The goal of the T2D-Data project is to develop data-driven solutions for identifying the risk of type 2 diabetes and individualized diabetes prevention with digital services, and to provide evidence of the long-term effectiveness of digital services.
The project aims to:
- improve the identification of individuals at increased risk of type 2 diabetes;
- find predictors for engagement to digital services and service efficiency;
- develop personalized and adaptive tools to support lasting lifestyle changes; and
- develop data-driven solutions for modeling the long-term effectiveness of digital tools.
The project mainly utilizes the comprehensive data collected in the StopDia study. In addition, the developed methods will be evaluated with the help of independent data from the Diabetes Prevention Study (DPS). Additionally, register data is used in the assessment of long-term effectiveness and in the development of health economic models.
The project is developing a new, individualized version of the BitHabit application based on the VTT’s BitHabit platform. The application is co-developed and evaluated with the target group, and finally its effectiveness is evaluated in a new type of SMART setup, which allows the evaluation of different and adaptive solutions in the same setup.
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