Accepted for/Published in: Journal of Medical Internet Research
Date Submitted: Jun 17, 2024
Open Peer Review Period: Jun 24, 2024 - Aug 19, 2024
Date Accepted: Dec 30, 2024
(closed for review but you can still tweet)
Bridging the Gap in Carbohydrate Counting with A Mobile Application: A Needs Assessment survey.
ABSTRACT
Background:
Carbohydrate counting (CC) can be burdensome and difficulty with adherence have been reported. Automated CC through mobile applications offers innovative solutions to ease this burden.
Objective:
A cross-sectional online survey was conducted to identify 1) perceived barriers to CC by Canadians living with type 1 diabetes (T1D), and 2) app-features that would help reduce these barriers. As a secondary objective, apps being used by participants were compared with the suggested app-features.
Methods:
Participants completed a 39-closed- and open-ended question online survey to identify barriers in CC, preferred CC app-features, and current CC app use. Respondents rated the importance of barriers and proposed app-features using a 5-point Likert scale.
Results:
Participants (n=196: 74% women, mean age 40±17 years, mean diabetes duration 22±14 years, 91% relied on CC to determine insulin doses at mealtimes) reported carbohydrate identification barriers, nutrient interaction and insulin dose calculation barriers, as well as psychosocial barriers. App-feature preferences emphasized the need for features for nutrient analysis (84%), personalization of the app (77%), insulin bolus calculation (74%), and support from healthcare professionals (69%). The rated features were cross-referenced in each app reported being used by participants (n=16 different apps). Most apps allowed nutrient analysis. However, none offered personalization, one app calculated bolus dose, and only one app provided support from healthcare professionals.
Conclusions:
Currently used CC mobile apps do not meet the needs of people with T1D. A novel CC app with app-features such as photo recognition, reliable nutrient values and personalized bolus calculations could reduce CC burden.
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