{"title":"聊天机器人健康咨询研究报告指南:聊天机器人评估报告工具(图表)声明。","authors":"","doi":"10.1370/afm.250386","DOIUrl":null,"url":null,"abstract":"<p><p>The Chatbot Assessment Reporting Tool (CHART) is a reporting guideline developed to provide reporting recommendations for studies evaluating the performance of chatbots driven by generative artificial intelligence when summarizing clinical evidence and providing health advice, referred to as chatbot health advice studies. CHART was developed in several phases after performing a comprehensive systematic review to identify variation in the conduct, reporting, and method in chatbot health advice studies. Findings from the review were used to develop a draft checklist that was revised through an international, multidisciplinary, modified, asynchronous Delphi consensus process of 531 stakeholders, 3 synchronous panel consensus meetings of 48 stakeholders, and subsequent pilot testing of the checklist. CHART includes 12 items and 39 subitems to promote transparent and comprehensive reporting of chatbot health advice studies. These include title (subitem 1a), abstract/summary (subitem 1b), background (subitems 2a,b), model identifiers (subitems 3a,b), model details (subitems 4a-c), prompt engineering (subitems 5a,b), query strategy (subitems 6a-d), performance evaluation (subitems 7a,b), sample size (subitem 8), data analysis (subitem 9a), results (subitems 10a-c), discussion (subitems 11a-c), disclosures (subitem 12a), funding (subitem 12b), ethics (subitem 12c), protocol (subitem 12d), and data availability (subitem 12e). The CHART checklist and corresponding diagram of the method were designed to support key stakeholders including clinicians, researchers, editors, peer reviewers, and readers in reporting, understanding, and interpreting the findings of chatbot health advice studies. KEY MESSAGES: CHART was developed by performing a systematic review, Delphi consensus of 531 international stakeholders, and several consensus meetings among an expert panel comprised of 48 membersThe CHART statement outlines 12 key reporting items for chatbot health advice studies in the form of a checklist and methodological diagramAll stakeholders including clinicians, researchers, and journal editors should encourage the transparent reporting of chatbot health advice studies.</p>","PeriodicalId":50973,"journal":{"name":"Annals of Family Medicine","volume":" ","pages":"389-398"},"PeriodicalIF":5.1000,"publicationDate":"2025-09-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12459699/pdf/","citationCount":"0","resultStr":"{\"title\":\"Reporting Guideline for Chatbot Health Advice Studies: Chatbot Assessment Reporting Tool (CHART) Statement.\",\"authors\":\"\",\"doi\":\"10.1370/afm.250386\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><p>The Chatbot Assessment Reporting Tool (CHART) is a reporting guideline developed to provide reporting recommendations for studies evaluating the performance of chatbots driven by generative artificial intelligence when summarizing clinical evidence and providing health advice, referred to as chatbot health advice studies. CHART was developed in several phases after performing a comprehensive systematic review to identify variation in the conduct, reporting, and method in chatbot health advice studies. Findings from the review were used to develop a draft checklist that was revised through an international, multidisciplinary, modified, asynchronous Delphi consensus process of 531 stakeholders, 3 synchronous panel consensus meetings of 48 stakeholders, and subsequent pilot testing of the checklist. CHART includes 12 items and 39 subitems to promote transparent and comprehensive reporting of chatbot health advice studies. These include title (subitem 1a), abstract/summary (subitem 1b), background (subitems 2a,b), model identifiers (subitems 3a,b), model details (subitems 4a-c), prompt engineering (subitems 5a,b), query strategy (subitems 6a-d), performance evaluation (subitems 7a,b), sample size (subitem 8), data analysis (subitem 9a), results (subitems 10a-c), discussion (subitems 11a-c), disclosures (subitem 12a), funding (subitem 12b), ethics (subitem 12c), protocol (subitem 12d), and data availability (subitem 12e). The CHART checklist and corresponding diagram of the method were designed to support key stakeholders including clinicians, researchers, editors, peer reviewers, and readers in reporting, understanding, and interpreting the findings of chatbot health advice studies. KEY MESSAGES: CHART was developed by performing a systematic review, Delphi consensus of 531 international stakeholders, and several consensus meetings among an expert panel comprised of 48 membersThe CHART statement outlines 12 key reporting items for chatbot health advice studies in the form of a checklist and methodological diagramAll stakeholders including clinicians, researchers, and journal editors should encourage the transparent reporting of chatbot health advice studies.</p>\",\"PeriodicalId\":50973,\"journal\":{\"name\":\"Annals of Family Medicine\",\"volume\":\" \",\"pages\":\"389-398\"},\"PeriodicalIF\":5.1000,\"publicationDate\":\"2025-09-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12459699/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Annals of Family Medicine\",\"FirstCategoryId\":\"3\",\"ListUrlMain\":\"https://doi.org/10.1370/afm.250386\",\"RegionNum\":2,\"RegionCategory\":\"医学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"MEDICINE, GENERAL & INTERNAL\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Annals of Family Medicine","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1370/afm.250386","RegionNum":2,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"MEDICINE, GENERAL & INTERNAL","Score":null,"Total":0}
Reporting Guideline for Chatbot Health Advice Studies: Chatbot Assessment Reporting Tool (CHART) Statement.
The Chatbot Assessment Reporting Tool (CHART) is a reporting guideline developed to provide reporting recommendations for studies evaluating the performance of chatbots driven by generative artificial intelligence when summarizing clinical evidence and providing health advice, referred to as chatbot health advice studies. CHART was developed in several phases after performing a comprehensive systematic review to identify variation in the conduct, reporting, and method in chatbot health advice studies. Findings from the review were used to develop a draft checklist that was revised through an international, multidisciplinary, modified, asynchronous Delphi consensus process of 531 stakeholders, 3 synchronous panel consensus meetings of 48 stakeholders, and subsequent pilot testing of the checklist. CHART includes 12 items and 39 subitems to promote transparent and comprehensive reporting of chatbot health advice studies. These include title (subitem 1a), abstract/summary (subitem 1b), background (subitems 2a,b), model identifiers (subitems 3a,b), model details (subitems 4a-c), prompt engineering (subitems 5a,b), query strategy (subitems 6a-d), performance evaluation (subitems 7a,b), sample size (subitem 8), data analysis (subitem 9a), results (subitems 10a-c), discussion (subitems 11a-c), disclosures (subitem 12a), funding (subitem 12b), ethics (subitem 12c), protocol (subitem 12d), and data availability (subitem 12e). The CHART checklist and corresponding diagram of the method were designed to support key stakeholders including clinicians, researchers, editors, peer reviewers, and readers in reporting, understanding, and interpreting the findings of chatbot health advice studies. KEY MESSAGES: CHART was developed by performing a systematic review, Delphi consensus of 531 international stakeholders, and several consensus meetings among an expert panel comprised of 48 membersThe CHART statement outlines 12 key reporting items for chatbot health advice studies in the form of a checklist and methodological diagramAll stakeholders including clinicians, researchers, and journal editors should encourage the transparent reporting of chatbot health advice studies.
期刊介绍:
The Annals of Family Medicine is a peer-reviewed research journal to meet the needs of scientists, practitioners, policymakers, and the patients and communities they serve.