The COVID-19 pandemic, and the response of governments to mitigate the pandemic's spread, resulted in exceptional circumstances that comprised a major global stressor, with broad implications for mental health. We aimed to delineate anxiety trajectories over three time-points in the first 6 months of the pandemic and identify baseline risk and resilience factors that predicted anxiety trajectories. Within weeks of the pandemic onset, we established a website (covid19resilience.org), and enrolled 1362 participants (n = 1064 from US; n = 222 from Israel) who provided longitudinal data between April-September 2020. We used latent growth mixture modelling to identify anxiety trajectories and ran multivariate regression models to compare characteristics between trajectory classes. A four-class model best fit the data, including a resilient trajectory (stable low anxiety) the most common (n = 961, 75.08%), and chronic anxiety (n = 149, 11.64%), recovery (n = 96, 7.50%) and delayed anxiety (n = 74, 5.78%) trajectories. Resilient participants were older, not living alone, with higher income, more education, and reported fewer COVID-19 worries and better sleep quality. Higher resilience factors' scores, specifically greater emotion regulation and lower conflict relationships, also uniquely distinguished the resilient trajectory. Results are consistent with the pre-pandemic resilience literature suggesting that most individuals show stable mental health in the face of stressful events. Findings can inform preventative interventions for improved mental health.
Keywords: COVID-19; LGMM; anxiety; resilience; risk.
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