The overall goal of WP1 is to develop a dynamic mathematical in silico model of resilience serving (a) to determine and predict the stability of an individuals’ mental health status in stressful life situations from multi-modal and longitudinal real-world empirical data, and (b) to better understand the dynamic interaction between personal and environmental factors that shape an individual’s mental health, aka resilience, in the face of adversity. For this purpose, WP1 will develop mixed-effects exogenous autoregressive models by incorporating resilience factors into the dynamics of mental health, as represented in a symptom network model. Thus, WP1 will generate the key tool for individualised decision-making in primary prevention (mechanistically targeted and suitably timed personalised preventive intervention) and for the improvement of our scientific knowledge about resilience. The model will be validated against real-world empirical data (by WP3 and WP4) and integrated into a mobile health (mHealth) application (WP2, WP3, WP5 and WP6). WP1 has the following objectives:

• Develop an in silico framework for modelling resilience based on key resilience factors
• Calibrate the model with real-world data
• Validate the model against observational and interventional empirical data

Prof. Dr. Jens Timmer (ALU-FR)

The challenge for WP2 is to link multi-modal and longitudinal real-world empirical data (as analysed in WP3) to a dynamic in silico model of resilience (developed in WP1). This means that an intermediate modelling step is required. Specifically, we need to deal with the integration of a large number of different measurements and real-world observation patterns, including irregular measurement patterns at different time scales, and missing data. The techniques to be developed in this work package will allow WP3 to pre-process the empirical data from the MARP, LORA and the observational empirical study (DynaM-OBS) from WP4 for in silico modelling in WP1, to derive subject-matter insight (in particular, a factor solution for multi-modal empirical data that will represent key resilience factors), and to translate results from the in silico model into real-world settings, such as the interventional empirical validation study (DynaM-INT) in WP4. The following objectives will be actively pursued by WP2:

• Develop a framework for coarse integrative modelling and pre-processing of empirical resilience data
• Adapt dimension reduction techniques to enable screening of key resilience factors for the in silico model
• Develop techniques for translating the in silico model to real-world data patterns

Prof. Dr. Harald Binder (UKLFR)

The overall goal of WP3 is to improve our conceptual knowledge (subject-matter insight) about the maintenance of mental health in the face of stressful life circumstances, aka resilience. WP3 unites the bio-psycho-social expertise available in the consortium and provides a comprehensive, yet non-mathematical model of resilience which constitutes the theoretical basis for formal mathematical model building in WP1. Further, WP3 organises access to, and centrally analyses, multi-modal longitudinal empirical data from the existing studies MARP, LORA, PIA, TATS, all acquired through other funding sources; as well as from the observational and interventional validation studies DynaM-OBS and DynaM-INT, conducted as part of the DynaMORE project by WP4. With the help of the techniques developed together with WP2, WP3 will first determine latent factors in MARP and LORA baseline data, and then evaluate their potential to predict resilient outcomes in MARP and LORA longitudinal data. Identified resilience factors will be translated into the in silico resilience model by WP1. WP3 will then use bio-psycho-social knowledge to conceptually evaluate the in silico model. Finally, WP3 will validate the model against empirical data from PIA, TATS, DynaM-OBS, and DynaM-INT, thereby also aiding WP1 in refining the model. The following objectives define WP3:

• Identify key bio-psycho-social resilience factors
• Evaluate and validate the translated in silico resilience model

Prof. Dr. Raffael Kalisch (UMC-Mainz)

In WP1 to WP3, a dynamic in silico model of resilience is being developed based on existing data from MARP and LORA. The overarching aim of WP4 is to provide suitable real-world empirical data that are multi-modal and longitudinal in nature against which the resilience model can be validated. This will be done in two empirical multicentre studies (MCSs): one purely observational (DynaM-OBS) and one interventional (DynaM-INT). We choose an MCS design because MCSs permit better generalisation of results, and make subject recruitment maximally efficient within a limited time frame. The interventional study also allows us to test the mHealth product demonstrator (such as a real-world resilience model application) and to evaluate the effects of personalised, mechanistically targeted, and appropriately timed resilience-promoting interventions that are advised by the model/product. A further objective of WP4 is to design the experimental set-up for DynaM-OBS and DynaM-INT and to coordinate these MCSs. Both studies will investigate resilience longitudinally in cohorts of students during particularly stressful study periods, using Ecological Momentary Assessment (EMA) and Ecological Physiological Assessment (EPA) technology. In DynaM-INT, the model-based interventions will employ Ecological Momentary Intervention (EMI) technology. The interventions will have been developed and piloted in WP6 and WP7, and will be advised by the in silico model. In summary, these are the objectives of WP4:

• Adapt and validate a condensed and methodologically updated test battery for two MCSs
• Plan and coordinate an observational MCS (DynaM-OBS) to validate the resilience model
• Plan and coordinate an interventional MCS (DynaM-INT) to further validate the model and to test its usefulness in choosing individually tailored interventions (product demonstrator testing)

Prof. Dr. Henrik Walter (Charité), co-lead: Dr. Ilya Veer (Charité)

