Carbohydrate Counting App Using Image Recognition for Youth With Type 1 Diabetes: Pilot Randomized Control Trial
| Autor: | Stacie-Ann S Sammott, Bryan Maguire, Mark R. Palmert, Jennifer Stinson, Jeffrey E. Alfonsi, Cynthia Nguyen, Vanita Pais, Taha Arshad, Elizabeth Choi |
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| Rok vydání: | 2020 |
| Předmět: |
medicine.medical_specialty
Adolescent type 1 diabetes Carbohydrates 030209 endocrinology & metabolism Health Informatics Pilot Projects digital health applications (apps) law.invention 03 medical and health sciences Carbohydrate counting 0302 clinical medicine Randomized controlled trial Diabetes management law Medicine Humans 030212 general & internal medicine Think aloud protocol Child mHealth Type 1 diabetes Original Paper youth business.industry carbohydrate counting Usability medicine.disease Digital health Mobile Applications Diabetes Mellitus Type 1 image recognition Physical therapy Nutrition Therapy business |
| Zdroj: | JMIR mHealth and uHealth |
| ISSN: | 2291-5222 |
| Popis: | Background Carbohydrate counting is an important component of diabetes management, but it is challenging, often performed inaccurately, and can be a barrier to optimal diabetes management. iSpy is a novel mobile app that leverages machine learning to allow food identification through images and that was designed to assist youth with type 1 diabetes in counting carbohydrates. Objective Our objective was to test the app's usability and potential impact on carbohydrate counting accuracy. Methods Iterative usability testing (3 cycles) was conducted involving a total of 16 individuals aged 8.5-17.0 years with type 1 diabetes. Participants were provided a mobile device and asked to complete tasks using iSpy app features while thinking aloud. Errors were noted, acceptability was assessed, and refinement and retesting were performed across cycles. Subsequently, iSpy was evaluated in a pilot randomized controlled trial with 22 iSpy users and 22 usual care controls aged 10-17 years. Primary outcome was change in carbohydrate counting ability over 3 months. Secondary outcomes included levels of engagement and acceptability. Change in HbA1c level was also assessed. Results Use of iSpy was associated with improved carbohydrate counting accuracy (total grams per meal, P=.008), reduced frequency of individual counting errors greater than 10 g (P=.047), and lower HbA1c levels (P=.03). Qualitative interviews and acceptability scale scores were positive. No major technical challenges were identified. Moreover, 43% (9/21) of iSpy participants were still engaged, with usage at least once every 2 weeks, at the end of the study. Conclusions Our results provide evidence of efficacy and high acceptability of a novel carbohydrate counting app, supporting the advancement of digital health apps for diabetes care among youth with type 1 diabetes. Further testing is needed, but iSpy may be a useful adjunct to traditional diabetes management. Trial Registration ClinicalTrials.gov NCT04354142; https://clinicaltrials.gov/ct2/show/NCT04354142 |
| Databáze: | OpenAIRE |
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