The levels and related factors of mental workload among nurses: A systematic review and meta-analysis

Factors influencing fatigue, mental workload and burnout among Chinese health care workers during public emergencies: an online cross-sectional study

OBJECTIVES

The purpose of this study was to investigate fatigue, mental workload, and burnout among health care workers (HCWs) and explore the possible underlying factors.

MATERIALS AND METHODS

An online cross-sectional survey design was used to collect data from HCWs in Chongqing, China. The online survey included the Fatigue Severity Scale, NASA Task Load Index, and Chinese version of the Maslach Burnout Inventory-General Survey to assess fatigue, mental workload, and burnout, respectively, and was conducted from February 1 to March 1, 2023.

RESULTS

In this study, the incidence of fatigue and burnout among HCWs was 76.40% and 89.14%, respectively, and the incidence of moderate to intolerable mental workloads was 90.26%. Work-family conflict, current symptoms, number of days of COVID-19 positivity, mental workload, burnout and reduced personal accomplishment were significantly associated with fatigue. Mental workload was affected by fatigue and reduced personal accomplishment. Furthermore, burnout was influenced by marital status and fatigue. Moreover, there was a correlation among mental workload, fatigue, and burnout.

CONCLUSIONS

Fatigue, mental workload and burnout had a high incidence and were influenced by multiple factors during COVID-19 public emergencies in China.

Quantifying emergency department nursing workload at the task level using NASA-TLX: An exploratory descriptive study

BACKGROUND

Emergency departments (ED) nurses experience high mental workloads because of unpredictable work environments; however, research evaluating ED nursing workload using a tool incorporating nurses' perception is lacking. Quantify ED nursing subjective workload and explore the impact of work experience on perceived workload.

METHODS

Thirty-two ED nurses at a tertiary academic hospital in the Republic of Korea were surveyed to assess their subjective workload for ED procedures using the National Aeronautics and Space Administration Task Load Index (NASA-TLX). Nonparametric statistical analysis was performed to describe the data, and linear regression analysis was conducted to estimate the impact of work experience on perceived workload.

RESULTS

Cardiopulmonary resuscitation (CPR) had the highest median workload, followed by interruption from a patient and their family members. Although inexperienced nurses perceived the 'special care' procedures (CPR and defibrillation) as more challenging compared with other categories, analysis revealed that nurses with more than 107 months of experience reported a significantly higher workload than those with less than 36 months of experience.

CONCLUSION

Addressing interruptions and customizing training can alleviate ED nursing workload. Quantified perceived workload is useful for identifying acceptable thresholds to maintain optimal workload, which ultimately contributes to predicting nursing staffing needs and ED crowding.

The mental workload of ICU nurses performing human-machine tasks and associated factors: A cross-sectional questionnaire survey

AIMS

To assess the level of mental workload (MWL) of intensive care unit (ICU) nurses in performing different human-machine tasks and examine the predictors of the MWL.

DESIGN

A cross-sectional questionnaire study.

METHODS

Between January and February 2021, data were collected from ICU nurses (n = 427) at nine tertiary hospitals selected from five (east, west, south, north, central) regions in China through an electronic questionnaire, including sociodemographic questions, the National Aeronautics and Space Administration Task Load Index, General Self-Efficacy Scale, Difficulty-assessing Index System of Nursing Operation Technique, and System Usability Scale. Descriptive statistics, t-tests, one-way ANOVA and multiple linear regression models were used.

RESULTS

ICU nurses experienced a medium level of MWL (score 52.04 on a scale of 0-100) while performing human-machine tasks. ICU nurses' MWL was notably higher in conducting first aid and life support tasks (using defibrillators or ventilators). Predictors of MWL were task difficulty, system usability, professional title, age, self-efficacy, ICU category, and willingness to study emerging technology actively. Task difficulty and system usability were the strongest predictors of nearly all typical tasks.

CONCLUSION

ICU nurses experience a medium MWL while performing human-machine tasks, but higher mental, temporal, and effort are perceived compared to physical demands. The MWL varied significantly across different human-machine tasks, among which are significantly higher: first aid and life support and information-based human-machine tasks. Task difficulty and system availability are decisive predictors of MWL.

