Workload Of Nurses Research Articles

Validation of SIPI and comparison with objective nursing workload

ABSTRACT Background Accurately estimating nursing care workload upon hospital admission is crucial for resource allocation. Despite the introduction of tools like the ‘Information System of Nursing Performance’ (SIPI) in Italy, studies evaluating their effectiveness are lacking. Aim This study aimed to validate SIPI based on nursing care demands in an internal medicine ward. Design Single-centre, observational study of all patients admitted to an internal medicine department in an Italian hospital from 1 September to 31 December 2022. Methods Nursing activities were documented over the first 3 days of hospitalization using a standardized form, measured as performance/5 min/patient/day. Multivariate analysis assessed SIPI’s association with nursing workload. SIPI’s ability to predict excessive nurse workload was evaluated using the AUROC curve. Results The study included 306 patients. Mean SIPI value was 53.9 (20.6). Daily average care demands varied by SIPI category: 20.7 performances in very low, 26.8 in medium-low, 28.7 in medium-high, and 32.4 in very high (P = 0.001). SIPI was independently associated with increased care demands (OR: 1.024; 1.002–1.047, P = 0.033). The AUROC for SIPI predicting excessive workload was 0.614 (95% CI: 0.545–0.683). Conclusions SIPI is useful for identifying nursing workload and correlates with patient care demands.

Decision fatigue experience of front-line nurses in the context of public health emergency: an interpretative phenomenological analysis

BackgroundDecision fatigue is a new concept in the field of psychology and refers to a state of fatigue alongside impaired cognitive processing and emotional regulation ability. Previous studies have confirmed that nurses are prone to decision fatigue, and nurses who experience decision fatigue may implement nursing measures that are inconsistent with clinical evidence, thus affecting patients’ benefits. COVID-19, as a large-scale global public health emergency, increased the workload and burden of nurses and aggravated decision fatigue. However, the factors leading to decision fatigue among nurses have not yet been identified.MethodsThis study is guided by interpretative phenomenology. During the epidemic period of COVID-19: From November 2022 to February 2023, a one-to-one, semi-structured in-depth interview was conducted among nurses with decision fatigue experience who were participating in front-line work in Jilin Province using homogenous sampling. The interview recordings and related data were transcribed into text within 24 h, and data analysis was assisted by NVivo 12.0 software.ResultsAfter a total of 14 front-line nurses were analyzed in this study, The thematic level reaches saturation, the findings present a persuasive and coherent narrative, and the study is terminated, and finally extracted and formed three core themes: “Cognition, influence and attitude of decision fatigue”, “Approaching factors of decision fatigue” and “Avoidant factors of decision fatigue”.ConclusionThis study confirmed that decision fatigue was widespread in the work of front-line nurses, affecting the physical and psychological health of nurses, the quality of nursing work, the degree of benefit of patients and the clinical outcome. However, nursing staff do not know enough about decision fatigue, so the popularization and research of decision fatigue should be strengthened. Improve the attention of medical institutions, nursing managers and nursing staff.Some suggestions are put forward for the intervention of decision fatigue through personnel, task, tool and technology, organization and environment.

Intensive care unit nursing workload estimation in smart hospitals

PurposeThe objectives of the proposed model are: aiding nursing staff in documentation tasks, which can be onerous and stressful; and helping management by offering an estimate of the nursing workload, which can be considered for administrative purposes, such as staff scheduling.Design/methodology/approachAn exploratory-descriptive study was conducted in order to identify, investigate, and describe the problem of documenting nursing activities and workload estimation in an intensive care unit. Technological solutions were explored, and models were proposed to address these issues.FindingsCross-dataset experiments were performed, and the model was able to offer an adequate estimate of the nursing workload. The results suggest that continuous retraining is essential for maintaining high accuracy. While the proposed model was considered in the context of an adult ICU, it can be adapted to other contexts, such as elderly care.Research limitations/implicationsWhile the proposed solution seems promising, further research is required, such as deploying this system in an ICU and facing challenges in the areas of computer security, medical ethics, and patient data privacy. More patients’ variables could also be collected to improve the workload estimates.Originality/valueNursing workload assessment is critical to improve the cost-benefit ratio in health care, offer high-quality patient care, and reduce unnecessary expenses, and this process is usually manual. An automated device can automatically document the amount of time spent in patient care activities in a more transparent, efficient, and accurate manner, freeing staff for more urgent activities and keeping management better informed about day-to-day nursing operations.

