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Protocol to acquire time series data on adverse reactions following vaccination using a smartphone or web-based platform

Data collection on adverse reactions in recipients after vaccination is vital to evaluate potential health issues, but health observation diaries are onerous for participants. Here, we present a protocol to collect time series information using a smartphone or web-based platform, thus eliminating th...

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Detalles Bibliográficos
Autores principales: Yamao, Yasuo, Oami, Takehiko, Kawakami, Eiryo, Nakada, Taka-aki
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2023
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10168702/
https://www.ncbi.nlm.nih.gov/pubmed/37148245
http://dx.doi.org/10.1016/j.xpro.2023.102284
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author Yamao, Yasuo
Oami, Takehiko
Kawakami, Eiryo
Nakada, Taka-aki
author_facet Yamao, Yasuo
Oami, Takehiko
Kawakami, Eiryo
Nakada, Taka-aki
author_sort Yamao, Yasuo
collection PubMed
description Data collection on adverse reactions in recipients after vaccination is vital to evaluate potential health issues, but health observation diaries are onerous for participants. Here, we present a protocol to collect time series information using a smartphone or web-based platform, thus eliminating the need for paperwork and data submission. We describe steps for setting up the platform using the Model-View-Controller web framework, uploading lists of recipients, sending notifications, and managing respondent data. For complete details on the use and execution of this protocol, please refer to Ikeda et al. (2022).(1)
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spelling pubmed-101687022023-05-10 Protocol to acquire time series data on adverse reactions following vaccination using a smartphone or web-based platform Yamao, Yasuo Oami, Takehiko Kawakami, Eiryo Nakada, Taka-aki STAR Protoc Protocol Data collection on adverse reactions in recipients after vaccination is vital to evaluate potential health issues, but health observation diaries are onerous for participants. Here, we present a protocol to collect time series information using a smartphone or web-based platform, thus eliminating the need for paperwork and data submission. We describe steps for setting up the platform using the Model-View-Controller web framework, uploading lists of recipients, sending notifications, and managing respondent data. For complete details on the use and execution of this protocol, please refer to Ikeda et al. (2022).(1) Elsevier 2023-05-05 /pmc/articles/PMC10168702/ /pubmed/37148245 http://dx.doi.org/10.1016/j.xpro.2023.102284 Text en © 2023 The Author(s) https://creativecommons.org/licenses/by-nc-nd/4.0/This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Protocol
Yamao, Yasuo
Oami, Takehiko
Kawakami, Eiryo
Nakada, Taka-aki
Protocol to acquire time series data on adverse reactions following vaccination using a smartphone or web-based platform
title Protocol to acquire time series data on adverse reactions following vaccination using a smartphone or web-based platform
title_full Protocol to acquire time series data on adverse reactions following vaccination using a smartphone or web-based platform
title_fullStr Protocol to acquire time series data on adverse reactions following vaccination using a smartphone or web-based platform
title_full_unstemmed Protocol to acquire time series data on adverse reactions following vaccination using a smartphone or web-based platform
title_short Protocol to acquire time series data on adverse reactions following vaccination using a smartphone or web-based platform
title_sort protocol to acquire time series data on adverse reactions following vaccination using a smartphone or web-based platform
topic Protocol
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10168702/
https://www.ncbi.nlm.nih.gov/pubmed/37148245
http://dx.doi.org/10.1016/j.xpro.2023.102284
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