title: What are the quality of life-related benefits and losses associated with real-time continuous glucose monitoring? A survey of current users.
abstract: 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.
  
  
  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.
authors: University of California, San Diego, San Diego, California, USA. whp@behavioraldiabetes.org
authors: William H
authors: WH
authors: Polonsky
authors: Danielle
authors: D
authors: Hessler
mesh_terms: D000328:Adult; D001786:Blood Glucose / Q000378:metabolism; D015190:Blood Glucose Self-Monitoring / Q000379:methods / Q000523:psychology*; D003430:Cross-Sectional Studies; D003922:Diabetes Mellitus, Type 1 / Q000097:blood / Q000453:epidemiology / Q000523:psychology*; D003924:Diabetes Mellitus, Type 2 / Q000097:blood / Q000453:epidemiology / Q000523:psychology*; D034742:Electronic Mail; D005260:Female; D006442:Glycated Hemoglobin / Q000378:metabolism; D006801:Humans; D007003:Hypoglycemia / Q000097:blood / Q000453:epidemiology / Q000517:prevention & control*; D007004:Hypoglycemic Agents / Q000627:therapeutic use; D007332:Insulin Infusion Systems; D008297:Male; D008875:Middle Aged; D018670:Monitoring, Ambulatory / Q000379:methods / Q000523:psychology*; D017060:Patient Satisfaction; D011788:Quality of Life; D015203:Reproducibility of Results; D011795:Surveys and Questionnaires
chemical_list: D001786:Blood Glucose; D006442:Glycated Hemoglobin; D007004:Hypoglycemic Agents; C517652:hemoglobin A1c protein, human