Delirium care burden of intensive care nurses caring for patients undergoing open-heart surgery: A mixed-method research.

Delirium is an acute confusional state characterized by inattention, cognitive dysfunction and an altered level of consciousness. Delirium causes negative outcomes in patients, and patients with delirium increase the workload of nurses. Therefore, it is important to recognize the challenges and burdens experienced by nurses caring for patients with delirium. To determine the subjective burden experienced by intensive care nurses caring for patients who have undergone open-heart surgery. A mixed-method sequential explanatory design. A non-probability purposive sampling method was used for the quantitative stage. Using OpenEpi, we employed the method of sample calculation with an unknown universe. The sample size of the quantitive study comprised 130 nurses. Quantitative data were collected with Google survey. For gathering qualitative data, online video interviews were conducted with 10 nurses, an interpretive phenomenological approach was used and content analysis was performed. In the quantitative phase, we found that the subjective burden was high. In the qualitative phase, five main themes emerged: difficulty in recognizing delirium, physical burden, emotional burden, burden in care management of patients with delirium and the effect of patients with delirium on other patients. The nurses experienced physical and emotional burden in delirium management and felt lonely while caring for patients with delirium. Because nurses play a key role in the care of patients with delirium, reducing the burden nurses experience when caring for patients with delirium should be considered important in ensuring that this patient population receives adequate care. Delirium patients create a care burden for intensive care nurses. To reduce this burden of care, in-service training in patient management and bedside teaching support should be provided to nurses. Furthermore, the use of a valid scale to diagnose delirium should be integrated into health policies. Nurses should not be left alone in the management of delirium. Managing delirium patients with a team including physicians, nurses and professionals from other health disciplines will ensure that patients receive high-quality care, thereby reducing the care burden of nurses.

Workload of home care nurses: Italian adaptation, validity, and reliability of the National Aeronautics and Space Administration Task Load Index questionnaire.

The aim of this study was to adapt the National Aeronautics and Space Administration Task Load Index (NASA-TLX) to the home care setting and translate and validate it in Italian. An online questionnaire containing the Italian version of the NASA-TLX adapted to the home care setting was administered to home care nurses to measure workload. Content Validity Index, Exploratory, and Confirmatory Factor Analyses were used to measure the psychometric characteristics of the modified NASA-TLX. The modified Italian version of NASA-TLX_HC-IT showed good psychometric characteristics in measuring the workload of home care nurses, with excellent fit indices. The reliability, calculated with Cronbach's alpha, was 0.73, indicating adequate reliability. A negative correlation between workload and job satisfaction among home care nurses, as well as a positive association between high workload and intention to leave the workplace, was verified. The modified Italian version of the NASA-TLX_HC-IT was confirmed to be a valid and reliable instrument to measure workload in home care nursing. Furthermore, the correlation between workload and the intention to leave the workplace among home care nurses was an important result that community nursing managers should consider preventing the shortage of home care nurses.

