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Determining rural risk for aneurysmal subarachnoid hemorrhages: A structural equation modeling approach

An aneurysmal subarachnoid hemorrhage (aSAH) carries a high disability burden. The true impact of rurality as a predictor of outcome severity is unknown. Our aim is to clarify the relationship between the proposed explanations of regional and rural health disparities linked to severity of outcome fo...

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Autores principales: Nichols, Linda Jayne, Gall, Seana, Stirling, Christine
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Medknow Publications & Media Pvt Ltd 2016
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5006469/
https://www.ncbi.nlm.nih.gov/pubmed/27695237
http://dx.doi.org/10.4103/0976-3147.188627
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author Nichols, Linda Jayne
Gall, Seana
Stirling, Christine
author_facet Nichols, Linda Jayne
Gall, Seana
Stirling, Christine
author_sort Nichols, Linda Jayne
collection PubMed
description An aneurysmal subarachnoid hemorrhage (aSAH) carries a high disability burden. The true impact of rurality as a predictor of outcome severity is unknown. Our aim is to clarify the relationship between the proposed explanations of regional and rural health disparities linked to severity of outcome following an aSAH. An initial literature search identified limited data directly linking geographical location, rurality, rural vulnerability, and aSAH. A further search noting parallels with ischemic stroke and acute myocardial infarct literature presented a number of diverse and interrelated predictors. This a priori knowledge informed the development of a conceptual framework that proposes the relationship between rurality and severity of outcome following an aSAH utilizing structural equation modeling. The presented conceptual framework explores a number of system, environmental, and modifiable risk factors. Socioeconomic characteristics, modifiable risk factors, and timely treatment that were identified as predictors of severity of outcome following an aSAH and within each of these defined predictors a number of contributing specific individual predictors are proposed. There are considerable gaps in the current knowledge pertaining to the impact of rurality on the severity of outcome following an aSAH. Absent from the literature is any investigation of the cumulative impact and multiplicity of risk factors associated with rurality. The proposed conceptual framework hypothesizes a number of relationships between both individual level and system level predictors, acknowledging that intervening predictors may mediate the effect of one variable on another.
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spelling pubmed-50064692016-10-01 Determining rural risk for aneurysmal subarachnoid hemorrhages: A structural equation modeling approach Nichols, Linda Jayne Gall, Seana Stirling, Christine J Neurosci Rural Pract Review Article An aneurysmal subarachnoid hemorrhage (aSAH) carries a high disability burden. The true impact of rurality as a predictor of outcome severity is unknown. Our aim is to clarify the relationship between the proposed explanations of regional and rural health disparities linked to severity of outcome following an aSAH. An initial literature search identified limited data directly linking geographical location, rurality, rural vulnerability, and aSAH. A further search noting parallels with ischemic stroke and acute myocardial infarct literature presented a number of diverse and interrelated predictors. This a priori knowledge informed the development of a conceptual framework that proposes the relationship between rurality and severity of outcome following an aSAH utilizing structural equation modeling. The presented conceptual framework explores a number of system, environmental, and modifiable risk factors. Socioeconomic characteristics, modifiable risk factors, and timely treatment that were identified as predictors of severity of outcome following an aSAH and within each of these defined predictors a number of contributing specific individual predictors are proposed. There are considerable gaps in the current knowledge pertaining to the impact of rurality on the severity of outcome following an aSAH. Absent from the literature is any investigation of the cumulative impact and multiplicity of risk factors associated with rurality. The proposed conceptual framework hypothesizes a number of relationships between both individual level and system level predictors, acknowledging that intervening predictors may mediate the effect of one variable on another. Medknow Publications & Media Pvt Ltd 2016 /pmc/articles/PMC5006469/ /pubmed/27695237 http://dx.doi.org/10.4103/0976-3147.188627 Text en Copyright: © Journal of Neurosciences in Rural Practice http://creativecommons.org/licenses/by-nc-sa/3.0 This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike 3.0 License, which allows others to remix, tweak, and build upon the work non-commercially, as long as the author is credited and the new creations are licensed under the identical terms.
spellingShingle Review Article
Nichols, Linda Jayne
Gall, Seana
Stirling, Christine
Determining rural risk for aneurysmal subarachnoid hemorrhages: A structural equation modeling approach
title Determining rural risk for aneurysmal subarachnoid hemorrhages: A structural equation modeling approach
title_full Determining rural risk for aneurysmal subarachnoid hemorrhages: A structural equation modeling approach
title_fullStr Determining rural risk for aneurysmal subarachnoid hemorrhages: A structural equation modeling approach
title_full_unstemmed Determining rural risk for aneurysmal subarachnoid hemorrhages: A structural equation modeling approach
title_short Determining rural risk for aneurysmal subarachnoid hemorrhages: A structural equation modeling approach
title_sort determining rural risk for aneurysmal subarachnoid hemorrhages: a structural equation modeling approach
topic Review Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5006469/
https://www.ncbi.nlm.nih.gov/pubmed/27695237
http://dx.doi.org/10.4103/0976-3147.188627
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