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

Détails

Ressource 1Télécharger: Alexandre_journal.pone.0245721.pdf (1139.60 [Ko])
Etat: Public
Version: Final published version
Licence: CC BY 4.0
ID Serval
serval:BIB_395DA46D13F8
Type
Article: article d'un périodique ou d'un magazine.
Sous-type
Synthèse (review): revue aussi complète que possible des connaissances sur un sujet, rédigée à partir de l'analyse exhaustive des travaux publiés.
Collection
Publications
Institution
Titre
Identification of diabetes self-management profiles in adults: A cluster analysis using selected self-reported outcomes.
Périodique
PloS one
Auteur⸱e⸱s
Alexandre K., Vallet F., Peytremann-Bridevaux I. (co-dernier), Desrichard O. (co-dernier)
ISSN
1932-6203 (Electronic)
ISSN-L
1932-6203
Statut éditorial
Publié
Date de publication
2021
Peer-reviewed
Oui
Volume
16
Numéro
1
Pages
e0245721
Langue
anglais
Notes
Publication types: Clinical Trial ; Journal Article
Publication Status: epublish
Résumé
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.
Mots-clé
Adult, Aged, Aged, 80 and over, Cross-Sectional Studies, Diabetes Mellitus, Type 1/therapy, Diabetes Mellitus, Type 2/therapy, Female, Health Behavior, Humans, Male, Middle Aged, Patient Reported Outcome Measures, Quality of Life, Self Report, Self-Management
Pubmed
Web of science
Open Access
Oui
Création de la notice
08/02/2021 9:52
Dernière modification de la notice
21/11/2022 9:31
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