David Musheyev, Alexander Pan, Abdo E Kabarriti, Stacy Loeb, James F Borin
{"title":"人工智能聊天机器人提供的肾结石相关信息的质量。","authors":"David Musheyev, Alexander Pan, Abdo E Kabarriti, Stacy Loeb, James F Borin","doi":"10.1089/end.2023.0484","DOIUrl":null,"url":null,"abstract":"<p><p><b><i>Introduction:</i></b> Kidney stones are common and morbid conditions in the general population with a rising incidence globally. Previous studies show substantial limitations of online sources of information regarding prevention and treatment. The objective of this study was to examine the quality of information on kidney stones from artificial intelligence (AI) chatbots. <b><i>Methods:</i></b> The most common online searches about kidney stones from Google Trends and headers from the National Institute of Diabetes and Digestive and Kidney Diseases website were used as inputs to four AI chatbots (ChatGPT version 3.5, Perplexity, Chat Sonic, and Bing AI). Validated instruments were used to assess the quality (DISCERN instrument from 1 low to 5 high), understandability, and actionability (PEMAT, from 0% to 100%) of the chatbot outputs. In addition, we examined the reading level of the information and whether there was misinformation compared with guidelines (5 point Likert scale). <b><i>Results:</i></b> AI chatbots generally provided high-quality consumer health information (median DISCERN 4 out of 5) and did not include misinformation (median 1 out of 5). The median understandability was moderate (median 69.6%), and actionability was moderate to poor (median 40%). Responses were presented at an advanced reading level (11th grade; median Flesch-Kincaid score 11.3). <b><i>Conclusions:</i></b> AI chatbots provide generally accurate information on kidney stones and lack misinformation; however, it is not easily actionable and is presented above the recommended reading level for consumer health information.</p>","PeriodicalId":15723,"journal":{"name":"Journal of endourology","volume":null,"pages":null},"PeriodicalIF":2.9000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Quality of Information About Kidney Stones from Artificial Intelligence Chatbots.\",\"authors\":\"David Musheyev, Alexander Pan, Abdo E Kabarriti, Stacy Loeb, James F Borin\",\"doi\":\"10.1089/end.2023.0484\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p><b><i>Introduction:</i></b> Kidney stones are common and morbid conditions in the general population with a rising incidence globally. Previous studies show substantial limitations of online sources of information regarding prevention and treatment. The objective of this study was to examine the quality of information on kidney stones from artificial intelligence (AI) chatbots. <b><i>Methods:</i></b> The most common online searches about kidney stones from Google Trends and headers from the National Institute of Diabetes and Digestive and Kidney Diseases website were used as inputs to four AI chatbots (ChatGPT version 3.5, Perplexity, Chat Sonic, and Bing AI). Validated instruments were used to assess the quality (DISCERN instrument from 1 low to 5 high), understandability, and actionability (PEMAT, from 0% to 100%) of the chatbot outputs. In addition, we examined the reading level of the information and whether there was misinformation compared with guidelines (5 point Likert scale). <b><i>Results:</i></b> AI chatbots generally provided high-quality consumer health information (median DISCERN 4 out of 5) and did not include misinformation (median 1 out of 5). The median understandability was moderate (median 69.6%), and actionability was moderate to poor (median 40%). Responses were presented at an advanced reading level (11th grade; median Flesch-Kincaid score 11.3). <b><i>Conclusions:</i></b> AI chatbots provide generally accurate information on kidney stones and lack misinformation; however, it is not easily actionable and is presented above the recommended reading level for consumer health information.</p>\",\"PeriodicalId\":15723,\"journal\":{\"name\":\"Journal of endourology\",\"volume\":null,\"pages\":null},\"PeriodicalIF\":2.9000,\"publicationDate\":\"2024-10-01\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Journal of endourology\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1089/end.2023.0484\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2024/7/29 0:00:00\",\"PubModel\":\"Epub\",\"JCR\":\"Q1\",\"JCRName\":\"UROLOGY & NEPHROLOGY\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of endourology","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1089/end.2023.0484","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/7/29 0:00:00","PubModel":"Epub","JCR":"Q1","JCRName":"UROLOGY & NEPHROLOGY","Score":null,"Total":0}
