Developmental Impacts of the COVID-19 Pandemic on Young Children: A Conceptual Model for Research with Integrated Administrative Data Systems

The COVID-19 pandemic made its mark on the entire world, upending economies, shifting work and education, and exposing deeply rooted inequities. A particularly vulnerable, yet less studied population includes our youngest children, ages zero to five, whose proximal and distal contexts have been exp...

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Autores principales:	Heather L. Rouse, Rebecca J. Bulotsky Shearer, Sydney S. Idzikowski, Amy Hawn Nelson, Mark Needle, Matthew F. Katz, Jhonelle Bailey, Justin T. Lane, Emily Berkowitz, Sharon Zanti, Astrid Pena, Maggie Reeves
Formato:	article
Lenguaje:	EN
Publicado:	Swansea University 2021
Materias:	data model child development COVID-19 integrated administrative data systems Demography. Population. Vital events HB848-3697
Acceso en línea:	https://doaj.org/article/585ebaa80fda438ca49a618cb80783ec
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spelling	oai:doaj.org-article:585ebaa80fda438ca49a618cb80783ec2021-12-03T15:47:29ZDevelopmental Impacts of the COVID-19 Pandemic on Young Children: A Conceptual Model for Research with Integrated Administrative Data Systems10.23889/ijpds.v5i4.16512399-4908https://doaj.org/article/585ebaa80fda438ca49a618cb80783ec2021-10-01T00:00:00Zhttps://ijpds.org/article/view/1651https://doaj.org/toc/2399-4908 The COVID-19 pandemic made its mark on the entire world, upending economies, shifting work and education, and exposing deeply rooted inequities. A particularly vulnerable, yet less studied population includes our youngest children, ages zero to five, whose proximal and distal contexts have been exponentially affected with unknown impacts on health, education, and social-emotional well-being. Integrated administrative data systems could be important tools for understanding these impacts. This article has three aims to guide research on the impacts of COVID-19 for this critical population using integrated data systems (IDS). First, it presents a conceptual data model informed by developmental-ecological theory and epidemiological frameworks to study young children. This data model presents five developmental resilience pathways (i.e. early learning, safe and nurturing families, health, housing, and financial/employment) that include direct and indirect influencers related to COVID-19 impacts and the contexts and community supports that can affect outcomes. Second, the article outlines administrative datasets with relevant indicators that are commonly collected, could be integrated at the individual level, and include relevant linkages between children and families to facilitate research using the conceptual data model. Third, this paper provides specific considerations for research using the conceptual data model that acknowledge the highly-localised political response to COVID-19 in the US. It concludes with a call to action for the population data science community to use and expand IDS capacities to better understand the intermediate and long-term impacts of this pandemic on young children. Heather L. RouseRebecca J. Bulotsky ShearerSydney S. IdzikowskiAmy Hawn NelsonMark NeedleMatthew F. Katz Jhonelle BaileyJustin T. LaneEmily BerkowitzSharon ZantiAstrid Pena Maggie ReevesSwansea Universityarticledata modelchild developmentCOVID-19integrated administrative data systemsDemography. Population. Vital eventsHB848-3697ENInternational Journal of Population Data Science, Vol 5, Iss 4 (2021)
institution	DOAJ
collection	DOAJ
language	EN
topic	data model child development COVID-19 integrated administrative data systems Demography. Population. Vital events HB848-3697
spellingShingle	data model child development COVID-19 integrated administrative data systems Demography. Population. Vital events HB848-3697 Heather L. Rouse Rebecca J. Bulotsky Shearer Sydney S. Idzikowski Amy Hawn Nelson Mark Needle Matthew F. Katz Jhonelle Bailey Justin T. Lane Emily Berkowitz Sharon Zanti Astrid Pena Maggie Reeves Developmental Impacts of the COVID-19 Pandemic on Young Children: A Conceptual Model for Research with Integrated Administrative Data Systems
description	The COVID-19 pandemic made its mark on the entire world, upending economies, shifting work and education, and exposing deeply rooted inequities. A particularly vulnerable, yet less studied population includes our youngest children, ages zero to five, whose proximal and distal contexts have been exponentially affected with unknown impacts on health, education, and social-emotional well-being. Integrated administrative data systems could be important tools for understanding these impacts. This article has three aims to guide research on the impacts of COVID-19 for this critical population using integrated data systems (IDS). First, it presents a conceptual data model informed by developmental-ecological theory and epidemiological frameworks to study young children. This data model presents five developmental resilience pathways (i.e. early learning, safe and nurturing families, health, housing, and financial/employment) that include direct and indirect influencers related to COVID-19 impacts and the contexts and community supports that can affect outcomes. Second, the article outlines administrative datasets with relevant indicators that are commonly collected, could be integrated at the individual level, and include relevant linkages between children and families to facilitate research using the conceptual data model. Third, this paper provides specific considerations for research using the conceptual data model that acknowledge the highly-localised political response to COVID-19 in the US. It concludes with a call to action for the population data science community to use and expand IDS capacities to better understand the intermediate and long-term impacts of this pandemic on young children.
format	article
author	Heather L. Rouse Rebecca J. Bulotsky Shearer Sydney S. Idzikowski Amy Hawn Nelson Mark Needle Matthew F. Katz Jhonelle Bailey Justin T. Lane Emily Berkowitz Sharon Zanti Astrid Pena Maggie Reeves
author_facet	Heather L. Rouse Rebecca J. Bulotsky Shearer Sydney S. Idzikowski Amy Hawn Nelson Mark Needle Matthew F. Katz Jhonelle Bailey Justin T. Lane Emily Berkowitz Sharon Zanti Astrid Pena Maggie Reeves
author_sort	Heather L. Rouse
title	Developmental Impacts of the COVID-19 Pandemic on Young Children: A Conceptual Model for Research with Integrated Administrative Data Systems
title_short	Developmental Impacts of the COVID-19 Pandemic on Young Children: A Conceptual Model for Research with Integrated Administrative Data Systems
title_full	Developmental Impacts of the COVID-19 Pandemic on Young Children: A Conceptual Model for Research with Integrated Administrative Data Systems
title_fullStr	Developmental Impacts of the COVID-19 Pandemic on Young Children: A Conceptual Model for Research with Integrated Administrative Data Systems
title_full_unstemmed	Developmental Impacts of the COVID-19 Pandemic on Young Children: A Conceptual Model for Research with Integrated Administrative Data Systems
title_sort	developmental impacts of the covid-19 pandemic on young children: a conceptual model for research with integrated administrative data systems
publisher	Swansea University
publishDate	2021
url	https://doaj.org/article/585ebaa80fda438ca49a618cb80783ec
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Developmental Impacts of the COVID-19 Pandemic on Young Children: A Conceptual Model for Research with Integrated Administrative Data Systems

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