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Development of an early warning resilience survey for healthcare organizations

OBJECTIVE: To design and validate a brief set of measures identifying staff and work areas exhibiting low levels of resilience within healthcare organizations. DATA SOURCES/STUDY DESIGN: Primary data were gathered via survey administration between April and August of 2016 from 33,622 respondents acr...

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Autores principales: Morgan, Kristopher H., Libby, Nicholas E., Weaver, Amy K., Cai, Cindy
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Elsevier 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6839017/
https://www.ncbi.nlm.nih.gov/pubmed/31720458
http://dx.doi.org/10.1016/j.heliyon.2019.e02670
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author Morgan, Kristopher H.
Libby, Nicholas E.
Weaver, Amy K.
Cai, Cindy
author_facet Morgan, Kristopher H.
Libby, Nicholas E.
Weaver, Amy K.
Cai, Cindy
author_sort Morgan, Kristopher H.
collection PubMed
description OBJECTIVE: To design and validate a brief set of measures identifying staff and work areas exhibiting low levels of resilience within healthcare organizations. DATA SOURCES/STUDY DESIGN: Primary data were gathered via survey administration between April and August of 2016 from 33,622 respondents across 123 facilities. These surveys included pilot items designed to measure resilience and were administered to all employees alongside employee engagement surveys. DATA COLLECTION/EXTRACTION METHODS: Following the data collection period for the pilot survey, data from all organizations were integrated into a single analytical dataset. Factor analyses were used to determine the underlying constructs of healthcare worker resilience. Cronbach's alpha and correlation analyses tested the internal consistency and validity of the instrument. PRINCIPAL FINDINGS: A brief set consisting of eight items was identified as a psychometrically validated measure of resilience. This measure consists of two subscales, Activation and Decompression. These measures exist independent of employee engagement, indicating an empirical distinction between the two concepts. Resilience was found to predict 38% of variance in engagement scores. CONCLUSIONS: An eight-item instrument can accurately measure resilience to identify burnout risk and serve as a predictor of other workforce outcomes such as engagement.
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spelling pubmed-68390172019-11-12 Development of an early warning resilience survey for healthcare organizations Morgan, Kristopher H. Libby, Nicholas E. Weaver, Amy K. Cai, Cindy Heliyon Article OBJECTIVE: To design and validate a brief set of measures identifying staff and work areas exhibiting low levels of resilience within healthcare organizations. DATA SOURCES/STUDY DESIGN: Primary data were gathered via survey administration between April and August of 2016 from 33,622 respondents across 123 facilities. These surveys included pilot items designed to measure resilience and were administered to all employees alongside employee engagement surveys. DATA COLLECTION/EXTRACTION METHODS: Following the data collection period for the pilot survey, data from all organizations were integrated into a single analytical dataset. Factor analyses were used to determine the underlying constructs of healthcare worker resilience. Cronbach's alpha and correlation analyses tested the internal consistency and validity of the instrument. PRINCIPAL FINDINGS: A brief set consisting of eight items was identified as a psychometrically validated measure of resilience. This measure consists of two subscales, Activation and Decompression. These measures exist independent of employee engagement, indicating an empirical distinction between the two concepts. Resilience was found to predict 38% of variance in engagement scores. CONCLUSIONS: An eight-item instrument can accurately measure resilience to identify burnout risk and serve as a predictor of other workforce outcomes such as engagement. Elsevier 2019-11-01 /pmc/articles/PMC6839017/ /pubmed/31720458 http://dx.doi.org/10.1016/j.heliyon.2019.e02670 Text en © 2019 Published by Elsevier Ltd. http://creativecommons.org/licenses/by-nc-nd/4.0/ This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
spellingShingle Article
Morgan, Kristopher H.
Libby, Nicholas E.
Weaver, Amy K.
Cai, Cindy
Development of an early warning resilience survey for healthcare organizations
title Development of an early warning resilience survey for healthcare organizations
title_full Development of an early warning resilience survey for healthcare organizations
title_fullStr Development of an early warning resilience survey for healthcare organizations
title_full_unstemmed Development of an early warning resilience survey for healthcare organizations
title_short Development of an early warning resilience survey for healthcare organizations
title_sort development of an early warning resilience survey for healthcare organizations
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6839017/
https://www.ncbi.nlm.nih.gov/pubmed/31720458
http://dx.doi.org/10.1016/j.heliyon.2019.e02670
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