How useful are artificial intelligence programs used by patients to obtain information prior to sleeve gastrectomy surgery?

How useful are artificial intelligence programs used by patients to obtain information prior to sleeve gastrectomy surgery? | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article How useful are artificial intelligence programs used by patients to obtain information prior to sleeve gastrectomy surgery? İlkay Halıcıoğlu, Özcem Öfkeli, Abit Yaman, M. Kadri Çolakoğlu This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-7019423/v1 This work is licensed under a CC BY 4.0 License Status: Posted Version 1 posted You are reading this latest preprint version Abstract Objective This study aims to compare the informational adequacy of two artificial intelligence models, ChatGPT and Gemini, which patients use to find information before undergoing sleeve gastrectomy surgery. Methods Eight expert surgeons specializing in obesity surgery evaluated the responses from both artificial intelligence applications to a 21-item form composed of potential patient questions on a scale of 100 points. The scores were then compared using a paired t-test. Results ChatGPT scored an average of 94.4, while Gemini scored 91.4. The difference was not statistically significant (p = 0.12). Both systems were sufficient in providing patient information, earning high scores. Conclusion Artificial intelligence systems can be an effective tool for informing patients who are candidates for sleeve gastrectomy. However, further studies with larger samples and comparisons with actual surgeon responses are needed. Artificial intelligence bariatric surgery patient education ChatGPT Gemini expert evaluation Introduction Obesity is a significant public health problem with a rapidly increasing prevalence worldwide. It is a leading cause of both mortality and morbidity. According to the World Health Organization, there were more than 650 million obese individuals worldwide as of 2022 [ 1 ]. The first-line approaches to treating obesity are lifestyle changes and medical treatments. However, when these interventions fail to yield satisfactory results, bariatric surgery becomes a viable option. Among these surgical methods, sleeve gastrectomy is one of the most commonly performed procedures [ 2 ]. The preoperative information process is important for motivating individuals considering bariatric surgery, ensuring postoperative compliance, and achieving successful outcomes [ 3 ]. Traditionally, this process has been carried out through face-to-face information sessions, brochures, or educational videos. However, the growing workload of healthcare systems and the increasing need for personalized counseling have sparked interest in alternative information methods. In this context, the use of artificial intelligence (AI)-based systems in patient education and healthcare information has increased [ 4 ]. Large language models (LLMs) and chatbots have the potential to improve health literacy by providing patients with quick, accessible information [ 5 ]. However, the content, accuracy, and adequacy of AI-supported information regarding patient safety have yet to be clearly established. In surgeries such as gastric bypass, which require multidisciplinary preparation and information, it is debatable whether AI applications can replace traditional clinical information processes [ 6 ]. This study aims to evaluate the effectiveness of artificial intelligence–supported platforms in educating individuals considering gastric sleeve surgery and to analyze the scope, accuracy, and referral capacity of this content. Materials and Methods A 21-question form was prepared for patients recommended laparoscopic sleeve gastrectomy to treat obesity. The form was submitted to ChatGPT and Google Gemini, two artificial intelligence bots. The responses were sent to eight general surgeons, gastroenterology surgeons, and surgical oncologists who specialize in obesity surgery. The experts were informed that the answers they evaluated were provided by two different AI bots. The experts were asked to rate the answers on a scale from 1 to 100. The scores were compared using a paired t-test. Approval was obtained from the local ethics committee. Results Following expert evaluations, ChatGPT 4.0 received an average score of 94.375, while Google Gemini received a score of 91.375. A paired t-test was used to compare the results, and although there was a 3-point difference, no statistically significant difference was found (p=0.120). Table 1 shows the scores given by each expert. Both applications scoring above 90 indicates they are