RESUMO
OBJECTIVES: Health-care workers (HCW) exposed to COVID-19 are at risk of experiencing psychological distress. Although several cross-sectional studies have been carried out, a longitudinal perspective is needed to better understand the evolution of psychological distress indicators within this population. The objectives of this study were to assess the evolution of psychological distress and to identify psychological distress trajectories of Canadian HCW during and after the first wave of COVID-19. METHOD: This prospective cohort study was conducted from May 8 to September 4, 2020, and includes a volunteer sample of 373 HCW. Symptoms of post-traumatic disorder, anxiety, and depression were assessed using the Post-Traumatic Stress Disorder Checklist for Diagnostic and Statistical Manual of Mental Disorders fifth edition (PCL-5), the Generalized Anxiety Disorder-7, and the Patient Health Questionnaire-9. Descriptive statistics were used to illustrate the evolution of psychological distress indicators, whereas latent class analysis was carried out to identify trajectories. RESULTS: During and after the first wave of COVID-19, the rates of clinical mental health symptoms among our sample varied between 6.2% and 22.2% for post-traumatic stress, 10.1% and 29.9% for depression, and 7.3% and 26.9% for anxiety. Finally, 4 trajectories were identified: recovered (18.77%), resilient (65.95%), subchronic (7.24%), and delayed (8.04%). CONCLUSION: The longitudinal nature of our study and the scarcity of our data are unique among existing studies on psychological distress of HCW in COVID-19 context and allow us to contextualize prior transversal data on the topic. Although our data illustrated an optimistic picture in showing that the majority of HCW follow a resilience trajectory, it is still important to focus our attention on those who present psychological distress. Implementing preventive mental health interventions in our health-care institutions that may prevent chronic distress is imperative. Further studies need to be done to identify predictors that may help to characterize these trajectories.