Evidence map›Paper›PMID 42919992›Full record

ArticleAesthetic plastic surgery2026

Bridging the Literacy Gap in Breast Reconstruction Patient Education Using Artificial Intelligence.

Erin Kim, Ethan D Paliwoda, Rhett Farmer, Melia Wakeman, Hanaa Shihadeh, Dzifa Kpodzo, Benjamin J Schalet

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Article in Aesthetic 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.

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1 · What the graph read from it

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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

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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

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0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

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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

7 authors.

Erin KimDivision of Plastic and Reconstructive Surgery, Department of Surgery, Albany Medical Center, Albany, NY, USA. kimer@amc.edu.ORCID http://orcid.org/0009-0004-1904-3470
Ethan D PaliwodaDivision of Plastic and Reconstructive Surgery, Department of Surgery, Albany Medical Center, Albany, NY, USA.
Rhett FarmerDivision of Plastic and Reconstructive Surgery, Department of Surgery, Albany Medical Center, Albany, NY, USA.
Melia WakemanDivision of Plastic and Reconstructive Surgery, Department of Surgery, Albany Medical Center, Albany, NY, USA.
Hanaa ShihadehDivision of Plastic and Reconstructive Surgery, Department of Surgery, Albany Medical Center, Albany, NY, USA.
Dzifa KpodzoDivision of Plastic and Reconstructive Surgery, Department of Surgery, Albany Medical Center, Albany, NY, USA.
Benjamin J SchaletDivision of Plastic and Reconstructive Surgery, Department of Surgery, Albany Medical Center, Albany, NY, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundArtificial intelligence is increasingly integrated into healthcare, demonstrating applications across surgical prediction, intraoperative precision, and patient communication. However, there is limited literature examining the role of artificial intelligence in improving patient comprehension of educational materials for breast reconstruction.

methods30 texts from online education resources for breast reconstruction surgery were selected. Readability of the texts was then evaluated using the Flesch-Kincaid grade level, the Gunning Fog index, and the Coleman-Liau index. ChatGPT 4.0 was instructed to translate the individual texts to the 6th-grade level of English comprehension, and the readability of the translated texts was analyzed. Patient Education Materials Assessment Tool analysis assessed the understandability and actionability of each text.

resultsShapiro-Wilk test on the paired differences showed that the Flesch-Kincaid grade level and the Gunning Fog index followed normal distributions, whereas the Coleman-Liau index did not. The mean Flesch-Kincaid grade level, the Gunning Fog index, and the Coleman-Liau index for the original texts were 11.2, 13.9, and 11.3. The mean Flesch-Kincaid grade level, the Gunning Fog index, and the Coleman-Liau index for the AI-translated counterparts were 8.6, 10.5, and 9.7 (all p < 0.001). The mean understandability (0.70 SD = 0.06 vs. 0.58 SD = 0.08, p < 0.001) and actionability (0.40, SD = 0.09 vs. 0.37 SD = 0.11, p = 0.057) scores of the artificial intelligence-translations were higher than that of the original texts upon Patient Education Materials Assessment Tool analysis.

conclusionArtificial intelligence may be a promising tool for enhancing comprehension of breast reconstruction education materials among individuals with limited health literacy. LEVEL OF EVIDENCE IV: This journal requires that authors assign a level of evidence to each article. For a full description of these Evidence-Based Medicine ratings, please refer to the Table of Contents or the online Instructions to Authors www.springer.com/00266 .

Indexed as

Artificial intelligenceHealth literacyPatient educationPlastic surgeryReadability

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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.