The two chronic widespread diseases of high blood pressure and type II diabetes affect millions of people in Germany, and their prevalence is steadily increasing. Both diseases can be treated effectively through lifestyle changes, but there is a lack of personalised, gender-sensitive therapeutic approaches to increase the effectiveness of behavioural interventions. As with many diseases, there are gender-specific differences in the course and effect of therapy, which have been little studied to date.
The ‘gEndurance’ project aims to develop gender-sensitive therapy recommendations for patients with high blood pressure and type II diabetes, thereby stabilising their health situation and improving their quality of life. To this end, a smartwatch and a telemonitoring platform are used to record physiological data as well as individual and socio-cultural factors. Machine learning and further methods of artificial intelligence are used to analyse this data in order to identify gender-specific differences and derive individualised interventions based on these findings. Evidence-based behavioural models such as the Behaviour Change Wheel are used for this purpose. A central component of the project is the development of a demonstrator, which will be tested and evaluated in a pilot trial. Gamification elements are intended to increase user motivation and support them in changing their behaviour in the long term. Ethical, legal and social implications (ELSA) will be taken into account throughout the entire course of the project in order to increase acceptance and willingness to use the system. gEndurance stands out from existing solutions thanks to its multi-perspective research approach and the integration of AI-supported analyses, and makes a significant contribution to gender-sensitive medicine. In the long term, the project aims to help reduce medical care costs for patients with hypertension and type II diabetes through smart, target group-specific health solutions.
DFKI contributes its expertise in machine learning, gendered research, fair AI systems, and interaction and UX design. One area of focus is interaction and interface design for all components of the project. Another area of work is the design, implementation and evaluation of machine learning methods for gender-specific analysis of the available data. The differences between the various approaches are being investigated, as these offer valuable insights beyond the added value in the project in terms of generalisability and applicability in other domains. Further analysis components, which are also in the hands of DFKI, include additional statistical analyses (e.g. for overviews and significance tests) as well as the implementation of intelligent methods for the automatic analysis of free text data (such as in diaries) in order to integrate the information into the overall analysis.
Partners
- Institut für Sozialforschung und Sozialwirtschaft e.V. (iso) - Koordinator
- Institut für Allgemeinmedizin, Goethe Universität Frankfurt (IFA)
- Institut für Medizininformatik, Goethe Universität Frankfurt (IMI)
- Qurasoft GmbH