suitable for patients to use to obtain information prior to sleeve gastrectomy. Based on feedback from the experts who participated in the study, ChatGPT 4.0 was found to use more informal language, while Google Gemini prefers a more formal narrative style. No restrictions were imposed on the sources of information, such as guides or textbooks, when questions were directed to AI robots. Questions were asked directly and openly. The goal was to provide answers based on the average level of awareness and knowledge of patients and their relatives with direct internet access. Experts took this into account when evaluating the answers and assigning scores. Discussion This study evaluated two artificial intelligence models, ChatGPT and Gemini, in terms of information accuracy and coverage when used to provide patient information before obesity surgery. Both models received high average scores from experts (ChatGPT: 94.4; Gemini: 91.4). However, statistical analyses revealed that the difference between the two models was not significant (p = 0.12). These results suggest that both models met a certain standard in the patient information process, and the difference between them may not be clinically significant. These findings are consistent with those of similar studies in the literature. For example, in a study by Samaan et al. that evaluated ChatGPT's responses to 151 patient questions related to obesity surgery, the model provided comprehensive responses in 86.8% of cases [7]. The same study showed that 90.7% of the responses were consistent. These results support ChatGPT's high scores in our study. Similarly, a more recent study by Samaan et al. emphasized that GPT-4 outperformed GPT-3.5 in terms of accuracy and comprehensiveness [8]. Knowing the technical versions of the models used in our study may contribute to a better interpretation of performance differences. However, it should be emphasized that artificial intelligence should be evaluated not only in terms of how information is presented, but also in terms of communicative dimensions, such as patient motivation, empathy level, and cultural appropriateness. Gilson et al. reported that AI-based responses were more empathetic than those given by physicians, but medical accuracy could vary [9]. The fact that eight different experts conducted the evaluations in our study reduces evaluator bias, which is commonly encountered in such studies, and enhances the reliability of the results. Since the number of evaluators is generally lower in similar studies, this is one of the strengths of our study. However, the lack of inter-rater reliability measurements limits the internal validity of the findings. An important limitation of this study is that it excluded real physician responses from the evaluation. The level at which artificial intelligence models understand patient information can only be assessed in terms of absolute performance when compared directly with responses provided by clinicians. Additionally, restricting the study to sleeve gastrectomy procedures limits the generalizability of the results to other surgical fields. In conclusion, this study demonstrates that AI-based systems achieve high accuracy and coverage rates in preoperative patient information processes in obesity surgery. However, more comprehensive research is required for these technologies to be integrated into clinical practice. This research must take into account not only content accuracy, but also ethical, communicative, and individualization dimensions. Declarations Acknowledgments and Conflict of Interest Disclosure We would like to thank the general surgeons who contributed to evaluating the artificial intelligence systems included in this study. The participating surgeons volunteered to take part in all stages of the study and conducted their evaluations independently. The authors declare that they have no financial conflicts of interest, sponsorships, consulting relationships, or institutional relationships related to this study. Author Contribution IH drafted the main manuscript. OO, AY, and MKC evaluated the expert assessments. All authors reviewed the final version of the manuscript. References World Health Organization. (2022). Obesity and overweight. https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight Angrisani, L., Santonicola, A., Iovino, P., Formisano, G., Buchwald, H., & Scopinaro, N. (2017). Bariatric Surgery Worldwide 2013. Obesity Surgery, 25(10), 1822–1832. https://doi.org/10.1007/s11695-015-1657-z Mechanick, J. I., Youdim, A., Jones, D. B., Garvey, W. T., Hurley, D. L., McMahon, M. M., Heinberg, L. J., … Dixon, J. B. (2013). Clinical