Abstract summary 

Most COVID-19-related mental health research focused on average levels of mental health parameters in the general population. However, considering heterogeneous groups and their long-term responses could deepen our understanding of mental health during community crises. This four-wave study aimed to (1) identify subgroups with different trajectories of depressive and anxiety symptoms in the German general population, and (2) investigate associated risk factors.We analyzed self-report data from N = 1257 German adults participating in a European cohort study, assessed in summer 2020 (T1), and at 6 (T2), 12 (T3), and 30 months (T4). Depressive and anxiety symptoms were measured using the PHQ-4. Sociodemographic, health-related, and pandemic-related variables were assessed at baseline. We applied growth mixture modeling to identify subgroups of symptom trajectories and conducted multinomial logistic regression to examine factors associated with class membership.We identified six symptom trajectories: Low-stable (n = 971, 77.2 %), Continuous deterioration (n = 30, 2.4 %), Transient deterioration (n = 75, 6.0 %), Continuous improvement (n = 97, 7.7 %), Transient improvement (n = 38, 3.0 %) and Chronicity (n = 46, 3.7 %). Age, education, work status, mental health diagnoses, self-reported health, and pandemic-related news consumption were significantly associated with subgroup membership.The generalizability of the study is constrained by an unrepresentative sampling method, a notable dropout rate, and limited consideration of risk factors.Most people experienced low symptoms or improvement during the pandemic, while others experienced chronic or transient symptoms. Specific risk factors were associated with these trajectories, revealing nuanced mental health dynamics.

Authors & Co-authors:  Kenntemich von Hülsen Eggert Kriston Gallinat Schäfer Lotzin

Study Outcome 

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