Psychosocial stress from pre- to post-pandemic times : latent class mixed model analysis using data from a German cohort

Abstract

Purpose

The COVID-19 pandemic and containment measures disrupted daily life and worsened mental health. Stress, a key driver of mental disorders, likely intensified during this period. However, longitudinal studies tracking stress trajectories in the general population remain limited. This study aims to identify psychosocial stress trajectories from the pre- to post-pandemic period and examine associated characteristics in a population-based sample from a German city. Methods

966 participants from the German National Cohort study-centre in Halle (240,000 inhabitants in Eastern Germany) were included. Those participated in a six-monthly intensified assessment and completed at least four questionnaires between 2019 and 2024 containing the PHQ-Stress module. First, latent class mixed models analysis identified heterogeneous stress trajectories. Second, associations between the most likely class membership and covariates were tested with multinomial and binomial logistic regressions. Results

We identified four psychosocial stress trajectory classes. Most participants followed a resilient trajectory (82%), while others showed chronic (4%), recovered (5%), or delayed (9%) trajectories. Membership in the resilient trajectory was associated with lower pre-pandemic psychological vulnerability, higher life satisfaction, greater agreeableness, and older age. Conclusion

Resilience predominated, while smaller subgroups showed less adaptive trajectories, with prior stress levels shaping long-term patterns. These findings demonstrate heterogeneity in stress responses and support the applicability of resilience frameworks such as Bonanno’s.