Evaluating a Glucose-Sensor-Based Tool to Help Clinicians and Adults With Type 1 Diabetes Improve Self-Management Skills

J Diabetes Sci Technol. 2018 Nov;12(6):1143-1151. doi: 10.1177/1932296818791534. Epub 2018 Jul 31.


Background: The goal of this uncontrolled pilot study was to assess the feasibility of a self-care management mobile app, called Sugar Sleuth, which incorporates the FreeStyle Libre™ glucose sensor, to help clinicians and people with type 1 diabetes (PWD) identify and mitigate self-care behaviors that contribute to glucose variability.

Methods: PWDs with a baseline A1c between 7.5 and 9.0% used the mobile app for 14 weeks. The app prompted the PWD to enter the suspected cause of detected glycemic excursions, and to record food and insulin information. PWDs met with clinicians to collaboratively review data, identify challenges, and devise a specific self-care plan. Outcome measures included a single glycemic outcome score (SGOS) and attitude rating scales to better understand how participant attitudes could affect glycemic outcome.

Results: Thirty enrolled PWDs had a mean age of 55 ± 2.6 years, and a mean diabetes duration of 32 ± 2.9 years. A significant average reduction in A1c of 0.5 ± 0.07% ( P < .01) and in mean daily carbohydrate intake of 43 ± 21 grams ( P = .05) was found. No statistically significant change in glycemic metrics, body weight, or total daily insulin dose was found. A significant negative association occurred between SGOS and "hypoglycemia tolerance" ( P = .04), and a positive correlation occurred that approached significance with "motivation to change behavior" ( P = .06).

Conclusions: These findings suggest that this mobile app system, in conjunction with CGM, provides a useful platform for helping clinicians and adults with T1D improve self-management skills to improve glycemic control.

Keywords: continuous glucose monitoring; diabetes therapy decision support; self-management.

Publication types

  • Observational Study
  • Research Support, Non-U.S. Gov't

MeSH terms

  • Adult
  • Aged
  • Biosensing Techniques / instrumentation*
  • Blood Glucose / analysis*
  • Blood Glucose Self-Monitoring / instrumentation
  • Decision Support Techniques
  • Diabetes Mellitus, Type 1 / blood
  • Diabetes Mellitus, Type 1 / drug therapy
  • Diabetes Mellitus, Type 1 / therapy*
  • Feasibility Studies
  • Female
  • Humans
  • Insulin / administration & dosage
  • Insulin Infusion Systems
  • Male
  • Middle Aged
  • Mobile Applications*
  • Pilot Projects
  • Self Care / instrumentation*
  • Self Care / methods
  • Self-Management* / methods
  • Smartphone* / instrumentation


  • Blood Glucose
  • Insulin