Departmental Workload and Job Satisfaction of Indonesian Nurses in Saudi Arabia: A Cross Sectional Study

Indonesian foreign nurses working in Saudi Arabia have not been surveyed regarding workload and job satisfaction in the healthcare setting. Understanding the workload at hospital that influences job satisfaction provides an overview of the nurse’s existence at work. This study aimed to determine the prevalence of workload, and job satisfaction of Indonesian nurses in Saudi Arabia. A cross sectional study using self- administered questionnaire by Nasa Task Load Index (NASA-TLX) was used to analyze the workload, and the Minnesota Satisfaction Questionnaire (MSQ) for the satisfaction. Data were analyzed using descriptive methods and univariate statistics by SPSS version 26. A total of 132 nurses participated in this research. Five departments, including intensive care unit (ICU), emergency department (ER), operating room (OR), hemodialysis (HD), and ward department (WD) reported high workload levels (61-80 points). Job satisfaction in five departments was neutral category, while the ward department showed dissatisfied category. The analysis of nurses' characteristics revealed that the majority were aged 31-40 years old (46.2%), length of work was 1-5 years (54.5%), and worked in the outpatient department (42.4%). The study suggests that healthcare management and policymakers should implement programs to improve job satisfaction and reduce workload, especially for foreign nurses working in critical areas, including the five departments mentioned.

The Effect of Academic Model Supervision on the Workload and Stress of Nurses in Hospitals: A Literature Review

Nurses often face high workloads and significant levels of stress due to the demands of complex work and high pressure. The academic supervision model is important because it can help nurses manage workload, improve skills and knowledge, and reduce stress levels. Effective supervision is expected to improve the quality of health services, job satisfaction, and have a positive impact on patients and the health system as a whole. This study aims to determine the influence of academic model supervision on the workload and stress of nurses in hospitals. This study uses a literature review method from research articles in the Scopus and Google Scholar databases published in 2014-2023 with the keywords "Supervision", "Academic Model", "Nurse Workload", and "Nurse Stress". Based on the analysis of 22 research articles, it was found that the supervision of the academic model had a positive impact on nurse performance, job satisfaction, work motivation, quality of nursing care, reduction of stress levels, and improvement of overall health service quality. Academic model supervision can help nurses improve skills and knowledge, improve services provided, develop professionalism, increase independence, improve nursing care, reduce workload, improve nurse performance, provide good emotional support, and continuous learning, and reduce the level of stress experienced by nurses. The implications of this research suggest that implementing academic model supervision in hospitals can lead to better nurse outcomes, including enhanced job satisfaction, reduced stress, and improved quality of care. Consequently, this can result in higher patient satisfaction and a more efficient and effective health care system overall.

The Relationship between Nurse Workload and Attitudes in Fulfilling Spiritual Needs in Hospital Inpatient Rooms Bhakti Husada Cikarang

The Relationship between Nurse Workload and Attitudes in Fulfilling Spiritual Needs in Hospital Inpatient Rooms Bhakti Husada Cikarang

Compassion fatigue and loneliness at work in nurses - the mediating role of resilience: a cross-sectional study.

Heavy workload, job stress and lack of colleague support can lead to loneliness and burnout in nurses. Caring for a patient with constant pain can cause compassion fatigue. Loneliness at work and compassion fatigue also negatively affect the quality of patient care. This study aims to determine the effect of resilience on loneliness at work and compassion fatigue in nurses. This is a descriptive cross-sectional study. The study was conducted with a total of 214 nurses. A statistically significant negative relationship was found between the level of loneliness at work and resilience, and between resilience and compassion fatigue in nurses. The mediating role of resilience was found to be significant in the effect of loneliness at work on compassion fatigue in nurses. The results of this study suggest empowering nurses who have loneliness at work and compassion fatigue. Compassion fatigue is seen as occupational deformation. Nurses need to learn how to manage compassion fatigue, develop coping skills and receive support to ensure job satisfaction. In addition, nurse managers should create a reasonable workload for nurses. These efforts can increase the job satisfaction and patient care quality of nursing departments.

Development of a Nursing Diagnosis/Record Generative AI System Based on Virtual Patient Data.