引用次数: 0
摘要
导言:肾结石是普通人群中的常见病和多发病,其发病率在全球范围内呈上升趋势。先前的研究表明,有关预防和治疗的在线信息来源存在很大的局限性。本研究旨在考察人工智能(AI)聊天机器人提供的肾结石相关信息的质量:方法:谷歌趋势(Google Trends)中有关肾结石的最常见在线搜索和美国国家糖尿病、消化道疾病和肾脏疾病研究所(National Institute of Diabetes and Digestive and Kidney Diseases)网站的标题被用作 4 个人工智能聊天机器人(ChatGPT 3.5 版、Perplexity、Chat Sonic 和 Bing AI)的输入信息。我们使用经过验证的工具来评估聊天机器人输出的质量(DISCERN工具,从1低到5高)、可理解性和可操作性(PEMAT,从0到100%)。此外,我们还检查了信息的阅读水平以及与指南相比是否存在错误信息(5 点李克特量表):结果:人工智能聊天机器人一般都能提供高质量的消费者健康信息(DISCERN 中位数为 4 分,满分为 5 分),并且不包含错误信息(中位数为 1 分,满分为 5 分)。可理解性的中位数为中等(中位数为 69.6%),可操作性为中等至较差(中位数为 40%)。回复的阅读水平较高(11 年级;Flesch-Kincaid 评分中位数为 11.3):结论:人工智能聊天机器人提供的肾结石信息基本准确,没有错误信息;但是,这些信息不容易操作,而且高于消费者健康信息的建议阅读水平。
Quality of Information About Kidney Stones from Artificial Intelligence Chatbots.
Introduction: Kidney stones are common and morbid conditions in the general population with a rising incidence globally. Previous studies show substantial limitations of online sources of information regarding prevention and treatment. The objective of this study was to examine the quality of information on kidney stones from artificial intelligence (AI) chatbots. Methods: The most common online searches about kidney stones from Google Trends and headers from the National Institute of Diabetes and Digestive and Kidney Diseases website were used as inputs to four AI chatbots (ChatGPT version 3.5, Perplexity, Chat Sonic, and Bing AI). Validated instruments were used to assess the quality (DISCERN instrument from 1 low to 5 high), understandability, and actionability (PEMAT, from 0% to 100%) of the chatbot outputs. In addition, we examined the reading level of the information and whether there was misinformation compared with guidelines (5 point Likert scale). Results: AI chatbots generally provided high-quality consumer health information (median DISCERN 4 out of 5) and did not include misinformation (median 1 out of 5). The median understandability was moderate (median 69.6%), and actionability was moderate to poor (median 40%). Responses were presented at an advanced reading level (11th grade; median Flesch-Kincaid score 11.3). Conclusions: AI chatbots provide generally accurate information on kidney stones and lack misinformation; however, it is not easily actionable and is presented above the recommended reading level for consumer health information.
期刊介绍:
Journal of Endourology, JE Case Reports, and Videourology are the leading peer-reviewed journal, case reports publication, and innovative videojournal companion covering all aspects of minimally invasive urology research, applications, and clinical outcomes.
The leading journal of minimally invasive urology for over 30 years, Journal of Endourology is the essential publication for practicing surgeons who want to keep up with the latest surgical technologies in endoscopic, laparoscopic, robotic, and image-guided procedures as they apply to benign and malignant diseases of the genitourinary tract. This flagship journal includes the companion videojournal Videourology™ with every subscription. While Journal of Endourology remains focused on publishing rigorously peer reviewed articles, Videourology accepts original videos containing material that has not been reported elsewhere, except in the form of an abstract or a conference presentation.
Journal of Endourology coverage includes:
The latest laparoscopic, robotic, endoscopic, and image-guided techniques for treating both benign and malignant conditions
Pioneering research articles
Controversial cases in endourology
Techniques in endourology with accompanying videos
Reviews and epochs in endourology
Endourology survey section of endourology relevant manuscripts published in other journals.