Anxiety, depression, and sleep disorders among healthcare workers during the COVID-19 pandemic.

OBJECTIVE: In this study, we examined the level of anxiety and depression, daytime sleepiness, and sleep quality in healthcare workers working during the COVID-19 pandemic. METHODS: This study was conducted in a tertiary care university hospital. Socio-demographic information form, Beck Anxiety Scale, Beck Depression Scale, Pittsburg Sleep Quality Index, and Epworth Sleepiness Scale were used as data collection tools. RESULTS: A total of 273 healthcare workers were recruited into the study. It was determined that there is an enormous mental health burden on healthcare workers. About 100% and 45.4% of the participants got above-threshold scores from Beck Anxiety Scale, and Beck Depression Scale, and the prevalence of daytime sleepiness and impaired sleep quality was 11.4% and 38.8%, respectively. The female gender was found to have more severe anxiety levels and lower sleep quality (p<0.001). In logistic regression analysis, the female gender was a risk factor for having a level of severe anxiety, and the nursing profession was a risk factor for having severe anxiety and low sleep quality (p<0.05). CONCLUSION: Global serious outbreaks cause increased depression and anxiety levels and sleep disorders in healthcare workers. Therefore, we believe that trainings and support which aims to strengthen the psychological well-being of healthcare workers should be implemented.

Prediction of anxiety and depression in general surgery inpatients: A prospective cohort study of 200 consecutive patients.

INTRODUCTION: Surgery is a major stress factor for patients, and is associated with significant anxiety or depression. The Hospital Anxiety and Depression Scale is one of the most common instruments used for assessment of patients' psychological stress. Here, we aimed to identify predictors of anxiety and depression in surgical inpatients. METHODS: The study group consisted of consecutive two-hundred patients who completed the Hospital Anxiety and Depression Scale questionnaire. A patient scoring more than cut-off values (10 for anxiety and seven for depression) was considered as being at risk of anxiety or depression. Demographical data, socioeconomic status, education level and diagnoses were recorded. The Chi-square, Fisher's exact, Mann-Whitney, Kruskal-Wallis tests and binary logistic regression analysis were used to identify the predictive parameters for anxiety and depression. RESULTS: It was found that female patients, patients older than 35 years, patients with low socioeconomic status and low education level had a relatively higher risk of anxiety. In addition, patients with low education and a hospital stay greater than seven days were at risk of depression. Logistic regression analysis revealed that socioeconomic status and education level were strongly predictive for anxiety. However, presence of anxiety was shown to be strongly predictive for depression. CONCLUSION: Healthcare providers should be aware of their patients' psychology and, therefore, it is recommended to consider predictive factors for anxiety and depression.