ABSTRACT
Background: Job burnout is a prolonged response to chronic emotional and interpersonal stressorsObjectives: This study aimed to evaluate job burnout and identify its effective predictors among health sector employees during the COVID-19 pandemic.Methods: This cross-sectional study encompassed 1898 employees of the Shahid Beheshti University of Medical Sciences in the sum-mer of 2020. Logistic regression was used to determine factors associated with job burnout. The required data were collected elec-tronically using the Maslach Burnout Inventory (MBI) and analyzed with SPSS software version 26 and R4.0.2 software.Results: Of 1898 participants, 74.3% were female. Composite job burnout (CJB), emotional exhaustion (EE), and depersonalization (DP) were the most common at low levels, whereas reduced personal accomplishment (RPA) was the most frequent at moderate levels. In this regard, factors such as female gender, age groups of 40 -49 and >= 50 years, and exposure to COVID-19 were the main independent risk factors for job burnout.Conclusions: Reduced personal accomplishment was moderate despite relatively low levels of job burnout, EE, and DP. Accordingly, effective interventions are suggested to improve different aspects of the work-life with an emphasis on critical situations. Moreover, regarding the significant relationship between job burnout with gender, age, and exposure to COVID-19, it is recommended to in-crease the employees' knowledge about job burnout.
ABSTRACT
Introduction: Given the importance of evidence-based decision-making, this study aimed to evaluate epidemiological and clinical characteristics as well as associate factors of mortality among admitted COVID-19 cases. Methods: This multicenter, cross-sectional study was conducted on confirmed and suspected COVID-19 cases who were hospitalized in 19 public hospitals affiliated to Shahid Beheshti University of Medical Sciences (SBMU), Tehran, Iran, between February 19 and May 12, 2020. Epidemiological and clinical characteristics of the infected cases were compared between the deceased and survivors after discharge. Case fatality rates (CFRs) were calculated across all study variables. Single and multiple logistic regressions were used to explore the risk factors associated with COIVD-19 mortality. Results: Out of the 16035 cases that referred to the hospitals affiliated to SBMU, 16016 patients (99.93% of Confirmed and 99.83% of suspected cases) were hospitalized. 1612 patients died with median hospitalization days of 5 (interquartile range (IQR): 2-9) and 3 (1-7) for confirmed and suspected COVID-19 cases, respectively. The highest death rate was observed among ages>65 (63.4% of confirmed cases, 62.3% of suspected cases) and intensive care unit (ICU)/critical care unit (CCU) patients (62.7% of confirmed cases, 52.2% of suspected cases). Total case fatality rate (CFR) was 10.05% (13.52% and 6.37% among confirmed and suspected cases, respectively). The highest total CFR was observed in patients with age>65 years (25.32%), underlying comorbidities (25.55%), and ICU/CCU patients (41.7%). The highest CFR was reported for patients who had diabetes and cardiovascular diseases (38.46%) as underlying non-communicable diseases (NCDs), and patients with cancer (35.79%). Conclusion: This study showed a high CFR among suspected and confirmed COVID-19 cases, and highlighted the main associated risk factors including age, sex, underlying NCDs, and ICU/CCU admission affecting survival of COVID-19 patients