TY - JOUR
T1 - Evaluation of the quality and quantity of artificial intelligence-generated responses about anesthesia and surgery
T2 - using ChatGPT 3.5 and 4.0
AU - Choi, Jisun
AU - Oh, Ah Ran
AU - Park, Jungchan
AU - Kang, Ryung A.
AU - Yoo, Seung Yeon
AU - Lee, Dong Jae
AU - Yang, Kwangmo
N1 - Publisher Copyright:
Copyright © 2024 Choi, Oh, Park, Kang, Yoo, Lee and Yang.
PY - 2024
Y1 - 2024
N2 - Introduction: The large-scale artificial intelligence (AI) language model chatbot, Chat Generative Pre-Trained Transformer (ChatGPT), is renowned for its ability to provide data quickly and efficiently. This study aimed to assess the medical responses of ChatGPT regarding anesthetic procedures. Methods: Two anesthesiologist authors selected 30 questions representing inquiries patients might have about surgery and anesthesia. These questions were inputted into two versions of ChatGPT in English. A total of 31 anesthesiologists then evaluated each response for quality, quantity, and overall assessment, using 5-point Likert scales. Descriptive statistics summarized the scores, and a paired sample t-test compared ChatGPT 3.5 and 4.0. Results: Regarding quality, “appropriate” was the most common rating for both ChatGPT 3.5 and 4.0 (40 and 48%, respectively). For quantity, responses were deemed “insufficient” in 59% of cases for 3.5, and “adequate” in 69% for 4.0. In overall assessment, 3 points were most common for 3.5 (36%), while 4 points were predominant for 4.0 (42%). Mean quality scores were 3.40 and 3.73, and mean quantity scores were − 0.31 (between insufficient and adequate) and 0.03 (between adequate and excessive), respectively. The mean overall score was 3.21 for 3.5 and 3.67 for 4.0. Responses from 4.0 showed statistically significant improvement in three areas. Conclusion: ChatGPT generated responses mostly ranging from appropriate to slightly insufficient, providing an overall average amount of information. Version 4.0 outperformed 3.5, and further research is warranted to investigate the potential utility of AI chatbots in assisting patients with medical information.
AB - Introduction: The large-scale artificial intelligence (AI) language model chatbot, Chat Generative Pre-Trained Transformer (ChatGPT), is renowned for its ability to provide data quickly and efficiently. This study aimed to assess the medical responses of ChatGPT regarding anesthetic procedures. Methods: Two anesthesiologist authors selected 30 questions representing inquiries patients might have about surgery and anesthesia. These questions were inputted into two versions of ChatGPT in English. A total of 31 anesthesiologists then evaluated each response for quality, quantity, and overall assessment, using 5-point Likert scales. Descriptive statistics summarized the scores, and a paired sample t-test compared ChatGPT 3.5 and 4.0. Results: Regarding quality, “appropriate” was the most common rating for both ChatGPT 3.5 and 4.0 (40 and 48%, respectively). For quantity, responses were deemed “insufficient” in 59% of cases for 3.5, and “adequate” in 69% for 4.0. In overall assessment, 3 points were most common for 3.5 (36%), while 4 points were predominant for 4.0 (42%). Mean quality scores were 3.40 and 3.73, and mean quantity scores were − 0.31 (between insufficient and adequate) and 0.03 (between adequate and excessive), respectively. The mean overall score was 3.21 for 3.5 and 3.67 for 4.0. Responses from 4.0 showed statistically significant improvement in three areas. Conclusion: ChatGPT generated responses mostly ranging from appropriate to slightly insufficient, providing an overall average amount of information. Version 4.0 outperformed 3.5, and further research is warranted to investigate the potential utility of AI chatbots in assisting patients with medical information.
KW - AI chatbot
KW - ChatGPT
KW - artificial intelligence
KW - quality
KW - quantity
UR - https://www.scopus.com/pages/publications/85199345304
U2 - 10.3389/fmed.2024.1400153
DO - 10.3389/fmed.2024.1400153
M3 - Article
AN - SCOPUS:85199345304
SN - 2296-858X
VL - 11
JO - Frontiers in Medicine
JF - Frontiers in Medicine
M1 - 1400153
ER -