IMPACT

This is the first study to investigate the level of MWL of ICU nurses performing different representative human-machine tasks and to explore its predictors, which provides a reference for future research. These findings suggest that healthcare organizations should pay attention to the MWL of ICU nurses and develop customized management strategies based on task characteristics to maintain a moderate level of MWL, thus enabling ICU nurses to perform human-machine tasks better.

PATIENT OR PUBLIC CONTRIBUTION

No patient or public contribution.

Nurses' mental workload and public health emergency response capacity in COVID-19 pandemic: A cross-sectional study

AIMS

The aim of this study was to assess the level of mental workload of Chinese nurses through a latent profile analysis and to explore its relationship with public health emergency response capacity.

DESIGN

A cross-sectional design with a convenience sample.

METHODS

A convenience sample of nurses from five tertiary hospitals in Chengdu between May and December 2022. Demographic, work-related information, Nurse's version of NASA's Task Load Index Scale and Nurse's Public Health Emergency Response Capacity Scale were used in this study.

RESULTS

The mean scores for mental workload and emergency response capacity for nurses were (57.19 ± 15.67) and (3.58 ± 0.77) respectively. We found that the mental workload of nurses fell into three potential categories. In addition, there were differences in psychological training and supply of epidemic prevention materials in the department among nurses with different mental workload subtypes. There was a moderate negative correlation between nurses' mental workload and public health emergency response capacity.

CONCLUSION

Our results show that there is still a strong mental workload on a proportion of nurses, and enhanced psychological training and material supply support are beneficial in relieving nurses' mental workload. The better the nurses' capacity to cope with public health emergencies, the lower their mental workload.

IMPACT

Nursing managers should pay ongoing attention to the mental workload status of nurses in the latter stages of a pandemic and individual differences in nurses' mental workload. In addition, nursing managers should be aware of the impact of public health emergency response capacity on nurses' mental workload. They can intervene in nurses mental workload from a new perspective.

PATIENT OR PUBLIC CONTRIBUTION

560 registered nurses participated in this study.

Stressors, emotions, and social support systems among respiratory nurses during the Omicron outbreak in China: a qualitative study

BACKGROUND

Respiratory nurses faced tremendous challenges when the Omicron variant spread rapidly in China from late 2022 to early 2023. An in-depth understanding of respiratory nurses' experiences during challenging times can help to develop better management and support strategies. The present study was conducted to explore and describe the work experiences of nurses working in the Department of Pulmonary and Critical Care Medicine (PCCM) during the Omicron outbreak in China.

METHODS

This study utilized a descriptive phenomenological method. Between January 9 and 22, 2023, semistructured and individual in-depth interviews were conducted with 11 respiratory nurses at a tertiary hospital in Wuhan, Hubei Province. A purposive sampling method was used to select the participants, and the sample size was determined based on data saturation. The data analysis was carried out using Colaizzi's method.

RESULTS

Three themes with ten subthemes emerged: (a) multiple stressors (intense workload due to high variability in COVID patients; worry about not having enough ability and energy to care for critically ill patients; fighting for anxious clients, colleagues, and selves); (b) mixed emotions (feelings of loss and responsibility; feelings of frustration and achievement; feelings of nervousness and security); and (c) a perceived social support system (team cohesion; family support; head nurse leadership; and the impact of social media).

CONCLUSION

Nursing managers should be attentive to frontline nurses' needs and occupational stress during novel coronavirus disease 2019 (COVID-19) outbreaks. Management should strengthen psychological and social support systems, optimize nursing leadership styles, and proactively consider the application of artificial intelligence (AI) technologies and products in clinical care to improve the ability of nurses to effectively respond to future public health crises.

Cognitive mental workload of emergency nursing: A scoping review

AIM

Emergency nurses work in an environment of high cognitive mental workload. Excessive cognitive mental workload may result in patient harm and nurses' burnout. Therefore, it is necessary to understand nurses' subjective experience of cognitive workload. This scoping review aimed to curate literature about the subjective experience of cognitive mental workload reported by nurses and psychometric measures of the phenomenon.

