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Determining the Optimal Outcome Measures for Studying the Social Determinants of Health
Americans have significantly poorer health outcomes and shorter longevity than citizens of other industrialized nations. Poverty is a major driver of these poor health outcomes in the United States. Innovative anti-poverty policies may help reduce economic malaise thereby increasing the health and l...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
MDPI
2020
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7246501/ https://www.ncbi.nlm.nih.gov/pubmed/32349268 http://dx.doi.org/10.3390/ijerph17093028 |
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author | Muennig, Peter McEwen, Bruce Belsky, Daniel W. Noble, Kimberly G. Riccio, James Manly, Jennifer |
author_facet | Muennig, Peter McEwen, Bruce Belsky, Daniel W. Noble, Kimberly G. Riccio, James Manly, Jennifer |
author_sort | Muennig, Peter |
collection | PubMed |
description | Americans have significantly poorer health outcomes and shorter longevity than citizens of other industrialized nations. Poverty is a major driver of these poor health outcomes in the United States. Innovative anti-poverty policies may help reduce economic malaise thereby increasing the health and longevity of the most vulnerable Americans. However, there is no consensus framework for studying the health impacts of anti-poverty social policies. In this paper, we describe a case study in which leading global experts systematically: (1) developed a conceptual model that outlines the potential pathways through which a social policy influences health, (2) fits outcome measures to this conceptual model, and (3) estimates an optimal time frame for collection of the selected outcome measures. This systematic process, called the Delphi method, has the potential to produce estimates more quickly and with less bias than might be achieved through expert panel discussions alone. Our case study is a multi-component randomized-controlled trial (RCT) of a workforce policy called MyGoals for Healthy Aging. |
format | Online Article Text |
id | pubmed-7246501 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | MDPI |
record_format | MEDLINE/PubMed |
spelling | pubmed-72465012020-06-11 Determining the Optimal Outcome Measures for Studying the Social Determinants of Health Muennig, Peter McEwen, Bruce Belsky, Daniel W. Noble, Kimberly G. Riccio, James Manly, Jennifer Int J Environ Res Public Health Communication Americans have significantly poorer health outcomes and shorter longevity than citizens of other industrialized nations. Poverty is a major driver of these poor health outcomes in the United States. Innovative anti-poverty policies may help reduce economic malaise thereby increasing the health and longevity of the most vulnerable Americans. However, there is no consensus framework for studying the health impacts of anti-poverty social policies. In this paper, we describe a case study in which leading global experts systematically: (1) developed a conceptual model that outlines the potential pathways through which a social policy influences health, (2) fits outcome measures to this conceptual model, and (3) estimates an optimal time frame for collection of the selected outcome measures. This systematic process, called the Delphi method, has the potential to produce estimates more quickly and with less bias than might be achieved through expert panel discussions alone. Our case study is a multi-component randomized-controlled trial (RCT) of a workforce policy called MyGoals for Healthy Aging. MDPI 2020-04-27 2020-05 /pmc/articles/PMC7246501/ /pubmed/32349268 http://dx.doi.org/10.3390/ijerph17093028 Text en © 2020 by the authors. Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Communication Muennig, Peter McEwen, Bruce Belsky, Daniel W. Noble, Kimberly G. Riccio, James Manly, Jennifer Determining the Optimal Outcome Measures for Studying the Social Determinants of Health |
title | Determining the Optimal Outcome Measures for Studying the Social Determinants of Health |
title_full | Determining the Optimal Outcome Measures for Studying the Social Determinants of Health |
title_fullStr | Determining the Optimal Outcome Measures for Studying the Social Determinants of Health |
title_full_unstemmed | Determining the Optimal Outcome Measures for Studying the Social Determinants of Health |
title_short | Determining the Optimal Outcome Measures for Studying the Social Determinants of Health |
title_sort | determining the optimal outcome measures for studying the social determinants of health |
topic | Communication |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7246501/ https://www.ncbi.nlm.nih.gov/pubmed/32349268 http://dx.doi.org/10.3390/ijerph17093028 |
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