Matching Items (2)
Description
Type 1 Diabetes Mellitus (T1DM) is a chronic disease that requires maintaining tight metabolic control through complex behavioral and pharmaceutical regimens. Subtle cognitive impairments and stress response dysregulation may partially account for problems negotiating life changes and maintaining treatment adherence among emerging adults. The current study examined whether young adults with T1DM physiologically respond to psychological stress in a dysregulated manner compared to non-diabetic peers, and if such individuals also demonstrated greater cognitive declines following psychological stress. Participants included 23 young adults with T1DM and 52 non-diabetic controls yoked to T1DM participants based on age, gender, ethnicity, participant education, and maternal education. Participants completed a laboratory-based social stressor, pre- and post-stressor neurocognitive testing, provided fingerstick blood spots (for glucose levels) and salivary samples (for cortisol levels) at five points across the protocol, and completed psychosocial questionnaires. Related measures ANOVAs were conducted to assess differences between T1DM participants and the average of yoked controls on cortisol and cognitive outcomes. Results demonstrated that differences in cortisol reactivity were dependent on T1DM participants' use of insulin pump therapy (IPT). T1DM participants not using IPT demonstrated elevated cortisol reactivity compared to matched controls. There was no difference in cortisol reactivity between the T1DM participants on IPT and matched controls. On the Stroop task, performance patterns did not differ between participants with T1DM not on IPT and matched controls. The performance of participants with T1DM on IPT slightly improved following the stressor and matched controls slightly worsened. On the Trail Making Test, the performance of participants with T1DM was not different following the stressor whereas participants without T1DM demonstrated a decline following the stressor. Participants with and without T1DM did not differ in patterns of performance on the Rey Verbal Learning Task, Sustained Attention Allocation Task, Controlled Oral Word Association Task, or overall cortisol output across participation. The results of this study are suggestive of an exaggerated cortisol response to psychological stress in T1DM and indicate potential direct and indirect protective influences of IPT.
ContributorsMarreiro, Catherine (Author) / Luecken, Linda (Thesis advisor) / Doane, Leah (Thesis advisor) / Barrera, Manuel (Committee member) / Aiken, Leona (Committee member) / Arizona State University (Publisher)
Created2013
Description
Type 1 diabetes (T1D) is a chronic disease that affects 1.25 million people in the United States. There is no known cure and patients must self-manage the disease to avoid complications resulting from blood glucose (BG) excursions. Patients are more likely to adhere to treatments when they incorporate lifestyle preferences. Current technologies that assist patients fail to consider two factors that are known to affect BG: exercise and alcohol. The hypothesis is postprandial blood glucose levels of adult patients with T1D can be improved by providing insulin bolus or carbohydrate recommendations that account for meal and alcohol carbohydrates, glycemic excursion, and planned exercise. I propose an evidence-based decision support tool, iDECIDE, to make recommendations to improve glucose control by taking into account meal and alcohol carbohydrates, glycemic excursion and planned exercise. iDECIDE is deployed as a low-cost and easy to disseminate smartphone application.
A literature review was conducted on T1D and the state-of-the-art in diabetes technology. To better understand self-management behaviors and guide the development of iDECIDE, several data sources were collected and analyzed: surveys, insulin pump paired with glucose monitoring, and self-tracking of exercise and alcohol. The analysis showed variability in compensation techniques for exercise and alcohol and that patients made unaided decisions, suggesting a need for better decision support.
The iDECIDE algorithm can make insulin and carbohydrate recommendations. Since there were no existing in-silico methods for assessing bolus calculators, like iDECIDE, I proposed a novel methodology to retrospectively compare insulin pump bolus calculators. Application of the methodology shows that iDECIDE outperformed the Medtronic insulin pump bolus calculator and could have improved glucose control.
This work makes contributions to diabetes technology researchers, clinicians and patients. The iDECIDE app provides patients easy access to a decision support tool that can improve glucose control. The study of behaviors from diabetes technology and self-report patient data can inform clinicians and the design of future technologies and bedside tools that integrate patient’s behaviors and perceptions. The comparison methodology provides a means for clinical informatics researchers to identify and retrospectively test promising insulin blousing algorithms using real-life data.
A literature review was conducted on T1D and the state-of-the-art in diabetes technology. To better understand self-management behaviors and guide the development of iDECIDE, several data sources were collected and analyzed: surveys, insulin pump paired with glucose monitoring, and self-tracking of exercise and alcohol. The analysis showed variability in compensation techniques for exercise and alcohol and that patients made unaided decisions, suggesting a need for better decision support.
The iDECIDE algorithm can make insulin and carbohydrate recommendations. Since there were no existing in-silico methods for assessing bolus calculators, like iDECIDE, I proposed a novel methodology to retrospectively compare insulin pump bolus calculators. Application of the methodology shows that iDECIDE outperformed the Medtronic insulin pump bolus calculator and could have improved glucose control.
This work makes contributions to diabetes technology researchers, clinicians and patients. The iDECIDE app provides patients easy access to a decision support tool that can improve glucose control. The study of behaviors from diabetes technology and self-report patient data can inform clinicians and the design of future technologies and bedside tools that integrate patient’s behaviors and perceptions. The comparison methodology provides a means for clinical informatics researchers to identify and retrospectively test promising insulin blousing algorithms using real-life data.
ContributorsGroat, Danielle (Author) / Grando, Maria Adela (Thesis advisor) / Kaufman, David (Committee member) / Thompson, Bithika (Committee member) / Arizona State University (Publisher)
Created2017