General Characteristics and Design Taxonomy of Chatbots for COVID-19: Systematic Review
BackgroundA 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 pande...
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JMIR Publications,
2024-01-01T00:00:00Z.
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001 | doaj_34e0ba2c7fc54b43a73f988c7d201b5b | ||
042 | |a dc | ||
100 | 1 | 0 | |a Wendell Adrian Lim |e author |
700 | 1 | 0 | |a Razel Custodio |e author |
700 | 1 | 0 | |a Monica Sunga |e author |
700 | 1 | 0 | |a Abegail Jayne Amoranto |e author |
700 | 1 | 0 | |a Raymond Francis Sarmiento |e author |
245 | 0 | 0 | |a General Characteristics and Design Taxonomy of Chatbots for COVID-19: Systematic Review |
260 | |b JMIR Publications, |c 2024-01-01T00:00:00Z. | ||
500 | |a 1438-8871 | ||
500 | |a 10.2196/43112 | ||
520 | |a BackgroundA 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. ObjectiveThis study aims to describe the general characteristics of COVID-19 chatbots and examine their system designs using a modified adapted design taxonomy framework. MethodsWe 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. ResultsResults 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. ConclusionsThe 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. | ||
546 | |a EN | ||
690 | |a Computer applications to medicine. Medical informatics | ||
690 | |a R858-859.7 | ||
690 | |a Public aspects of medicine | ||
690 | |a RA1-1270 | ||
655 | 7 | |a article |2 local | |
786 | 0 | |n Journal of Medical Internet Research, Vol 26, p e43112 (2024) | |
787 | 0 | |n https://www.jmir.org/2024/1/e43112 | |
787 | 0 | |n https://doaj.org/toc/1438-8871 | |
856 | 4 | 1 | |u https://doaj.org/article/34e0ba2c7fc54b43a73f988c7d201b5b |z Connect to this object online. |