Subtypes of nurses’ mental workload and interaction patterns with fatigue and work engagement during coronavirus disease 2019 (COVID-19) outbreak: A latent class analysis

The coronavirus disease 2019 (COVID-19) outbreak caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) has threatened to overwhelm healthcare systems worldwide [1]. In mainland China, nurses are at the forefront of providing critical healthcare for COVID-19 patients and have been considered the major workforce in pandemic control [2]. Nurses have been inevitably faced with increased psychological distress and physical exhaustion during this time, which may have adverse effects on not only their mental health, but also their level of work engagement and COVID-19 exposure risk. Although the relationship between physical workload and its direct neuropsychiatric consequences has been well established, few studies have focused on examining the combination of these factors, in terms of mental workload in healthcare workers.

Mental workload refers to the amount of mental effort required in relation to a worker’s ability in completing a task, which may be influenced by numerous factors such as task demand, external support, worker’s cognition, and past experience [3, 4]. Mental workload involves subjective processes and can affect physical skills causing fatigue and functional errors, then leading to change behavior and job performance [4]. High mental workload in workers may result in a decreased capacity for attention, and an increased risk of delayed responses, ultimately contributing to workplace errors [5]. Therefore, it is necessary to pay more attention to the medical personnel’s mental workload. Mental workload level is measured by the National Aeronautics and Space Administration Task Load Index (NASA-TLX) and contains a total of six dimensions: mental, physical, and temporal task demands, as well as effort, frustration, and perceived performance [6]. Due to its multidimensional characteristics, measurement of mental workload may provide a more comprehensive understanding of nurses’ work status and performance during the COVID-19 outbreak.

The job demands-resources (JD-R) model proposes that working conditions can be categorized into job demands and job resources, that are differentially related to specific outcomes [7]. Job demands such as high workload results in stress responses, that are posited to be more strongly related to fatigue, whereas resources are related to work engagement [8]. A study among Italian researchers showed that mental workload only indirectly leads to fatigue through stress and emotional dissonance, but rather was highly predictive of the level of work engagement [9]. The relationship between mental workload and work engagement among front-line nurses in Wuhan was recently documented [10], which showed that work engagement was negatively associated with frustration, but positively associated with mental demand and perceived performance. In general, studies investigating workers’ mental workload usually analyzed only a single outcome, thereby limiting the understanding of potential links between mental workload, fatigue and work engagement. Recent evidence from ergonomics research suggests that analysis of mental workload using the NASA-TLX needs to take into account each of its subtypes rather than a global score.

In actuality, characterization of mental workload subtypes and its related factors are rather complicated. Other than fatigue and work engagement, the demographic data may also have potential correlations with mental workload. In the current study, we assessed the exposure risk of COVID-19 as one of the covariables, and hypothesized that the mental workload level and its subtypes may differ according to the risk exposure level of COVID-19 in healthcare workers. Current studies tend to rely on variable-centered methods, which can obscure individual variations in the six dimensions of NASA-TLX, and therefore a “person-centered” approach may be more effective [11, 12]. One of the most popular and useful methods involves latent class analysis (LCA), which can identify subtypes of participants who share similar patterns based on the variables of interest [13].

There are few previous studies to explore whether there exist different mental workload subgroups in nursing, especially during COVID-19 outbreak. The main study objective is to investigate the level of nurses’ mental workload during the COVID-19 outbreak, clarify the subgroups of nurses’ mental workload, and examine how demographic variables, fatigue and work engagement differ among nurses belonging to different subgroups. We hypothesized that nurses can be separated into different subgroups based on the assessment of NASA-TLX, and that key factors including demographic characteristics, fatigue, and work engagement differed across different subgroups. Specifically, we examined the risk of COVID-19 exposure in order to determine the discrepancy in self-perception and perceived workload during this global health crisis. This study is the first of its type that has been conducted in China, and provides an important reference point for comparison with future international studies.

In this study, we identified three separate mental workload classes among nurses who had worked in hospitals during the COVID-19 outbreak. The three classes can be separated from one another by a relatively low, medium and high workload level. Of the 1337 nurses, the majority (62.9%) belonged to class 3 “high workload perception & low self-evaluation group”, who are most likely to be associated with longer professional years, more fatigue, better work engagement and higher COVID-19 exposure.

Self-perceived stress and mental demands are often underestimated using conventional objective workload indices, such as patient-to-nurse staffing ratios or patient acuity scores. The NASA-TLX is frequently used in emergency and Critical Care Units as a subjective measure of hospital staff workload and is supposed to be a stronger predictor of patient outcomes [23].

