What is it about?
Few studies on diabetes self-management considered the patterns and relationships of different self-management behaviours (SMB). The aims of the present study are 1) to identify patterns of SMB among persons with diabetes, 2) to identify sociodemographic and disease-related predictors of SMB among persons with diabetes
Featured Image
Photo by Mykenzie Johnson on Unsplash
Why is it important?
In the present nationwide population-based study, a large proportion of persons with diabetes showed suboptimal self-management behaviour. Participation in a DSME program was the strongest predictor of good self-management. Results underline the need for continual and consistent health education for patients with diabetes.
Perspectives
The present study adds an empirical typology of different types of self-management patterns based on population-based data to the existent literature. By employing latent class models, we identify coherent patterns of diabetes self-management by a data-appropriate method. In opposition to composite scores or the analysis of single item indicators, latent class models take account of the co-occurrences of various forms of diabetes self-management. Contrary to other operationalisations of diabetes self-management, we conceptualized adherence in diabetes self-management as a categorical, latent variable and used latent class models to separate this construct from its corresponding measurement error.
Marcus Heise
Martin Luther University Halle-Wittenberg
Read the Original
This page is a summary of: Patterns and associated factors of diabetes self-management: Results of a latent class analysis in a German population-based study, PLoS ONE, March 2021, PLOS,
DOI: 10.1371/journal.pone.0248992.
You can read the full text:
Resources
Contributors
The following have contributed to this page
