Personalized services for the prevention of type 2 diabetes by using health data, artificial intelligence, and statistical methods
When it comes to promoting health, there is rarely a one-size-fits-all solution.
VTT, the University of Eastern Finland, and the Finnish Institute for Health and Welfare (THL) have launched the T2D-Data project, supported by the Academy of Finland, in which they develop personalized services for the prevention of type 2 diabetes by using health data, artificial intelligence, and statistical methods. The study will yield new information and solutions for supporting permanent lifestyle changes, improve the well-being of those at risk of diabetes and, eventually, generate savings for society.
Type 2 diabetes is a serious global health problem that is largely preventable by maintaining a healthy lifestyle. Digital services are being used more and more to support healthy lifestyles and prevent lifestyle diseases. Better access to services alone is not enough; people should also commit to using the services in the long term and making permanent lifestyle changes. After the initial enthusiasm, however, most people tend to lose motivation, forget the use of the services, and go back to their old ways.
The existing digital services do not recognize an individual’s risks, personal needs, and preferences sufficiently well, and since they are not adaptive, they are unable to support different people in the best possible way.
With the support of international partners, and by utilizing statistical methods and artificial intelligence, the project team aims to discover which background factors explain the commitment to lifestyle interventions and what measures can reduce the risk of diabetes. The goal is also to test how the new data-driven methods work as part of the national self-care system.
The T2D-Data project builds on data collected by the consortium in the StopDia project, which was completed in 2019 and coordinated by the University of Eastern Finland, as well as data collected in the THL-coordinated Diabetes
Prevention Study (DPS) on people’s lifestyles, related change processes, metabolomics, and genome.
Tens of thousands of Finns took part in the StopDia project online to assess their risk for type 2 diabetes. Almost 3,000 of them participated in a one-year study, in which they were helped to establish small health-enhancing habits in their everyday life through a digital application.
Some were also invited to take part in group training. By combining the mobile application with group training, the participants gained better dietary habits and a narrower waistline. During the study, a massive amount of data was collected related to the participants’ health, physical and psychological well-being, lifestyle, use of the application, and user experiences.
These data can be used to develop new methods to identify risks for type 2 diabetes and to create individual, digital services to support permanent lifestyle changes.