The aim of WP5 is to develop the content, structure and software platform of the Ecological Momentary Assessment (EMA) and Ecological Momentary Intervention (EMI, developed by WP7). These will be integrated with the Ecological Physiological Assessments (EPA) developed by WP6 and eventually be used in the observational (DynaM-OBS) and interventional (DynaM-INT) multicentre studies (MCSs) of WP4, which serve to validate the in silico resilience model against real-world empirical data and to test new interventions. WP5 has the following objectives:

• Develop an EMA platform that can be integrated with EPA
• Develop an EMI platform that integrates EMA and EPA data

Prof. Dr. Inez Myin-Germeys (KUL)

WP6 will integrate Ecological Momentary Assessments (EMA, developed in WP5) with Ecological Physiological Assessments (EPAs) using wearable biosensors. Combined EMA/EPA assessments will be implemented and tested for feasibility in a single-centre pilot study. Specific methods for the analysis of EPA data will be developed, including in real time. Hardware and information and communication technology (ICT) solutions (central data storage and processing of EMA/EPA data) as well as data-analytical solutions will be made available to all multicentre study (MCS) sites of WP4. EMA/EPA assessments will be applied in the observational MCS DynaM-OBS in WP4, which serves to validate the in-silico resilience model developed by WP1 against empirical data. Our developments will also help WP5 and WP7 to establish a platform for Ecological Momentary Interventions (EMI) integrated with EMA and EPA, which will be applied in the interventional MCS DynaM-INT in WP4. Here, WP6 will also provide the hardware and ICT solutions for integrated EMA/EPA/EMI. In brief, WP6 has the following three objectives:

• Integrate EPA with the EMA developed in WP5, and provide technical solutions for the observational MCS DynaM-OBS in WP4
• Develop data reduction (feature extraction) methods for EPA measures and develop real-time analysis
• Provide technical solutions (integrated EMA/EPA/EMI) for the interventional MCS DynaM-INT in WP4

Dr. Erno Hermans (SKU)

Overall objective of WP7 is to develop and test mechanistically targeted interventions to promote resilience that can be delivered using mobile technology (Ecological Momentary Interventions, EMI). Specifically, EMIs will target neurocognitive resilience factors identified by WP3 to be important for the maintenance of mental health in times of adversity (aka resilience). The EMIs will then be used in the interventional multicentre study (MCS) DynaM-INT in WP4, which serves to validate the in-silico resilience model by testing whether targeted interventions have the protective effects on subjects’ mental health that are predicted by the model. Further, WP7 and WP4 together contribute to the goal of developing novel resilience interventions. The following objectives are pursued by WP7:

• Develop new, mechanistically targeted EMIs
• Test the effectiveness and efficiency of the new EMIs

Prof. Dr. Birgit Kleim (UZH)

Multicentre studies (MCSs), in particular when they are transnational, often suffer from significant delays and weaknesses because of regionally different rules and regulations on ethical issues. In order to establish highest standards of ethical conduct and in order to make applications, problem solutions and approval as smooth as possible, WP8 will coordinate all ethics issues centrally. This is particularly important as DynaMORE tries to support and implement open-access policies. This has to be taken into account into study design, consent forms, and ethical approvals from the start. Moreover, we strive to continuously coach our early-career scientists, and to educate them ethically as well as methodologically because neuroimaging methods and studies involving ecological momentary assessments (EMA), ecological physiological assessments (EPA) and ecological momentary interventions (EMI) are constantly evolving. WP8 pursues the following objectives:

• Ensure implementation of shared transnational ethical rules and regulations within DynaMORE
• Maximise open-science policy in DynaMORE
• Organise early-career researcher training and education

Prof. Dr. Henrik Walter (Charité), co-lead: Dr. Ilya Veer (Charité)

WP9 aims to increase the visibility of DynaMORE by reaching out to scientific and professional communities, industry, immediately concerned stakeholders (students and university counselling services) as well as other potentially interested groups (e.g. healthcare providers, health insurers, policy-makers) as well as the general public. A dissemination and communication plan is being implemented with the following strategic objectives:

• Make DynaMORE known to the scientific community and the public
• Disseminate the results of DynaMORE to the scientific community in the academic, healthcare and health technology sectors, and foster interaction and exchange with the scientific community and the general public
• Manage intellectual property generated within DynaMORE, and develop an exploitation strategy

Prof. Dr. Oliver Tüscher (intresa), co-lead: Dr. Nina Donner (concentris)

Effective project management is a central element of successful research. This is because large research projects entail a lot of administrative work. The following objectives will be actively pursued by WP10:

• Make DynaMORE achieve its objectives and deliver in time: financial statements and high quality milestones and deliverables
• Help the consortium abide by the regulations and contractual obligations according to the grant agreement, its annexes and the consortium agreement
• Monitor the project’s finances and report them properly to the European Commission
• Establish a communication infrastructure which enables the partners to communicate efficiently and to stay connected for the run-time of the project
• Preserve the rights of the partners regarding intellectual property, and to act as a mediator in case of disputes

Prof. Dr. Raffael Kalisch (UMC-Mainz), co-lead: Sonja Leissner (concentris)