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Maximizing research on the adverse effects of child poverty through consensus measures.

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Title: Maximizing research on the adverse effects of child poverty through consensus measures.
Authors: Pollak, Seth D. (AUTHOR), Wolfe, Barbara L. (AUTHOR)
Source: Developmental Science. Nov2020, Vol. 23 Issue 6, p1-11. 11p.
Subjects: Poor children, Child development, Income, Poverty rate
Abstract: A variety of new research approaches are providing new ways to better understand the developmental mechanisms through which poverty affects children's development. However, studies of child poverty often characterize samples using different markers of poverty, making it difficult to contrast and reconcile findings across studies. Ideally, scientists can maximize the benefits of multiple disciplinary approaches if data from different kinds of studies can be directly compared and linked. Here, we suggest that individual studies can increase their potential usefulness by including a small set of common key variables to assess socioeconomic status and family income. These common variables can be used to (a) make direct comparisons between studies and (b) better enable diversity of subjects and aggregation of data regarding many facets of poverty that would be difficult within any single study. If kept brief, these items can be easily balanced with the need for investigators to creatively address the research questions in their specific study designs. To advance this goal, we identify a small set of brief, low‐burden consensus measures that researchers could include in their studies to increase cross‐study data compatibility. These US based measures can be adopted for global contexts. Research on child poverty employs a variety of different indices of poverty, making it difficult to contrast and reconcile findings across studies. This Open Access paper provides a small set of brief key variables to assess socio‐economic status and family income, allowing studies to be directly compared. This measure can be used to make direct comparisons between studies and better enable diversity of subjects and aggregation of data regarding many facets of poverty that would be difficult within any single study. [ABSTRACT FROM AUTHOR]
Copyright of Developmental Science is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Psychology and Behavioral Sciences Collection
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  Data: Maximizing research on the adverse effects of child poverty through consensus measures.
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  Data: <searchLink fieldCode="AR" term="%22Pollak%2C+Seth+D%2E%22">Pollak, Seth D.</searchLink> (AUTHOR)<br /><searchLink fieldCode="AR" term="%22Wolfe%2C+Barbara+L%2E%22">Wolfe, Barbara L.</searchLink> (AUTHOR)
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  Data: <searchLink fieldCode="DE" term="%22Poor+children%22">Poor children</searchLink><br /><searchLink fieldCode="DE" term="%22Child+development%22">Child development</searchLink><br /><searchLink fieldCode="DE" term="%22Income%22">Income</searchLink><br /><searchLink fieldCode="DE" term="%22Poverty+rate%22">Poverty rate</searchLink>
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  Data: A variety of new research approaches are providing new ways to better understand the developmental mechanisms through which poverty affects children's development. However, studies of child poverty often characterize samples using different markers of poverty, making it difficult to contrast and reconcile findings across studies. Ideally, scientists can maximize the benefits of multiple disciplinary approaches if data from different kinds of studies can be directly compared and linked. Here, we suggest that individual studies can increase their potential usefulness by including a small set of common key variables to assess socioeconomic status and family income. These common variables can be used to (a) make direct comparisons between studies and (b) better enable diversity of subjects and aggregation of data regarding many facets of poverty that would be difficult within any single study. If kept brief, these items can be easily balanced with the need for investigators to creatively address the research questions in their specific study designs. To advance this goal, we identify a small set of brief, low‐burden consensus measures that researchers could include in their studies to increase cross‐study data compatibility. These US based measures can be adopted for global contexts. Research on child poverty employs a variety of different indices of poverty, making it difficult to contrast and reconcile findings across studies. This Open Access paper provides a small set of brief key variables to assess socio‐economic status and family income, allowing studies to be directly compared. This measure can be used to make direct comparisons between studies and better enable diversity of subjects and aggregation of data regarding many facets of poverty that would be difficult within any single study. [ABSTRACT FROM AUTHOR]
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  Data: <i>Copyright of Developmental Science is the property of Wiley-Blackwell and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
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