practice guidelines for the perioperative nutritional, metabolic, and nonsurgical support of the bariatric surgery patient. Obesity, 21(S1), S1–S27. https://doi.org/10.1002/oby.20461 Topol, E. J. (2019). High-performance medicine: the convergence of human and artificial intelligence. Nature Medicine, 25(1), 44–56. https://doi.org/10.1038/s41591-018-0300-7 Esteva, A., Robicquet, A., Ramsundar, B., Kuleshov, V., DePristo, M., Chou, K., … Dean, J. (2021). A guide to deep learning in healthcare. Nature Medicine, 25, 24–29. https://doi.org/10.1038/s41591-018-0316-z Blease, C., Kaptchuk, T. J., Bernstein, M. H., Mandl, K. D., Halamka, J. D., & DesRoches, C. M. (2022). Artificial intelligence and the future of primary care: Exploratory qualitative study of UK general practitioners’ views. Journal of Medical Internet Research, 24(3), e30235. https://doi.org/10.2196/30235 Samaan, J. S., Yeo, Y. H., Rajeev, N., Hawley, L., Abel, S., Ng, W. H., … Samakar, K. (2023). Assessing the Accuracy of Responses by the Language Model ChatGPT to Questions Regarding Bariatric Surgery. Obesity Surgery, 33(6), 1790–1796. https://doi.org/10.1007/s11695-023-06603-5 Samaan, J. S., Rajeev, N., Ng, W. H., Srinivasan, N., Busam, J. A., Yeo, Y. H., & Samakar, K. (2024). ChatGPT as a Source of Information for Bariatric Surgery Patients: a Comparative Analysis of Accuracy and Comprehensiveness Between GPT-4 and GPT-3.5. Obesity Surgery, 34(5), 1987–1989. https://doi.org/10.1007/s11695-024-07212-6 Gilson, A., Safranek, C. W., Huang, T., Socrates, V., Chi, L., Taylor, R. A., & Chartash, D. (2023). How Does ChatGPT Perform on the United States Medical Licensing Examination (USMLE)? JMIR Medical Education, 9, e45312. https://doi.org/10.2196/45312 Table Additional Declarations No competing interests reported. Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. As a division of Research Square Company, we’re committed to making research communication faster, fairer, and more useful. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-7019423","acceptedTermsAndConditions":true,"allowDirectSubmit":true,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":482466458,"identity":"91688e96-6945-41e2-b967-627236d586a5","order_by":0,"name":"İlkay Halıcıoğlu","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA6ElEQVRIiWNgGAWjYBACNnY2BgbGBgsGBnbmA0C+hAxhLcxgLRIMDMxsCSAtPIStQWjhMQDxCWvhY2ZL/My7Q0Je3pnn86sbNRY8DOyHj24g4LDD0rxnJAw3HubdZp1zDOgwnrS0G/i1sDdI87ZJJBg2824zzmEDapHgMSOkpfk3RAvPM+Ocf0RpYTsGtkWemYf5cW4bcVrSLOe2SRhuYGYzY87tk+BhI+QX+fY24xtv22zk5dubH3/O+VYnx89++BheLSDABIoLgwMMbBJgewkpBwHGHyDrGhiYPxCjehSMglEwCkYeAAAN4Dq2CoImRAAAAABJRU5ErkJggg==","orcid":"","institution":"Diyarbakır Gazi Yaşargil Eğitim ve Araştırma Hastanesi","correspondingAuthor":true,"prefix":"","firstName":"İlkay","middleName":"","lastName":"Halıcıoğlu","suffix":""},{"id":482466459,"identity":"4a658f96-d17f-485b-bda4-5e43b41c46e1","order_by":1,"name":"Özcem Öfkeli","email":"","orcid":"","institution":"Diyarbakır Gazi Yaşargil Eğitim ve Araştırma Hastanesi","correspondingAuthor":false,"prefix":"","firstName":"Özcem","middleName":"","lastName":"Öfkeli","suffix":""},{"id":482466460,"identity":"e1b5cf88-6d40-4615-b0f3-d95714872243","order_by":2,"name":"Abit Yaman","email":"","orcid":"","institution":"Diyarbakır Gazi Yaşargil Eğitim ve Araştırma Hastanesi","correspondingAuthor":false,"prefix":"","firstName":"Abit","middleName":"","lastName":"Yaman","suffix":""},{"id":482466461,"identity":"9e023973-d01f-43a2-8520-b0b032ec8d39","order_by":3,"name":"M. Kadri Çolakoğlu","email":"","orcid":"","institution":"Ankara City Hospital","correspondingAuthor":false,"prefix":"","firstName":"M.","middleName":"Kadri","lastName":"Çolakoğlu","suffix":""}],"badges":[],"createdAt":"2025-07-01 10:53:08","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-7019423/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-7019423/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":86893794,"identity":"da1ffd95-579d-4a55-9922-3abf0bd80639","added_by":"auto","created_at":"2025-07-16 21:31:28","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":353079,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-7019423/v1/cdfc5ee9-2569-4ba3-999b-8a743497da38.