It would be invaluable to understanding therapeutic and behavioral adherence if we could discern what the patient was thinking at a decision point, e.g. Investigators have primarily studied self-reported data from surveys and interviews to typify SMB. However, even when these tools are available it is still difficult for patients to meet glycemic goals and little is understood about how patients include bolus calculators into their self-care beyond measuring frequency of use. Tools such as insulin bolus calculators embedded into glucose meters and insulin pumps are designed to aid patients in making accurate insulin dosing decisions. Patients who consistently engage in self-management behaviors (SMBs) and are adherent to standard treatment protocols are more likely to have better glycemic control.Įxamples of SMBs include monitoring BG, recording carbohydrate intake, administering insulin boluses (i.e., one large dose, generally between 1 and 15 units) to compensate for carbohydrate intake, and exercising. Poor glycemic control can lead to devastating complications including organ damage and increased mortality from heart disease. The goal of glycemic management is to maintain BG levels in a desired target range avoiding high blood sugars (hyperglycemia) and low blood sugars (hypoglycemia). Effective treatment requires insulin injections before meals and throughout the day both to maintain BG as well as to offset above-target glucose levels. The lack of insulin results in elevated blood glucose (BG). T1D is a chronic condition in which the pancreas does not produce insulin. Type 1 diabetes (T1D) is a complex disease that affects 1.2 million people in the United States and has an estimated worldwide prevalence of 5 to 10% of all cases of diabetes. Future work will use the developed app to collect SMBs and CTs and identify patient-specific diabetes adherence barriers that could be addressed with individualized education interventions. The high variability found in SMBs and CTs highlights the need for real-time diabetes self-tracking mechanisms to better understand SMBs and CTs. There was low concordance of 35% (35) and 46% (41) for alcohol and exercise events, respectively. Comparisons of survey responses and iDECIDE logs showed mean% (standard deviation) concordance of 77% (25) for SMBs related to meals, where concordance of 100% indicates a perfect match. Participants also recorded 76 alcohol and 166 exercise CTs. Thirteen participants recorded over 1,200 CTs for carbohydrates during the 30-day study. Usability studies revealed that participants desired advanced features for self-tracking meals and alcohol intake. Survey results were compared against iDECIDE logs. A survey designed to capture diabetes SMBs and CTs was administered prior to the 30-day pilot test. These were followed by a 30-day pilot test of the redesigned app. Two usability studies were used to improve iDECIDE's functionality. The article aims to use a patient-centered approach to design iDECIDE, a smartphone application that gathers daily diabetes SMBs and CTs related to meal and alcohol intake and exercise in real-time, and contrast patients' actual behaviors against those self-reported with the app. There is little information on adult T1D SMBs, along with corresponding compensation techniques (CTs), gathered in real-time. Preliminary studies on SMBs rely mainly on self-reported survey and interview data. Type 1 diabetes (T1D) care requires multiple daily self-management behaviors (SMBs).

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