Evidence map›Paper›PMID 42835891›Full record

ArticleArchives of plastic surgery2026

The Use of Artificial Intelligence to Improve Readability and Quality of Informed Consent Forms in Plastic and Reconstructive Surgery.

Grace S Ryu, Grace Hwang, Charles C Lee, Timothy S Johnson

Abstract read
In one paragraph

Article in Archives of plastic surgery, 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

4 authors.

Grace S RyuCollege of Medicine, Penn State Milton S. Hershey Medical CenterHershey PennsylvaniaUnited States.ORCID 0009-0002-4912-1519
Grace HwangCollege of Medicine, Penn State Milton S. Hershey Medical CenterHershey PennsylvaniaUnited States.ORCID 0009-0008-3610-5214
Charles C LeeDivision of Plastic Surgery Department of SurgeryPenn State Milton S. Hershey Medical CenterHershey PennsylvaniaUnited States.ORCID 0000-0001-9884-5893
Timothy S JohnsonDivision of Plastic Surgery Department of SurgeryPenn State Milton S. Hershey Medical CenterHershey PennsylvaniaUnited States.ORCID 0000-0002-2030-0460

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: The readability and length of informed consent forms have been debated for over three decades. Despite national guidelines promoting patient-friendly language, many forms fall short. This study compares the readability and content quality of informed consents from the American Society of Plastic Surgeons (ASPS) and ChatGPT for common plastic and reconstructive surgery (PRS) procedures. Methods: ASPS consents for seven common PRS procedures were obtained online. ChatGPT was then queried to create equivalent consents. Readability was assessed using the Flesch Reading Ease Score, Flesch-Kincaid Grade Level, and Lexical Density. Quality was graded using a modified National Quality Forum-based scale across domains: Procedure description, clinical rationale, patient-oriented benefit, quantitative and qualitative risks, and alternatives. Scores were compared between ASPS and ChatGPT consent forms. Results: ASPS versus ChatGPT conversion yielded mean Flesch scores of 30.09 versus 46.18 ( Conclusion: ChatGPT improved the readability and brevity of PRS consent forms while maintaining accuracy. Readily available artificial intelligence (AI) tools may enhance descriptions of procedures, rationale, patient benefits, and quantitative risks, offering a practical tool to aid in patient-provider communication.

Indexed as

artificial intelligenceconsent formsplastic and reconstructive surgeryqualityreadability

Identifiers

PMID42835891
PMCPMC13638244

What OpenQuestion holds

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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.