Our results showed that nurses’ mental workload score during the COVID-19 outbreak was 77.42 ± 14.82, and it demonstrated higher levels of mental workload than previous studies in terms of the overall score of NASA-TLX [24, 25], especially evident in those in class 3 (mean score of 85.28 ± 0.32), which can be attributed to the heavier overload faced by Chinese nurses during the COVID-19 outbreak. Another characteristic of nurses in class 3 was relatively low self-evaluation (mean score of 14.33 ± 0.28), meaning that they felt more frustrated while working in the hospitals, and this can be partly explained by tense patient-nurse relationships and the higher risk of COVID-19 exposure during the outbreak. During working hours, nurses were required to wear personal protective equipment (PPE) for 6 h or more of work, and coupled with the frequent and time-consuming process of putting on and taking off PPE, would have had adverse effects on the nurses’ mental burden [26].

Comparisons of demographic variables across different subgroups showed that the majority of nurses in class 3 shared the characteristics of older, higher education level, married with child, having more years of clinical practice and working under higher COVID-19 exposure risk, which shows that these individuals were senior professionals who generally took on more challenging and complex nursing tasks. This result is consistent with a previous study that showed employees over 36 years of age had heavier work pressure than those younger than 36 [27]. Older nurses are often imposed with increased responsibility, which may in turn lead to a heavier workload. Nurses in class 1 had the lowest mean mental workload score (mean score of 36.02 ± 2.11) and tended to be younger among the three classes. This might due to the less complexity of clinical practice and technical for novice nurses. However, in contrast to other previous findings [28], our study showed that there were no sex differences between different subgroups, which may be attributed to the substantially lower proportions of male nurses. In order to further assess the impact of the COVID-19 outbreak exposure on nurses’ mental workload, we stratified all subjects to three categories according to the risk of virus exposure across different nursing units. Nurses with the highest exposure risk were those who had direct contact with confirmed COVID-19 positive patients [26]. Group comparison results indicated that COVID-19 exposure contributed to significantly higher mental workload levels. A recent study showed that nurses showed excitability, irritability, unwillingness to rest, and signs of psychological distress in mobile hospitals [29]. Thus, psychological interventions and assistance should be provided to nurses, whether online or face-to-face, in order to help decrease work-related stress.

According to the JD-R model [30], the balance between the job resources and the job demands may lead to higher motivation and positive organizational outcomes, or to the exhaustion of mental and physical energy. Fatigue was recognized as negative outcome, and the work engagement refers to the positive aspect [31]. Previous studies have regarded these three variables as interrelated factors, and mostly used structural equation models to analyze the potential relationship. As suggested by Francesco Pace et al. [9], mental workload leads to fatigue only indirectly through stress and emotional dissonance, while significantly predicting the work engagement among Italian researchers. Similarly, fatigue may be indirectly influenced by mental workload, but also mediated by an individual’s work engagement and their proficiency towards specific tasks [32]. Due to the multidimensional concept of mental workload, the relationships between mental load, fatigue and work engagement are more complicated than that. Our current study showed significant differences in fatigue among nurses belonging to the different subgroups. Multivariate analysis further demonstrated that high cognitive workload significantly increased the subjective assessment of fatigue, regardless of demographic variables such as sex, age, marital state and professional years. This result is in line with a previous study that showed excess cognitive workload resulted in fatigue, independent of inadequate sleep [33]. Theoretically, high mental workloads can result in increased physical fatigue and mental distress in a clinical setting, which may negatively affect nurses’ work engagement [34]. On the contrary, our current study showed that nurses with higher UWES scores belonged to the high workload perception & low self-evaluation group. Thus, there may be a potential positive correlation between nurses’ mental workload and work engagement. Moreover, a positive and supportive working environment can often accommodate nurses’ psychological needs and provide greater work engagement, which requires further investigation.

The current study examined the mental workload patterns and responses faced by nurses during the COVID-19 outbreak. A total of 62.9% of participants belonged to class 3, that is, those who reported to be the most fatigued. High COVID-19 exposure risk was associated with higher mental workload in nurses. The complex scenario for the care of patients with infectious diseases, especially during an epidemic, raises the need for improved consideration of nurses’ perceived workload, as well as their physical fatigue, work engagement and personal safety. Demographic factors may have variations based on the type of mental workload and may pose a challenge for health institutions in adapting to the changing needs of the environment, and require improved human resource management strategies that are not only patient-centered, but also safe and efficient for nurses.