Evidence map›Paper›PMID 35999872›Full record

ArticlePlastic and reconstructive surgery. Global open2022

#TheUglyTruth? A Qualitative Evaluation of Outcomes Photography on Instagram: Introducing the SEPIA Scoring System.

Danny J Soares, Haley N von Haven, Christina H Yi

Open access · goldAbstract read
In one paragraph

Article in Plastic and reconstructive surgery. Global open, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.2field-weighted citation impact, top 21% of its field
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

4 citing papers in PubMed, 6 citations in OpenAlex.

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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

3 authors at 1 institution in 1 country.

Danny J SoaresCollege of Medicine, University of Central Florida, Orlando, Fla.
Haley N von HavenAmerican Foundation for Aesthetic Medicine (AFFAM), Fellowship Research Department, Fruitland Park, Fla.
Christina H YiAmerican Foundation for Aesthetic Medicine (AFFAM), Fellowship Research Department, Fruitland Park, Fla.
University of Central Florida · US

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Photographs of cosmetic treatment outcomes on social media are prone to bias and misrepresentation from nonadherence to established photographic standards. However, there is currently insufficient information regarding which norms are most-commonly violated, precluding quality improvement efforts. Methods: A qualitative study of cosmetic treatment photographs published on Instagram was undertaken in accordance with the Guidelines for Reporting Reliability and Agreement Studies using a newly proposed Standards for the Evaluation of Photographs In Aesthetics (SEPIA) nine-point photograph scoring system and grading scale. Results: A total of 510 posts encompassing 2020 clinical photographs published by 102 practitioner accounts on Instagram were audited for photographic quality. The average score was 4 out of 9 (medium quality), with approximately 40% of posts scoring in the low-quality range. Zoom, lighting, timing, and presentation of multiple views were the standards most-commonly disregarded. Plastic and Reconstructive Surgery specialty and subspecialty (PRSS) practitioners scored higher (4.5/9 versus 3.1/9, Conclusions: Before and after photographs of surgical and nonsurgical cosmetic treatment outcomes on social media are frequently of substandard quality. This study outlines specific items frequently neglected in outcomes photography to assist practitioners in maximizing adherence to established standards of photography online.

Identifiers

PMID35999872
PMCPMC9390810
OpenAlexW4292363427

What OpenQuestion holds

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LicenceCC BY-NC-ND
Read underepoch 390

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.