Evaluation of a Simulation-Based Educational Tool for Personalized Feedback in Insulin Therapy Management
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ClinicalTrials.gov Identifier: NCT01767831 |
Recruitment Status :
Terminated
(study team will review the collected data and make any necessary changes to the educational tool.)
First Posted : January 14, 2013
Last Update Posted : April 28, 2014
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Condition or disease | Intervention/treatment |
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Type 1 Diabetes Mellitus | Behavioral: iBOLUSED |
Study Type : | Observational |
Actual Enrollment : | 15 participants |
Observational Model: | Case-Crossover |
Time Perspective: | Prospective |
Official Title: | Evaluation of a Simulation-Based Educational Tool for Personalized Feedback in Insulin Therapy Management |
Study Start Date : | March 2013 |
Actual Primary Completion Date : | August 2013 |
Actual Study Completion Date : | August 2013 |

Group/Cohort | Intervention/treatment |
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Group A: CGM monitoring (1) vs Intervention
Participants will undergo a 1 week CGM monitoring period (session 1), followed by a 4 week intervention period using the iBOLUSED intervention. The 4 week intervention period will be followed by an additional CGM monitoring period (session 2). For those in Group A, we compare the data collection in CGM monitoring session 1 to the data collection in the intervention period.
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Behavioral: iBOLUSED
The intervention will involve daily diary data upload and daily simulation-based feedback based on the collected diary data. Throughout the educational intervention, participants will record diary data every day through the use of a diary component in the internet-based system. Diary entries include data on meals, physical activity, history of the insulin basal rate and insulin boluses given that day, self-reported stress level, hypo- and hyperglycemic fear levels, and, if applicable, menstrual cycle and any physical illness. Participants will also upload data from the CGM via the Dexcom DM3 software or the Dexcom Studio Software.
Other Name: iBOLUSED is an acronym for "Insight-Based Online Learning Using Simulation and Education for Diabetes" |
Group B: CGM monitoring (2) vs Intervention
Participants will undergo a 1 week CGM monitoring period (session 1), followed by a 4 week intervention period using the iBOLUSED intervention. The 4 week intervention period will be followed by an additional CGM monitoring period (session 2). For those in Group B, we compare the data collection in CGM monitoring session 2 to the data collection in the intervention period.
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Behavioral: iBOLUSED
The intervention will involve daily diary data upload and daily simulation-based feedback based on the collected diary data. Throughout the educational intervention, participants will record diary data every day through the use of a diary component in the internet-based system. Diary entries include data on meals, physical activity, history of the insulin basal rate and insulin boluses given that day, self-reported stress level, hypo- and hyperglycemic fear levels, and, if applicable, menstrual cycle and any physical illness. Participants will also upload data from the CGM via the Dexcom DM3 software or the Dexcom Studio Software.
Other Name: iBOLUSED is an acronym for "Insight-Based Online Learning Using Simulation and Education for Diabetes" |
- Accuracy of Feedback and Intervention Feasibility [ Time Frame: within 6 months of study conclusion ]We will assess the ability of our intervention to provide accurate, useful data to participants that can improve quality of life and educate patients regarding glycemic outcome based on participant feedback collected in focus groups, the post-intervention psychobehavioral assessment, and based on an analysis of the accuracy of the feedback data presented to users based on the input (diary) data. A comparison of input diary data metrics (glucose and insulin data) to output feedback (BG risk profiles, glycemic variability metrics) will allow us to quantify this accuracy. Feasibility of the intervention will be assessed through analysis of pre- and post- assessments, and through feedback provided by subjects during the focus group sessions. A statistician with a background in qualitative data analysis will analyze the psychobehavioral assessment and focus group data.
- Ability of Behavioral Intervention to Improve Glycemic Outcome [ Time Frame: within 6 months of study conclusion ]
Measure the ability of the simulation-based feedback system intervention to assist in improving the nominal glucose profile based on a pre- and post-intervention assessment of the data.
We hypothesize that, compared to the use of CGM alone, the educational system will result in:
A2.1: Increased time within target range, defined as 70-140mg/dl overnight and 70-180mg/dl during the day; A2.2: Reduced risk for hypoglycemia, specifically reduction in nocturnal hypoglycemic episodes; A2.3: Reduced postprandial glucose variability and avoidance of hypoglycemia 3-4 hours after a meal; and A2.4: Acceptance of the system feedback by patients.
- Psychobehavioral Data to Inform Closed Loop Control Aggressiveness [ Time Frame: within 1 year of study conclusion ]
Collection of psychobehavioral data on individuals' fear of hypo- and hyperglycemia, and connecting the influence of these factors on insulin therapy self-management can facilitate the individualization of controller aggressiveness in the development of a closed-loop system.
We study the ability of the psychobehavioral data to facilitate the individualization of controller aggressiveness in the development of a closed-loop system. The data that is used for this analysis are collected in through the pre- and post-intervention psychobehavioral assessments.
- Relationships Between Physiology and Behavior Transferred to In Silico Environment [ Time Frame: within 2 years from study conclusion ]
Collection of relevant data to establish relationships between behavior and physiology will allow to iteratively transfer, in simulation, the influence of behavioral triggers through individual physiological parameters and metabolic mechanisms, to the final element of BG fluctuation.
The collected diary data will be used to establish relationships, specifically stochastic models, between behavioral events, physiology, and self-treatment. The models are developed based on the collected data and will be incorporated into the simulation environment to capture realistically physiologic response to behavior and self-treatment strategies.

