Background: To examine whether the social adaptability index (SAI) alone or components of the index provide a better explanatory model for self-care and diabetes outcomes.

Methods: Six hundred fifteen patients were recruited from two primary care settings. A series of multiple linear regression models were run to assess (1) associations between the SAI and diabetes self-care/outcomes, and (2) associations between individual SAI indicator variables and diabetes self-care/outcomes. Separate models were run for each self-care behavior and outcome. Two models were run for each dependent variable to compare associations with the SAI and components of the index.

Results: The SAI has a significant association with the mental component of quality of life (0.23, p < 0.01). In adjusted analyses, the SAI score did not have a significant association with any of the self-care behaviors. Individual components from the index had significant associations between self-care and multiple SAI indicator variables. Significant associations also exist between outcomes and the individual SAI indicators for education and employment.

Conclusions: In this population, the SAI has low explanatory power and few significant associations with diabetes self-care/outcomes. While the use of a composite index to predict outcomes within a diabetes population would have high utility, particularly for clinical settings, this SAI lacks statistical and clinical significance in a representative diabetes population. Based on these results, the index does not provide a good model fit and masks the relationship of individual components to diabetes self-care and outcomes. These findings suggest that five items alone are not adequate to explain or predict outcomes for patients with type 2 diabetes.

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Published in BMC Endocrine Disorders, v. 17, 34, p. 1-9.

© The Author(s). 2017

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This study was supported by the National Institute of Diabetes and Digestive and Kidney Diseases (Grant K24DK093699, Principal Investigator: Leonard Egede, MD).

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The datasets generated and/or analysed during the current study are not publicly available due to the collection of data from United States Veterans. The Department of Veterans Affairs prohibits data collected from veterans from being made publically available without prior consent and authorization.