Diabetes is a chronic metabolic disease characterized by elevated levels of blood glucose, which can lead to serious damage to the heart, blood vessels, eyes, kidneys, and nerves. But it is more than just a disease, it is a global health crisis as the prevalence of diabetes has been continuously increasing over the past few decades. Diabetes does not just affect glucose levels as it has an influence on every aspect of an individual life. Diabetes burden is described by all the physical, emotional, interpersonal, regimen-related and financial challenges of managing and living with diabetes.
It includes, for instance, the need to monitor blood glucose levels, taking medication, adhering to a strict diet and exercise regimen which are daily concerns and taking decisions related to those. It can also include the impact of the disease on an individual’s social life and relationships, as well as its economic burden due to the cost of healthcare and related expenses.
All these create a mental load on people with diabetes that patients are trying to balance using coping mechanisms, external support (e.g. family, friends) or with the help of healthcare professionals. Such distress is currently assessed on the basis of questionnaires, which are biased in several ways because 1) they are non-evolutive measure (it captures diabetes distress at the time of the questionnaire and may not reflect changes over time), 2) some component of diabetes distress are missing (e.g. work-related issues, cost of treatment) and 3) patients may provide answers they believe healthcare providers want to hear rather than expressing their true feelings, also called the “make my doctor happy” effect.
The World Diabetes Distress Studies project aims to shed light on these underexplored facets of diabetes.
Using Artificial Intelligence, Big Data analytics, and a cross-disciplinary approach, we are working to identify key determinants of diabetes burden and distress.
Our goal is not just to quantify these challenges but to develop tools and guidelines that will improve patients’ care and make a real difference in the lives people with diabetes. This project paves the way for modern research on diabetes at the interface between computer and data science, epidemiology, and medical research.
