Evidence map›Paper›PMID 42221288›Full record

ArticlePlastic and reconstructive surgery. Global open2026

Health Communication Patterns in Breast Implant Illness Content on TikTok: A DISCERN-based Analysis by Creator Type.

Madhulika R Kastury, Fatima Z Khan, Amber L Edson, Abigail M Royfman, Noelle T Thompson, Kirollos Tadrousse, Haripriya S Ayyala, Richard Simman

Abstract read
In one paragraph

Article in Plastic and reconstructive surgery. Global open, 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

8 authors.

Madhulika R KasturyFrom the College of Medicine and Life Sciences, University of Toledo, Toledo, OH.
Fatima Z KhanFrom the College of Medicine and Life Sciences, University of Toledo, Toledo, OH.
Amber L EdsonFrom the College of Medicine and Life Sciences, University of Toledo, Toledo, OH.
Abigail M RoyfmanFrom the College of Medicine and Life Sciences, University of Toledo, Toledo, OH.
Noelle T ThompsonFrom the College of Medicine and Life Sciences, University of Toledo, Toledo, OH.
Kirollos TadrousseFrom the College of Medicine and Life Sciences, University of Toledo, Toledo, OH.
Haripriya S AyyalaDivision of Plastic Surgery, Department of Surgery, Yale School of Medicine, New Haven, CT.
Richard SimmanDepartment of Surgery, College of Medicine and Life Sciences, University of Toledo, Toledo, OH.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Breast implant illness (BII) describes a constellation of patient-reported symptoms attributed to implants. Despite lacking diagnostic consensus, BII remains prominent on TikTok, where health-related content often lacks expert oversight. This study evaluates the presentation, quality, and reliability of BII-related TikTok videos using the DISCERN framework, comparing healthcare professional (HCP) and non-HCP content. Methods: This observational study analyzed the top 30 videos from 5 BII-related hashtags. Videos were categorized by creator type and independently assessed by 4 raters using the DISCERN tool. Statistical methods included the Mann-Whitney U test, intraclass correlation coefficients, analysis of variance, and multivariable linear regression with log-transformed engagement metrics. Results: Of 150 videos screened, 36 met inclusion criteria. HCP videos (41.7%, n = 15) demonstrated significantly higher DISCERN reliability (20.9 versus 16.4, Conclusions: The reliability and quality of BII content on TikTok varied by creator type. HCP videos scored higher across DISCERN domains, especially when paired with higher follower counts. These findings signify the need for platform-specific strategies to promote evidence-based voices in digital health communication.

Identifiers

PMID42221288
PMCPMC13218758

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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.