GPT-4生成准确且易读的患者教育材料,与当前肿瘤学指南一致:随机评估。

IF 2.6 3区 综合性期刊 Q1 MULTIDISCIPLINARY SCIENCES
PLoS ONE Pub Date : 2025-06-04 eCollection Date: 2025-01-01 DOI:10.1371/journal.pone.0324175
Severin Rodler, Francesco Cei, Conner Ganjavi, Enrico Checcucci, Pieter De Backer, Ines Rivero Belenchon, Mark Taratkin, Stefano Puliatti, Alessandro Veccia, Pietro Piazza, Loïc Baekelandt, Karl-Friedrich Kowalewski, Juan Gómez Rivas, Christian D Fankhauser, Marco Moschini, Giorgio Gandaglia, Riccardo Campi, Andre De Castro Abreu, Giorgio I Russo, Andrea Cocci, Serena Maruccia, Giovanni E Cacciamani
{"title":"GPT-4生成准确且易读的患者教育材料,与当前肿瘤学指南一致:随机评估。","authors":"Severin Rodler, Francesco Cei, Conner Ganjavi, Enrico Checcucci, Pieter De Backer, Ines Rivero Belenchon, Mark Taratkin, Stefano Puliatti, Alessandro Veccia, Pietro Piazza, Loïc Baekelandt, Karl-Friedrich Kowalewski, Juan Gómez Rivas, Christian D Fankhauser, Marco Moschini, Giorgio Gandaglia, Riccardo Campi, Andre De Castro Abreu, Giorgio I Russo, Andrea Cocci, Serena Maruccia, Giovanni E Cacciamani","doi":"10.1371/journal.pone.0324175","DOIUrl":null,"url":null,"abstract":"<p><strong>Introduction and aim: </strong>Guideline-based patient educational materials (PEMs) empower patients and reduce misinformation, but require frequent updates and must be adapted to the readability level of patients. The aim is to assess whether generative artificial intelligence (GenAI) can provide readable, accurate, and up-to-date PEMs that can be subsequently translated into multiple languages for broad dissemination.</p><p><strong>Study design and methods: </strong>The European Association of Urology (EAU) guidelines for prostate, bladder, kidney, and testicular cancer were used as the knowledge base for GPT-4 to generate PEMs. Additionally, the PEMs were translated into five commonly spoken languages within the European Union (EU). The study was conducted through a single-blinded, online randomized assessment survey. After an initial pilot assessment of the GenAI-generated PEMs, thirty-two members of the Young Academic Urologists (YAU) groups evaluated the accuracy, completeness, and clarity of the original versus GPT-generated PEMs. The translation assessment involved two native speakers from different YAU groups for each language: Dutch, French, German, Italian, and Spanish. The primary outcomes were readability, accuracy, completeness, faithfulness, and clarity. Readability was measured using Flesch Kincaid Reading Ease (FKRE), Flesch Kincaid Grade Level (FKGL), Gunning Fog (GFS) scores and Smog (SI), Coleman Liau (CLI), Automated Readability (ARI) indexes. Accuracy, completeness, faithfulness, and clarity were rated on a 5-item Likert scale.</p><p><strong>Results: </strong>The mean time to create layperson PEMs based on the latest guideline by GPT-4 was 52.1 seconds. The readability scores for the 8 original PEMs were lower than for the 8 GPT-4-generated PEMs (Mean FKRE: 43.5 vs. 70.8; p < .001). The required reading education levels were higher for original PEMs compared to GPT-4 generated PEMs (Mean FKGL: 11.6 vs. 6.1; p < .001). For all urological localized cancers, the original PEMs were not significantly different from the GPT-4 generated PEMs in accuracy, completeness, and clarity. Similarly, no differences were observed for metastatic cancers. Translations of GPT-generated PEMs were rated as faithful in 77.5% of cases and clear in 67.5% of cases.</p><p><strong>Conclusions and relevance: </strong>GPT-4 generated PEMs have better readability levels compared to original PEMs while maintaining similar accuracy, completeness, and clarity. The use of GenAI's information extraction and language capabilities, integrated with human oversight, can significantly reduce the workload and ensure up-to-date and accurate PEMs.</p><p><strong>Patient summary: </strong>Some cancer facts made for patients can be hard to read or not in the right words for those with prostate, bladder, kidney, or testicular cancer. This study used AI to quickly make short and easy-to-read content from trusted facts. Doctors checked the AI content and found that they were just as accurate, complete, and clear as the original text made for patients. They also worked well in many languages. This AI tool can assist providers in making it easier for patients to understand their cancer and the best care they can get.</p>","PeriodicalId":20189,"journal":{"name":"PLoS ONE","volume":"20 6","pages":"e0324175"},"PeriodicalIF":2.6000,"publicationDate":"2025-06-04","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12136319/pdf/","citationCount":"0","resultStr":"{\"title\":\"GPT-4 generates accurate and readable patient education materials aligned with current oncological guidelines: A randomized assessment.