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Identification of diabetes self-management profiles in adults: A cluster analysis using selected self-reported outcomes

The present study describes adult diabetes self-management (DSM) profiles using self-reported outcomes associated with the engagement in diabetes care activities and psychological adjustment to the disease. We used self-reported data from a community-based cohort of adults with diabetes (N = 316) an...

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Autores principales: Alexandre, Ketia, Vallet, Fanny, Peytremann-Bridevaux, Isabelle, Desrichard, Olivier
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2021
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7822269/
https://www.ncbi.nlm.nih.gov/pubmed/33481883
http://dx.doi.org/10.1371/journal.pone.0245721
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author Alexandre, Ketia
Vallet, Fanny
Peytremann-Bridevaux, Isabelle
Desrichard, Olivier
author_facet Alexandre, Ketia
Vallet, Fanny
Peytremann-Bridevaux, Isabelle
Desrichard, Olivier
author_sort Alexandre, Ketia
collection PubMed
description The present study describes adult diabetes self-management (DSM) profiles using self-reported outcomes associated with the engagement in diabetes care activities and psychological adjustment to the disease. We used self-reported data from a community-based cohort of adults with diabetes (N = 316) and conducted a cluster analysis of selected self-reported DSM outcomes (i.e., DSM behaviors, self-efficacy and perceived empowerment, diabetes distress and quality of life). We tested whether clusters differed according to sociodemographic, clinical, and care delivery processes variables. Cluster analysis revealed four distinct DSM profiles that combined high/low levels of engagement in diabetes care activities and good/poor psychological adjustment to the disease. The profiles were differently associated with the variables of perceived financial insecurity, taking insulin treatment, having depression, and the congruence of the care received with the Chronic Care Model. The results could help health professionals gain a better understanding of the different realities facing people living with diabetes, identify patients at risk of poor outcomes related to their DSM, and lead to the development of profile-specific DSM interventions.
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spelling pubmed-78222692021-01-29 Identification of diabetes self-management profiles in adults: A cluster analysis using selected self-reported outcomes Alexandre, Ketia Vallet, Fanny Peytremann-Bridevaux, Isabelle Desrichard, Olivier PLoS One Research Article The present study describes adult diabetes self-management (DSM) profiles using self-reported outcomes associated with the engagement in diabetes care activities and psychological adjustment to the disease. We used self-reported data from a community-based cohort of adults with diabetes (N = 316) and conducted a cluster analysis of selected self-reported DSM outcomes (i.e., DSM behaviors, self-efficacy and perceived empowerment, diabetes distress and quality of life). We tested whether clusters differed according to sociodemographic, clinical, and care delivery processes variables. Cluster analysis revealed four distinct DSM profiles that combined high/low levels of engagement in diabetes care activities and good/poor psychological adjustment to the disease. The profiles were differently associated with the variables of perceived financial insecurity, taking insulin treatment, having depression, and the congruence of the care received with the Chronic Care Model. The results could help health professionals gain a better understanding of the different realities facing people living with diabetes, identify patients at risk of poor outcomes related to their DSM, and lead to the development of profile-specific DSM interventions. Public Library of Science 2021-01-22 /pmc/articles/PMC7822269/ /pubmed/33481883 http://dx.doi.org/10.1371/journal.pone.0245721 Text en © 2021 Alexandre et al http://creativecommons.org/licenses/by/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution License (http://creativecommons.org/licenses/by/4.0/) , which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
spellingShingle Research Article
Alexandre, Ketia
Vallet, Fanny
Peytremann-Bridevaux, Isabelle
Desrichard, Olivier
Identification of diabetes self-management profiles in adults: A cluster analysis using selected self-reported outcomes
title Identification of diabetes self-management profiles in adults: A cluster analysis using selected self-reported outcomes
title_full Identification of diabetes self-management profiles in adults: A cluster analysis using selected self-reported outcomes
title_fullStr Identification of diabetes self-management profiles in adults: A cluster analysis using selected self-reported outcomes
title_full_unstemmed Identification of diabetes self-management profiles in adults: A cluster analysis using selected self-reported outcomes
title_short Identification of diabetes self-management profiles in adults: A cluster analysis using selected self-reported outcomes
title_sort identification of diabetes self-management profiles in adults: a cluster analysis using selected self-reported outcomes
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7822269/
https://www.ncbi.nlm.nih.gov/pubmed/33481883
http://dx.doi.org/10.1371/journal.pone.0245721
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