A Novel Carbohydrate Counting Smartphone App for Youth With Type 1 Diabetes

NCT ID: NCT04354142

Last Updated: 2020-04-21

Study Results

Results pending

The study team has not published outcome measurements, participant flow, or safety data for this trial yet. Check back later for updates.

Basic Information

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Recruitment Status

COMPLETED

Clinical Phase

NA

Total Enrollment

46 participants

Study Classification

INTERVENTIONAL

Study Start Date

2018-07-12

Study Completion Date

2020-01-27

Brief Summary

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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.

Detailed Description

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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.

Conditions

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Diabetes Mellitus, Type 1

Study Design

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Allocation Method

RANDOMIZED

Intervention Model

PARALLEL

Primary Study Purpose

SUPPORTIVE_CARE

Blinding Strategy

NONE

Study Groups

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iSpy

In addition to usual care, participants in the intervention group will receive the iSpy intervention.

Group Type EXPERIMENTAL

iSpy

Intervention Type DEVICE

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.

Control

The control group participants will continue to use their usual method of carbohydrate counting for a 3-month period.

Group Type NO_INTERVENTION

No interventions assigned to this group

Interventions

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iSpy

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.

Intervention Type DEVICE

Eligibility Criteria

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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;
Minimum Eligible Age

10 Years

Maximum Eligible Age

17 Years

Eligible Sex

ALL

Accepts Healthy Volunteers

No

Sponsors

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The Physicians' Services Incorporated Foundation

OTHER

Sponsor Role collaborator

The Hospital for Sick Children

OTHER

Sponsor Role lead

Responsible Party

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Mark Palmert

Associate Chair of Pediatrics

Responsibility Role PRINCIPAL_INVESTIGATOR

Principal Investigators

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Mark Palmert

Role: PRINCIPAL_INVESTIGATOR

The Hospital for Sick Children

Locations

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The Hospital for Sick Children

Toronto, Ontario, Canada

Site Status

Countries

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Canada

References

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Alfonsi JE, Choi EEY, Arshad T, Sammott SS, Pais V, Nguyen C, Maguire BR, Stinson JN, Palmert MR. Carbohydrate Counting App Using Image Recognition for Youth With Type 1 Diabetes: Pilot Randomized Control Trial. JMIR Mhealth Uhealth. 2020 Oct 28;8(10):e22074. doi: 10.2196/22074.

Reference Type DERIVED
PMID: 33112249 (View on PubMed)

Other Identifiers

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1000054297

Identifier Type: -

Identifier Source: org_study_id

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