This study investigates how to reduce nurses' repetitive electronic nursing record tasks. We applied generative AI by learning nursing record data practiced with virtual patient data. We aim to evaluate generative AI's usefulness, usability, and availability when applied to nursing record creation tasks. The nursing record data collected through the electronic nursing record system for nursing students without privacy issues is in the form of NANDA, FocusDAR, SOAPIE, and narrative records. We trained 50,000 nursing record data and upgraded the performance through generative AI and fine-tuning. A separate API was used to connect with the practice electronic nursing record system, and 40 experienced nurses from a university hospital conducted tests. The electronic nursing record, through generative AI, is expected to contribute to easing the workload of nurses.

Prevalence and factors associated with poor sleep quality among nurses in COVID-19 wards

The COVID-19 pandemic has significantly impacted the working conditions of nurses, leading to a detrimental effect on their sleep quality. This cross-sectional study aimed to investigate the prevalence of poor sleep quality and its associated factors among nurses working in COVID-19 wards in Kermanshah, Iran. A total of 97 nurses were selected through simple random sampling from COVID-19 wards. Data was collected using a demographic information sheet and the Pittsburgh Sleep Quality Index. Descriptive and inferential statistical methods, including chi-square and multiple logistic regression, were used for data analysis. The results showed that 74.2% (n = 72) of the nurses experienced poor sleep quality. Significant associations were found between poor sleep quality and work experience (p = 0.045) as well as the type of work shift (p = 0.001). However, no significant relationships were observed between poor sleep quality and factors such as age, sex, body mass index, overtime hours per month, physical activity, or underlying diseases. The high prevalence of poor sleep quality among nurses working in COVID-19 wards underscores the necessity of implementing targeted interventions to address this issue. In this regard, in addition to periodic shift schedule changes and reductions in working hours, it is necessary to adopt purposeful measures to improve working conditions and enhance the physical and mental health of nurses. These measures may include providing sufficient human resources to reduce the workload and fatigue of nurses, appropriate scheduling of working hours, and the implementation of stress management programs.

Workload Indicator Staffing Need (WISN) as A Method for Analyzing Clinic Health Personnel Needs in Surakarta

Introduction: Health Human Resources (HR) has an important role in providing health services to the community. HR management has a positive effect on organizational performance. Lack of health human resources is an important obstacle in achieving the highest level of health and as a result will limit opportunities to achieve comprehensive health goals. Health workforce planning is an important element in health service planning in building a responsive and efficient health service system. The use of workforce planning methods can contribute to the analysis and decision-making process for allocating the right number of professionals. WISN as a workload-based method can provide more accurate staff needs. This method has been used in various countries and has proven its significance in policy making regarding recruitment, distribution, training and reduction of human resources. Objective: This research aims to analyze the need for health workers at the Surakarta City Clinic using the WISN method. Method: This type of research is descriptive qualitative using interview methods with respondents and observation. The research was conducted at the 'Aisyiyah Medical Center Surakarta Clinic. The data was processed using qualitative data analysis and simple statistical techniques. Result: The research results showed that the need for health workers at the AMC Clinic based on the WISN method was 1 Dentist, 2 General Practitioners, 2 Nurses, 2 Midwives and 1 Pharmacy Personnel, this shows that the Clinic has an excess number of General Practitioner health workers but a shortage of Nurses. Conclusion: The workload of General Practitioners and Dentists is low, the workload of Midwives and Pharmacy Personnel is normal, and the workload of Nurses is high.

Blood Pressure Trends, Demographic Data, Workload, and Lifestyle Factors Among Nurses in the Subcarpathian Region of Poland: A Cross-Sectional Observational Study.

