Abstract
Type 2 diabetes is known to contribute to health disparities in the U.S. and failure to adhere to recommended self-care behaviors is a contributing factor. Intervention programs face difficulties as a result of patient diversity and limited resources. With data from the 2005 Behavioral Risk Factor Surveillance System, this study employs a logistic regression tree algorithm to identify characteristics of sub-populations with type 2 diabetes according to their reported frequency of adherence to four recommended diabetes self-care behaviors including blood glucose monitoring, foot examination, eye examination and HbA1c testing. Using Andersen’s health behavior model, need factors appear to dominate the definition of which sub-groups were at greatest risk for low as well as high adherence. Findings demonstrate the utility of easily interpreted tree diagrams to design specific culturally appropriate intervention programs targeting sub-populations of diabetes patients who need to improve their self-care behaviors. Limitations and contributions of the study are discussed.
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We gratefully acknowledge Dr. Jennifer M. Kinney’s helpful comments and editorial suggestions in the earlier version of this paper.
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Yamashita, T., Kart, C.S. & Noe, D.A. Predictors of adherence with self-care guidelines among persons with type 2 diabetes: results from a logistic regression tree analysis. J Behav Med 35, 603–615 (2012). https://doi.org/10.1007/s10865-011-9392-y
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DOI: https://doi.org/10.1007/s10865-011-9392-y