Relationship of COVID-۱۹ Anxiety With Depression, Stress, and Anxiety Among Administrative Staff and Nurses in a Referral Hospital for Corona

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نوع سند: مقاله ژورنالی
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JR_INJER-9-3_005

تاریخ نمایه سازی: 20 شهریور 1401

Abstract:

Background and aims: The prevalence of the coronavirus disease ۲۰۱۹ (COVID-۱۹) was associated with many psychological consequences among personnel of hospitals. The aim of this study was to investigate the relationship between COVID-۱۹ anxiety and depression, stress, and anxiety among administrative staff and nurses. Methods: This is a cross-sectional study that was conducted in January ۲۰۲۲. All ۱۰۰ nurses and administrative staff of a hospital participated in this study. Demographic information questionnaires, Corona Disease Anxiety Scale, and Depression Anxiety Stress Scale (DASS-۲۱) were employed to collect data. Statistical analysis was performed using SPSS software version ۲۴. Results: The mean ± standard deviation age of participants was ۳۳.۵۳ ± ۶.۷۳ years. The median (interquartile range) disease anxiety in nurses and administrative staff was equal to ۷ (۴.۲۵) and ۱۰ (۸), respectively. Further, COVID-۱۹ anxiety was significantly higher in administrative staff (P = ۰.۰۰۱); moreover, a significant relationship was found between the history of COVID-۱۹ disease and disease anxiety (P = ۰.۰۴). Nurses reported higher stress than administrative staff (P = ۰.۰۲), and no significant relationship was found between COVID-۱۹ anxiety and components of DASS (P > ۰.۰۵). Conclusion: In this study, COVID-۱۹ anxiety was significantly higher in administrative staff. Therefore, during the COVID-۱۹ pandemic, it is necessary to pay attention to all jobs. Nurses reported higher stress and depression. Therefore, it is suggested that the necessary psychological measures be taken to improve their psychological states. Increasing the number of nurses, improving working conditions, reducing workload, and training can be effective in improving the mental health of nurses.

Authors

Rohollah Fallah Madvari

Industrial Diseases Research Center, Center of Excellence for Occupational Medicine, Shahid Sadoughi University of Medical Sciences, Yazd, Iran

Mahdi Jafari Nodoushan

Industrial Diseases Research Center, Center of Excellence for Occupational Medicine, Shahid Sadoughi University of Medical Sciences, Yazd, Iran

Reyhane Sefidkar

Center for Healthcare Data Modeling, Departments of Biostatistics and Epidemiology, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran

Ziba Loukzadeh

Industrial Diseases Research Center, Center of Excellence for Occupational Medicine, Shahid Sadoughi University of Medical Sciences, Yazd, Iran

Fahimeh Teimouri

Environmental Science and Technology Research Center, Department of Environmental Health Engineering, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran

Mohammad Hassan Basirinezhad

Center for Healthcare Data Modeling, Departments of Biostatistics and Epidemiology, School of Public Health, Shahid Sadoughi University of Medical Sciences, Yazd, Iran

Moein Nemati

Industrial Diseases Research Center, Center of Excellence for Occupational Medicine, Shahid Sadoughi University of Medical Sciences, Yazd, Iran

Mohadeseh Bagheshahi

Industrial Diseases Research Center, Center of Excellence for Occupational Medicine, Shahid Sadoughi University of Medical Sciences, Yazd, Iran

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