School of Public Health, Shahrekord University of Medical Sciences, Shahrekord, Iran.
Behbahan university of medical sciences, Behbahan, Iran.
BMC Health Serv Res. 2024 Aug 1;24(1):877. doi: 10.1186/s12913-024-11307-2.
Turnover intention is considered a significant challenge for healthcare and treatment organizations. The challenging conditions of treating COVID-19 patients and the physical and mental stress imposed on nurses during the pandemic may lead them to leave their jobs. The present study aimed to determine the role of psychological factors (general health, mental workload, work-family conflicts, and resilience) on turnover intention using a Bayesian approach during the COVID-19 pandemic.
The present cross-sectional study was carried out during the winter of 2021 at three hospitals in Khuzestan Province, Iran. To collect data for this investigation, 300 nurses were chosen based on Cochran's formula and random sampling technique. Seven questionnaires, including General Health, Mental Workload, Work-Family Conflict, Resilience, Job Stress, Fear of COVID-19, and Turnover Intention Questionnaires. Bayesian Networks (BNs) were used to draw probabilistic and graphical models. A sensitivity analysis also was performed to study the effects of the variables. The GeNIe academic software, version 2.3, facilitated the examination of the Bayesian network.
The statistically significant associations occurred between the variables of fear of COVID-19 and job stress (0.313), job stress and turnover intention (0.302), and resilience and job stress (0.298), respectively. Job stress had the highest association with the fear of COVID-19 (0.313), and resilience had the greatest association with the work-family conflict (0.296). Also, the association between turnover intention and job stress (0.302) was higher than the association between this variable and resilience (0.219). At the low resilience and high job stress with the probability of 100%, the turnover intention variable increased by 20%, while at high resilience and low job stress with the probability of 100%, turnover intention was found to decrease by 32%.
In general, the results showed that four psychological factors affect job turnover intention. However, the greatest impact was related to job stress and resilience. These results can be used to manage job turnover intention in medical environments, especially in critical situations such as COVID-19.
离职意愿被认为是医疗保健和医疗机构面临的重大挑战。在新冠疫情期间,治疗新冠患者的挑战性条件以及护士所承受的身心压力,可能导致他们离职。本研究旨在采用贝叶斯方法,在新冠疫情期间,确定心理因素(一般健康、精神工作负荷、工作-家庭冲突和适应力)对离职意愿的作用。
本横断面研究于 2021 年冬季在伊朗胡齐斯坦省的三家医院进行。为了进行这项调查,根据 Cochran 公式和随机抽样技术,选择了 300 名护士作为研究对象。使用了包括一般健康、精神工作负荷、工作-家庭冲突、适应力、工作压力、对新冠的恐惧和离职意愿问卷在内的 7 份问卷。采用贝叶斯网络(BNs)绘制概率和图形模型。还进行了敏感性分析,以研究变量的影响。GeNIe 学术软件,版本 2.3,用于检查贝叶斯网络。
在变量方面,新冠恐惧和工作压力(0.313)、工作压力和离职意愿(0.302)以及适应力和工作压力(0.298)之间存在统计学显著关联。工作压力与新冠恐惧的关联度最高(0.313),适应力与工作-家庭冲突的关联度最高(0.296)。此外,离职意愿与工作压力(0.302)的关联度高于与适应力(0.219)的关联度。在低适应力和高工作压力下,概率为 100%时,离职意愿变量增加 20%,而在高适应力和低工作压力下,概率为 100%时,离职意愿变量降低 32%。
总体而言,结果表明,四个心理因素影响工作离职意愿。然而,最大的影响与工作压力和适应力有关。这些结果可用于管理医疗环境中的工作离职意愿,特别是在新冠等危急情况下。