Journal of Occupational
Health and Epidemiology
Rafsanjan university Of medical sciences
1- Ph.D. Student in Occupational Health Engineering, Dept. of Occupational Health Engineering, School of Public Health, Student Research Committee, Ahvaz Jundishapur University of Medical Sciences, Ahvaz, Iran.
2- Professor, Dept. of Occupational Health Engineering, Social Determinants of Health Research Center, Research Institute for Prevention of Non-Communicable Diseases, Faculty of Health, Qazvin University of Medical Sciences, Qazvin, Iran. ,svarmazyar@qums.ac.ir
2- Professor, Dept. of Occupational Health Engineering, Social Determinants of Health Research Center, Research Institute for Prevention of Non-Communicable Diseases, Faculty of Health, Qazvin University of Medical Sciences, Qazvin, Iran. ,
Article history
Received: 2024/06/2
Accepted: 2024/09/16
Accepted: 2024/09/16
Subject:
Occupational Health
Abstract: (23 Views)
Background: This study aimed to predict the resilience of hospital nurses based on workplace psychosocial factors.
Materials and Methods: This cross-sectional study was conducted among 548 nurses working at an educational hospital in Iran in 2023. Samples were selected using the census method and inclusion criteria. Data were collected using a demographic questionnaire, the Copenhagen Psychosocial Questionnaire (COPSOQ), and the Connor–Davidson Resilience Scale (CD-RISC). Data were analyzed using the Independent T-test, One-way ANOVA, Pearson, and multiple linear regression tests.
Results: The mean and standard deviation of the CD-RISC total score was 75.9±5.4. Four hundred fifty-six nurses (83.2%) reported low resilience. Significant statistical relationships were observed between resilience and gender, marital status, education (t=2.679, t=2.469, t=-2.061, P<0.05, respectively), categorized age, and work experience. Furthermore, a statistically significant correlation was found between four psychosocial factors and the mean resilience score (rfactor1=0.457, rfactor2=-0.265, rfactor3=0.197, and rfactor4=-0.349, all with P<0.001). The four psychosocial factors within the hospital environment predict 31.5% (Adjusted R2=0.315) of the nurse's resilience. Low resilience is reported more frequently among females, married individuals, those with lower education, older individuals, and those with more work experience.
Conclusion: Psychosocial factors predicted approximately one-third of the resilience levels among nurses. Factor 1, which includes quality of leadership, social support from supervisors, rewards, justice and respect, trust, and predictability) had the greatest impact on nurses' resilience. By identifying and addressing these factors, healthcare organizations can, through implementing psychosocial interventions, create supportive work environments that promote nurse resilience and ultimately improve overall healthcare outcomes.
Materials and Methods: This cross-sectional study was conducted among 548 nurses working at an educational hospital in Iran in 2023. Samples were selected using the census method and inclusion criteria. Data were collected using a demographic questionnaire, the Copenhagen Psychosocial Questionnaire (COPSOQ), and the Connor–Davidson Resilience Scale (CD-RISC). Data were analyzed using the Independent T-test, One-way ANOVA, Pearson, and multiple linear regression tests.
Results: The mean and standard deviation of the CD-RISC total score was 75.9±5.4. Four hundred fifty-six nurses (83.2%) reported low resilience. Significant statistical relationships were observed between resilience and gender, marital status, education (t=2.679, t=2.469, t=-2.061, P<0.05, respectively), categorized age, and work experience. Furthermore, a statistically significant correlation was found between four psychosocial factors and the mean resilience score (rfactor1=0.457, rfactor2=-0.265, rfactor3=0.197, and rfactor4=-0.349, all with P<0.001). The four psychosocial factors within the hospital environment predict 31.5% (Adjusted R2=0.315) of the nurse's resilience. Low resilience is reported more frequently among females, married individuals, those with lower education, older individuals, and those with more work experience.
Conclusion: Psychosocial factors predicted approximately one-third of the resilience levels among nurses. Factor 1, which includes quality of leadership, social support from supervisors, rewards, justice and respect, trust, and predictability) had the greatest impact on nurses' resilience. By identifying and addressing these factors, healthcare organizations can, through implementing psychosocial interventions, create supportive work environments that promote nurse resilience and ultimately improve overall healthcare outcomes.
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