The promising role of chatbots in keratorefractive surgery patient education.

PURPOSE

To evaluate the appropriateness, understandability, actionability, and readability of responses provided by ChatGPT-3.5, Bard, and Bing Chat to frequently asked questions about keratorefractive surgery (KRS).

METHOD

Thirty-eight frequently asked questions about KRS were directed three times to a fresh ChatGPT-3.5, Bard, and Bing Chat interfaces. Two experienced refractive surgeons categorized the chatbots' responses according to their appropriateness and the accuracy of the responses was assessed using the Structure of the Observed Learning Outcome (SOLO) taxonomy. Flesch Reading Ease (FRE) and Coleman-Liau Index (CLI) were used to evaluate the readability of the responses of chatbots. Furthermore, the understandability scores of responses were evaluated using the Patient Education Materials Assessment Tool (PEMAT).

RESULTS

The appropriateness of the ChatGPT-3.5, Bard, and Bing Chat responses was 86.8% (33/38), 84.2% (32/38), and 81.5% (31/38), respectively (P>0.05). According to the SOLO test, ChatGPT-3.5 (3.91±0.44) achieved the highest mean accuracy and followed by Bard (3.64±0.61) and Bing Chat (3.19±0.55). For understandability (mean PEMAT-U score the ChatGPT-3.5: 68.5%, Bard: 78.6%, and Bing Chat: 67.1%, P<0.05), and actionability (mean PEMAT-A score the ChatGPT-3.5: 62.6%, Bard: 72.4%, and Bing Chat: 60.9%, P<0.05) the Bard scored better than the other chatbots. Two readability analyses showed that Bing had the highest readability, followed by the ChatGPT-3.5 and Bard, however, the understandability and readability scores were more challenging than the recommended level.

CONCLUSION

Artificial intelligence supported chatbots have the potential to provide detailed and appropriate responses at acceptable levels in KRS. Chatbots, while promising for patient education in KRS, require further progress, especially in readability and understandability aspects.