Evidence map›Paper›PMID 37817924›Full record

ArticlePlastic and reconstructive surgery. Global open2023

Quality Assessment of Online Resources for Gender-affirming Surgery.

Charlotte E Berry, Alexander Z Fazilat, Andrew A Churukian, Darren B Abbas, Michelle Griffin, Mauricio Downer, Micheal Januszyk, Arash Momeni, Shane D Morrison, Derrick C Wan

Abstract read
In one paragraph

Article in Plastic and reconstructive surgery. Global open, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Evaluating quality, understandability, and actionability of YouTube content for gender-affirming surgery.Canadian Urological Association journal = Journal de l'Association des urologues du Canada · 2025
    Article
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

10 authors.

Charlotte E BerryFrom Hagey Laboratory for Pediatric Regenerative Medicine, Division of Plastic and Reconstructive Surgery, Department of Surgery, Stanford University School of Medicine, Stanford, Calif.
Alexander Z FazilatFrom Hagey Laboratory for Pediatric Regenerative Medicine, Division of Plastic and Reconstructive Surgery, Department of Surgery, Stanford University School of Medicine, Stanford, Calif.
Andrew A ChurukianFrom Hagey Laboratory for Pediatric Regenerative Medicine, Division of Plastic and Reconstructive Surgery, Department of Surgery, Stanford University School of Medicine, Stanford, Calif.
Darren B AbbasFrom Hagey Laboratory for Pediatric Regenerative Medicine, Division of Plastic and Reconstructive Surgery, Department of Surgery, Stanford University School of Medicine, Stanford, Calif.
Michelle GriffinFrom Hagey Laboratory for Pediatric Regenerative Medicine, Division of Plastic and Reconstructive Surgery, Department of Surgery, Stanford University School of Medicine, Stanford, Calif.
Mauricio DownerFrom Hagey Laboratory for Pediatric Regenerative Medicine, Division of Plastic and Reconstructive Surgery, Department of Surgery, Stanford University School of Medicine, Stanford, Calif.
Micheal JanuszykFrom Hagey Laboratory for Pediatric Regenerative Medicine, Division of Plastic and Reconstructive Surgery, Department of Surgery, Stanford University School of Medicine, Stanford, Calif.
Arash MomeniFrom Hagey Laboratory for Pediatric Regenerative Medicine, Division of Plastic and Reconstructive Surgery, Department of Surgery, Stanford University School of Medicine, Stanford, Calif.
Shane D MorrisonHarborview Medical Center, Division of Plastic Surgery, University of Washington at Harborview, Seattle, Wash.
Derrick C WanFrom Hagey Laboratory for Pediatric Regenerative Medicine, Division of Plastic and Reconstructive Surgery, Department of Surgery, Stanford University School of Medicine, Stanford, Calif.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: As visibility of the transgender patient population and utilization of online resources increases, it is imperative that web-based gender-affirming surgery (GAS) materials for patients are readable, accessible, and of high quality. Methods: A search trends analysis was performed to determine frequency of GAS-related searches over time. The top 100 most common results for GAS-related terms were analyzed using six readability formulas. Accessibility of patient-facing GAS sources was determined by categorizing types of search results. Frequency of article types was compared in low- and high-population dense areas. Quality was assigned to GAS web-based sources using the DISCERN score. Results: Search engine trend data demonstrates increasing occurrence of searches related to GAS. Readability scores of the top 100 online sources for GAS were discovered to exceed recommended levels for patient proficiency. Availability of patient-facing online information related to GAS was found to be 60%, followed by information provided by insurance companies (17%). Differences in availability of online resources in varying dense cities were found to be minimal. The average quality of sources determined by the DISCERN score was found to be 3, indicating "potential important shortcomings." Conclusions: Despite increasing demand for web-based GAS information, the readability of online resources related to GAS was found to be significantly greater than the grade level of proficiency recommended for patients. A high number of nonpatient-facing search results appear in response to GAS search terms. Quality sources are still difficult for patients to find, as search results have a high incidence of low-quality resources.

Identifiers

PMID37817924
PMCPMC10561794

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.