Coronavirus (COVID-19)-Associated Psychological Distress Among Medical Students in Iran.

Aim The COVID-19 was declared a pandemic in early 2020 and is associated with high public anxiety all over the world. The healthcare community is at the highest risk of infection and thereby prone to most distress. The aim of this study was to explore and evaluate the degree of depression, anxiety, and stress levels among medical college students during the COVID-19 epidemic in Iran. Methods A cross-sectional study was conducted in February and March 2020, 3 weeks after the first reported COVID-19 infection was identified in Iran. All medical college students who entered clinical courses were eligible for the study. Depression, stress, and anxiety were evaluated in these students using the DASS-21 questionnaire. Participants were selected by using availability sampling. All statistical analyses were performed using R version 3.5.1. Results The total number of participants was 207, with 143 males and 64 females. More than half of the participants (57.97%) were married. The mean duration of working experience among students with COVID-19 infection and experience in a medical ward was 3.00 ± 1.27 days and 17.40 ± 7.26 months, respectively. The majority of students had 2 or 3 days working experience with COVID-19 infection. The mean anxiety score of participants was 28.56 ± 4.68, the depression score was 29.36 ± 4.42, and the stress score was 28.99 ± 4.53. Our findings indicated that the mean scores of depression were at an "extremely severe" level, while stress and anxiety were at "severe" levels. The prevalence of "severe" symptoms of depression, stress, and anxiety was 69.57%, 60.87%, and 99.04%, respectively. Conclusions There is a high prevalence of anxiety and depression among medical students who were exposed to COVID-19-infected patients. Our results highlight the need to establish psychological support programs, training, and self-care for medical college students in relation to mental health. We recommend incorporation of molecular biomarker tests into an algorithm to aid in assessments and consideration of the appropriate therapeutic responses.