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"How useful are artificial intelligence programs used by patients to obtain information prior to sleeve gastrectomy surgery?","fulltext":[{"header":"Introduction","content":"\u003cp\u003eObesity is a significant public health problem with a rapidly increasing prevalence worldwide. It is a leading cause of both mortality and morbidity. According to the World Health Organization, there were more than 650\u0026nbsp;million obese individuals worldwide as of 2022 [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. The first-line approaches to treating obesity are lifestyle changes and medical treatments. However, when these interventions fail to yield satisfactory results, bariatric surgery becomes a viable option. Among these surgical methods, sleeve gastrectomy is one of the most commonly performed procedures [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThe preoperative information process is important for motivating individuals considering bariatric surgery, ensuring postoperative compliance, and achieving successful outcomes [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e]. Traditionally, this process has been carried out through face-to-face information sessions, brochures, or educational videos. However, the growing workload of healthcare systems and the increasing need for personalized counseling have sparked interest in alternative information methods.\u003c/p\u003e\u003cp\u003eIn this context, the use of artificial intelligence (AI)-based systems in patient education and healthcare information has increased [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Large language models (LLMs) and chatbots have the potential to improve health literacy by providing patients with quick, accessible information [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. However, the content, accuracy, and adequacy of AI-supported information regarding patient safety have yet to be clearly established. In surgeries such as gastric bypass, which require multidisciplinary preparation and information, it is debatable whether AI applications can replace traditional clinical information processes [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e\u003cp\u003eThis study aims to evaluate the effectiveness of artificial intelligence\u0026ndash;supported platforms in educating individuals considering gastric sleeve surgery and to analyze the scope, accuracy, and referral capacity of this content.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cp\u003eA 21-question form was prepared for patients recommended laparoscopic sleeve gastrectomy to treat obesity. The form was submitted to ChatGPT and Google Gemini, two artificial intelligence bots. The responses were sent to eight general surgeons, gastroenterology surgeons, and surgical oncologists who specialize in obesity surgery. The experts were informed that the answers they evaluated were provided by two different AI bots. The experts were asked to rate the answers on a scale from 1 to 100. The scores were compared using a paired t-test. Approval was obtained from the local ethics committee.\u003c/p\u003e"},{"header":"Results","content":"\u003cp\u003eFollowing expert evaluations, ChatGPT 4.0 received an average score of 94.375, while Google Gemini received a score of 91.375. A paired t-test was used to compare the results, and although there was a 3-point difference, no statistically significant difference was found (p=0.120). Table 1 shows the scores given by each expert. Both applications scoring above 90 indicates they are suitable for patients to use to obtain information prior to sleeve gastrectomy. Based on feedback from the experts who participated in the study, ChatGPT 4.0 was found to use more informal language, while Google Gemini prefers a more formal narrative style.\u003c/p\u003e\n\u003cp\u003eNo restrictions were imposed on the sources of information, such as guides or textbooks, when questions were directed to AI robots. Questions were asked directly and openly. The goal was to provide answers based on the average level of awareness and knowledge of patients and their relatives with direct internet access. Experts took this into account when evaluating the answers and assigning scores.\u003c/p\u003e"},{"header":"Discussion","content":"\u003cp\u003eThis study evaluated two artificial intelligence models, ChatGPT and Gemini, in terms of information accuracy and coverage when used to provide patient information before obesity surgery. Both models received high average scores from experts (ChatGPT: 94.4; Gemini: 91.4). However, statistical analyses revealed that the difference between the two models was not significant (p = 0.12). These results suggest that both models met a certain standard in the patient information process, and the difference between them may not be clinically significant.