Testing behaviour change with an artificial intelligence chatbot in a randomized controlled study.

IF 2.3 3区 医学 Q2 HEALTH CARE SCIENCES & SERVICES Journal of Public Health Policy Pub Date : 2024-09-01 Epub Date: 2024-07-26 DOI:10.1057/s41271-024-00500-6
Simon T van Baal, Suong T T Le, Farhad Fatehi, Antonio Verdejo-Garcia, Jakob Hohwy
{"title":"Testing behaviour change with an artificial intelligence chatbot in a randomized controlled study.","authors":"Simon T van Baal, Suong T T Le, Farhad Fatehi, Antonio Verdejo-Garcia, Jakob Hohwy","doi":"10.1057/s41271-024-00500-6","DOIUrl":null,"url":null,"abstract":"<p><p>Chatbots can effect large-scale behaviour change because they are accessible through social media, flexible, scalable, and gather data automatically. Yet research on the feasibility and effectiveness of chatbot-administered behaviour change interventions is sparse. The effectiveness of established behaviour change interventions when implemented in chatbots is not guaranteed, given the unique human-machine interaction dynamics. We pilot-tested chatbot-based behaviour change through information provision and embedded animations. We evaluated whether the chatbot could increase understanding and intentions to adopt protective behaviours during the pandemic. Fifty-nine culturally and linguistically diverse participants received a compassion intervention, an exponential growth intervention, or no intervention. We measured participants' COVID-19 testing intentions and measured their staying-home attitudes before and after their chatbot interaction. We found reduced uncertainty about protective behaviours. The exponential growth intervention increased participants' testing intentions. This study provides preliminary evidence that chatbots can spark behaviour change, with applications in diverse and underrepresented groups.</p>","PeriodicalId":50070,"journal":{"name":"Journal of Public Health Policy","volume":" ","pages":"506-522"},"PeriodicalIF":2.3000,"publicationDate":"2024-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"https://www.ncbi.nlm.nih.gov/pmc/articles/PMC11315670/pdf/","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Public Health Policy","FirstCategoryId":"3","ListUrlMain":"https://doi.org/10.1057/s41271-024-00500-6","RegionNum":3,"RegionCategory":"医学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"2024/7/26 0:00:00","PubModel":"Epub","JCR":"Q2","JCRName":"HEALTH CARE SCIENCES & SERVICES","Score":null,"Total":0}
引用次数: 0

Abstract

Chatbots can effect large-scale behaviour change because they are accessible through social media, flexible, scalable, and gather data automatically. Yet research on the feasibility and effectiveness of chatbot-administered behaviour change interventions is sparse. The effectiveness of established behaviour change interventions when implemented in chatbots is not guaranteed, given the unique human-machine interaction dynamics. We pilot-tested chatbot-based behaviour change through information provision and embedded animations. We evaluated whether the chatbot could increase understanding and intentions to adopt protective behaviours during the pandemic. Fifty-nine culturally and linguistically diverse participants received a compassion intervention, an exponential growth intervention, or no intervention. We measured participants' COVID-19 testing intentions and measured their staying-home attitudes before and after their chatbot interaction. We found reduced uncertainty about protective behaviours. The exponential growth intervention increased participants' testing intentions. This study provides preliminary evidence that chatbots can spark behaviour change, with applications in diverse and underrepresented groups.

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
在随机对照研究中测试人工智能聊天机器人的行为变化。
聊天机器人可以实现大规模的行为改变,因为它们可以通过社交媒体访问,灵活、可扩展,并能自动收集数据。然而,有关聊天机器人管理行为改变干预措施的可行性和有效性的研究还很少。鉴于独特的人机互动动力学,在聊天机器人中实施既有的行为改变干预措施的有效性无法保证。我们通过提供信息和嵌入动画对基于聊天机器人的行为改变进行了试点测试。我们评估了聊天机器人是否能在大流行期间提高人们对采取保护行为的理解和意愿。59 名不同文化和语言的参与者接受了同情干预、指数增长干预或无干预。我们测量了参与者的 COVID-19 测试意向,并在聊天机器人互动前后测量了他们的居家态度。我们发现,保护行为的不确定性降低了。指数增长干预增加了参与者的测试意愿。这项研究提供了初步证据,证明聊天机器人可以引发行为改变,并可应用于不同的和代表性不足的群体。
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
Journal of Public Health Policy
Journal of Public Health Policy 医学-公共卫生、环境卫生与职业卫生
CiteScore
5.70
自引率
2.60%
发文量
62
审稿时长
>12 weeks
期刊介绍: The Journal of Public Health Policy (JPHP) will continue its 35 year tradition: an accessible source of scholarly articles on the epidemiologic and social foundations of public health policy, rigorously edited, and progressive. JPHP aims to create a more inclusive public health policy dialogue, within nations and among them. It broadens public health policy debates beyond the ''health system'' to examine all forces and environments that impinge on the health of populations. It provides an exciting platform for airing controversy and framing policy debates - honing policies to solve new problems and unresolved old ones. JPHP welcomes unsolicited original scientific and policy contributions on all public health topics. New authors are particularly encouraged to enter debates about how to improve the health of populations and reduce health disparities.
期刊最新文献
COVID-19, migrants, and world large urban areas: a thematic policy brief. Global Public Health Association policies related to women, children and youth. Caregiver policies in the United States: a systematic review. COVID-19, social determinants, and African American-White disparities: policy response and pathways forward. State adoption of paid sick leave and cardiovascular disease mortality among adults in the United States, 2008-2019.
×
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