From readability to representation: A systematic review and meta-analysis of online patient education in breast reduction and augmentation surgery.

Abstract

Online patient education materials (OPEMs) play a critical role in shaping patient decision-making for breast augmentation and reduction surgery. However, concerns persist regarding their readability, quality, and inclusivity. We present the first comprehensive systematic review and meta-analysis to evaluate OPEMs across traditional, artificial intelligence (AI)-generated, and social media platforms. We systematically reviewed 23 studies evaluating OPEMs related to breast augmentation and reduction. Outcomes included the Flesch-Kincaid Grade Level (FKGL), Simple Measure of Gobbledygook (SMOG) scores, DISCERN and Ensuring quality information for patients quality assessments, diversity in visual representation, and AI performance. A random-effects meta-analysis was conducted on FKGL scores and binomial test was used to assess the proportion of studies exceeding the recommended readability thresholds. Meta-analysis of 3 studies revealed a pooled FKGL of 12.28 (95% CI: 11.16-13.41), with significant heterogeneity (I² = 96.4%, p < 0.0001). A binomial test confirmed that 100% of the studies evaluating readability concluded that OPEMs exceeded the sixth-grade level (p = 0.0005). Nine studies reported suboptimal content quality, with common deficiencies in risk disclosure, source attribution, and citation. Three studies found representation and linguistic disparities in educational visuals and content accessibility. AI-generated materials showed promise but often lacked surgical nuance and detail. Our findings suggest that OPEMs for breast surgery are consistently written above the recommended readability levels, frequently omit essential content, and exhibit inequities in representation. These findings demonstrate the need for standardizing and improving digital patient education content to meet the informational and cultural needs of all surgical candidates.