Analysis of online materials regarding DIEP and TRAM flap autologous breast reconstruction

Reading Between the Tabloids: An Objective Analysis of the Quality and Readability of Patient Encountered Online Material for Face Transplantation

Face transplantation is a highly sensationalized procedure in the media. The purpose of this study is to assess the content and readability of online materials that prospective patients/public encounter regarding face transplantation. A search for face transplantation was performed on Google. Sites were categorized under 3 groups: established face transplant programs, informational third-party sources (eg, Wikipedia), and news article/tabloid sites. Each site was assessed for readability using 6 different readability metrics, while quality was assessed utilizing JAMA benchmark criteria and DISCERN instrument. One-way ANOVA with post hoc Tukey's multiple comparisons test was used for analysis. News sources were significantly easier to read than face transplant program sites (10.4 grade reading level vs. 12.4). For the JAMA benchmark, face transplant programs demonstrated the lowest average score relative to third-party sites, and news sources (2.05 vs. 2.91 vs. 3.67, respectively; P<0.001), but had significantly greater DISCERN scores than news sources (53.50 vs. 45.83, P=0.019). News sources were significantly more accessible, readable, and offered greater transparency of authorship compared with reputable sources, despite their lack of expertise on face transplantation. Face transplant programs should update their websites to ensure readability and accessibility of the information provided to the public.

Artificial Intelligence as a Triage Tool during the Perioperative Period: Pilot Study of Accuracy and Accessibility for Clinical Application

Background

Given the dialogistic properties of ChatGPT, we hypothesized that this artificial intelligence (AI) function can be used as a self-service tool where clinical questions can be directly answered by AI. Our objective was to assess the content, accuracy, and accessibility of AI-generated content regarding common perioperative questions for reduction mammaplasty.

Methods

ChatGPT (OpenAI, February Version, San Francisco, Calif.) was used to query 20 common patient concerns that arise in the perioperative period of a reduction mammaplasty. Searches were performed in duplicate for both a general term and a specific clinical question. Query outputs were analyzed both objectively and subjectively. Descriptive statistics, t tests, and chi-square tests were performed where appropriate with a predetermined level of significance of P less than 0.05.

Results

From a total of 40 AI-generated outputs, mean word length was 191.8 words. Readability was at the thirteenth grade level. Regarding content, of all query outputs, 97.5% were on the appropriate topic. Medical advice was deemed to be reasonable in 100% of cases. General queries more frequently reported overarching background information, whereas specific queries more frequently reported prescriptive information (P < 0.0001). AI outputs specifically recommended following surgeon provided postoperative instructions in 82.5% of instances.

Conclusions

Currently available AI tools, in their nascent form, can provide recommendations for common perioperative questions and concerns for reduction mammaplasty. With further calibration, AI interfaces may serve as a tool for fielding patient queries in the future; however, patients must always retain the ability to bypass technology and be able to contact their surgeon.