Using Large Language Models to Address Health Literacy in mHealth: Case Report.

IF 1.3 4区 医学 Q4 COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS Cin-Computers Informatics Nursing Pub Date : 2024-10-01 DOI:10.1097/CIN.0000000000001152
Elliot Loughran, Madison Kane, Tami H Wyatt, Alex Kerley, Sarah Lowe, Xueping Li
{"title":"Using Large Language Models to Address Health Literacy in mHealth: Case Report.","authors":"Elliot Loughran, Madison Kane, Tami H Wyatt, Alex Kerley, Sarah Lowe, Xueping Li","doi":"10.1097/CIN.0000000000001152","DOIUrl":null,"url":null,"abstract":"<p><p>The innate complexity of medical topics often makes it challenging to produce educational content for the public. Although there are resources available to help authors appraise the complexity of their content, there are woefully few resources available to help authors reduce that complexity after it occurs. In this case study, we evaluate using ChatGPT to reduce the complex language used in health-related educational materials. ChatGPT adapted content from the SmartSHOTS mobile application, which is geared toward caregivers of children aged 0 to 24 months. SmartSHOTS helps reduce barriers and improve adherence to vaccination schedules. ChatGPT reduced complex sentence structure and rewrote content to align with a third-grade reading level. Furthermore, using ChatGPT to edit content already written removes the potential for unnoticed, artificial intelligence-produced inaccuracies. As an editorial tool, ChatGPT was effective, efficient, and free to use. This article discusses the potential of ChatGPT as an effective, time-efficient, and open-source method for editing health-related educational materials to reflect a comprehendible reading level.</p>","PeriodicalId":50694,"journal":{"name":"Cin-Computers Informatics Nursing","volume":" ","pages":"696-703"},"PeriodicalIF":1.3000,"publicationDate":"2024-10-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Cin-Computers Informatics Nursing","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1097/CIN.0000000000001152","RegionNum":4,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"COMPUTER SCIENCE, INTERDISCIPLINARY APPLICATIONS","Score":null,"Total":0}
引用次数: 0

Abstract

The innate complexity of medical topics often makes it challenging to produce educational content for the public. Although there are resources available to help authors appraise the complexity of their content, there are woefully few resources available to help authors reduce that complexity after it occurs. In this case study, we evaluate using ChatGPT to reduce the complex language used in health-related educational materials. ChatGPT adapted content from the SmartSHOTS mobile application, which is geared toward caregivers of children aged 0 to 24 months. SmartSHOTS helps reduce barriers and improve adherence to vaccination schedules. ChatGPT reduced complex sentence structure and rewrote content to align with a third-grade reading level. Furthermore, using ChatGPT to edit content already written removes the potential for unnoticed, artificial intelligence-produced inaccuracies. As an editorial tool, ChatGPT was effective, efficient, and free to use. This article discusses the potential of ChatGPT as an effective, time-efficient, and open-source method for editing health-related educational materials to reflect a comprehendible reading level.

查看原文
分享 分享
微信好友 朋友圈 QQ好友 复制链接
本刊更多论文
使用大型语言模型解决移动医疗中的健康扫盲问题:案例报告。
医学主题与生俱来的复杂性往往使制作面向公众的教育内容具有挑战性。虽然有一些资源可以帮助作者评估其内容的复杂性,但很少有资源可以帮助作者在内容复杂化之后降低复杂性。在本案例研究中,我们对使用 ChatGPT 减少健康相关教育材料中的复杂语言进行了评估。ChatGPT 采用了 SmartSHOTS 移动应用程序的内容,该应用程序面向 0 到 24 个月大儿童的看护者。SmartSHOTS 有助于减少接种疫苗的障碍,提高接种疫苗的依从性。ChatGPT 减少了复杂的句子结构,并根据三年级的阅读水平重写了内容。此外,使用 ChatGPT 来编辑已撰写的内容还能消除人工智能产生的不准确内容。作为一种编辑工具,ChatGPT 是有效、高效和免费的。本文讨论了 ChatGPT 作为一种有效、省时、开源的编辑健康相关教育材料的方法的潜力,以反映可理解的阅读水平。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
求助全文
约1分钟内获得全文 去求助
来源期刊
Cin-Computers Informatics Nursing
Cin-Computers Informatics Nursing 工程技术-护理
CiteScore
2.00
自引率
15.40%
发文量
248
审稿时长
6-12 weeks
期刊介绍: For over 30 years, CIN: Computers, Informatics, Nursing has been at the interface of the science of information and the art of nursing, publishing articles on the latest developments in nursing informatics, research, education and administrative of health information technology. CIN connects you with colleagues as they share knowledge on implementation of electronic health records systems, design decision-support systems, incorporate evidence-based healthcare in practice, explore point-of-care computing in practice and education, and conceptually integrate nursing languages and standard data sets. Continuing education contact hours are available in every issue.
期刊最新文献
A Pilot Randomized Controlled Study to Determine the Effect of Real-Time Videos With Smart Glass on the Performance of the Cardiopulmonary Resuscitation. A Question Answering Chatbot for Gastric Cancer Patients After Curative Gastrectomy: Development and Evaluation of User Experience and Performance. Migrating Mobile Applications to the Web: Adult Crash Cart Training. Relationship Between Individual Innovativeness Levels and Attitudes Toward Artificial Intelligence Among Nursing and Midwifery Students. The Content, Reliability, and Quality of Insulin Pen Injection Videos on YouTube as Patient Education Resource.
×
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
现在去查看 取消
×
提示
确定
0
微信
客服QQ
Book学术公众号 扫码关注我们
反馈
×
意见反馈
请填写您的意见或建议
请填写您的手机或邮箱
已复制链接
已复制链接
快去分享给好友吧!
我知道了
×
扫码分享
扫码分享
Book学术官方微信
Book学术文献互助
Book学术文献互助群
群 号:481959085
Book学术
文献互助 智能选刊 最新文献 互助须知 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 Book学术 All rights reserved.
ghs 京公网安备 11010802042870号 京ICP备2023020795号-1