AG Dynamics of Risk and Resilience
Focus
The Dynamics of Risk and Resilience research group investigates how mental health problems emerge, change over time, and develop along different clinical trajectories. Our work is grounded in the view that mental health is not a static state, but a dynamic process that can stabilise or destabilise through the interplay of internal and external factors.
A particular focus is on early stages of mental illness, when symptoms may not yet map clearly onto a diagnostic category. We study transdiagnostic developmental pathways and pluripotent risk states — early risk profiles that may lead to different clinical outcomes — and examine these processes within a clinical staging framework.
Research Approach
We combine longitudinal clinical research with digital and computational approaches to study changes in mental health in everyday life and over time. Our work draws on intensive longitudinal data, including Ecological Momentary Assessment (EMA), actigraphy, passive smartphone sensing, and repeated clinical assessments.
Depending on the research question, we draw on longitudinal and trajectory-based analyses, network modelling, dynamical systems approaches, machine learning, and simulation-based methods. Our aim is to better understand how individual mental health trajectories unfold, which processes contribute to stability or deterioration, and how this knowledge can inform future approaches to early detection and prevention.
Current Projects
SiReD-MH is a BMFTR-funded research programme developing an in-silico framework to study resilience dynamics and clinical transitions in young people at increased risk of mental illness. Using longitudinal digital phenotyping data, the project combines generative modelling and simulation to represent individual trajectories and systematically investigate how mental health systems respond to changing conditions.
