Self-Management Model fails to Predict Quality of Life for People Living with Dual Diagnosis of HIV and Diabetes.

Abstract

The objective of this study was to test a self-management model for self-management in people living with HIV and type 2 diabetes (PLWH + T2DM). We conducted a predictive, longitudinal study of data from a national research cohort of PLWH using lag analysis to test short- and long-term health outcomes for PLWH + T2DM. We used a dataset from the Center for AIDS Research (CFAR) Network of Integrated Clinic Systems (CNICS), a nation-wide research network of 8 clinics that serves PLWH. Patient-reported outcomes, collected at clinic visit, included depression, adherence, CD4 cell count, and health-related quality of life (HRQoL). We computed summary statistics to describe the sample. Using lag analysis, we then modeled the three variables of adherence, CD4 count, and HRQoL as a function of their predecessors in our conceptual model. In the final model, an increase of in medication adherence corresponded to a small increase in HRQoL. An increase in CD4 count corresponded to a small increase in HRQoL. An increase in lagged depression was associated with a small decrease in HRQoL. The model was not sufficient to predict short- or long-term outcomes in PLWH + T2DM. Although depression had a moderate impact, the final model was not clinically significant. For people with a dual diagnosis of HIV and T2DM, variables other than those traditionally addressed in self-management interventions may be more important.