%0 Journal Article
%@ 1438-8871
%I JMIR Publications
%V 26
%N 
%P e43112
%T General Characteristics and Design Taxonomy of Chatbots for COVID-19: Systematic Review
%A Lim,Wendell Adrian
%A Custodio,Razel
%A Sunga,Monica
%A Amoranto,Abegail Jayne
%A Sarmiento,Raymond Francis
%+ National Telehealth Center, National Institutes of Health, University of the Philippines Manila, 670 Padre Faura Street, Ermita, Manila, 1000, Philippines, 63 9269819254, wolim@up.edu.ph
%K COVID-19
%K health chatbot
%K conversational agent in health care
%K artificial intelligence
%K systematic review
%K mobile phone
%D 2024
%7 5.1.2024
%9 Review
%J J Med Internet Res
%G English
%X Background: A conversational agent powered by artificial intelligence, commonly known as a chatbot, is one of the most recent innovations used to provide information and services during the COVID-19 pandemic. However, the multitude of conversational agents explicitly designed during the COVID-19 pandemic calls for characterization and analysis using rigorous technological frameworks and extensive systematic reviews. Objective: This study aims to describe the general characteristics of COVID-19 chatbots and examine their system designs using a modified adapted design taxonomy framework. Methods: We conducted a systematic review of the general characteristics and design taxonomy of COVID-19 chatbots, with 56 studies included in the final analysis. This review followed the PRISMA (Preferred Reporting Items for Systematic Reviews and Meta-Analyses) guidelines to select papers published between March 2020 and April 2022 from various databases and search engines. Results: Results showed that most studies on COVID-19 chatbot design and development worldwide are implemented in Asia and Europe. Most chatbots are also accessible on websites, internet messaging apps, and Android devices. The COVID-19 chatbots are further classified according to their temporal profiles, appearance, intelligence, interaction, and context for system design trends. From the temporal profile perspective, almost half of the COVID-19 chatbots interact with users for several weeks for >1 time and can remember information from previous user interactions. From the appearance perspective, most COVID-19 chatbots assume the expert role, are task oriented, and have no visual or avatar representation. From the intelligence perspective, almost half of the COVID-19 chatbots are artificially intelligent and can respond to textual inputs and a set of rules. In addition, more than half of these chatbots operate on a structured flow and do not portray any socioemotional behavior. Most chatbots can also process external data and broadcast resources. Regarding their interaction with users, most COVID-19 chatbots are adaptive, can communicate through text, can react to user input, are not gamified, and do not require additional human support. From the context perspective, all COVID-19 chatbots are goal oriented, although most fall under the health care application domain and are designed to provide information to the user. Conclusions: The conceptualization, development, implementation, and use of COVID-19 chatbots emerged to mitigate the effects of a global pandemic in societies worldwide. This study summarized the current system design trends of COVID-19 chatbots based on 5 design perspectives, which may help developers conveniently choose a future-proof chatbot archetype that will meet the needs of the public in the face of growing demand for a better pandemic response. 
%M 38064638
%R 10.2196/43112
%U https://www.jmir.org/2024/1/e43112
%U https://doi.org/10.2196/43112
%U http://www.ncbi.nlm.nih.gov/pubmed/38064638