ArticleJournal of diabetes science and technology2020
Patient Input for Design of a Decision Support Smartphone Application for Type 1 Diabetes.
Article in Journal of diabetes science and technology, 2020. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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The trial behind it
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Who cites it
7 citing papers in PubMed.
- T1D REACHOUT-A Mobile App to Deliver Peer-Led Mental Health Support to Adults Living With Type 1 Diabetes: Co-Design and Development Process.JMIR diabetes · 2026Article
- Digital Health Technology in Diabetes Management in the Asia-Pacific Region: A Narrative Review of the Current Scenario and Future Outlook.Diabetes therapy : research, treatment and education of diabetes and related disorders · 2025Review
- Systematic review to understand users perspectives on AI-enabled decision aids to inform shared decision making.NPJ digital medicine · 2024Article
- Enhancing the Capabilities of Continuous Glucose Monitoring With a Predictive App.Journal of diabetes science and technology · 2024Article
- The Development of an Exercise Advisor App for Type 1 Diabetes: Digitization Facilitates More Individualized Guidance.Journal of diabetes science and technology · 2022Article
- Quantifying the impact of physical activity on future glucose trends using machine learning.iScience · 2022Article
- Feature-Based Machine Learning Model for Real-Time Hypoglycemia Prediction.Journal of diabetes science and technology · 2021Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
backgroundDecision support smartphone applications integrated with continuous glucose monitors may improve glycemic control in type 1 diabetes (T1D). We conducted a survey to understand trends and needs of potential users to inform the design of decision support technology.
methodsA 70-question survey was distributed October 2017 through May 2018 to adults aged 18-80 with T1D from a specialty clinic and T1D Exchange online health community (myglu.org). The survey responses were used to evaluate potential features of a diabetes decision support tool by Likert scale and open responses.
resultsThere were 1542 responses (mean age 46.1 years [SD 15.2], mean duration of diabetes 26.5 years [SD 15.8]). The majority (84.2%) have never used an app to manage diabetes; however, a large majority (77.8%) expressed interest in using a decision support app. The ability to predict and avoid hypoglycemia was the most important feature identified by a majority of the respondents, with 91% of respondents indicating the highest level of interest in these features. The task that respondents find most difficult was management of glucose during exercise (only 47% of participants were confident in glucose management during exercise). The respondents also highly desired features that help manage glucose during exercise (85% of respondents were interested). The responses identified integration and interoperability with peripheral devices/apps and customization of alerts as important. Responses from participants were generally consistent across stratified categories.
conclusionsThese results provide valuable insight into patient needs in decision support applications for management of T1D.
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Registered trials
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