BackgroundA better understanding of the factors and their correlation with clinical first-line nurses’ sleep, fatigue and mental workload is of great significance to personnel scheduling strategies and rapid responses to anti-pandemic tasks in the post-COVID-19 pandemic era.ObjectiveThis multicenter and cross-sectional study aimed to investigate the nurses’ sleep, fatigue and mental workload and contributing factors to each, and to determine the correlation among them.MethodsA total of 1,004 eligible nurses (46 males, 958 females) from three tertiary hospitals participated in this cluster sampling survey. The Questionnaire Star online tool was used to collect the sociodemographic and study target data: Sleep quality, fatigue, and mental workload. Multi-statistical methods were used for data analysis using SPSS 25.0 and Amos 21.0.ResultsThe average sleep quality score was 10.545 ± 3.399 (insomnia prevalence: 80.2%); the average fatigue score was 55.81 ± 10.405 (fatigue prevalence: 100%); and the weighted mental workload score was 56.772 ± 17.26. Poor sleep was associated with mental workload (r = 0.303, P < 0.05) and fatigue (r = 0.727, P < 0.01). Fatigue was associated with mental workload (r = 0.321, P < 0.05). COVID-19 has caused both fatigue and mental workload. As 49% of nurses claimed their mental workload has been severely affected by COVID-19, while it has done slight harm to 68.9% of nurses’ sleep quality.ConclusionIn the post-COVID-19 pandemic era, the high prevalence of sleep disorders and fatigue emphasizes the importance of paying enough attention to the mental health of nurses in first-class tertiary hospitals. Efficient nursing strategies should focus on the interaction of sleep, fatigue and mental workload in clinical nurses. In that case, further research on solutions to the phenomenon stated above proves to be of great significance and necessity.Clinical trial registration[https://clinicaltrials.gov/], identifier [ChiCTR2100053133].

Objective : To generate a concept of brain performance capacity (BPC) with sleep, fatigue and mental workload as evaluation indicators and to analyze the correlation between BPC and the impact of COVID-19. Methods: A cluster sampling method was adopted to randomly select 259 civil air crew members. The measurements of sleep quality, fatigue and mental workload (MWL) were assessed using the Pittsburgh Sleep Quality Index (PSQI), Multidimensional Fatigue Inventory (MFI-20) and NASA Task Load Index. The impact of COVID-19 included 7 dimensions scored on a Likert scale. Canonical correlation analysis (CCA) was conducted to examine the relationship between BPC and COVID-19. Results: A total of 259 air crew members participated in the survey. Participants’ average PSQI score was 7.826 (SD = 3.796), with 49.8% reporting incidents of insomnia, mostly of a minor degree. Participants’ MFI was an average 56.112 (SD = 10.040), with 100% reporting some incidence of fatigue, mainly severe. The weighted mental workload (MWL) score was an average of 43.084 (SD = 17.543), with reports of mostly a mid-level degree. There was a significant relationship between BPC and COVID-19, with a canonical correlation coefficient of 0.507 ( P =0.000), an eigenvalue of 0.364 and a contribution rate of 69.1%. All components of the BPC variable set: PSQI, MFI and MWL contributed greatly to BPC, with absolute canonical loadings of 0.790, 0.606 and 0.667, respectively; the same was true for the COVID-19 variable set, with absolute canonical loadings ranging from 0.608 to 0.951. Conclusion: Multiple indicators to measure BPC and the interrelationship of BPC and COVID-19 should be used in future research to gain a comprehensive understanding of anti-epidemic measures to ensure victory in the battle against the spread of the disease.