BACKGROUND Hypertension is one of the main modifiable risk factors linked to cardiovascular disease and its prevalence is currently increasing in various age groups. This study aimed to evaluate blood pressure, demographic data, workload, and lifestyle factors in nurses employed in hospitals in the Subcarpathian region of southeastern Poland. MATERIAL AND METHODS This cross-sectional observational study was conducted among 627 professionally active nurses. Certified devices were used for measurements: body mass analyzer (Tanita MC-980 PLUS MA), automated sphygmomanometer (Welch Allyn 4200B), stadiometer (Seca 213), and tape measure (Seca 201). The frequency of consumption of specific product groups was assessed using a survey method. Analysis using R software (version 4.3.1) employed logistic regression to examine variables affecting hypertension occurrence. RESULTS The study found that elevated blood pressure is more prevalent among nurses than they self-report. Logistic regression analysis identified significant predictors for hypertension, including age (odds ratio; OR=1.061; OR=1.045), working more than 1 job (OR=1.579; OR=1.864), and body mass index (OR=1.152; OR=1.113). CONCLUSIONS Regular monitoring of blood pressure is necessary for early detection and timely intervention of hypertension. Enhancing nurses' awareness of their own health will encourage proactive preventive measures. Implementing comprehensive education programs focused on the latest advances in cardiovascular disease prevention is essential.

Webcam technology on neonatal wards—examining the objective and subjective workload of nurses: a combined observational and survey study

BackgroundThis study was conducted to estimate the additional objective and perceived workload of nurses resulting from the use of webcams. The successful implementation of webcam technology into routine care requires an analysis to prevent adverse events of increased nursing workload.MethodsThe study took place on three neonatal wards in two University Hospitals in Germany. In the first Hospital, the study was conducted from February to July 2021; in the second one it was conducted between June and November 2021. Data were collected using a combined approach of a standardised diary questionnaire study and passive observations. The participants were accompanied in their daily work and their activities were recorded 65 nurses participated.Results2,031 h were observed in 1,630 observation blocks. In 14.74% of the observation blocks webcam activities were detected. The extent to which the nurses had webcam-related additional workloads was rated as no additional workload in 82.16% of the daily questionnaires (n = 1,026).ConclusionThe observed low workload due to the webcams is in line with the nurses’ perception. The observational data revealed, on a number of different analysis levels, that a limited additional workload was generated. There was no decrease in activity performance observed and no clear indication for interruptions due to the webcam-related activities for the nurses. However, it is important to raise awareness about the individual workload levels for the successful implementation. Additional education programs can be provided for nurses.Trial registrationThe Neo-CamCare study is registered at the German Clinical Trials Register. DRKS-ID: DRKS00017755.

The Effectiveness of Electronic Cannulation Atlas in Patients with Arteriovenous Fistula.

This study aimed to assess the effectiveness of an electronic cannulation atlas in preventing and treating complications of arteriovenous fistula. The observation group, consisting of 92 dialysis patients from July to December 2021, was managed with an electronic cannulation atlas. After 6 months, the incidence of complications such as stenosis, hematoma, thrombus, aneurysm, and cannulation failure was compared between the groups. Nurse satisfaction with the electronic cannulation atlas system was also assessed through a questionnaire. The observation group had lower incidence rates of arteriovenous fistula stenosis, thrombus, aneurysm, and failure rate of cannulation compared to the control group, with statistically significant differences (p<0.05). The incidence rates of hematoa were similar in both groups, showing no significant difference (p>0.05). After 3 months of management, the incidence of arteriovenous fistula complications in the observation group was significantly lower than in the control group (p<0.05). Additionally, utilizing the electronic cannulation atlas system was found to increase nurses' job satisfaction. The use of electronic cannulation atlas for the treatment of patients' arteriovenous fistula could effectively reduce the incidence of complications of patients' arteriovenous fistula, reduce the failure rate of cannulation, reduce the workload of nurses, and improve the job satisfaction of nurses.