\u003c/p\u003e\n\u003cp\u003eThese findings are consistent with those of similar studies in the literature. For example, in a study by Samaan et al. that evaluated ChatGPT\u0026apos;s responses to 151 patient questions related to obesity surgery, the model provided comprehensive responses in 86.8% of cases [7]. The same study showed that 90.7% of the responses were consistent. These results support ChatGPT\u0026apos;s high scores in our study. Similarly, a more recent study by Samaan et al. emphasized that GPT-4 outperformed GPT-3.5 in terms of accuracy and comprehensiveness [8]. Knowing the technical versions of the models used in our study may contribute to a better interpretation of performance differences.\u003c/p\u003e\n\u003cp\u003eHowever, it should be emphasized that artificial intelligence should be evaluated not only in terms of how information is presented, but also in terms of communicative dimensions, such as patient motivation, empathy level, and cultural appropriateness. Gilson et al. reported that AI-based responses were more empathetic than those given by physicians, but medical accuracy could vary [9].\u003c/p\u003e\n\u003cp\u003eThe fact that eight different experts conducted the evaluations in our study reduces evaluator bias, which is commonly encountered in such studies, and enhances the reliability of the results. Since the number of evaluators is generally lower in similar studies, this is one of the strengths of our study. However, the lack of inter-rater reliability measurements limits the internal validity of the findings.\u003c/p\u003e\n\u003cp\u003eAn important limitation of this study is that it excluded real physician responses from the evaluation. The level at which artificial intelligence models understand patient information can only be assessed in terms of absolute performance when compared directly with responses provided by clinicians. Additionally, restricting the study to sleeve gastrectomy procedures limits the generalizability of the results to other surgical fields.\u003c/p\u003e\n\u003cp\u003eIn conclusion, this study demonstrates that AI-based systems achieve high accuracy and coverage rates in preoperative patient information processes in obesity surgery. However, more comprehensive research is required for these technologies to be integrated into clinical practice. This research must take into account not only content accuracy, but also ethical, communicative, and individualization dimensions.\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eAcknowledgments and Conflict of Interest Disclosure\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe would like to thank the general surgeons who contributed to evaluating the artificial intelligence systems included in this study. The participating surgeons volunteered to take part in all stages of the study and conducted their evaluations independently.\u003c/p\u003e\n\u003cp\u003eThe authors declare that they have no financial conflicts of interest, sponsorships, consulting relationships, or institutional relationships related to this study.\u003c/p\u003e\u003ch2\u003eAuthor Contribution\u003c/h2\u003e\u003cp\u003eIH drafted the main manuscript. OO, AY, and MKC evaluated the expert assessments. All authors reviewed the final version of the manuscript.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWorld Health Organization. (2022). Obesity and overweight. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight\u003c/span\u003e\u003cspan address=\"https://www.who.int/news-room/fact-sheets/detail/obesity-and-overweight\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eAngrisani, L., Santonicola, A., Iovino, P., Formisano, G., Buchwald, H., \u0026amp; Scopinaro, N. (2017). Bariatric Surgery Worldwide 2013. Obesity Surgery, 25(10), 1822\u0026ndash;1832. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11695-015-1657-z\u003c/span\u003e\u003cspan address=\"10.1007/s11695-015-1657-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eMechanick, J. I., Youdim, A., Jones, D. B., Garvey, W. T., Hurley, D. L., McMahon, M. M., Heinberg, L. J., \u0026hellip; Dixon, J. B. (2013). Clinical practice guidelines for the perioperative nutritional, metabolic, and nonsurgical support of the bariatric surgery patient. Obesity, 21(S1), S1\u0026ndash;S27. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1002/oby.20461\u003c/span\u003e\u003cspan address=\"10.1002/oby.20461\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eTopol, E. J. (2019). High-performance medicine: the convergence of human and artificial intelligence. Nature Medicine, 25(1), 44\u0026ndash;56. