Evaluating user experience with a chatbot designed as a public health response to the Covid-19 pandemic in Brazil: a mixed-methods study

Detalhes bibliográficos
Autor(a) principal: Bruno Azevedo Chagas
Data de Publicação: 2022
Outros Autores: Thais Marques Pedroso, Alline Beleigoli, Clara Rodrigues Alves Oliveira, Milena Soriano Marcolino, Adriana Silvina Pagano, Raquel Oliveira Prates, Elisa Cordeiro Praes, Kícila Ferreguetti, Helena Vaz, Zilma Silveira Nogueira Reis, Leonardo Bonisson Ribeiro, Antonio Luiz Pinho Ribeiro
Tipo de documento: Artigo
Idioma: eng
Título da fonte: Repositório Institucional da UFMG
Texto Completo: https://doi.org/10.2196/43135
http://hdl.handle.net/1843/65887
https://orcid.org/0000-0002-8571-3135
https://orcid.org/0000-0003-0149-9731
https://orcid.org/0000-0002-7848-3183
https://orcid.org/0000-0002-9437-2344
https://orcid.org/0000-0003-4278-3771
https://orcid.org/0000-0002-3150-3503
https://orcid.org/0000-0002-7128-4974
https://orcid.org/0000-0001-6495-993X
https://orcid.org/0000-0002-1919-0073
https://orcid.org/0000-0001-6374-9295
https://orcid.org/0000-0001-9035-0722
https://orcid.org/0000-0002-0364-3584
Resumo: Background: The potential of chatbots for screening and monitoring COVID-19 was envisioned since the outbreak of the disease. Chatbots can help disseminate up-to-date and trustworthy information, promote healthy social behavior, and support the provision of health care services safely and at scale. In this scenario and in view of its far-reaching postpandemic impact, it is important to evaluate user experience with this kind of application. Objective: We aimed to evaluate the quality of user experience with a COVID-19 chatbot designed by a large telehealth service in Brazil, focusing on the usability of real users and the exploration of strengths and shortcomings of the chatbot, as revealed in reports by participants in simulated scenarios. Methods: We examined a chatbot developed by a multidisciplinary team and used it as a component within the workflow of a local public health care service. The chatbot had 2 core functionalities: assisting web-based screening of COVID-19 symptom severity and providing evidence-based information to the population. From October 2020 to January 2021, we conducted a mixed methods approach and performed a 2-fold evaluation of user experience with our chatbot by following 2 methods: a posttask usability Likert-scale survey presented to all users after concluding their interaction with the bot and an interview with volunteer participants who engaged in a simulated interaction with the bot guided by the interviewer. Results: Usability assessment with 63 users revealed very good scores for chatbot usefulness (4.57), likelihood of being recommended (4.48), ease of use (4.44), and user satisfaction (4.38). Interviews with 15 volunteers provided insights into the strengths and shortcomings of our bot. Comments on the positive aspects and problems reported by users were analyzed in terms of recurrent themes. We identified 6 positive aspects and 15 issues organized in 2 categories: usability of the chatbot and health support offered by it, the former referring to usability of the chatbot and how users can interact with it and the latter referring to the chatbot’s goal in supporting people during the pandemic through the screening process and education to users through informative content. We found 6 themes accounting for what people liked most about our chatbot and why they found it useful—3 themes pertaining to the usability domain and 3 themes regarding health support. Our findings also identified 15 types of problems producing a negative impact on users—10 of them related to the usability of the chatbot and 5 related to the health support it provides. Conclusions: Our results indicate that users had an overall positive experience with the chatbot and found the health support relevant. Nonetheless, qualitative evaluation of the chatbot indicated challenges and directions to be pursued in improving not only our COVID-19 chatbot but also health chatbots in general.