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Ages Eligible for Study: | 21 Years to 65 Years (Adult, Older Adult) |
Sexes Eligible for Study: | All |
Accepts Healthy Volunteers: | No |
Sampling Method: | Probability Sample |
Inclusion Criteria:
For this pilot trial, recruitment will ONLY occur through UVa's IRB-HSR #14263 Recruitment Database.
Inclusion criteria for subject to enroll:
- T1DM (as defined by the American Diabetes Association criteria or judgment of a physician) for at least 2 years prior to the enrollment in the study
- Age 21-65.
- Use of an insulin pump to treat their diabetes for at least 6 months.
- Use of a CGM for at least a 6 week period in the past 2 years.
- Has the ability to use a computer that is capable of running the Dexcom Data Manager 3 (DM3) software daily.
- Has regular access to the Internet.
- Has an identified healthcare provider who can provide advice about diabetes care.
- Actively using a bolus calculator function with the current insulin pump with pre-defined parameters for glucose goal, carbohydrate ratio, and insulin sensitivity factor.
- Willingness to participate in the study for 11 weeks wearing a DexCom CGM for the duration of the study and perform daily journaling of BG, pump activity, meals, physical activity, stress level and menstrual cycle for 3 weeks during the study intervention period.
- Willingness to do extra fingersticks when CGM alarms at low or high end (<70 mg/dl or >300 mg/dl),
- Willingness to come to Center for Diabetes Technology on at least two occasions to obtain and return supplies.
- Willingness to avoid consumption of acetaminophen-containing products for the duration of the study.
- Demonstration of proper mental status and cognition for completion of the study.
- Has the ability to contact their own personal diabetes care team to have clinical questions answered about changes to diabetes treatment.
Exclusion Criteria:
- Individuals with cognitive impairment that prevents understanding either consent form or intervention content
- Active renal dialysis
- Psychiatric disorders that would interfere with study tasks (e.g., substance abuse)
- History of a systemic deep tissue infection with methicillin-resistant staph aureus or Candida albicans
- Known bleeding diathesis or dyscrasia
- Pregnant or intending to get pregnant during study
- Active enrollment in another clinical trial
- Medical requirement for acetaminophen-containing products during the study period for more than 1 week
- Medical condition that would make operating a CGM or insulin pump difficult (e.g. blindness, severe arthritis, extensive scar tissue at sites where devices are inserted)
- Individuals who do not have access to their diabetes care team to have clinical questions answered about changes in their diabetes treatment.
- Need for magnetic resonance imaging (MRI)/magnetic resonance angiogram (MRA)during the study
List any restrictions on use of other drugs or treatments:
The CGM must be removed prior to Magnetic Resonance Imaging and use of acetaminophen-containing medications while using the CGM sensor may affect the performance of the device. Therefore, MRI and products containing acetaminophen will be restricted. If either is required out of medical necessity, the DexCom® will be removed and participant will have the option of repeating the involved study week. If the medical condition requires use of acetaminophen for longer than 1 week, the participant will be dropped from the study.

To learn more about this study, you or your doctor may contact the study research staff using the contact information provided by the sponsor.
Please refer to this study by its ClinicalTrials.gov identifier (NCT number): NCT01767831
United States, Virginia | |
University of Virginia Center for Diabetes Technology | |
Charlottesville, Virginia, United States, 22904 |
Principal Investigator: | Linda Gonder-Fredrick, Ph.D. | University of Virginia Center for Diabetes Technology |
Responsible Party: | Linda Gonder-Frederick, Associate Professor, University of Virginia |
ClinicalTrials.gov Identifier: | NCT01767831 |
Other Study ID Numbers: |
16226 R01DK085623 ( U.S. NIH Grant/Contract ) DP3DK094331 ( U.S. NIH Grant/Contract ) |
First Posted: | January 14, 2013 Key Record Dates |
Last Update Posted: | April 28, 2014 |
Last Verified: | April 2014 |
Type 1 Diabetes Mellitus (T1DM) Continuous Glucose Monitor (CGM) Simulation-based Education |
Diabetes Mellitus Diabetes Mellitus, Type 1 Glucose Metabolism Disorders Metabolic Diseases |
Endocrine System Diseases Autoimmune Diseases Immune System Diseases |