Escuela de Medicina, Universidad César Vallejo, Trujillo, Peru.
Instituto Peruano de Orientación Psicológica, Lima, Peru.
BMC Psychiatry. 2022 Oct 10;22(1):638. doi: 10.1186/s12888-022-04277-4.
The context of the COVID-19 pandemic has harmed the mental health of the population, increasing the incidence of mental health problems such as depression, especially in those who have had COVID-19. Our study puts forward an explanatory model of depressive symptoms based on subjective psychological factors in those hospitalized for COVID-19 with and without biological markers (i.e., inflammatory markers). Therefore, we aim to evaluate the hypotheses proposed in the model to predict the presence of depressive symptoms.
We conducted a cross-sectional study, using a simple random sampling. Data from 277 hospitalized patients with COVID-19 in Lima-Peru, were collected to assess mental health variables (i.e., depressive, anxiety, post-traumatic stress, and somatic symptoms), self-perception of COVID-19 related symptoms, and neutrophil/lymphocyte ratio (NLR) such as inflammatory marker. We performed a structural equation modeling analysis to evaluate a predictive model of depressive symptoms.
The results showed a prevalence of depressive symptoms (11.2%), anxiety symptoms (7.9%), somatic symptoms (2.2%), and symptoms of post-traumatic stress (6.1%) in the overall sample. No association was found between the prevalence of these mental health problems among individuals with and without severe inflammatory response. The mental health indicators with the highest prevalence were sleep problems (48%), low energy (47.7%), nervousness (48.77%), worry (47.7%), irritability (43.7%) and back pain (52%) in the overall sample. The model proposed to explain depressive symptoms was able to explain more than 83.7% of the variance and presented good goodness-of-fit indices. Also, a different performance between the proposed model was found between those with and without severe inflammatory response. This difference was mainly found in the relationship between anxiety and post-traumatic stress symptoms, and between the perception of COVID-19 related symptoms and somatic symptoms.
Results demonstrated that our model of mental health variables may explain depressive symptoms in hospitalized patients of COVID-19 from a third-level hospital in Peru. In the model, perception of symptoms influences somatic symptoms, which impact both anxiety symptoms and symptoms of post-traumatic stress. Thus, anxiety symptoms could directly influence depressive symptoms or through symptoms of post-traumatic stress. Our findings could be useful to decision-makers for the prevention of depression, used to inform the creation of screening tools (i.e., perception of symptoms, somatic and anxiety symptoms) to identify vulnerable patients to depression.
COVID-19 大流行的背景损害了人们的心理健康，增加了抑郁等心理健康问题的发生率，尤其是在那些感染过 COVID-19 的人群中。我们的研究提出了一个基于 COVID-19 住院患者主观心理因素的抑郁症状解释模型，这些患者有或没有生物标志物（即炎症标志物）。因此，我们旨在评估模型中预测抑郁症状的假设。
我们进行了一项横断面研究，采用简单随机抽样。在秘鲁利马，共收集了 277 名 COVID-19 住院患者的数据，以评估心理健康变量（即抑郁、焦虑、创伤后应激和躯体症状）、对 COVID-19 相关症状的自我感知，以及中性粒细胞/淋巴细胞比值（NLR）等炎症标志物。我们进行了结构方程模型分析，以评估抑郁症状的预测模型。
结果显示，在总体样本中，抑郁症状（11.2%）、焦虑症状（7.9%）、躯体症状（2.2%）和创伤后应激症状（6.1%）的患病率。在有或没有严重炎症反应的个体中，这些心理健康问题的患病率之间没有关联。在总体样本中，心理健康指标中睡眠问题（48%）、精力不足（47.7%）、紧张不安（48.77%）、担忧（47.7%）、易怒（43.7%）和背痛（52%）的患病率最高。提出的解释抑郁症状的模型能够解释超过 83.7%的方差，并且具有良好的拟合优度指数。此外，在有或没有严重炎症反应的个体中，提出的模型表现不同。这种差异主要存在于焦虑和创伤后应激症状之间，以及对 COVID-19 相关症状和躯体症状之间的感知。
结果表明，我们的心理健康变量模型可以从秘鲁一家三级医院的 COVID-19 住院患者中解释抑郁症状。在该模型中，症状感知会影响躯体症状，进而影响焦虑症状和创伤后应激症状。因此，焦虑症状可能直接影响抑郁症状，也可能通过创伤后应激症状影响抑郁症状。我们的研究结果可能对决策者预防抑郁有用，可以用来为脆弱人群创建筛选工具（即症状感知、躯体和焦虑症状），以识别易患抑郁症的患者。