\",\"authors\":\"Severin Rodler, Francesco Cei, Conner Ganjavi, Enrico Checcucci, Pieter De Backer, Ines Rivero Belenchon, Mark Taratkin, Stefano Puliatti, Alessandro Veccia, Pietro Piazza, Loïc Baekelandt, Karl-Friedrich Kowalewski, Juan Gómez Rivas, Christian D Fankhauser, Marco Moschini, Giorgio Gandaglia, Riccardo Campi, Andre De Castro Abreu, Giorgio I Russo, Andrea Cocci, Serena Maruccia, Giovanni E Cacciamani\",\"doi\":\"10.1371/journal.pone.0324175\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<p><strong>Introduction and aim: </strong>Guideline-based patient educational materials (PEMs) empower patients and reduce misinformation, but require frequent updates and must be adapted to the readability level of patients. The aim is to assess whether generative artificial intelligence (GenAI) can provide readable, accurate, and up-to-date PEMs that can be subsequently translated into multiple languages for broad dissemination.</p><p><strong>Study design and methods: </strong>The European Association of Urology (EAU) guidelines for prostate, bladder, kidney, and testicular cancer were used as the knowledge base for GPT-4 to generate PEMs. Additionally, the PEMs were translated into five commonly spoken languages within the European Union (EU). The study was conducted through a single-blinded, online randomized assessment survey. After an initial pilot assessment of the GenAI-generated PEMs, thirty-two members of the Young Academic Urologists (YAU) groups evaluated the accuracy, completeness, and clarity of the original versus GPT-generated PEMs. The translation assessment involved two native speakers from different YAU groups for each language: Dutch, French, German, Italian, and Spanish. The primary outcomes were readability, accuracy, completeness, faithfulness, and clarity. Readability was measured using Flesch Kincaid Reading Ease (FKRE), Flesch Kincaid Grade Level (FKGL), Gunning Fog (GFS) scores and Smog (SI), Coleman Liau (CLI), Automated Readability (ARI) indexes. Accuracy, completeness, faithfulness, and clarity were rated on a 5-item Likert scale.</p><p><strong>Results: </strong>The mean time to create layperson PEMs based on the latest guideline by GPT-4 was 52.1 seconds. The readability scores for the 8 original PEMs were lower than for the 8 GPT-4-generated PEMs (Mean FKRE: 43.5 vs. 70.8; p < .001). The required reading education levels were higher for original PEMs compared to GPT-4 generated PEMs (Mean FKGL: 11.6 vs. 6.1; p < .001). For all urological localized cancers, the original PEMs were not significantly different from the GPT-4 generated PEMs in accuracy, completeness, and clarity. Similarly, no differences were observed for metastatic cancers. Translations of GPT-generated PEMs were rated as faithful in 77.5% of cases and clear in 67.5% of cases.</p><p><strong>Conclusions and relevance: </strong>GPT-4 generated PEMs have better readability levels compared to original PEMs while maintaining similar accuracy, completeness, and clarity. The use of GenAI's information extraction and language capabilities, integrated with human oversight, can significantly reduce the workload and ensure up-to-date and accurate PEMs.</p><p><strong>Patient summary: </strong>Some cancer facts made for patients can be hard to read or not in the right words for those with prostate, bladder, kidney, or testicular cancer. This study used AI to quickly make short and easy-to-read content from trusted facts. Doctors checked the AI content and found that they were just as accurate, complete, and clear as the original text made for patients. They also worked well in many languages. This AI tool can assist providers in making it easier for patients to understand their cancer and the best care they can get.</p>\",\"PeriodicalId\":20189,\"journal\":{\"name\":\"PLoS ONE\",\"volume\":\"20 6\",\"pages\":\"e0324175\"},\"PeriodicalIF\":2.6000,\"publicationDate\":\"2025-06-04\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC12136319/pdf/\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"PLoS ONE\",\"FirstCategoryId\":\"103\",\"ListUrlMain\":\"https://doi.org/10.1371/journal.pone.0324175\",\"RegionNum\":3,\"RegionCategory\":\"综合性期刊\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"2025/1/1 0:00:00\",\"PubModel\":\"eCollection\",\"JCR\":\"Q1\",\"JCRName\":\"MULTIDISCIPLINARY SCIENCES\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"PLoS ONE","FirstCategoryId":"103","ListUrlMain":"https://doi.org/10.1371/journal.pone.0324175","RegionNum":3,"RegionCategory":"综合性期刊","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2025/1/1 0:00:00","PubModel":"eCollection","JCR":"Q1","JCRName":"MULTIDISCIPLINARY SCIENCES","Score":null,"Total":0}
引用次数: 0

