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 expo...
| Main Authors: | , , , , , , , , , , , |
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| Format: | Article |
| Language: | English |
| Published: |
Swansea University
2021-10-01
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| Series: | International Journal of Population Data Science |
| Subjects: | |
| Online Access: | https://ijpds.org/article/view/1651 |
| _version_ | 1797420895646515200 |
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| 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 |
| collection | DOAJ |
| 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. |
| first_indexed | 2024-03-09T07:08:15Z |
| format | Article |
| id | doaj.art-585ebaa80fda438ca49a618cb80783ec |
| institution | Directory Open Access Journal |
| issn | 2399-4908 |
| language | English |
| last_indexed | 2024-03-09T07:08:15Z |
| publishDate | 2021-10-01 |
| publisher | Swansea University |
| record_format | Article |
| series | International Journal of Population Data Science |
| spelling | doaj.art-585ebaa80fda438ca49a618cb80783ec2023-12-03T09:18:24ZengSwansea UniversityInternational Journal of Population Data Science2399-49082021-10-015410.23889/ijpds.v5i4.1651Developmental Impacts of the COVID-19 Pandemic on Young Children: A Conceptual Model for Research with Integrated Administrative Data SystemsHeather L. Rouse0Rebecca J. Bulotsky Shearer1Sydney S. Idzikowski2Amy Hawn Nelson3Mark Needle4Matthew F. Katz 5Jhonelle Bailey6Justin T. Lane7Emily Berkowitz8Sharon Zanti9Astrid Pena 10Maggie Reeves11Department of Human Development and Family Studies, 2330 Palmer Building, 2222 Osborn Drive, Ames, Iowa 50011-1084Department of Psychology, University of Miami, P.O. Box 248185, Coral Gables, FL 33124University of North Carolina at Charlotte Urban Institute, Institute for Social Capital, Sycamore Hall, 9310 Mary Alexander Road, Charlotte, NC 28223Actionable Intelligence for Social Policy (AISP), University of Pennsylvania, 3701 Locust Walk, Philadelphia, PA 19104Department of Psychology, University of Miami, P.O. Box 248185, Coral Gables, FL 33124Actionable Intelligence for Social Policy (AISP), University of Pennsylvania, 3701 Locust Walk, Philadelphia, PA 19104Department of Psychology, University of Miami, P.O. Box 248185, Coral Gables, FL 33124University of North Carolina at Charlotte Urban Institute, Institute for Social Capital, Sycamore Hall, 9310 Mary Alexander Road, Charlotte, NC 28223Actionable Intelligence for Social Policy (AISP), University of Pennsylvania, 3701 Locust Walk, Philadelphia, PA 19104Actionable Intelligence for Social Policy (AISP), University of Pennsylvania, 3701 Locust Walk, Philadelphia, PA 19104Department of Psychology, University of Miami, P.O. Box 248185, Coral Gables, FL 33124Georgia Policy Labs, Georgia State University, 14 Marietta Street NW, 5th Floor, Atlanta, GA 30303The 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.https://ijpds.org/article/view/1651data modelchild developmentCOVID-19integrated administrative data systems |
| spellingShingle | 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 International Journal of Population Data Science data model child development COVID-19 integrated administrative data systems |
| title | 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_short | 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 |
| topic | data model child development COVID-19 integrated administrative data systems |
| url | https://ijpds.org/article/view/1651 |
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