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.

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.

Inclusion Criteria:

• Diagnosed with T1DM for ≥6 months;
• Completion of initial carbohydrate counting classes;
• Incorporating carbohydrate counting into treatment regimen;
• Having access to a smart phone and data plan;

Exclusion Criteria:

• Cognitive impairments or co-morbid physical or psychiatric condition (e.g. blindness, clinical depression, anxiety disorder) that might impact ability to use iSpy;
• Diagnosis of condition that affects dietary exposure (e.g. celiac disease);
• Participation in usability study;