Background: This study has two aims. First, determine the fit of the fear model to COVID-19, anxiety, and post-traumatic stress in the general population and health-care workers. Second, determine which model best explains the relationship between depression and the triad of fear, anxiety, and post-traumatic stress in both groups.
Method: A cross-sectional study was conducted using self-reported questionnaires for anxiety, fear of COVID-19, depression, and post-traumatic stress. Information was collected from adults living in Lima, the capital and the most populous city in Peru. The explanatory models were evaluated using a structural regression model.
Results: A high overall prevalence of depressive symptoms (16%), anxiety (11.7%), and post-traumatic stress (14.9%) were identified. A higher prevalence of depressive, anxious, or stress symptoms was identified in the general population (28.6%) compared to health-care workers (17.9%). The triad model of fear of COVID-19, anxiety, and stress presented adequate goodness-of-fit indices for both groups. A model was identified that manages to explain depressive symptoms in more than 70% of the general population and health-care workers, based on the variables of the triad (CFI=0.94; TLI=0.94; RMSEA=0.06; SRMR=0.06). Limitations: The prevalence estimates relied on self-reported information. Other variables of interest, such as intolerance to uncertainty or income level, could not be evaluated.
Conclusions: Our study proposes and tests one model that explains more than 70% of depressive symptoms. This explanatory model can be used in health contexts and populations to determine how emotional factors can affect depressive symptoms. Keywords: Depression, post-traumatic stress, anxiety, fear of COVID-19, Peru