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Technological innovation and its effect on public health in the United States

BACKGROUND: Good public health ensures an efficient work force. Organizations can ensure a prominent position on the global stage by staying on the leading edge of technological development. Public health and technological innovation are vital elements of prosperous economies. It is important to und...

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Autor principal: Gill, Preetinder Singh
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Dove Medical Press 2013
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3556917/
https://www.ncbi.nlm.nih.gov/pubmed/23378771
http://dx.doi.org/10.2147/JMDH.S34810
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author Gill, Preetinder Singh
author_facet Gill, Preetinder Singh
author_sort Gill, Preetinder Singh
collection PubMed
description BACKGROUND: Good public health ensures an efficient work force. Organizations can ensure a prominent position on the global stage by staying on the leading edge of technological development. Public health and technological innovation are vital elements of prosperous economies. It is important to understand how these elements affect each other. This research study explored and described the relationship between these two critical elements/constructs. METHODS: Indicators representing technological innovation and public health were identified. Indicator data from 2000 to 2009 were collected from various US federal government sources, for the four US Census regions. The four US Census regions were then compared in terms of these indicators. Canonical correlation equations were formulated to identify combinations of the indicators that are strongly related to each other. Additionally, the cause–effect relationship between public health and technological innovation was described using the structural equation modeling technique. RESULTS: The four US Census regions ranked differently in terms of both type of indicators in a statistically significant manner. The canonical correlation analysis showed that the first set of canonical variables had a fairly strong relationship, with a magnitude > 0.65 at the 95% confidence interval, for all census regions. Structural equation modeling analysis provided β < −0.69 and Student’s t statistic > 12.98, for all census regions. The threshold Student’s t statistic was 1.98. Hence, it was found that the β values were significant at the 95% confidence interval, for all census regions. DISCUSSION: The results of the study showed that better technological innovation indicator scores were associated with better public health indicator scores. Furthermore, the study provided preliminary evidence that technological innovation shares causal relation with public health.
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spelling pubmed-35569172013-02-01 Technological innovation and its effect on public health in the United States Gill, Preetinder Singh J Multidiscip Healthc Original Research BACKGROUND: Good public health ensures an efficient work force. Organizations can ensure a prominent position on the global stage by staying on the leading edge of technological development. Public health and technological innovation are vital elements of prosperous economies. It is important to understand how these elements affect each other. This research study explored and described the relationship between these two critical elements/constructs. METHODS: Indicators representing technological innovation and public health were identified. Indicator data from 2000 to 2009 were collected from various US federal government sources, for the four US Census regions. The four US Census regions were then compared in terms of these indicators. Canonical correlation equations were formulated to identify combinations of the indicators that are strongly related to each other. Additionally, the cause–effect relationship between public health and technological innovation was described using the structural equation modeling technique. RESULTS: The four US Census regions ranked differently in terms of both type of indicators in a statistically significant manner. The canonical correlation analysis showed that the first set of canonical variables had a fairly strong relationship, with a magnitude > 0.65 at the 95% confidence interval, for all census regions. Structural equation modeling analysis provided β < −0.69 and Student’s t statistic > 12.98, for all census regions. The threshold Student’s t statistic was 1.98. Hence, it was found that the β values were significant at the 95% confidence interval, for all census regions. DISCUSSION: The results of the study showed that better technological innovation indicator scores were associated with better public health indicator scores. Furthermore, the study provided preliminary evidence that technological innovation shares causal relation with public health. Dove Medical Press 2013-01-23 /pmc/articles/PMC3556917/ /pubmed/23378771 http://dx.doi.org/10.2147/JMDH.S34810 Text en © 2013 Gill, publisher and licensee Dove Medical Press Ltd. This is an Open Access article which permits unrestricted noncommercial use, provided the original work is properly cited.
spellingShingle Original Research
Gill, Preetinder Singh
Technological innovation and its effect on public health in the United States
title Technological innovation and its effect on public health in the United States
title_full Technological innovation and its effect on public health in the United States
title_fullStr Technological innovation and its effect on public health in the United States
title_full_unstemmed Technological innovation and its effect on public health in the United States
title_short Technological innovation and its effect on public health in the United States
title_sort technological innovation and its effect on public health in the united states
topic Original Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC3556917/
https://www.ncbi.nlm.nih.gov/pubmed/23378771
http://dx.doi.org/10.2147/JMDH.S34810
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