JMIR Publications

ABSTRACT

Background:

Stress-related mental disorders are highly prevalent and pose a significant burden on individuals and society. Improving strategies of their treatment and prevention requires knowledge about risk and resilience. This multi-center study aims to contribute to this endeavor by investigating psychological resilience in healthy, but vulnerable young adults over nine months. Resilience is operationalized as maintained or quickly recovered mental health despite exposure to stressors and assessed longitudinally in a frequent monitoring approach.

Objective:

We aim to investigate factors predicting, and adaptive processes and mechanisms contributing to mental resilience, and to provide a methodological and evidence-based framework for later intervention studies.

Methods:

In a multi-center setting, across five research sites, a sample with the total target size of N=250 male and female young adults is assessed longitudinally over nine months. Participants are included if they had an elevated level of (internalizing) mental health problems and reported at least three stressful life events while not affected by any mental disorder other than mild depression. At baseline, sociodemographic, psychological, neuropsychological, structural and functional brain imaging data, salivary cortisol and alpha-amylase, as well as cardiovascular data are acquired. In a six-months longitudinal phase I, bi-weekly online monitoring of stressor exposure, mental health problems, and positive appraisal style takes place, as well as monthly one-week ecological momentary assessments (EMA) and ecological physiological assessments (EPA). In a subsequent three-months longitudinal phase II, online monitoring is reduced to once a month and psychological resilience and risk factors are assessed again at the end of the nine-month period. In addition, genetic, epigenetic, and microbiome data are assessed at baseline, month three (microbiome only), and month six. As an approximation of resilience, an individual stressor reactivity (SR) score will be calculated. Using regularized regression methods, network modeling, ordinary differential equations, landmarking methods, and neural net-based methods for imputation and dimension reduction, we will identify predictors and mechanisms of SR and thus be able to identify resilience factors and mechanisms that facilitate adaptation to stressors.

Results:

Participant inclusion started in October 2020 and data acquisition is expected to be completed in June 2022.

Conclusions:

The DynaM-OBS study provides a methodological framework and dataset to identify predictors and mechanisms of mental resilience, which are intended to serve as an empirical foundation for future intervention studies.