Department of Biomedical Informatics, University of Utah, Salt Lake City, Utah, United States.
Department of Biomedical Informatics, Arizona State University, Scottsdale, Arizona, United States.
Appl Clin Inform. 2018 Apr;9(2):440-449. doi: 10.1055/s-0038-1660438. Epub 2018 Jun 20.
Type 1 diabetes (T1D) care requires multiple daily self-management behaviors (SMBs). Preliminary studies on SMBs rely mainly on self-reported survey and interview data. There is little information on adult T1D SMBs, along with corresponding compensation techniques (CTs), gathered in real-time.
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.
Two usability studies were used to improve iDECIDE's functionality. These were followed by a 30-day pilot test of the redesigned app. A survey designed to capture diabetes SMBs and CTs was administered prior to the 30-day pilot test. Survey results were compared against iDECIDE logs.
Usability studies revealed that participants desired advanced features for self-tracking meals and alcohol intake. Thirteen participants recorded over 1,200 CTs for carbohydrates during the 30-day study. Participants also recorded 76 alcohol and 166 exercise CTs. 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. There was low concordance of 35% (35) and 46% (41) for alcohol and exercise events, respectively.
The high variability found in SMBs and CTs highlights the need for real-time diabetes self-tracking mechanisms to better understand SMBs and CTs. 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.
1 型糖尿病（T1D）的护理需要患者进行多次日常自我管理行为（SMB）。初步的 SMB 研究主要依赖于自我报告的调查和访谈数据。目前，很少有关于成人 T1D SMB 及其相应补偿技术（CT）的实时信息。
本文旨在采用以患者为中心的方法设计 iDECIDE，这是一款智能手机应用程序，可实时收集与进餐、饮酒和运动相关的日常糖尿病 SMB 和 CT，并将患者的实际行为与应用程序中的自我报告进行对比。
我们进行了两项可用性研究来改进 iDECIDE 的功能。之后，对重新设计的应用程序进行了为期 30 天的试点测试。在 30 天试点测试之前，我们采用了一项旨在捕获糖尿病 SMB 和 CT 的调查。将调查结果与 iDECIDE 日志进行了对比。
可用性研究表明，参与者希望为自我记录进餐和饮酒摄入情况添加高级功能。在 30 天的研究中，有 13 名参与者记录了超过 1200 次碳水化合物 CT。参与者还记录了 76 次饮酒和 166 次运动 CT。调查回复和 iDECIDE 日志的对比显示，与进餐相关的 SMB 的平均%（标准差）一致性为 77%（25），一致性达到 100%表示完全匹配。饮酒和运动事件的一致性分别为 35%（35）和 46%（41），一致性较低。
在 SMB 和 CT 中发现的高度可变性突出表明，需要实时糖尿病自我跟踪机制来更好地理解 SMB 和 CT。未来的工作将使用开发的应用程序来收集 SMB 和 CT，并确定可能需要个体化教育干预来解决的特定于患者的糖尿病依从性障碍。
