, comments, and shares, was investigated.

resultsOf the videos analyzed, 93.0% were posted by doctors. Content integrity scores were as follows: definition 0.61 ± 0.77, symptoms 0.34 ± 0.71, evaluation 0.39 ± 0.71, risk factors 0.55 ± 0.65, management 0.82 ± 0.56, and outcomes 1.17 ± 0.75. The average DISCERN score was 36.51 ± 6.87, the majority of videos were rated as poor (71.1%) or fair (22.7%) in quality. DISCERN scores of videos published by doctors were lower than those created by non-professionals (Z = -2.062, P = 0.039). DISCERN scores were significantly correlated with video duration (r = 0.581, P < 0.001). Engagement metrics such as likes, comments, favorites, and shares were highly interrelated (r = 0.855 to 0.901, P < 0.001), but did not correlate with video quality (P > 0.05).

conclusionAlthough the videos about osteoporosis on TikTok are mainly provided by doctors, their quality is low. We found a positive correlation between video duration and video quality. High-quality videos received low attention, while popular videos were of low quality. The medical information on TikTok is currently not rigorous enough to guide patients to make accurate judgments. Due to the low quality and reliability of the information, TikTok is not an appropriate source of knowledge to educate patients.

Indexed as

OsteoporosisVideo RecordingCross-Sectional StudiesHumansBone healthHealth informationOsteoporosisPatient educationTikTokVideo quality

Identifiers

PMID40815350

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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.