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A Personalized Avatar-Based Web Application to Help People Understand How Social Distancing Can Reduce the Spread of COVID-19: Cross-sectional, Observational, Pre-Post Study

BACKGROUND: To reduce the transmission of SARS-CoV-2 and the associated spread of COVID-19, many jurisdictions around the world imposed mandatory or recommended social or physical distancing. As a result, at the beginning of the pandemic, various communication materials appeared online to promote di...

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Autores principales: Etienne, Doriane, Archambault, Patrick, Aziaka, Donovan, Chipenda-Dansokho, Selma, Dubé, Eve, Fallon, Catherine S, Hakim, Hina, Kindrachuk, Jason, Krecoum, Dan, MacDonald, Shannon E, Ndjaboue, Ruth, Noubi, Magniol, Paquette, Jean-Sébastien, Parent, Elizabeth, Witteman, Holly O
Formato: Online Artículo Texto
Lenguaje:English
Publicado: JMIR Publications 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10170367/
https://www.ncbi.nlm.nih.gov/pubmed/36961787
http://dx.doi.org/10.2196/38430
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author Etienne, Doriane
Archambault, Patrick
Aziaka, Donovan
Chipenda-Dansokho, Selma
Dubé, Eve
Fallon, Catherine S
Hakim, Hina
Kindrachuk, Jason
Krecoum, Dan
MacDonald, Shannon E
Ndjaboue, Ruth
Noubi, Magniol
Paquette, Jean-Sébastien
Parent, Elizabeth
Witteman, Holly O
author_facet Etienne, Doriane
Archambault, Patrick
Aziaka, Donovan
Chipenda-Dansokho, Selma
Dubé, Eve
Fallon, Catherine S
Hakim, Hina
Kindrachuk, Jason
Krecoum, Dan
MacDonald, Shannon E
Ndjaboue, Ruth
Noubi, Magniol
Paquette, Jean-Sébastien
Parent, Elizabeth
Witteman, Holly O
author_sort Etienne, Doriane
collection PubMed
description BACKGROUND: To reduce the transmission of SARS-CoV-2 and the associated spread of COVID-19, many jurisdictions around the world imposed mandatory or recommended social or physical distancing. As a result, at the beginning of the pandemic, various communication materials appeared online to promote distancing. Explanations of the science underlying these mandates or recommendations were either highly technical or highly simplified. OBJECTIVE: This study aimed to understand the effects of a dynamic visualization on distancing. Our overall aim was to help people understand the dynamics of the spread of COVID-19 in their community and the implications of their own behavior for themselves, those around them, the health care system, and society. METHODS: Using Scrum, which is an agile framework; JavaScript (Vue.js framework); and code already developed for risk communication in another context of infectious disease transmission, we rapidly developed a new personalized web application. In our application, people make avatars that represent themselves and the people around them. These avatars are integrated into a 3-minute animation illustrating an epidemiological model for COVID-19 transmission, showing the differences in transmission with and without distancing. During the animation, the narration explains the science of how distancing reduces the transmission of COVID-19 in plain language in English or French. The application offers full captions to complement the narration and a descriptive transcript for people using screen readers. We used Google Analytics to collect standard usage statistics. A brief, anonymous, optional survey also collected self-reported distancing behaviors and intentions in the previous and coming weeks, respectively. We launched and disseminated the application on Twitter and Facebook on April 8, 2020, and April 9, 2020. RESULTS: After 26 days, the application received 3588 unique hits from 82 countries. The optional survey at the end of the application collected 182 responses. Among this small subsample of users, survey respondents were nearly (170/177, 96%) already practicing distancing and indicated that they intended to practice distancing in the coming week (172/177, 97.2%). Among the small minority of people (n=7) who indicated that they had not been previously practicing distancing, 2 (29%) reported that they would practice distancing in the week to come. CONCLUSIONS: We developed a web application to help people understand the relationship between individual-level behavior and population-level effects in the context of an infectious disease spread. This study also demonstrates how agile development can be used to quickly create personalized risk messages for public health issues like a pandemic. The nonrandomized design of this rapid study prevents us from concluding the application’s effectiveness; however, results thus far suggest that avatar-based visualizations may help people understand their role in infectious disease transmission.