id UFMG_4af9beac193c17fc33ecfad1f80100b8
oai_identifier_str oai:repositorio.ufmg.br:1843/65887
network_acronym_str UFMG
network_name_str Repositório Institucional da UFMG
repository_id_str
spelling 2024-03-14T22:21:18Z2024-03-14T22:21:18Z2022-09-3010116https://doi.org/10.2196/431352292-9495http://hdl.handle.net/1843/65887https://orcid.org/0000-0002-8571-3135https://orcid.org/0000-0003-0149-9731https://orcid.org/0000-0002-7848-3183https://orcid.org/0000-0002-9437-2344https://orcid.org/0000-0003-4278-3771https://orcid.org/0000-0002-3150-3503https://orcid.org/0000-0002-7128-4974https://orcid.org/0000-0001-6495-993Xhttps://orcid.org/0000-0002-1919-0073https://orcid.org/0000-0001-6374-9295https://orcid.org/0000-0001-9035-0722https://orcid.org/0000-0002-0364-3584Background: The potential of chatbots for screening and monitoring COVID-19 was envisioned since the outbreak of the disease. Chatbots can help disseminate up-to-date and trustworthy information, promote healthy social behavior, and support the provision of health care services safely and at scale. In this scenario and in view of its far-reaching postpandemic impact, it is important to evaluate user experience with this kind of application. Objective: We aimed to evaluate the quality of user experience with a COVID-19 chatbot designed by a large telehealth service in Brazil, focusing on the usability of real users and the exploration of strengths and shortcomings of the chatbot, as revealed in reports by participants in simulated scenarios. Methods: We examined a chatbot developed by a multidisciplinary team and used it as a component within the workflow of a local public health care service. The chatbot had 2 core functionalities: assisting web-based screening of COVID-19 symptom severity and providing evidence-based information to the population. From October 2020 to January 2021, we conducted a mixed methods approach and performed a 2-fold evaluation of user experience with our chatbot by following 2 methods: a posttask usability Likert-scale survey presented to all users after concluding their interaction with the bot and an interview with volunteer participants who engaged in a simulated interaction with the bot guided by the interviewer. Results: Usability assessment with 63 users revealed very good scores for chatbot usefulness (4.57), likelihood of being recommended (4.48), ease of use (4.44), and user satisfaction (4.38). Interviews with 15 volunteers provided insights into the strengths and shortcomings of our bot. Comments on the positive aspects and problems reported by users were analyzed in terms of recurrent themes. We identified 6 positive aspects and 15 issues organized in 2 categories: usability of the chatbot and health support offered by it, the former referring to usability of the chatbot and how users can interact with it and the latter referring to the chatbot’s goal in supporting people during the pandemic through the screening process and education to users through informative content. We found 6 themes accounting for what people liked most about our chatbot and why they found it useful—3 themes pertaining to the usability domain and 3 themes regarding health support. Our findings also identified 15 types of problems producing a negative impact on users—10 of them related to the usability of the chatbot and 5 related to the health support it provides. Conclusions: Our results indicate that users had an overall positive experience with the chatbot and found the health support relevant. Nonetheless, qualitative evaluation of the chatbot indicated challenges and directions to be pursued in improving not only our COVID-19 chatbot but also health chatbots in general.engUniversidade Federal de Minas GeraisUFMGBrasilFALE - FACULDADE DE LETRASICX - DEPARTAMENTO DE CIÊNCIA DA COMPUTAÇÃOMED - DEPARTAMENTO DE CLÍNICA MÉDICAJMIR Hum FactorsInteração homem-máquinaCuidados médicosTelemática médicaTelecomunicação em medicinaUser experienceChatbotsTelehealthCOVID-19Human-computer interactionHCIEmpirical studies in human-computer interactionEmpirical studies in HCIHealth care information systemsEvaluating user experience with a chatbot designed as a public health response to the Covid-19 pandemic in Brazil: a mixed-methods studyinfo:eu-repo/semantics/publishedVersioninfo:eu-repo/semantics/articleBruno Azevedo ChagasThais Marques PedrosoAlline BeleigoliClara Rodrigues Alves OliveiraMilena Soriano MarcolinoAdriana Silvina PaganoRaquel Oliveira PratesElisa Cordeiro PraesKícila FerreguettiHelena VazZilma Silveira Nogueira ReisLeonardo Bonisson RibeiroAntonio Luiz Pinho Ribeiroapplication/pdfinfo:eu-repo/semantics/openAccessreponame:Repositório Institucional da UFMGinstname:Universidade Federal de Minas Gerais (UFMG)instacron:UFMGLICENSELicense.txtLicense.txttext/plain; charset=utf-82042https://repositorio.ufmg.br/bitstream/1843/65887/1/License.txtfa505098d172de0bc8864fc1287ffe22MD51ORIGINALEvaluating user experience with a chatbot designed as a public health response to the Covid-19 pandemic in Brazil a mixed-methods study.pdfEvaluating user experience with a chatbot designed as a public health response to the Covid-19 pandemic in Brazil a mixed-methods study.pdfapplication/pdf767071https://repositorio.ufmg.br/bitstream/1843/65887/2/Evaluating%20user%20experience%20with%20a%20chatbot%20designed%20as%20a%20public%20health%20response%20to%20the%20Covid-19%20pandemic%20in%20Brazil%20a%20mixed-methods%20study.pdfbc9601e231a41b32ce53fda7ec40b56eMD521843/658872024-03-15 16:31:47.002oai:repositorio.ufmg.br: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Repositório de PublicaçõesPUBhttps://repositorio.ufmg.br/oaiopendoar:2024-03-15T19:31:47Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)false
dc.title.pt_BR.fl_str_mv Evaluating user experience with a chatbot designed as a public health response to the Covid-19 pandemic in Brazil: a mixed-methods study
