Demographic predictors of resilience among nurses during the COVID-19 pandemic.

Afshari, Davood; Nourollahi-Darabad, Maryam; Chinisaz, Niloofar

BACKGROUND Coronavirus disease 2019 (COVID-19) is mostly transmitted through respiratory droplets. One of the exposure methods pf this disease is through occupational exposures and, thereby, a large number of people are prone to catching this disease due to their occupations. Nurses during the COVID-19 pandemic are at the forefront of healthcare. There is no information about the level of resilience and the demographic and job factors predicting resilience in the critical conditions of this occupational group. OBJECTIVE The present study aims to determine the resilience score and its predictive demographic factors among the nurses working at the hospitals involved with COVID-19 in Ahvaz, Iran. METHODS 387 nurses from Ahvaz hospitals participated in this study. The Connor-Davidson Resilience Scale (CD-RISC) was used to assess resilience. Demographic information was also collected using a designed questionnaire. Since the present study was conducted during the COVID-19 pandemic, the questionnaires were sent online. Data were entered into software SPSS (version 23) and T-test, ANOVA and regression methods were used for data analysis. RESULTS The mean score of 61.18 (±14.8) was obtained for CD-RISC. The results of this study showed that age (r = 0.610, P = 0.003), work experience (r = 0.572, P = 0.030), and level of education (r = 0.514, P = 0.044) had a significant positive correlation with nurses' resilience score during the COVID-19 pandemic. Multiple regression analysis indicated that work experience and level of education were the predictors of nurses' resilience (R2 = 0.15). CONCLUSION The score of nurses' resilience was low. Based on the results, education and work experience were determined as the contributing factors for resilience. The findings can help to better understand effective and predictive demographic factors to achieve higher resilience in stressful situations.