Four major pillars build the structural core of the DynaMORE project. These are in silico modelling, improving human lives, developing new technology, and eventually exerting a broader societal impact via dissemination, exploitation and valorisation of the scientific achievements.


  • Build a formal mathematical in silico model of resilience
  • based on an existing non-mathematical theory of resilience, namely the positive appraisal style theory of resilience (PASTOR)
  • based on two existing, currently acquired large-scale multi-modal longitudinal real-world data sets of mental health and overall well-being in subjects exposed to everyday life stressors, namely the Mainz Resilience Project (MARP) and the Longitudinal Resilience Assessment (LORA)
  • Conceptually evaluate the in silico model using subject-matter insight from all of our bio-psycho-social resilience experts who comprise the DynaMORE consortium
  • Validate the in silico resilience model
  • against two new multi-modal longitudinal real-world data sets from subjects exposed to everyday stressors, to be acquired in DynaMORE. Both studies – one purely observational (DynaM-OBS study), one interventional (DynaM-INT study) – are specifically designed and optimised for testing the model.
  • against two additional multi-modal longitudinal real-world data sets from subjects exposed to employment-specific stressors (Police-in-Action study, PIA) and particularly adverse stressors (Tel Aviv Trauma Study, TATS). The latter will allow us to test the model regarding its generalisability.


  • Derive deepened conceptual knowledge about the bio-psycho-social mechanisms of resilience
  • Real-world monitoring and intervention (DynaM-INT study)
  • Applying the in silico resilience model as a tool to monitor subjects at risk for developing stress-related mental health problems while they undergo a stressful period of their lives. The tool serves to predict the reactivity of individuals to potential future stressors in real life, in other words their mental health (in)stability, as a function of their current mental health status and the configuration and strength of their individual resilience factors (protective and stabilising mechanisms). These resilience factors are represented by key model parameters, so to speak a subject’s “aggregate resilience status”.
  • Using that knowledge to identify time points when an individual needs an intervention because he/she approaches a critical „tipping point“ beyond which the person might become instable
  • Specifying the intervention an individual needs at a certain time point. An intervention will target specific model parameters, for example boosting a crucial resilience factor in order to stabilise the person.
  • Thus, the DynaM-INT study serves as a proof of principle because it validates the model by means of mechanistically targeted manipulations and tests the effectiveness of model-based mobile health (mHealth) interventions.


  • Develop novel, interactive, resilience-promoting mHealth interventions that specifically target identified resilience factors (key model parameters). Prevention and intervention will be ambulatory, such as smartphone-based (Ecological Momentary Interventions, EMI), in conjunction with Ecological Momentary Assessment (EMA) and Ecological Physiological Assessment (EPA), which serve to guide the timing of EMIs and to read out their immediate effects. These novel technologies will be tested in DynaM-INT.
  • Develop new analytical methods for data integration and modelling of dynamic resilience processes with mixed-effect exogenous autoregressive models
  • Develop information and communication technology solutions for the exchange, merging, easy processing, and reliable analysis of the data


  • Educate and train a new generation of interdisciplinary resilience researchers
  • Disseminate results to the scientific community, to interested groups, stakeholders, and to the general public
  • Actively explore and prepare commercial exploitation and valorisation of a package consisting of baseline subject characterisation, regular online assessments, and in silico model-based EMIs with EMA and EPA, plus the associated information and communication technology solutions as a tool for the promotion of resilience