Evidence map›Paper›PMID 41083987›Full record

ArticleBMC oral health2025

Beyond virality: evaluating evidence-based content delivery in social media-based pediatric orthodontic education.

Jinmei Wu, Zhili Dong, Peiqi Lin, Yiran Luo, Liping Wu, Xin'an Li

Abstract read
In one paragraph

Article in BMC oral health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 13 papers.

0numbers the graph read from it
0cells of the map it votes in
13citing 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

13 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

6 authors.

Jinmei Wu *Department of Stomatology, Longyan First Affiliated Hospital of Fujian Medical University, No.105 Jiuyibei Road, Longyan, 364000, China.
Zhili Dong *Hospital of Stomatology, Guangdong Provincial Clinical Research Center of Oral Diseases, Guanghua School of Stomatology, Sun Yat-sen University, No.56 Lingyuanxi Road, Guangzhou, 510055, China.
Peiqi LinDepartment of Stomatology, Longyan First Affiliated Hospital of Fujian Medical University, No.105 Jiuyibei Road, Longyan, 364000, China.
Yiran LuoDepartment of Stomatology, Longyan First Affiliated Hospital of Fujian Medical University, No.105 Jiuyibei Road, Longyan, 364000, China.
Liping WuHospital of Stomatology, Guangdong Provincial Clinical Research Center of Oral Diseases, Guanghua School of Stomatology, Sun Yat-sen University, No.56 Lingyuanxi Road, Guangzhou, 510055, China. wulping@mail.sysu.edu.cn.
Xin'an LiDepartment of Stomatology, Longyan First Affiliated Hospital of Fujian Medical University, No.105 Jiuyibei Road, Longyan, 364000, China. m18250166536@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundMalocclusion, affecting over 260 million Chinese children, demands early orthodontic intervention to address both physiological and psychosocial impacts. While social media platforms have become primary sources of health guidance for parents, their algorithm-driven ecosystems often prioritize engagement over scientific rigor. Content creators, including unqualified influencers, frequently disseminate unverified claims about treatment timing, methods, and outcomes. Such misinformation may exacerbate parental anxiety, or promote non-evidence-based interventions. This study evaluates the quality of high-engagement videos across platforms, identifies systemic gaps enabling misinformation proliferation, and proposes safeguards to align content dissemination with evidence-based practices.

methodsA cross-sectional analysis was conducted on 200 top-viewed videos (100 per platform) retrieved via keyword searches on TikTok and Rednote. Videos were assessed using three validated tools: Global Quality Score (GQS), JAMA benchmark criteria, and a Modified DISCERN score. Statistical analyses included Mann-Whitney U tests, Spearman correlations, and inter-rater reliability assessments.

resultsTikTok videos exhibited significantly higher engagement (likes, shares) and superior quality scores (GQS: 2.89 vs. 2.32; mDISCERN: 1.75 vs. 1.20) compared to Rednote (all P < 0.01). Orthodontist-produced content scored higher in JAMA and mDISCERN across both platforms (P < 0.01). On Rednote, quality metrics (GQS, mDISCERN) correlated positively with user engagement and video duration (R: 0.27–0.49, P < 0.01), whereas TikTok showed inverse trends between quality and engagement (R: -0.23 to -0.35, P < 0.05). Inter-rater reliability was excellent (ICC: 0.780–1.000).

conclusionsDespite higher engagement metrics, TikTok demonstrated superior video quality compared to Rednote, yet both platforms exhibited concerning inconsistencies in orthodontic information accuracy, a reflection of systemic algorithm-driven health misinformation risks. Content from credentialed professionals consistently outperformed non-expert sources in reliability, underscoring the public health dangers of prioritizing influencer-generated material lacking scientific validation. Strategic integration of medical expertise into content algorithms, standardization of quality verification frameworks, and enhanced public health literacy are imperative to counteract misinformation propagation and align social media’s educational potential with evidence-based orthodontic care.

Indexed as

OrthodonticsSocial MediaChildCross-Sectional StudiesDigital MediaHumansVideo RecordingEarly orthodontic treatmentMalocclusionQuality analysisRednoteShort videosSocial mediaTikTok

Identifiers

PMID41083987
PMCPMC12519754

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC-ND
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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.