We are a multidisciplinary team of researchers with the joint goal of developing an in silico model of stress resilience. To do so, we monitor healthy at-risk individuals (18+ years old) during stressful life phases, such as transition into adulthood or higher education, training-to-street transition (police officers), or abruptly changed life situations (accident victims in recovery). Multiple longitudinal studies collect psychological, behavioural, neural, and physiological markers, and apply advanced mathematical modelling to identify key risk indicators and resilience factors. The ultimate goal is a prognostic tool for people to monitor their mental stability, and to intervene effectively before the personal „tipping point“.
Our approach is health- rather than disease-focussed, that is, we aim to avoid mental problems rather than trying to cure them after they have already developed into full-blown psychiatric diseases. We pursue this goal by advancing the mathematical data integration and modelling of mental health. In return, the model itself will help us to deepen our scientific understanding of what comprises stress resilience versus stress susceptibility, which stressors are most detrimental, and which interventions, resilience mechanisms, or resilience-enhancing behaviours are most effective and beneficial. The overall aim of DynaMORE is to improve the prevention of, or quick recovery from, stress-related mental health problems. We hope to increase individual well-being, reduce healthcare demands and indirect economic costs, and contribute to a healthier society.
In short, we are about to generate and validate the first in silico model of stress resilience, and will use it as a basis for developing a novel mobile health (mHealth) product for the primary prevention of stress-related disorders!