Suppr超能文献

一个旨在促进新冠疫苗接种的人工智能自然语言处理聊天机器人:一项概念验证性试点研究。

An artificially intelligent, natural language processing chatbot designed to promote COVID-19 vaccination: A proof-of-concept pilot study.

作者信息

Zhou Shuo, Silvasstar Joshva, Clark Christopher, Salyers Adam J, Chavez Catia, Bull Sheana S

机构信息

Department of Communication Studies, School of Communication and the System Health Lab, Hong Kong Baptist University, Hong Kong.

Department of Community and Behavioral Health and the mHealth Impact Lab, Colorado School of Public Health, Aurora, CO, USA.

出版信息

Digit Health. 2023 Mar 5;9:20552076231155679. doi: 10.1177/20552076231155679. eCollection 2023 Jan-Dec.

Abstract

OBJECTIVE

Our goal is to establish the feasibility of using an artificially intelligent chatbot in diverse healthcare settings to promote COVID-19 vaccination.

METHODS

We designed an artificially intelligent chatbot deployed via short message services and web-based platforms. Guided by communication theories, we developed persuasive messages to respond to users' COVID-19-related questions and encourage vaccination. We implemented the system in healthcare settings in the U.S. between April 2021 and March 2022 and logged the number of users, topics discussed, and information on system accuracy in matching responses to user intents. We regularly reviewed queries and reclassified responses to better match responses to query intents as COVID-19 events evolved.

RESULTS

A total of 2479 users engaged with the system, exchanging 3994 COVID-19 relevant messages. The most popular queries to the system were about boosters and where to get a vaccine. The system's accuracy rate in matching responses to user queries ranged from 54% to 91.1%. Accuracy lagged when new information related to COVID emerged, such as that related to the Delta variant. Accuracy increased when we added new content to the system.

CONCLUSIONS

It is feasible and potentially valuable to create chatbot systems using AI to facilitate access to current, accurate, complete, and persuasive information on infectious diseases. Such a system can be adapted to use with patients and populations needing detailed information and motivation to act in support of their health.

摘要

目的

我们的目标是确定在不同医疗环境中使用人工智能聊天机器人来促进新冠疫苗接种的可行性。

方法

我们设计了一个通过短信服务和基于网络的平台部署的人工智能聊天机器人。以沟通理论为指导,我们编写了有说服力的信息,以回应用户与新冠相关的问题并鼓励接种疫苗。我们于2021年4月至2022年3月在美国的医疗环境中实施了该系统,并记录了用户数量、讨论的话题以及系统在将回复与用户意图匹配方面的准确性信息。随着新冠事件的发展,我们定期审查查询并重新分类回复,以使回复更好地与查询意图匹配。

结果

共有2479名用户与该系统互动,交换了3994条与新冠相关的信息。对该系统最常见的查询是关于加强针以及在哪里可以接种疫苗。系统将回复与用户查询匹配的准确率在54%至91.1%之间。当出现与新冠相关的新信息(如与德尔塔变种相关的信息)时,准确率会滞后。当我们向系统添加新内容时,准确率会提高。

结论

使用人工智能创建聊天机器人系统以促进获取关于传染病的及时、准确、完整且有说服力的信息是可行的,且可能具有价值。这样的系统可以适用于需要详细信息和行动动机以支持其健康的患者和人群。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/10b9/9989411/9318f5eb6c1f/10.1177_20552076231155679-fig1.jpg

文献AI研究员

20分钟写一篇综述,助力文献阅读效率提升50倍。

立即体验

用中文搜PubMed

大模型驱动的PubMed中文搜索引擎

马上搜索

文档翻译

学术文献翻译模型,支持多种主流文档格式。

立即体验