{"title":"Evaluation of ChatGPT-4 Performance in Answering Patients' Questions About the Management of Type 2 Diabetes.","authors":"Puren Gokbulut, Serife Mehlika Kuskonmaz, Cagatay Emir Onder, Isilay Taskaldiran, Gonul Koc","doi":"10.14744/SEMB.2024.23697","DOIUrl":null,"url":null,"abstract":"<p><strong>Objectives: </strong>Type 2 diabetes mellitus is a disease with a rising prevalence worldwide. Person-centered treatment factors, including comorbidities and treatment goals, should be considered in determining the pharmacological treatment of type 2 diabetes. ChatGPT-4 (Generative Pre-trained Transformer), a large language model, holds the potential performance in various fields, including medicine. We aimed to examine the reliability, quality, reproducibility, and readability of ChatGPT-4's responses to clinical scenarios about the medical treatment approach and management of type 2 diabetes patients.</p><p><strong>Methods: </strong>ChatGPT-4's responses to 24 questions were independently graded by two endocrinologists with clinical experience in endocrinology and resolved by a third reviewer based on the ADA(American Diabetes Association) 2023 guidelines. DISCERN (Quality Criteria for Consumer Health Information) Measurement Tool was used to evaluate the reliability and quality of information.</p><p><strong>Results: </strong>Responses to questions by ChatGPT-4 were fairly consistent in both sessions. No false or misleading information was found in any ChatGPT-4 responses. In terms of reliability, most of the answers showed good (87.5%), followed by excellent (12.5%) reliability. Reading Level was classified as fairly difficult to read (8.3%), difficult to read (50%), and very difficult to read (41.7%).</p><p><strong>Conclusion: </strong>ChatGPT-4 may have a role as an additional informative tool for type 2 diabetes patients for medical treatment approaches.</p>","PeriodicalId":42218,"journal":{"name":"Medical Bulletin of Sisli Etfal Hospital","volume":"58 4","pages":"483-490"},"PeriodicalIF":1.0000,"publicationDate":"2024-12-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11729837/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Medical Bulletin of Sisli Etfal Hospital","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.14744/SEMB.2024.23697","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/1/1 0:00:00","PubModel":"eCollection","JCR":"Q3","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
引用次数: 0
Abstract
Objectives: Type 2 diabetes mellitus is a disease with a rising prevalence worldwide. Person-centered treatment factors, including comorbidities and treatment goals, should be considered in determining the pharmacological treatment of type 2 diabetes. ChatGPT-4 (Generative Pre-trained Transformer), a large language model, holds the potential performance in various fields, including medicine. We aimed to examine the reliability, quality, reproducibility, and readability of ChatGPT-4's responses to clinical scenarios about the medical treatment approach and management of type 2 diabetes patients.
Methods: ChatGPT-4's responses to 24 questions were independently graded by two endocrinologists with clinical experience in endocrinology and resolved by a third reviewer based on the ADA(American Diabetes Association) 2023 guidelines. DISCERN (Quality Criteria for Consumer Health Information) Measurement Tool was used to evaluate the reliability and quality of information.
Results: Responses to questions by ChatGPT-4 were fairly consistent in both sessions. No false or misleading information was found in any ChatGPT-4 responses. In terms of reliability, most of the answers showed good (87.5%), followed by excellent (12.5%) reliability. Reading Level was classified as fairly difficult to read (8.3%), difficult to read (50%), and very difficult to read (41.7%).
Conclusion: ChatGPT-4 may have a role as an additional informative tool for type 2 diabetes patients for medical treatment approaches.