Evaluation of ChatGPT as a Counselling Tool for Italian-Speaking MASLD Patients: Assessment of Accuracy, Completeness and Comprehensibility

Author:

Pugliese Nicola12ORCID,Polverini Davide12,Lombardi Rosa34ORCID,Pennisi Grazia5,Ravaioli Federico67ORCID,Armandi Angelo89ORCID,Buzzetti Elena1011ORCID,Dalbeni Andrea1213ORCID,Liguori Antonio14ORCID,Mantovani Alessandro15ORCID,Villani Rosanna16ORCID,Gardini Ivan17,Hassan Cesare118,Valenti Luca419,Miele Luca1420ORCID,Petta Salvatore5,Sebastiani Giada21ORCID,Aghemo Alessio12,

Affiliation:

1. Department of Biomedical Sciences, Humanitas University, Pieve Emanuele, 20072 Milan, Italy

2. Division of Internal Medicine and Hepatology, Department of Gastroenterology, IRCCS Humanitas Research Hospital, Rozzano, 20089 Milan, Italy

3. Unit of Internal Medicine and Metabolic Disease, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico of Milan, 20122 Milan, Italy

4. Department of Pathophysiology and Transplantation, Università degli Studi di Milano, 20122 Milan, Italy

5. Section of Gastroenterology and Hepatology, PROMISE, University of Palermo, 90127 Palermo, Italy

6. Department of Medical and Surgical Sciences (DIMEC), University of Bologna, 40138 Bologna, Italy

7. Division of Internal Medicine, Hepatobiliary and Immunoallergic Diseases, IRCCS Azienda Ospedaliero Universitaria di Bologna, 40138 Bologna, Italy

8. Division of Gastroenterology and Hepatology, Department of Medical Sciences, University of Turin, Corso Dogliotti 14, 10126 Turin, Italy

9. Metabolic Liver Disease Research Program, I. Department of Internal Medicine, University Medical Center of Mainz, 55131 Mainz, Germany

10. Internal Medicine and Centre for Hemochromatosis and Hereditary Liver Diseases, ERN-EuroBloodNet Center for Iron Disorders, Azienda Ospedaliero-Universitaria di Modena-Policlinico, 41125 Modena, Italy

11. Department of Medical and Surgical Sciences, Università degli Studi di Modena e Reggio Emilia, 41125 Modena, Italy

12. Division of General Medicine C, Department of Medicine, University and Azienda Ospedaliera Universitaria Integrata of Verona, University of Verona, 37134 Verona, Italy

13. Liver Unit, Department of Medicine, University and Azienda Ospedaliera Universitaria Integrata of Verona, University of Verona, 37134 Verona, Italy

14. DiSMeC—Department of Scienze Mediche e Chirurgiche, Fondazione Policlinico Gemelli IRCCS, 00168 Rome, Italy

15. Section of Endocrinology, Diabetes and Metabolism, Department of Medicine, University and Azienda Ospedaliera Universitaria Integrata of Verona, Piazzale Stefani, 37126 Verona, Italy

16. C.U.R.E. (University Center for Liver Disease Research and Treatment), Liver Unit, Department of Medical and Surgical Sciences, University of Foggia, 71122 Foggia, Italy

17. EpaC Onlus, Italian Liver Patient Association, 10141 Turin, Italy

18. Division of Gastroenterology and Digestive Endoscopy, Humanitas Research Hospital, IRCCS, Rozzano, 20089 Milan, Italy

19. Precision Medicine Lab, Biological Resource Center, Department of Transfusion Medicine, Fondazione IRCCS Ca’ Granda Ospedale Maggiore Policlinico, 20122 Milan, Italy

20. Department of Medicina e Chirurgia Traslazionale, Università Cattolica Del Sacro Cuore, 00168 Rome, Italy

21. Division of Gastroenterology and Hepatology, McGill University Health Centre, Montreal, QC H4A 3J1, Canada

Abstract

Background: Artificial intelligence (AI)-based chatbots have shown promise in providing counseling to patients with metabolic dysfunction-associated steatotic liver disease (MASLD). While ChatGPT3.5 has demonstrated the ability to comprehensively answer MASLD-related questions in English, its accuracy remains suboptimal. Whether language influences these results is unclear. This study aims to assess ChatGPT’s performance as a counseling tool for Italian MASLD patients. Methods: Thirteen Italian experts rated the accuracy, completeness and comprehensibility of ChatGPT3.5 in answering 15 MASLD-related questions in Italian using a six-point accuracy, three-point completeness and three-point comprehensibility Likert’s scale. Results: Mean scores for accuracy, completeness and comprehensibility were 4.57 ± 0.42, 2.14 ± 0.31 and 2.91 ± 0.07, respectively. The physical activity domain achieved the highest mean scores for accuracy and completeness, whereas the specialist referral domain achieved the lowest. Overall, Fleiss’s coefficient of concordance for accuracy, completeness and comprehensibility across all 15 questions was 0.016, 0.075 and −0.010, respectively. Age and academic role of the evaluators did not influence the scores. The results were not significantly different from our previous study focusing on English. Conclusion: Language does not appear to affect ChatGPT’s ability to provide comprehensible and complete counseling to MASLD patients, but accuracy remains suboptimal in certain domains.

Publisher

MDPI AG

Cited by 1 articles. 订阅此论文施引文献 订阅此论文施引文献,注册后可以免费订阅5篇论文的施引文献,订阅后可以查看论文全部施引文献

同舟云学术

1.学者识别学者识别

2.学术分析学术分析

3.人才评估人才评估

"同舟云学术"是以全球学者为主线,采集、加工和组织学术论文而形成的新型学术文献查询和分析系统,可以对全球学者进行文献检索和人才价值评估。用户可以通过关注某些学科领域的顶尖人物而持续追踪该领域的学科进展和研究前沿。经过近期的数据扩容,当前同舟云学术共收录了国内外主流学术期刊6万余种,收集的期刊论文及会议论文总量共计约1.5亿篇,并以每天添加12000余篇中外论文的速度递增。我们也可以为用户提供个性化、定制化的学者数据。欢迎来电咨询!咨询电话:010-8811{复制后删除}0370

www.globalauthorid.com

TOP

Copyright © 2019-2024 北京同舟云网络信息技术有限公司
京公网安备11010802033243号  京ICP备18003416号-3