Rafiee Maryam, Eskandari Tahereh, Mahmood Evan Abdulkareem, Zokaei Mojtaba, Falahati Mohsen, Khalilzadeh Naghneh Mohammad Hossein
School of Public Health and Safety, Shahid Beheshti University of Medical Sciences, Tehran, Iran.
Department of Occupational Health Engineering, School of Public Health, Iran University of Medical Sciences, Tehran, Iran.
Heliyon. 2024 Jul 6;10(14):e34099. doi: 10.1016/j.heliyon.2024.e34099. eCollection 2024 Jul 30.
This study aims to predict how COVID-19 anxiety affects productivity determinants by examining the role of perceived workload and individual job performance as mediators using Bayesian mediation analysis. To achieve the study's objectives, all nurses working at Imam Reza Hospital were recruited to participate. To gather data, all eligible and voluntary nurses were asked to complete questionnaires that included the Corona Disease Anxiety Scale (CDAS), Individual Job Performance Questionnaire (IJPQ), NASA Task Load Index (NASA-TLX), and Workforce Productivity Questionnaire. Of the total number of nurses employed, 222 (126 women and 96 men) nurses fully completed the questionnaires. Out of these, 140 individuals were married and 82 were single. The mean ± standard deviation (SD) of the age and experience were 28.56 ± 5.78 and 8.49 ± 6.50, respectively. GeNIe software version 2.0 utilized to analyze the Bayesian network. The results showed that for the high COVID-19 anxiety and high workload states, with a probability of 100 %, the probability of high evaluation and high environment increased by 16.6 % and 16.3 %, respectively, but low evaluation and low environment decreased by 22.4 % and 22 %, respectively. In the high COVID-19 anxiety and low IJP states with a probability of 100 %, most change was related to the high ability (6 % increase), low evaluation (3.9 % increase), high incentive (3.8 % increase), low ability (4.6 % decrease) and low support (2 % decrease). Regarding COVID-19 anxiety (high 100 %), workload (high 100 %) and IJP (low 100 %), most of the increase was related to high environment and high evaluation by an increase of 17.3 and 17.2 %, respectively. Also, the value of low evaluation and low environment was reduced by 24 and 23.4 %, respectively. The study's findings confirm that nurses have been more productive during the COVID-19 pandemic, despite facing high workloads and the COVID-19 anxiety.
本研究旨在通过使用贝叶斯中介分析，检验感知工作量和个人工作绩效作为中介的作用，来预测新冠焦虑如何影响生产力决定因素。为实现该研究目标，招募了在伊玛目礼萨医院工作的所有护士参与。为收集数据，要求所有符合条件的自愿护士完成问卷，问卷包括新冠疾病焦虑量表（CDAS）、个人工作绩效问卷（IJPQ）、美国国家航空航天局任务负荷指数（NASA-TLX）和劳动力生产力问卷。在受雇护士总数中，222名护士（126名女性和96名男性）完全完成了问卷。其中，140人已婚，82人单身。年龄和工作经验的平均值±标准差分别为28.56±5.78和8.49±6.50。使用GeNIe软件2.0版分析贝叶斯网络。结果显示，对于高新冠焦虑和高工作量状态，概率为100%时，高评价和高环境的概率分别增加16.6%和16.3%，但低评价和低环境分别降低22.4%和22%。在高新冠焦虑和低个人工作绩效状态下，概率为100%时，大多数变化与高能力（增加6%）、低评价（增加3.9%）、高激励（增加3.8%）、低能力（降低4.6%）和低支持（降低2%）有关。关于新冠焦虑（高概率100%）、工作量（高概率100%）和个人工作绩效（低概率100%），大多数增加与高环境和高评价有关，分别增加17.3%和17.2%。此外，低评价和低环境的值分别降低24%和23.4%。该研究结果证实，尽管面临高工作量和新冠焦虑，护士在新冠疫情期间的工作效率更高。
