Predictors of Adherence with Self-care Guidelines Among Persons with Type 2 Diabetes: Results from a Logistic Regression Tree Analysis

Overview

Journal J Behav Med

Specialty Social Sciences

Date 2011 Dec 14

PMID 22160934

Citations 5

Authors

Takashi Yamashita

Cary S Kart

Douglas A Noe

Affiliations

Soon will be listed here.

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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