Aesthetic plastic surgery · 2026
Bridging the Literacy Gap in Breast Reconstruction Patient Education Using Artificial Intelligence.
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Kim Erin, Paliwoda Ethan D, Farmer Rhett, Wakeman Melia, Shihadeh Hanaa, Kpodzo Dzifa, Schalet Benjamin J
Аннотация
BACKGROUND: Artificial 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.
METHODS: 30 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.
RESULTS: Shapiro-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.
CONCLUSION: Artificial 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 .
METHODS: 30 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.
RESULTS: Shapiro-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.
CONCLUSION: Artificial 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 .