Please use this identifier to cite or link to this item: http://hdl.handle.net/1843/54564
Type: Artigo de Periódico
Title: Chatbot as a telehealth intervention strategy in the COVID-19 pandemic: lessons learned from an action research approach
Authors: Bruno Azevedo Chagas
Antonio L. Ribeiro
Kícila Ferreguetti
Thiago C. Ferreira
Milena S. Marcolino
Leonardo B. Ribeiro
Adriana Silvina Pagano
Zilma S. N. Reis
Raquel O. Prates
Wagner Meira Jr.
Abstract: The COVID-19 pandemic and the need for social distancing have created a demand for new and innovative solutions in healthcare systems worldwide. One of the strategies that have been implemented are chatbots, which can be helpful in providing reliable health information and preventing people from seeking assistance in healthcare centers and being unnecessarily exposed to the virus. In this context, although a high number of chatbots have been implemented worldwide, little has been discussed about the process and challenges in developing and implementing this technology. This paper reports on an action research, which designed a novel chatbot as a prompt response to the COVID-19 pandemic. The chatbot is intended to be a first layer of interaction with the public, performing triage of patients and providing information about COVID-19 on a large scale and without human contact. Our contribution is twofold: (i) we reflected on the development process and discussed lessons learned and recommendations to support a multidisciplinary development and evolution process of the chatbot; and (ii) we identified some interactive and technological features that can be used as a reference framework for this kind of technology. These contributions can be useful to other researchers and multidisciplinary teams facing similar challenges.
Subject: Ciência da Computação
Saúde Coletiva
language: eng
metadata.dc.publisher.country: Brasil
Publisher: Universidade Federal de Minas Gerais
Publisher Initials: UFMG
metadata.dc.publisher.department: FALE - FACULDADE DE LETRAS
ICX - DEPARTAMENTO DE ESTATÍSTICA
MED - DEPARTAMENTO DE CLÍNICA MÉDICA
MED - DEPARTAMENTO DE GINECOLOGIA OBSTETRÍCIA
Rights: Acesso Aberto
metadata.dc.identifier.doi: https://doi.org/10.19153/cleiej.24.3.6
URI: http://hdl.handle.net/1843/54564
Issue Date: 13-Dec-2021
metadata.dc.relation.ispartof: CLEI Electronic Journal
Appears in Collections:Artigo de Periódico



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