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. 2016:2016:6708164.
doi: 10.1155/2016/6708164. Epub 2015 Dec 1.

Sociodemographic and Clinical Predictors of Self-Management among People with Poorly Controlled Type 1 and Type 2 Diabetes: The Role of Illness Perceptions and Self-Efficacy

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Sociodemographic and Clinical Predictors of Self-Management among People with Poorly Controlled Type 1 and Type 2 Diabetes: The Role of Illness Perceptions and Self-Efficacy

Abdul-Razak Abubakari et al. J Diabetes Res. 2016.

Abstract

Self-management is critical if people with diabetes are to minimise their risk of macrovascular and microvascular complications, yet adherence to self-management recommendations is suboptimal. Understanding the predictors of optimal diabetes self-management in specific populations is needed to inform effective interventions. This study investigated the role of demographic and clinical characteristics, illness perceptions, and self-efficacy in explaining adherence to self-management recommendations among people with poorly controlled diabetes in North West of England. Illness perceptions and self-efficacy data were collected using validated questionnaires and clinical data were obtained from hospital records. Correlations were used to investigate bivariate relationships between independent variables and self-management, and multiple regression techniques were used to determine demographic and psychosocial predictors of self-management. Various demographic and clinical characteristics were associated with adherence to self-management recommendations. In particular, employment status explained 11% of the variation in adherence to foot care whilst diabetes treatment category explained 9% of exercise and 21% of the variations in SMBG recommendations. Also, 22% and 8% of the variations in overall self-management were explained by illness perceptions and self-efficacy beliefs, respectively. Illness perceptions and self-efficacy beliefs of people with poorly controlled diabetes are important predictors of their self-management behaviours and could potentially guide effective interventions.

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