Development of the Support self-guided, web application for adults living with type 1 diabetes in Canada by a multi-disciplinary team using a people-oriented approach based on the Behaviour Change Wheel.
Digit Health
; 9: 20552076231152760, 2023.
Article
em En
| MEDLINE
| ID: mdl-36762025
Background: Diabetes self-management education and support (DSME/S) are central in type 1 diabetes (T1D) where individuals are responsible for 95% of care. In-person DSME/S programs have been proven clinically effective (e.g. optimizing glycemic management, improving diabetes-related behaviors) but are limited by a lack of accessibility and long-term follow-up. Self-guided digital tools such as web applications (web apps) can be an alternative for delivering DSME/S. Objective: This article describes the development of Support, a behavioral theory-based, self-guided, web application for adults living with T1D in the province of Quebec, Canada. Methods: A multi-disciplinary team developed Support. Patient partners first proposed its focus, learning topics, and expressed barriers to using digital tools for DSME/S. These barriers were analyzed based on the Behaviour Change Wheel. A group of healthcare professionals (HCPs) drafted the evidence-based learning content which was reviewed by external HCPs and by patient partners. Results: Support is a bilingual (English and French) web app accessible at any time via the Internet. It has four learning paths focusing on hypoglycemia and based on the user's method of diabetes treatment. Learning modules are divided into six categories with a maximum of three learning levels. It contains features such as a discussion forum, videos, and quizzes to ensure interactivity, provide social support, and maintain the motivation and long-term engagement of users. Conclusions: To the best of the authors' knowledge, Support is the first self-guided evidence-based web app for adults living with T1D. It is currently under study to evaluate its feasibility and clinical impacts.
Texto completo:
1
Coleções:
01-internacional
Base de dados:
MEDLINE
Tipo de estudo:
Qualitative_research
Idioma:
En
Revista:
Digit Health
Ano de publicação:
2023
Tipo de documento:
Article
País de afiliação:
Canadá