Ethics code: IR.TUMS.MEDICINE.REC.1400.544
1- Associate Professor, Department of Anesthesia, School of Allied Medical Sciences, Tehran University of Medical Sciences, Tehran, Iran , ashamsi@tums.ac.ir
2- Instructor, Department of Nursing, Khalkhal University of Medical Sciences, Khalkhal, Iran
3- Master of Science in Medical-Surgical Nursing, Ziaeian Hospital, Tehran University of Medical Sciences, Tehran, Iran
Abstract: (992 Views)
Background and Aim: One of the risks of the nursing profession is psychosocial risks that affect their adaptation and, consequently, their resilience. This risk can have a deeper impact in certain situations such as the COVID-19 pandemic; Accordingly, the present study was conducted with the aim of “determining the relationship between resilience and demographic information in nurses working in COVID-19 special wards”.
Materials and Methods: The present study was a cross-sectional descriptive-analytical study and was conducted among 128 nurses working in the COVID-19 special wards of Ziaian Hospital in 2021. Participants were selected using convenience sampling based on inclusion criteria. Data were collected using demographic questionnaires and the Connor-Davidson Resilience Scale (CD-RISC). The scale’s score ranges from 0 to 100 (cutoff point 50), with scores above 50 indicating resilience. This questionnaire has been translated and validated by Iranian researchers. Its content validity was 0.82, and its reliability, based on Cronbach’s alpha, ranged from 0.74 to 0.9 for all subscales. The data were then analyzed using SPSS software with descriptive and inferential statistical tests. A P-value of less than 0.05 was considered statistically significant.
Results: The mean age of the participants was 35.59±7.22 years. The majority of nurses were male (61.7%) and married (89.8%). The mean resilience score among nurses was 37.25±5.68, which is considered very low given the cutoff point of 50. Results from linear regression showed that work experience (β=0.485, P=0.000), shift work (β=0.233, P=0.084), and employment type (β=0.189, P=0.021) had significant predictive power for overall resilience. This indicates that nurses with fixed shifts, more work experience, and permanent or contractual employment tend to have greater resilience. This analysis revealed that these variables, in total, predict 26% of the variance in the overall resilience variable.
Conclusion: Finally, the results of this study showed that the resilience of nurses working in COVID-19 special wards was low. Factors such as service history, work shift, and employment status were effective on their resilience. Accordingly, planning to improve the level of nurses’ resilience is necessary, especially in critical situations.