Abstract
Background: Considering the previous evidence regarding SARS/MERS outbreaks, ıt is expected that emergent psychiatric conditions such as mood disorders, anxiety, and depression disorders may occur in survivors of COVID-19.
Objectives: In this study, the effects of clinical/neurological symptoms and sociodemographic characteristics of COVID-19 patients during the infection period on the level of anxiety/depression after recovery were investigated.
Methods: Firstly, the socio-demographic characteristics of the participants and their clinical/ neurological symptoms during the infection period were determined. In addition, the Beck anxiety/depression scale was administered to the participants upon discharge. Then, the odds ratio of the variables was calculated by applying the Poisson regression method to determine the predictors affecting the level of anxiety/depression.
Results: In this study, the clinical/neurological symptoms and the sociodemographic characteristics affecting the level of anxiety/depression were found to be associated with adults (mean age 45-years). The number of days of hospitalization was the only clinical feature that increased both anxiety and depression levels. In addition, post-discharge sleep disorder, headache, and alcohol use were found to be predictors of increased anxiety levels. In addition, smoking, the presence of a person with COVID-19 infection in the immediate vicinity, traveling in the last month before the illness, fever, and loss of smell during the infection period was found to increase the level of depression. Moreover, asthma was the only significant comorbidity that increased the anxiety level, while diabetes was the only comorbidity that increased the depression level.
Conclusion: It is expected that this study will support social-psychological intervention and have some effects on reducing depressive/anxiety symptoms, which can vary widely in adults during stressful events.
Keywords: SARS-Cov-2, COVID-19, depression, anxiety disorders, poisson regression models, comorbidity.
Graphical Abstract
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