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

被引:12
|
作者
Zhou, Shuo [1 ,2 ,6 ]
Silvasstar, Joshva [3 ,4 ]
Clark, Christopher [3 ,4 ,5 ]
Salyers, Adam J. [3 ,4 ]
Chavez, Catia [3 ,4 ]
Bull, Sheana S. [3 ,4 ]
机构
[1] Hong Kong Baptist Univ, Sch Commun, Dept Commun Studies, Hong Kong, Peoples R China
[2] Hong Kong Baptist Univ, Syst Hlth Lab, Hong Kong, Peoples R China
[3] Colorado Sch Publ Hlth, Dept Community & Behav Hlth, Aurora, CO USA
[4] Colorado Sch Publ Hlth, mHealth Impact Lab, Aurora, CO USA
[5] Univ Colorado Denver, Dept Math & Stat Sci, Denver, CO USA
[6] Hong Kong Baptist Univ, Dept Commun Studies, Syst Hlth Lab, Sch Commun,Kowloon Tong,Kowloon, 913 CVA Bldg,5 Hereford Rd, Hong Kong, Peoples R China
来源
DIGITAL HEALTH | 2023年 / 9卷
关键词
Artificial intelligent; chatbot; COVID-19; pandemic; vaccine hesitancy; feasibility; BEHAVIOR;
D O I
10.1177/20552076231155679
中图分类号
R19 [保健组织与事业(卫生事业管理)];
学科分类号
摘要
ObjectiveOur goal is to establish the feasibility of using an artificially intelligent chatbot in diverse healthcare settings to promote COVID-19 vaccination. MethodsWe 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. ResultsA 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. ConclusionsIt 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.
引用
收藏
页数:17
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