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spelling pubmed-101703672023-05-11 A Personalized Avatar-Based Web Application to Help People Understand How Social Distancing Can Reduce the Spread of COVID-19: Cross-sectional, Observational, Pre-Post Study Etienne, Doriane Archambault, Patrick Aziaka, Donovan Chipenda-Dansokho, Selma Dubé, Eve Fallon, Catherine S Hakim, Hina Kindrachuk, Jason Krecoum, Dan MacDonald, Shannon E Ndjaboue, Ruth Noubi, Magniol Paquette, Jean-Sébastien Parent, Elizabeth Witteman, Holly O JMIR Form Res Original Paper BACKGROUND: To reduce the transmission of SARS-CoV-2 and the associated spread of COVID-19, many jurisdictions around the world imposed mandatory or recommended social or physical distancing. As a result, at the beginning of the pandemic, various communication materials appeared online to promote distancing. Explanations of the science underlying these mandates or recommendations were either highly technical or highly simplified. OBJECTIVE: This study aimed to understand the effects of a dynamic visualization on distancing. Our overall aim was to help people understand the dynamics of the spread of COVID-19 in their community and the implications of their own behavior for themselves, those around them, the health care system, and society. METHODS: Using Scrum, which is an agile framework; JavaScript (Vue.js framework); and code already developed for risk communication in another context of infectious disease transmission, we rapidly developed a new personalized web application. In our application, people make avatars that represent themselves and the people around them. These avatars are integrated into a 3-minute animation illustrating an epidemiological model for COVID-19 transmission, showing the differences in transmission with and without distancing. During the animation, the narration explains the science of how distancing reduces the transmission of COVID-19 in plain language in English or French. The application offers full captions to complement the narration and a descriptive transcript for people using screen readers. We used Google Analytics to collect standard usage statistics. A brief, anonymous, optional survey also collected self-reported distancing behaviors and intentions in the previous and coming weeks, respectively. We launched and disseminated the application on Twitter and Facebook on April 8, 2020, and April 9, 2020. RESULTS: After 26 days, the application received 3588 unique hits from 82 countries. The optional survey at the end of the application collected 182 responses. Among this small subsample of users, survey respondents were nearly (170/177, 96%) already practicing distancing and indicated that they intended to practice distancing in the coming week (172/177, 97.2%). Among the small minority of people (n=7) who indicated that they had not been previously practicing distancing, 2 (29%) reported that they would practice distancing in the week to come. CONCLUSIONS: We developed a web application to help people understand the relationship between individual-level behavior and population-level effects in the context of an infectious disease spread. This study also demonstrates how agile development can be used to quickly create personalized risk messages for public health issues like a pandemic. The nonrandomized design of this rapid study prevents us from concluding the application’s effectiveness; however, results thus far suggest that avatar-based visualizations may help people understand their role in infectious disease transmission. JMIR Publications 2023-04-25 /pmc/articles/PMC10170367/ /pubmed/36961787 http://dx.doi.org/10.2196/38430 Text en ©Doriane Etienne, Patrick Archambault, Donovan Aziaka, Selma Chipenda-Dansokho, Eve Dubé, Catherine S Fallon, Hina Hakim, Jason Kindrachuk, Dan Krecoum, Shannon E MacDonald, Ruth Ndjaboue, Magniol Noubi, Jean-Sébastien Paquette, Elizabeth Parent, Holly O Witteman. Originally published in JMIR Formative Research (https://formative.jmir.org), 25.04.2023. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work, first published in JMIR Formative Research, is properly cited. The complete bibliographic information, a link to the original publication on https://formative.jmir.org, as well as this copyright and license information must be included.
spellingShingle Original Paper
Etienne, Doriane
Archambault, Patrick
Aziaka, Donovan
Chipenda-Dansokho, Selma
Dubé, Eve
Fallon, Catherine S
Hakim, Hina
Kindrachuk, Jason
Krecoum, Dan
MacDonald, Shannon E
Ndjaboue, Ruth
Noubi, Magniol
Paquette, Jean-Sébastien
Parent, Elizabeth
Witteman, Holly O
A Personalized Avatar-Based Web Application to Help People Understand How Social Distancing Can Reduce the Spread of COVID-19: Cross-sectional, Observational, Pre-Post Study
title A Personalized Avatar-Based Web Application to Help People Understand How Social Distancing Can Reduce the Spread of COVID-19: Cross-sectional, Observational, Pre-Post Study
title_full A Personalized Avatar-Based Web Application to Help People Understand How Social Distancing Can Reduce the Spread of COVID-19: Cross-sectional, Observational, Pre-Post Study
title_fullStr A Personalized Avatar-Based Web Application to Help People Understand How Social Distancing Can Reduce the Spread of COVID-19: Cross-sectional, Observational, Pre-Post Study
title_full_unstemmed A Personalized Avatar-Based Web Application to Help People Understand How Social Distancing Can Reduce the Spread of COVID-19: Cross-sectional, Observational, Pre-Post Study
title_short A Personalized Avatar-Based Web Application to Help People Understand How Social Distancing Can Reduce the Spread of COVID-19: Cross-sectional, Observational, Pre-Post Study
title_sort personalized avatar-based web application to help people understand how social distancing can reduce the spread of covid-19: cross-sectional, observational, pre-post study
topic Original Paper
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10170367/
https://www.ncbi.nlm.nih.gov/pubmed/36961787
http://dx.doi.org/10.2196/38430
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