title Evaluating user experience with a chatbot designed as a public health response to the Covid-19 pandemic in Brazil: a mixed-methods study
spellingShingle Evaluating user experience with a chatbot designed as a public health response to the Covid-19 pandemic in Brazil: a mixed-methods study
Bruno Azevedo Chagas
User experience
Chatbots
Telehealth
COVID-19
Human-computer interaction
HCI
Empirical studies in human-computer interaction
Empirical studies in HCI
Health care information systems
Interação homem-máquina
Cuidados médicos
Telemática médica
Telecomunicação em medicina
title_short Evaluating user experience with a chatbot designed as a public health response to the Covid-19 pandemic in Brazil: a mixed-methods study
title_full Evaluating user experience with a chatbot designed as a public health response to the Covid-19 pandemic in Brazil: a mixed-methods study
title_fullStr Evaluating user experience with a chatbot designed as a public health response to the Covid-19 pandemic in Brazil: a mixed-methods study
title_full_unstemmed Evaluating user experience with a chatbot designed as a public health response to the Covid-19 pandemic in Brazil: a mixed-methods study
title_sort Evaluating user experience with a chatbot designed as a public health response to the Covid-19 pandemic in Brazil: a mixed-methods study
author Bruno Azevedo Chagas
author_facet Bruno Azevedo Chagas
Thais Marques Pedroso
Alline Beleigoli
Clara Rodrigues Alves Oliveira
Milena Soriano Marcolino
Adriana Silvina Pagano
Raquel Oliveira Prates
Elisa Cordeiro Praes
Kícila Ferreguetti
Helena Vaz
Zilma Silveira Nogueira Reis
Leonardo Bonisson Ribeiro
Antonio Luiz Pinho Ribeiro
author_role author
author2 Thais Marques Pedroso
Alline Beleigoli
Clara Rodrigues Alves Oliveira
Milena Soriano Marcolino
Adriana Silvina Pagano
Raquel Oliveira Prates
Elisa Cordeiro Praes
Kícila Ferreguetti
Helena Vaz
Zilma Silveira Nogueira Reis
Leonardo Bonisson Ribeiro
Antonio Luiz Pinho Ribeiro
author2_role author
author
author
author
author
author
author
author
author
author
author
author
dc.contributor.author.fl_str_mv Bruno Azevedo Chagas
Thais Marques Pedroso
Alline Beleigoli
Clara Rodrigues Alves Oliveira
Milena Soriano Marcolino
Adriana Silvina Pagano
Raquel Oliveira Prates
Elisa Cordeiro Praes
Kícila Ferreguetti
Helena Vaz
Zilma Silveira Nogueira Reis
Leonardo Bonisson Ribeiro
Antonio Luiz Pinho Ribeiro
dc.subject.por.fl_str_mv User experience
Chatbots
Telehealth
COVID-19
Human-computer interaction
HCI
Empirical studies in human-computer interaction
Empirical studies in HCI
Health care information systems
topic User experience
Chatbots
Telehealth
COVID-19
Human-computer interaction
HCI
Empirical studies in human-computer interaction
Empirical studies in HCI
Health care information systems
Interação homem-máquina
Cuidados médicos
Telemática médica
Telecomunicação em medicina
dc.subject.other.pt_BR.fl_str_mv Interação homem-máquina
Cuidados médicos
Telemática médica
Telecomunicação em medicina
description Background: The potential of chatbots for screening and monitoring COVID-19 was envisioned since the outbreak of the disease. Chatbots can help disseminate up-to-date and trustworthy information, promote healthy social behavior, and support the provision of health care services safely and at scale. In this scenario and in view of its far-reaching postpandemic impact, it is important to evaluate user experience with this kind of application. Objective: We aimed to evaluate the quality of user experience with a COVID-19 chatbot designed by a large telehealth service in Brazil, focusing on the usability of real users and the exploration of strengths and shortcomings of the chatbot, as revealed in reports by participants in simulated scenarios. Methods: We examined a chatbot developed by a multidisciplinary team and used it as a component within the workflow of a local public health care service. The chatbot had 2 core functionalities: assisting web-based screening of COVID-19 symptom severity and providing evidence-based information to the population. From October 2020 to January 2021, we conducted a mixed methods approach and performed a 2-fold evaluation of user experience with our chatbot by following 2 methods: a posttask usability Likert-scale survey presented to all users after concluding their interaction with the bot and an interview with volunteer participants who engaged in a simulated interaction with the bot guided by the interviewer. Results: Usability assessment with 63 users revealed very good scores for chatbot usefulness (4.57), likelihood of being recommended (4.48), ease of use (4.44), and user satisfaction (4.38). Interviews with 15 volunteers provided insights into the strengths and shortcomings of our bot. Comments on the positive aspects and problems reported by users were analyzed in terms of recurrent themes. We identified 6 positive aspects and 15 issues organized in 2 categories: usability of the chatbot and health support offered by it, the former referring to usability of the chatbot and how users can interact with it and the latter referring to the chatbot’s goal in supporting people during the pandemic through the screening process and education to users through informative content. We found 6 themes accounting for what people liked most about our chatbot and why they found it useful—3 themes pertaining to the usability domain and 3 themes regarding health support. Our findings also identified 15 types of problems producing a negative impact on users—10 of them related to the usability of the chatbot and 5 related to the health support it provides. Conclusions: Our results indicate that users had an overall positive experience with the chatbot and found the health support relevant. Nonetheless, qualitative evaluation of the chatbot indicated challenges and directions to be pursued in improving not only our COVID-19 chatbot but also health chatbots in general.
