Factors affecting self-care behavior levels among elderly patients with type 2 diabetes: A quantile regression approach

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Abstract

Background and objectives: Identifying factors that affect self-care according to low, middle, and high self-care levels among elderly patients with diabetes is the best way to prevent various life-threatening complications, and this can be accomplished by using an individualized approach to improve self-care. A quantile regression model is beneficial for estimating such factors because it allows the consideration of the entire conditional distribution of a dependent variable as it relates to independent variables. The objective of this study was to identify factors that affect self-care among elderly patients with diabetes using quantile regression. Materials and Methods: A cross-sectional survey of elderly patients with diabetes was conducted using the Self-Care Scale and six other related scales at three medical health centers in South Korea. Results: In the 10% quantile, the factors affecting self-care were age, smoking within the past six months, being educated about diabetes, depression, knowledge related to diabetes, self-efficacy, diabetes distress, and family support. Additional factors were as follows: age, smoking within the past six months, self-efficacy, and diabetes distress in the 25% quantile; age, self-efficacy, perceived health status, and diabetes distress in the 50% quantile; age, self-efficacy, perceived health status, and diabetes distress in the 75% quantile; and self-efficacy and perceived health status in the 90% quantile. Conclusions: Based on the results of this study, suggestions include providing education for sub-groups incapable of self-care, teaching stress management strategies, and increasing family support. In addition, for individuals capable of self-care, simplified programs that consist of self-efficacy improvement and stress control strategies are necessary.

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Kim, M. Y., & Lee, E. J. (2019). Factors affecting self-care behavior levels among elderly patients with type 2 diabetes: A quantile regression approach. Medicina (Lithuania), 55(7). https://doi.org/10.3390/medicina55070340

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