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. 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 equation model. A total of 830 participants were included, including general population (n = 640) and health-care workers (n = 190). 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). In the general population post-traumatic stress mediated the relationship between anxiety and depression (β = 0.12; 95%CI = 0.06 to 0.18) which was significant, but the indirect effect of post-traumatic stress was not significant in health care workers (β = 0.03; 95%CI = − 0.11 to 0.19). The prevalence estimates relied on self-reported information. Other variables of interest, such as intolerance to uncertainty or income level, could not be evaluated. 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.

中文翻译：

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普通人群和医护人员对 COVID-19 的抑郁、创伤后应激、焦虑和恐惧：秘鲁的患病率、关系和解释模型

这项研究有两个目的。首先，确定恐惧模型与普通人群和医护人员中的 COVID-19、焦虑和创伤后压力的拟合度。其次，确定哪种模型最能解释两组中抑郁症与恐惧、焦虑和创伤后应激三元组之间的关系。使用自我报告的焦虑、对 COVID-19 的恐惧、抑郁和创伤后应激障碍的问卷进行了一项横断面研究。信息是从居住在秘鲁首都和人口最多的城市利马的成年人收集的。使用结构方程模型评估解释模型。共有 830 名参与者参与其中，其中包括普通人群 (n = 640) 和卫生保健工作者 (n = 190)。抑郁症状（16%）、焦虑（11.7%）和创伤后应激（14.9%）的总体患病率很高。与卫生保健工作者 (17.9%) 相比，普通人群 (28.6%) 抑郁、焦虑或压力症状的患病率更高。对 COVID-19 的恐惧、焦虑和压力的三元组模型为两组提供了足够的拟合优度指数。基于三联变量（CFI = 0.94；TLI = 0.94；RMSEA = 0.06；SRMR = 0.06），建立了一个模型，能够解释 70% 以上的普通人群和卫生保健工作者的抑郁症状。在普通人群中，创伤后应激介导了焦虑和抑郁之间的关系（β = 0.12；95%CI = 0.06 至 0.18），这种关系显着，但创伤后应激的间接影响在医护人员中并不显着（β = 0.03；95%CI = − 0.11 至 0.19）。患病率估计依赖于自我报告的信息。其他感兴趣的变量，例如对不确定性或收入水平的不容忍度，无法评估。我们的研究提出并测试了一种可以解释 70% 以上抑郁症状的模型。该解释模型可用于健康环境和人群，以确定情绪因素如何影响抑郁症状。