Published December 3, 2025 | Version v1
Poster Open

ResiMETA: Building an Open-Access FAIR Database for Trajectory-Based Resilience Research

  • 1. ROR icon Leibniz Institute for Resilience Research
  • 2. ROR icon Technische Universität Braunschweig
  • 3. Leibniz-Institut für Resilienzforschung (LIR) gGmbH
  • 4. University Medical Centre Mainz

Description

Psychological resilience research is rapidly expanding, but diverse concepts, heterogeneous study designs, inconsistent reporting, and missing metadata standards limit data reuse and robust evidence synthesis. To address these challenges, we introduce ResiMETA, a continuously updated open-access database for trajectory-based resilience research that systematizes evidence from longitudinal studies on responses to stressor exposure and psychosocial resilience factors. The database compiles aggregated study-level data and metadata, including population characteristics, study designs, mental health outcomes, modeled trajectories, and resilience factors. For data harmonization, we developed categorization schemes for key variables and an ordinal rating scheme synthesizing evidence from heterogeneous statistical models. Data extraction and organization follow a customized metadata scheme informed by existing frameworks. ResiMETA is documented according to FAIR principles and openly accessible via the Open Science Framework (OSF: https://osf.io/xcwtk/). Currently, ResiMETA includes 344 primary studies with ongoing updates. We will present the ResiMETA metadata architecture and demonstrate its potential to enhance evidence synthesis and foster collaboration in resilience research. Although not yet aligned with DDI standards, ResiMETA offers opportunities for future integration, particularly in standardizing psychological variables using controlled vocabularies. We invite engagement with the DDI community to explore how metadata standards can advance evidence synthesis in psychology and related disciplines.

Files

2025_EDDI_Poster_Svenja_Mrugalla.pdf

Files (503.6 kB)

Name Size Download all
md5:696172ea06416a1c435c582df2897a42
503.6 kB Preview Download