The Hospital for Sick Children
Toronto, Ontario, M5G 1X8, Canada
NCT Number: NCT04354142
Type 1 Diabetes Mellitus (T1DM) is a common chronic disease of childhood. T1DM has substantial impact on quality of life (QOL), including burdensome dietary restrictions and the need to count carbohydrates in foods to safely dose insulin. Carbohydrate counting is challenging, inconvenient, and, if done wrong, can cause high or low blood glucose levels.
To address these challenges, iSpy, a novel smartphone application, was created to identify foods and determine their carbohydrate content using pictures or speech. This pilot study is to evaluate if using iSpy improves carbohydrate counting accuracy and efficiency. Pilot participants will have carbohydrate counting (accuracy and efficiency) and their overall QoL (with respect to carbohydrate counting) assessed at baseline and after 3-months.
The investigators hypothesize that using iSpy will make carbohydrate counting easier (by improving accuracy and efficiency) and enhance QoL for patients and/or their caregivers. If so, iSpy may help lessen the burden of living with T1DM.
Looking for future studies?
Notify Me10 year–17 year
All sexes
Interventional
Not applicable
Toronto, Ontario, M5G 1X8, Canada
Nutrition is an integral component of management of many chronic diseases and of overall wellness. Helping individuals to understand what they are eating can empower them to better manage their diseases. For example, the growing number of youth living with Type 1 Diabetes Mellitus (T1DM) struggle with carbohydrate counting, an essential and daily aspect of their lives, because of required reliance on memorization and numeracy skills. Effective carbohydrate counting has been demonstrated to improve blood glucose control, while inaccurate carbohydrate counting results in more variable blood glucose. Concerns related to carbohydrate counting accuracy can also limit food choices, provoke anxiety, and decrease quality of life. Since there is no cure for T1DM, enhancing patients' ability to understand and apply carbohydrate counting is an important part in helping them manage their condition most effectively.
iSpy is a novel healthcare application that addresses an important clinical need by facilitating carbohydrate counting using pictures or voice recognition. Proprietary algorithms adjust for portion size and identify hidden carbohydrates (such as in ketchup or other condiments) and quantify the amount of carbohydrates in a meal.
Healthy volunteers accepted: No
Only the study team can determine whether someone qualifies for participation.
Inclusion criteria
Exclusion criteria
iSpy is a novel healthcare application that hopes to address an important clinical need by facilitating carbohydrate counting using pictures or voice recognition. Proprietary algorithms adjust for portion size and identify hidden carbohydrates (such as in ketchup or other condiments) and quantify the amount of carbohydrates in a meal.
Time frame: 3 months
Assessing CHO counting using 10 food items from all major food groups. For each group, a simple food (e.g. an apple) and complex food (e.g. food with 2+ components but base food from targeted group) is included. A Co-investigator, Registered Dietitian (RD)/Certified Diabetes Educator (CDE), selected 2 sets of 10 food items for the study visits (verified that both sets were similar difficulty).
The net CHO value (true value) for each food will be based on the nutrition label, USDA Nutrient Database (Release 28), Canadian Nutrient File, or by RD/CDE.
For each food, data will be obtained from all participants:
And with the above data, the following will be calculated:
Time frame: 3 months
Assessing CHO counting using 10 food items from all major food groups. For each group, a simple food (e.g. an apple) and complex food (e.g. food with 2+ components but base food from targeted group) is included. A Co-investigator, Registered Dietitian (RD)/Certified Diabetes Educator (CDE), selected 2 sets of 10 food items for the study visits (verified that both sets were similar difficulty).
The net CHO value (true value) for each food will be based on the nutrition label, USDA Nutrient Database (Release 28), Canadian Nutrient File, or by RD/CDE.
For each food, data will be obtained from all participants:
In order to calculate the following:
Time frame: 3 months
Quality of Life questionnaires will be analyzed for any change from baseline to 3-month follow-up within both the intervention and control groups.
The first questionnaire including:
Time frame: 3 months
Quality of Life questionnaires will be analyzed for any change from baseline to 3-month follow-up within both the intervention and control groups.
The second questionnaire including:
Time frame: 3 months
Quality of Life questionnaires will be analyzed for any change from baseline to 3-month follow-up within both the intervention and control groups.
The third questionnaire including:
Time frame: 3 months
Quality of Life questionnaires will be analyzed for any change from baseline to 3-month follow-up within both the intervention and control groups.
The last questionnaire including:
Time frame: 3 months
Time frame: 3 months
Time frame: 3 months
The Hospital for Sick Children
Other
iSpy: A Pilot Randomized Control Trial of a Novel Carbohydrate Counting Smartphone App for Youth With Type 1 Diabetes
OpenTrials presents study information sourced from ClinicalTrials.gov. The official registry record should be consulted for the latest information.
View the official ClinicalTrials.gov record (opens in a new tab)This listing is for discovery and informational purposes only. It is not medical advice, does not guarantee that a study is recruiting, and does not determine eligibility. Contact the study team and a qualified healthcare professional when considering participation.
Published trials that share one or more normalized conditions with this study.
NCT06238778
Autoimmune Diseases, Diabetes Mellitus
Huntington Beach, California, United States
View Trial DetailsNCT06236256
Autoimmune Diseases, Diabetes Mellitus
Ramat Gan, Israel
View Trial DetailsNCT07711275
Autoimmune Diseases, Diabetes Mellitus
Istanbul, Turkey (Türkiye)
View Trial DetailsNCT03938324
Anemia, Anemia, Hemolytic
Durham, North Carolina, United States
View Trial Details