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41591-018-0300-7\u003c/span\u003e\u003cspan address=\"10.1038/s41591-018-0300-7\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eEsteva, A., Robicquet, A., Ramsundar, B., Kuleshov, V., DePristo, M., Chou, K., \u0026hellip; Dean, J. (2021). A guide to deep learning in healthcare. Nature Medicine, 25, 24\u0026ndash;29. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1038/s41591-018-0316-z\u003c/span\u003e\u003cspan address=\"10.1038/s41591-018-0316-z\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBlease, C., Kaptchuk, T. J., Bernstein, M. H., Mandl, K. D., Halamka, J. D., \u0026amp; DesRoches, C. M. (2022). Artificial intelligence and the future of primary care: Exploratory qualitative study of UK general practitioners\u0026rsquo; views. Journal of Medical Internet Research, 24(3), e30235. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2196/30235\u003c/span\u003e\u003cspan address=\"10.2196/30235\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSamaan, J. S., Yeo, Y. H., Rajeev, N., Hawley, L., Abel, S., Ng, W. H., \u0026hellip; Samakar, K. (2023). Assessing the Accuracy of Responses by the Language Model ChatGPT to Questions Regarding Bariatric Surgery. Obesity Surgery, 33(6), 1790\u0026ndash;1796. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11695-023-06603-5\u003c/span\u003e\u003cspan address=\"10.1007/s11695-023-06603-5\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eSamaan, J. S., Rajeev, N., Ng, W. H., Srinivasan, N., Busam, J. A., Yeo, Y. H., \u0026amp; Samakar, K. (2024). ChatGPT as a Source of Information for Bariatric Surgery Patients: a Comparative Analysis of Accuracy and Comprehensiveness Between GPT-4 and GPT-3.5. Obesity Surgery, 34(5), 1987\u0026ndash;1989. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.1007/s11695-024-07212-6\u003c/span\u003e\u003cspan address=\"10.1007/s11695-024-07212-6\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eGilson, A., Safranek, C. W., Huang, T., Socrates, V., Chi, L., Taylor, R. A., \u0026amp; Chartash, D. (2023). How Does ChatGPT Perform on the United States Medical Licensing Examination (USMLE)? JMIR Medical Education, 9, e45312. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://doi.org/10.2196/45312\u003c/span\u003e\u003cspan address=\"10.2196/45312\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"},{"header":"Table","content":"\u003cp\u003e\u003cimg 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\" width=\"388\" height=\"460\"\u003e\u003c/p\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":true,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"Artificial intelligence, bariatric surgery, patient education, ChatGPT, Gemini, expert evaluation","lastPublishedDoi":"10.21203/rs.3.rs-7019423/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-7019423/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eObjective\u003c/h2\u003e\u003cp\u003eThis study aims to compare the informational adequacy of two artificial intelligence models, ChatGPT and Gemini, which patients use to find information before undergoing sleeve gastrectomy surgery.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e\u003cp\u003eEight expert surgeons specializing in obesity surgery evaluated the responses from both artificial intelligence applications to a 21-item form composed of potential patient questions on a scale of 100 points. The scores were then compared using a paired t-test.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e\u003cp\u003eChatGPT scored an average of 94.4, while Gemini scored 91.4. The difference was not statistically significant (p\u0026thinsp;=\u0026thinsp;0.12). Both systems were sufficient in providing patient information, earning high scores.\u003c/p\u003e\u003ch2\u003eConclusion\u003c/h2\u003e\u003cp\u003eArtificial intelligence systems can be an effective tool for informing patients who are candidates for sleeve gastrectomy. However, further studies with larger samples and comparisons with actual surgeon responses are needed.\u003c/p\u003e","manuscriptTitle":"How useful are artificial intelligence programs used by patients to obtain information prior to sleeve gastrectomy surgery?","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-07-09 14:39:01","doi":"10.21203/rs.3.rs-7019423/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"d14a49cf-e46e-49dd-8fd9-1dbaddcee070","owner":[],"postedDate":"July 9th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[],"tags":[],"updatedAt":"2025-07-16T21:23:22+00:00","versionOfRecord":[],"versionCreatedAt":"2025-07-09 14:39:01","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-7019423","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-7019423","identity":"rs-7019423","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}