Contribution of risk and resilience factors to anxiety trajectories during the early stages of the COVID-19 pandemic: A longitudinal study

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.