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Creating a measure to operationalize engaged well-being at work

BACKGROUND: Mental well-being and work engagement are both desirable, positive states of mind that help employees to better function in the workplace. While occupational researchers have argued in favor of considering both states concurrently, it is less clear how this might be translated to provide...

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Autores principales: Bosle, Catherin, Fischer, Joachim E., Herr, Raphael M.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7962289/
https://www.ncbi.nlm.nih.gov/pubmed/33726800
http://dx.doi.org/10.1186/s12995-021-00297-0
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author Bosle, Catherin
Fischer, Joachim E.
Herr, Raphael M.
author_facet Bosle, Catherin
Fischer, Joachim E.
Herr, Raphael M.
author_sort Bosle, Catherin
collection PubMed
description BACKGROUND: Mental well-being and work engagement are both desirable, positive states of mind that help employees to better function in the workplace. While occupational researchers have argued in favor of considering both states concurrently, it is less clear how this might be translated to provide an instrument characterizing the workforce accordingly. The present study describes empirical efforts to operationalize a construct called engaged well-being. METHODS: We used employee-level data (n = 13,538) from three waves of the German linked personnel panel (LPP; 2012–2017). Exploratory factor analysis and a combination of hierarchical and non-hierarchical cluster analyses linked with within-sum-of-squares statistics were used to identify distinct profiles describing mental well-being and work engagement concurrently. These profiles were then used as the basis to identify cut-offs to create replicable categories of engaged well-being. Using the longitudinal data from a subgroup providing data across more than one wave, we observed whether the newly constructed indicator changed over time. RESULTS: The exploratory factor analysis suggested that both states were two distinct factors. Cluster analysis linked with within-sum-of-squares statistics suggested a four-cluster solution: engaged well-being (46.9%), disengaged well-being (27.5%), engaged strain (8.8%), and disengaged strain (16.8%). One cut-off for each state was identified to replicate the cluster solution. Across observation periods, we could observe changes in engaged well-being. CONCLUSIONS: Our measure of engaged well-being can be used to simultaneously characterize a workforce’s mental well-being and work engagement. Changes in this measure over time suggest its potential utility in organizational interventions. Future studies are needed to further explore both the antecedents, correlates, and potential effects of engaged well-being.
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spelling pubmed-79622892021-03-16 Creating a measure to operationalize engaged well-being at work Bosle, Catherin Fischer, Joachim E. Herr, Raphael M. J Occup Med Toxicol Research BACKGROUND: Mental well-being and work engagement are both desirable, positive states of mind that help employees to better function in the workplace. While occupational researchers have argued in favor of considering both states concurrently, it is less clear how this might be translated to provide an instrument characterizing the workforce accordingly. The present study describes empirical efforts to operationalize a construct called engaged well-being. METHODS: We used employee-level data (n = 13,538) from three waves of the German linked personnel panel (LPP; 2012–2017). Exploratory factor analysis and a combination of hierarchical and non-hierarchical cluster analyses linked with within-sum-of-squares statistics were used to identify distinct profiles describing mental well-being and work engagement concurrently. These profiles were then used as the basis to identify cut-offs to create replicable categories of engaged well-being. Using the longitudinal data from a subgroup providing data across more than one wave, we observed whether the newly constructed indicator changed over time. RESULTS: The exploratory factor analysis suggested that both states were two distinct factors. Cluster analysis linked with within-sum-of-squares statistics suggested a four-cluster solution: engaged well-being (46.9%), disengaged well-being (27.5%), engaged strain (8.8%), and disengaged strain (16.8%). One cut-off for each state was identified to replicate the cluster solution. Across observation periods, we could observe changes in engaged well-being. CONCLUSIONS: Our measure of engaged well-being can be used to simultaneously characterize a workforce’s mental well-being and work engagement. Changes in this measure over time suggest its potential utility in organizational interventions. Future studies are needed to further explore both the antecedents, correlates, and potential effects of engaged well-being. BioMed Central 2021-03-16 /pmc/articles/PMC7962289/ /pubmed/33726800 http://dx.doi.org/10.1186/s12995-021-00297-0 Text en © The Author(s) 2021 Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Research
Bosle, Catherin
Fischer, Joachim E.
Herr, Raphael M.
Creating a measure to operationalize engaged well-being at work
title Creating a measure to operationalize engaged well-being at work
title_full Creating a measure to operationalize engaged well-being at work
title_fullStr Creating a measure to operationalize engaged well-being at work
title_full_unstemmed Creating a measure to operationalize engaged well-being at work
title_short Creating a measure to operationalize engaged well-being at work
title_sort creating a measure to operationalize engaged well-being at work
topic Research
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7962289/
https://www.ncbi.nlm.nih.gov/pubmed/33726800
http://dx.doi.org/10.1186/s12995-021-00297-0
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