Population subgroup differences in the use of a COVID-19 chatbot

Abstract COVID-19 chatbots are widely used to screen for symptoms and disseminate information about the virus, yet little is known about the population subgroups that interact with this technology and the specific features that are used. An analysis of 1,000,740 patients invited to use a COVID-19 ch...

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Autores principales:	Laura C. Schubel, Deliya B. Wesley, Ethan Booker, John Lock, Raj M. Ratwani
Formato:	article
Lenguaje:	EN
Publicado:	Nature Portfolio 2021
Materias:	Computer applications to medicine. Medical informatics R858-859.7
Acceso en línea:	https://doaj.org/article/8888afdf17b949e99bbb7bb7fde4f83f
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spelling	oai:doaj.org-article:8888afdf17b949e99bbb7bb7fde4f83f2021-12-02T14:21:51ZPopulation subgroup differences in the use of a COVID-19 chatbot10.1038/s41746-021-00405-82398-6352https://doaj.org/article/8888afdf17b949e99bbb7bb7fde4f83f2021-02-01T00:00:00Zhttps://doi.org/10.1038/s41746-021-00405-8https://doaj.org/toc/2398-6352Abstract COVID-19 chatbots are widely used to screen for symptoms and disseminate information about the virus, yet little is known about the population subgroups that interact with this technology and the specific features that are used. An analysis of 1,000,740 patients invited to use a COVID-19 chatbot, 69,451 (6.94%) of which agreed to participate, shows differences in chatbot feature use by gender, race, and age. These results can inform future public health COVID-19 symptom screening and information dissemination strategies.Laura C. SchubelDeliya B. WesleyEthan BookerJohn LockRaj M. RatwaniNature PortfolioarticleComputer applications to medicine. Medical informaticsR858-859.7ENnpj Digital Medicine, Vol 4, Iss 1, Pp 1-3 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	Computer applications to medicine. Medical informatics R858-859.7
spellingShingle	Computer applications to medicine. Medical informatics R858-859.7 Laura C. Schubel Deliya B. Wesley Ethan Booker John Lock Raj M. Ratwani Population subgroup differences in the use of a COVID-19 chatbot
description	Abstract COVID-19 chatbots are widely used to screen for symptoms and disseminate information about the virus, yet little is known about the population subgroups that interact with this technology and the specific features that are used. An analysis of 1,000,740 patients invited to use a COVID-19 chatbot, 69,451 (6.94%) of which agreed to participate, shows differences in chatbot feature use by gender, race, and age. These results can inform future public health COVID-19 symptom screening and information dissemination strategies.
format	article
author	Laura C. Schubel Deliya B. Wesley Ethan Booker John Lock Raj M. Ratwani
author_facet	Laura C. Schubel Deliya B. Wesley Ethan Booker John Lock Raj M. Ratwani
author_sort	Laura C. Schubel
title	Population subgroup differences in the use of a COVID-19 chatbot
title_short	Population subgroup differences in the use of a COVID-19 chatbot
title_full	Population subgroup differences in the use of a COVID-19 chatbot
title_fullStr	Population subgroup differences in the use of a COVID-19 chatbot
title_full_unstemmed	Population subgroup differences in the use of a COVID-19 chatbot
title_sort	population subgroup differences in the use of a covid-19 chatbot
publisher	Nature Portfolio
publishDate	2021
url	https://doaj.org/article/8888afdf17b949e99bbb7bb7fde4f83f
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Population subgroup differences in the use of a COVID-19 chatbot

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