Diabetes Technology & Therapeutics · 2013 · 116 citations · 17 references
Social SciencesHealth BehaviorPsychologyHealth AssessmentHealth PsychologyPsychometricsContinuous Glucose MonitoringDiabetes ManagementDiabetes MellitusGlycemic ControlGlycemic MonitoringQuality Of LifeAccuracyGlucose MonitoringGlucose Monitoring DevicesPatient-reported Utility MeasurementPerceived Benefits Of ChangePerceived ControlPerceived Control Loss
BACKGROUND: How does real-time (RT) continuous glucose monitoring (CGM) affect quality of life (QOL)? We explored the types and frequencies of diabetes-specific QOL changes resulting from RT-CGM as reported by current users and investigated what patient-reported factors predict these changes. SUBJECTS AND METHODS: Current RT-CGM users (n = 877) completed an online questionnaire investigating perceived QOL benefits/losses since RT-CGM initiation and RT-CGM attitudes and behavior. Exploratory factor analysis (EFA) examined the 16 QOL benefit/loss items to identify underlying factors. Regression analyses examined associations between demographics and RT-CGM attitudes and behavior with the QOL factors emerging from the EFA. RESULTS: Three major QOL factors emerged: Perceived Control over Diabetes, Hypoglycemic Safety, and Interpersonal Support. QOL improvement was common for Perceived Control over Diabetes and Hypoglycemic Safety (86% and 85% of respondents, respectively), although less common for Interpersonal Support (37%). Consistent independent predictors of perceived benefits were greater confidence in using RT-CGM data (P<0.001), satisfaction with device accuracy (P ≤ 0.05) and usability (P<0.01), older age (P<0.01), more frequent receiver screen views (P<0.05), and use of multiple daily injections (Hypoglycemic Safety and Interpersonal Support, P ≤ 0.05). CONCLUSIONS: Diabetes-specific QOL benefits resulting from RT-CGM were common. Major predictors of QOL benefits were satisfaction with device accuracy and usability and trust in one's ability to use RT-CGM data, suggesting that "perceived efficacy," for both device and self, are key QOL determinants. Psychoeducational strategies to boost confidence in using RT-CGM data and provide reasonable device expectations might enhance QOL benefits.
17
Assessing Psychosocial Distress in Diabetes
William H. Polonsky, Lawrence Fisher, Jay E. Earles et al. · Diabetes Care · 2005 · 1.6K citations · Full text
Nursing, Psychology, Diabetology +16
Effect of Continuous Glucose Monitoring on Hypoglycemia in Type 1 Diabetes
Tadej Battelino, Moshe Phillip, Nataša Bratina et al. · Diabetes Care · 2011 · 491 citations · Full text
The Effect of Continuous Glucose Monitoring in Well-Controlled Type 1 Diabetes
Diabetes Care · 2009 · 397 citations · Full text
Medicine, Endocrinology, Pediatrics +17