Analysis of needs for nurses with the workload indicator staffing needs (WISN) approach to inpatient services in the Konawe islands regional public hospital, southeast Sulawesi Province, Indonesia 2024

Background: Nurses are health human resources who have a strategic role and make a major contribution to health services to patients in hospitals. The number of health workers on duty in a hospital greatly influences services. The number of inpatient nurses at Konawe Hospital is 13 people compared to the total population, which is still in the low category with a BOR above 80%, which shows that nurses have a high workload. Objectives: This research aims to determine the analysis of nursing staff needs using the Workload Indicator Staffing Needs (WISN) approach in inpatient services at the Regional General Hospital of Konawe Islands Regency in 2023. Method: The research carried out was a qualitative descriptive study using the work sampling method. The sample for this research was all 13 inpatient nursing staff at the Konawe Islands Regional Hospital. Results: Based on the research results, it is known that the calculation of the need for nursing staff based on workload obtained 16.89 number of nursing staff with a WISN ratio of 0.7. The working days available for the HR category are multiplied by the nurses' working time so the total working time available is 1996.8. The ratio of nurses to the number of beds is 13:25 with the number of patients in 2022 being 683 patients. The workload consists of 16 types of activities, the largest of which is changing IV fluids and installing identification bracelets, namely 57048 times, while the smallest workload activities are wound care, changing dressings, nurses going around patient observation rooms, cleaning beds, taking/moving patients to another place, and received patients from other rooms, namely 11410 times. Conclusion: The current amount of power is smaller than the amount of power needed to run the existing workload. There needs to be an additional 3 people from the existing 13 people to achieve a balanced situation. Therefore, it is necessary to manage nursing staff optimally to achieve quality nursing services, considering the workload of nurses as a reference in determining the need for nursing staff.

Socialization of The Effects of Nurses Workload in Preventing The Risk of Falls in Patients at Grandmed Lubuk Pakam Hospital

The quality of nursing services is a value for health services in society. Patients are consumers who always hope to receive good health services. Many incidents may occur if the nurse's workload is too high. To overcome the danger of patients falling, it is necessary to take action to reduce the risk of patients falling. So nurses will always try to prevent patients from falling by installing identification bracelets, triangular labels on patient mattresses, warning signs, adjusting mattress height, and mattress railings. Precautions must also be in accordance with SOP. Nurse workload is the allocation of working time in providing services. The high workload of nurses occurs due to the limited number of staff and uncertain job descriptions. This outreach activity will provide knowledge and courage to communicate about workload so that we can prevent the risk of patient falls. PkM activities were socialized using lecture, question and answer and discussion methods to PkM participants, namely 15 nursing staff. To measure changes in PkM participants' knowledge, pre and post-tests were given to participants. The PkM results show that PkM participants have experienced increased knowledge in preventing the risk of patient falls. Participants also have the courage to discuss with the leadership if the workload is too heavy so that they can get the best solution. Participants also become more diligent in processing their daily work.

A Scalable and Extensible Logical Data Model of Electronic Health Record Audit Logs for Temporal Data Mining (RNteract): Model Conceptualization and Formulation.

Increased workload, including workload related to electronic health record (EHR) documentation, is reported as a main contributor to nurse burnout and adversely affects patient safety and nurse satisfaction. Traditional methods for workload analysis are either administrative measures (such as the nurse-patient ratio) that do not represent actual nursing care or are subjective and limited to snapshots of care (eg, time-motion studies). Observing care and testing workflow changes in real time can be obstructive to clinical care. An examination of EHR interactions using EHR audit logs could provide a scalable, unobtrusive way to quantify the nursing workload, at least to the extent that nursing work is represented in EHR documentation. EHR audit logs are extremely complex; however, simple analytical methods cannot discover complex temporal patterns, requiring use of state-of-the-art temporal data-mining approaches. To effectively use these approaches, it is necessary to structure the raw audit logs into a consistent and scalable logical data model that can be consumed by machine learning (ML) algorithms. We aimed to conceptualize a logical data model for nurse-EHR interactions that would support the future development of temporal ML models based on EHR audit log data. We conducted a preliminary review of EHR audit logs to understand the types of nursing-specific data captured. Using concepts derived from the literature and our previous experience studying temporal patterns in biomedical data, we formulated a logical data model that can describe nurse-EHR interactions, the nurse-intrinsic and situational characteristics that may influence those interactions, and outcomes of relevance to the nursing workload in a scalable and extensible manner. We describe the data structure and concepts from EHR audit log data associated with nursing workload as a logical data model named RNteract. We conceptually demonstrate how using this logical data model could support temporal unsupervised ML and state-of-the-art artificial intelligence (AI) methods for predictive modeling. The RNteract logical data model appears capable of supporting a variety of AI-based systems and should be generalizable to any type of EHR system or health care setting. Quantitatively identifying and analyzing temporal patterns of nurse-EHR interactions is foundational for developing interventions that support the nursing documentation workload and address nurse burnout.