摘要

介绍和目的:基于指南的患者教育材料(PEMs)赋予患者权力,减少错误信息,但需要经常更新,必须适应患者的可读性水平。目的是评估生成式人工智能(GenAI)是否能够提供可读、准确和最新的PEMs,这些PEMs随后可以翻译成多种语言以广泛传播。研究设计和方法:采用欧洲泌尿外科协会(EAU)前列腺癌、膀胱癌、肾癌和睾丸癌指南作为GPT-4生成PEMs的知识库。此外,这些文件还被翻译成欧洲联盟(欧盟)内常用的五种语言。该研究通过单盲、在线随机评估调查进行。在对genai生成的PEMs进行初步试点评估后,青年学术泌尿科医师(YAU)小组的32名成员评估了原始PEMs与gpt生成的PEMs的准确性、完整性和清晰度。翻译评估涉及两名来自不同语言群体的母语人士:荷兰语、法语、德语、意大利语和西班牙语。主要结果为可读性、准确性、完整性、可靠性和清晰度。可读性采用Flesch Kincaid Reading Ease (FKRE)、Flesch Kincaid Grade Level (FKGL)、Gunning Fog (GFS)评分和Smog (SI)、Coleman Liau (CLI)、Automated Readability (ARI)指数进行测量。准确性、完整性、信誉度和清晰度以5项李克特量表评定。结果:根据最新GPT-4指南制作外行人pms的平均时间为52.1 s。8个原始PEMs的可读性得分低于8个gpt -4生成的PEMs(平均FKRE: 43.5 vs. 70.8;p结论和相关性:GPT-4生成的PEMs与原始PEMs相比具有更好的可读性水平,同时保持了相似的准确性、完整性和清晰度。使用GenAI的信息提取和语言能力,结合人工监督,可以显著减少工作量,并确保最新和准确的PEMs。患者总结:对于前列腺癌、膀胱癌、肾癌或睾丸癌患者来说,一些癌症事实可能很难读懂,或者用不合适的词语。这项研究利用人工智能从可信的事实中快速制作出简短易读的内容。医生检查了人工智能的内容,发现它们和为患者制作的原始文本一样准确、完整、清晰。它们在许多语言中也很好用。这种人工智能工具可以帮助提供者更容易地让患者了解自己的癌症,并得到最好的治疗。
本文章由计算机程序翻译,如有差异,请以英文原文为准。

GPT-4 generates accurate and readable patient education materials aligned with current oncological guidelines: A randomized assessment.

GPT-4 generates accurate and readable patient education materials aligned with current oncological guidelines: A randomized assessment.

GPT-4 generates accurate and readable patient education materials aligned with current oncological guidelines: A randomized assessment.

GPT-4 generates accurate and readable patient education materials aligned with current oncological guidelines: A randomized assessment.