publishDate 2022
dc.date.issued.fl_str_mv 2022-09-30
dc.date.accessioned.fl_str_mv 2024-03-14T22:21:18Z
dc.date.available.fl_str_mv 2024-03-14T22:21:18Z
dc.type.status.fl_str_mv info:eu-repo/semantics/publishedVersion
dc.type.driver.fl_str_mv info:eu-repo/semantics/article
format article
status_str publishedVersion
dc.identifier.uri.fl_str_mv http://hdl.handle.net/1843/65887
dc.identifier.doi.pt_BR.fl_str_mv https://doi.org/10.2196/43135
dc.identifier.issn.pt_BR.fl_str_mv 2292-9495
dc.identifier.orcid.pt_BR.fl_str_mv https://orcid.org/0000-0002-8571-3135
https://orcid.org/0000-0003-0149-9731
https://orcid.org/0000-0002-7848-3183
https://orcid.org/0000-0002-9437-2344
https://orcid.org/0000-0003-4278-3771
https://orcid.org/0000-0002-3150-3503
https://orcid.org/0000-0002-7128-4974
https://orcid.org/0000-0001-6495-993X
https://orcid.org/0000-0002-1919-0073
https://orcid.org/0000-0001-6374-9295
https://orcid.org/0000-0001-9035-0722
https://orcid.org/0000-0002-0364-3584
url https://doi.org/10.2196/43135
http://hdl.handle.net/1843/65887
https://orcid.org/0000-0002-8571-3135
https://orcid.org/0000-0003-0149-9731
https://orcid.org/0000-0002-7848-3183
https://orcid.org/0000-0002-9437-2344
https://orcid.org/0000-0003-4278-3771
https://orcid.org/0000-0002-3150-3503
https://orcid.org/0000-0002-7128-4974
https://orcid.org/0000-0001-6495-993X
https://orcid.org/0000-0002-1919-0073
https://orcid.org/0000-0001-6374-9295
https://orcid.org/0000-0001-9035-0722
https://orcid.org/0000-0002-0364-3584
identifier_str_mv 2292-9495
dc.language.iso.fl_str_mv eng
language eng
dc.relation.ispartof.pt_BR.fl_str_mv JMIR Hum Factors
dc.rights.driver.fl_str_mv info:eu-repo/semantics/openAccess
eu_rights_str_mv openAccess
dc.format.none.fl_str_mv application/pdf
dc.publisher.none.fl_str_mv Universidade Federal de Minas Gerais
dc.publisher.initials.fl_str_mv UFMG
dc.publisher.country.fl_str_mv Brasil
dc.publisher.department.fl_str_mv FALE - FACULDADE DE LETRAS
ICX - DEPARTAMENTO DE CIÊNCIA DA COMPUTAÇÃO
MED - DEPARTAMENTO DE CLÍNICA MÉDICA
publisher.none.fl_str_mv Universidade Federal de Minas Gerais
dc.source.none.fl_str_mv reponame:Repositório Institucional da UFMG
instname:Universidade Federal de Minas Gerais (UFMG)
instacron:UFMG
instname_str Universidade Federal de Minas Gerais (UFMG)
instacron_str UFMG
institution UFMG
reponame_str Repositório Institucional da UFMG
collection Repositório Institucional da UFMG
bitstream.url.fl_str_mv https://repositorio.ufmg.br/bitstream/1843/65887/1/License.txt
https://repositorio.ufmg.br/bitstream/1843/65887/2/Evaluating%20user%20experience%20with%20a%20chatbot%20designed%20as%20a%20public%20health%20response%20to%20the%20Covid-19%20pandemic%20in%20Brazil%20a%20mixed-methods%20study.pdf
bitstream.checksum.fl_str_mv fa505098d172de0bc8864fc1287ffe22
bc9601e231a41b32ce53fda7ec40b56e
bitstream.checksumAlgorithm.fl_str_mv MD5
MD5
repository.name.fl_str_mv Repositório Institucional da UFMG - Universidade Federal de Minas Gerais (UFMG)
repository.mail.fl_str_mv
_version_ 1803589150367023104