Evaluating user experience with a chatbot designed as a public health response to the Covid-19 pandemic in Brazil: a mixed-methods study
Autor(a) principal: | |
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Data de Publicação: | 2022 |
Outros Autores: | , , , , , , , , , , , |
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. |
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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 |
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info:eu-repo/semantics/publishedVersion |
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info:eu-repo/semantics/article |
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article |
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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 |
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2292-9495 |
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eng |
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eng |
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JMIR Hum Factors |
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Universidade Federal de Minas Gerais |
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Brasil |
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FALE - FACULDADE DE LETRAS ICX - DEPARTAMENTO DE CIÊNCIA DA COMPUTAÇÃO MED - DEPARTAMENTO DE CLÍNICA MÉDICA |
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Universidade Federal de Minas Gerais |
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