Introduction and aim: Guideline-based patient educational materials (PEMs) empower patients and reduce misinformation, but require frequent updates and must be adapted to the readability level of patients. The aim is to assess whether generative artificial intelligence (GenAI) can provide readable, accurate, and up-to-date PEMs that can be subsequently translated into multiple languages for broad dissemination.

Study design and methods: The European Association of Urology (EAU) guidelines for prostate, bladder, kidney, and testicular cancer were used as the knowledge base for GPT-4 to generate PEMs. Additionally, the PEMs were translated into five commonly spoken languages within the European Union (EU). The study was conducted through a single-blinded, online randomized assessment survey. After an initial pilot assessment of the GenAI-generated PEMs, thirty-two members of the Young Academic Urologists (YAU) groups evaluated the accuracy, completeness, and clarity of the original versus GPT-generated PEMs. The translation assessment involved two native speakers from different YAU groups for each language: Dutch, French, German, Italian, and Spanish. The primary outcomes were readability, accuracy, completeness, faithfulness, and clarity. Readability was measured using Flesch Kincaid Reading Ease (FKRE), Flesch Kincaid Grade Level (FKGL), Gunning Fog (GFS) scores and Smog (SI), Coleman Liau (CLI), Automated Readability (ARI) indexes. Accuracy, completeness, faithfulness, and clarity were rated on a 5-item Likert scale.

Results: The mean time to create layperson PEMs based on the latest guideline by GPT-4 was 52.1 seconds. The readability scores for the 8 original PEMs were lower than for the 8 GPT-4-generated PEMs (Mean FKRE: 43.5 vs. 70.8; p < .001). The required reading education levels were higher for original PEMs compared to GPT-4 generated PEMs (Mean FKGL: 11.6 vs. 6.1; p < .001). For all urological localized cancers, the original PEMs were not significantly different from the GPT-4 generated PEMs in accuracy, completeness, and clarity. Similarly, no differences were observed for metastatic cancers. Translations of GPT-generated PEMs were rated as faithful in 77.5% of cases and clear in 67.5% of cases.

Conclusions and relevance: GPT-4 generated PEMs have better readability levels compared to original PEMs while maintaining similar accuracy, completeness, and clarity. The use of GenAI's information extraction and language capabilities, integrated with human oversight, can significantly reduce the workload and ensure up-to-date and accurate PEMs.

Patient summary: Some cancer facts made for patients can be hard to read or not in the right words for those with prostate, bladder, kidney, or testicular cancer. This study used AI to quickly make short and easy-to-read content from trusted facts. Doctors checked the AI content and found that they were just as accurate, complete, and clear as the original text made for patients. They also worked well in many languages. This AI tool can assist providers in making it easier for patients to understand their cancer and the best care they can get.

求助全文
通过发布文献求助,成功后即可免费获取论文全文。 去求助
来源期刊
PLoS ONE
PLoS ONE 生物-生物学
CiteScore
6.20
自引率
5.40%
发文量
14242
审稿时长
3.7 months
期刊介绍: PLOS ONE is an international, peer-reviewed, open-access, online publication. PLOS ONE welcomes reports on primary research from any scientific discipline. It provides: * Open-access—freely accessible online, authors retain copyright * Fast publication times * Peer review by expert, practicing researchers * Post-publication tools to indicate quality and impact * Community-based dialogue on articles * Worldwide media coverage
×
引用
GB/T 7714-2015
复制
MLA
复制
APA
复制
导出至
BibTeX EndNote RefMan NoteFirst NoteExpress
×
提示
您的信息不完整,为了账户安全,请先补充。
现在去补充
×
提示
您因"违规操作"
具体请查看互助需知
我知道了
×
提示
确定
请完成安全验证×
copy
已复制链接
快去分享给好友吧!
我知道了
右上角分享
点击右上角分享
0
联系我们:info@booksci.cn Book学术提供免费学术资源搜索服务,方便国内外学者检索中英文文献。致力于提供最便捷和优质的服务体验。 Copyright © 2023 布克学术 All rights reserved.
京ICP备2023020795号-1
ghs 京公网安备 11010802042870号
Book学术文献互助
Book学术文献互助群
群 号:604180095
Book学术官方微信