DESIGN

The scoping review was conducted in accordance with JBI methodology and reported using PRISMA extension for scoping review checklist.

METHODS

A priori protocol was created with Peer Review of Electronic Search Strategies checklist and registered in the OSF registry. Databases including PubMed, CINAHL, ProQuest, Scopus, Science Direct, Web of Science and Google Scholar were searched. Published reports were reviewed against the eligibility criteria by performing Title and Abstract screening, followed by Full-text screening. The initial search yielded 1373 studies. Of these, 57 studies met the criteria for inclusion in this study.

RESULTS

The search revealed five general measures of cognitive mental workload and their variations. Only one customised measure specifically for medical-surgical nurses was found in the study. Identified measures were collated and categorised into a framework for conceptual clarity. NASA Task Load Index and its variations were the most popular subjective measure of cognitive mental workload in nursing. However, no measure or self-report scale customised for emergency nurses was identified.

PATIENT OR PUBLIC CONTRIBUTION

The findings of this scoping review can inform future research into the cognitive mental workload of nurses. The findings have implications for workplace health and safety for nurses and patients.

Decoding Nursing Job Demands: A Multicenter Cross-Sectional Descriptive Study Assessing Nursing Workload in Hospital Medical-Surgical Wards

Background

Nursing workload is largely studied but poorly explored under physical, mental, and emotional dimensions. Currently, only a limited number of variables have been linked to nursing workload and work contexts.

Purpose

The study aimed to investigate whether it is feasible to identify variables that consistently correlate with nursing workload and others that are specific to the context.

Methods

We employed a descriptive correlational analysis and a cross-sectional design. Data were collected through a survey distributed to registered nurses working across Italy, at the conclusion of randomly assigned morning or afternoon shifts.

Results

We received 456 surveys from 195 shifts, collected from nurses in four public and two private hospitals. Commonly associated variables with nursing workload dimensions included patient complexity of care, admission/discharge or transfer, informing patients/relatives, contacting physicians, and unscheduled activities. Variables categorized as setting-specific were patient isolation and specialties, nurse-to-patient ratio, adequacy of staff in the shift, peer collaboration, healthcare documentation, educating others, and medical urgency.

Conclusions

In summary, certain variables consistently correlate with nursing workload across settings, while others are specific to the context of care. It is imperative for nurses and nurse managers to measure the nursing workload in various dimensions, enabling the prompt implementation of improvement actions.

Resource Deployment in Response to Trauma Patients

Background Variance in the deployment of the trauma team to the emergency department (ED) can result in patient treatment delays and excess burden on ED personnel. Characteristics of trauma patients, including mechanism of injury, injury type, and age, have been associated with differences in trauma resource deployment. Therefore, this retrospective, single-site study aimed to examine the deployment patterns of trauma resources, the characteristics of the trauma patients associated with levels of trauma resource deployment, and the deployment impact on ED workforce utilization and non-trauma ED patients. Methodology This was an investigator-initiated, single-institution, retrospective cohort study of all patients designated as a trauma response and admitted to a community hospital's ED from July 01, 2019, through July 01, 2022. Results Resource deployment for trauma patients varied by mechanism of injury (p < 0.001), injury type (p < 0.001), and patient age groups (p < 0.001). Specifically, there was a lower average trauma activation for geriatric trauma patients with a fall as a mechanism of injury compared to all younger patient groups with any mechanism of injury (F(5) = 234.49, p < 0.001). In the subsample, there was an average of 3.35 ED registered nurses (RNs) allocated to each trauma patient. Additionally, the ED RNs were temporarily reallocated from an average of 4.09 non-trauma patients to respond to trauma patients, despite over a third of the trauma patients in the subsample being the trauma patients being discharged home from the ED. Conclusions Trauma activation responses need to be standardized with a specific plan for geriatric fall patients to ensure efficient use of trauma and ED personnel resources.