The dual protective role of accountability: Mitigating missed nursing care and nurse moral distress in a nested diary study design.

To examine a novel moderated-mediation model, investigating whether personal accountability moderates the link between nurse workload and missed nursing care and whether missed nursing care mediates the association between workload and moral distress. Nested diary study. Data spanning from February 2019 to February 2023 were collected from 137 nurses working in various inpatient wards in two medium-sized hospitals. Nurses reported care given to specific patients on three to five occasions across different shifts, establishing nurse-patient dyads. Validated measures of missed nursing care, personal accountability, moral distress and workload were analyzed using mixed linear models to test the nested moderated-mediation model. Under high workload conditions, nurses with higher personal accountability reported lower frequencies of missed nursing care compared to those with lower personal accountability. In contrast, under low workload conditions, personal accountability did not significantly influence missed nursing care occurrences. Furthermore, the interaction between workload and personal accountability indirectly affected nurses' moral distress through missed nursing care. Specifically, higher personal accountability combined with lower missed nursing care contributed to reduced levels of moral distress among nurses. The study highlights accountability's dual role-safeguarding against care omissions and influencing nurses' moral distress amid rising workload pressures. Cultivating a culture of accountability within healthcare settings can serve as a protective factor against the negative effects of workload on patient care quality and nurse psychological distress, highlighting the need for organizational interventions to promote accountability among nursing staff. By recognizing accountability's pivotal role, organizations can implement targeted interventions fostering accountability among nurses, including training programs focused on enhancing responsibility/ownership in care delivery and creating supportive environments prioritizing accountability to achieve positive patient outcomes. The study has adhered to STROBE guidelines. No patient or public contribution.

The mediating effect of coping styles between emergency capacity and mental workload among clinical nurses: A cross-sectional study.

This study aimed to examine the relationship between emergency capacity, coping styles, and mental workload among nurses. Emergency capacity, coping styles, and mental workload are all variables associated with work. Identifying the relationship between these variables can facilitate administrators to implement tailored and effective intervention strategies to improve individual performance, quality of care, and medical safety. A quantitative cross-sectional study was carried out to investigate 605 Chinese clinical nurses in seven tertiary hospitals by using personal information form, emergency capacity scale for nurses, simplified coping skill questionnaire, and the NASA-Task Load Index. Emergency capacity and mental workload were found at moderate levels. The multiple linear regression model suggested that spinsterhood, no children, high workload, always anxiety or nervousness, and lower monthly income were the influencing factors of mental workload. Positive coping style was positively correlated with emergency capacity and negatively correlated with mental workload. Negative coping style was negatively related to emergency capacity and positively related to mental workload. Additionally, coping styles played a partial mediating role in the relationship between emergency capacity and mental workload through constructing a structural equation model, but the effects of positive coping style and negative coping style are opposite. Our results showed that coping styles played a mediating role in the relationship between emergency capacity and mental workload. Managers can alleviate the mental workload of nurses by cultivating positive coping styles and improving emergency capacity. Mental workload of nurses deserves more attention in medical institutions. The results of our study provide evidence for improving employee health, promoting positive behaviors, and optimizing organizational management. Nursing managers should take feasible measures to fulfill nurses' needs for emergency capacity and coping strategies to alleviate nurses' mental workload, so as to stimulate their intrinsic motivation and positive organizational behavior.