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患者在健康应用中与对话式代理的互动 2016-2022:系统回顾和荟萃分析。

Patient Engagement with Conversational Agents in Health Applications 2016-2022: A Systematic Review and Meta-Analysis.

机构信息

Department of Global and Community Health, George Mason University, 4400 University Dr., Fairfax, 22030, VA, USA.

Department of Health Administration and Policy, George Mason University, Fairfax, VA, USA.

出版信息

J Med Syst. 2024 Apr 10;48(1):40. doi: 10.1007/s10916-024-02059-x.

Abstract

Clinicians and patients seeking electronic health applications face challenges in selecting effective solutions due to a high market failure rate. Conversational agent applications ("chatbots") show promise in increasing healthcare user engagement by creating bonds between the applications and users. It is unclear if chatbots improve patient adherence or if past trends to include chatbots in electronic health applications were due to technology hype dynamics and competitive pressure to innovate. We conducted a systematic literature review using Preferred Reporting Items for Systematic reviews and Meta-Analyses methodology on health chatbot randomized control trials. The goal of this review was to identify if user engagement indicators are published in eHealth chatbot studies. A meta-analysis examined patient clinical trial retention of chatbot apps. The results showed no chatbot arm patient retention effect. The small number of studies suggests a need for ongoing eHealth chatbot research, especially given the claims regarding their effectiveness made outside the scientific literatures.

摘要

临床医生和寻求电子健康应用的患者面临挑战,因为市场高失败率导致难以选择有效的解决方案。对话代理应用程序(“聊天机器人”)通过在应用程序和用户之间建立联系,有望提高医疗保健用户的参与度。目前尚不清楚聊天机器人是否能提高患者的依从性,也不清楚过去在电子健康应用程序中引入聊天机器人的趋势是否是由于技术炒作动态和创新竞争压力所致。我们使用系统评价和荟萃分析方法进行了一项关于健康聊天机器人随机对照试验的系统文献综述。本综述的目的是确定用户参与指标是否在电子健康聊天机器人研究中发表。一项荟萃分析检查了聊天机器人应用程序的患者临床试验保留率。结果显示,聊天机器人组的患者保留效果并不显著。研究数量较少表明需要对电子健康聊天机器人进行持续研究,特别是考虑到科学文献之外对其有效性的相关声明。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/501c/11004048/23f9be8c87ab/10916_2024_2059_Fig1_HTML.jpg

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