Workload Levels Research Articles

A prediction model for the oceanauts’ cognitive performance based on the mental workload of typical tasks

High-level cognitive abilities are essential for the oceanauts to successfully complete the tasks, such as assessing cruising positions, operating interface commands, and responding to voice instructions. However, it is still unknown which variables impact oceanauts’ cognitive performance and how, and how best to create and implement analytic approaches to predict oceanaut’s personalized cognitive performance. As a result, we attempted to conduct cognitive tests trials on four typical activities among oceanauts. Oceanaut cognition characteristics were collected in order to create a quantitative model of cognitive performance. We utilised Radial Basis Functions to predict the oceanauts’ cognitive performance and investigated the impact of mental workload, personal characteristics, and comfort on their cognitive performance. The findings indicated that establishing an appropriate level of mental workload for the visual, auditory, cognitive, and psychomotor channels can enhance the oceanaut’s cognitive performance of individuals engaged in ocean exploration. It is worth noting that the optimal values for mental workload vary across these channels. Furthermore, the presence of suitable comfort, appropriate age, and a relatively higher level of educational background contribute to the enhancement of cognitive performance among oceanauts.

Enhanced Sustainability Assessment Framework for Plywood Manufacturing: A Multi-Method Approach Using Delphi Technique, BWM, and S-VSM

Sustainable manufacturing has emerged as a critical priority in addressing the complex environmental, social, and economic challenges of modern industry. This study focuses on the plywood sector, a significant contributor to manufacturing, which faces distinct sustainability issues such as high energy consumption, material inefficiencies, and hazardous working conditions. To address these challenges, the research introduces workload and noise level as critical indicators for assessing sustainability, broadening the scope of traditional evaluation methods. A multi-method framework was employed, integrating the Delphi technique to identify key sustainability indicators, the Best Worst Method (BWM) to assign weights to these indicators, and Sustainable Value Stream Mapping (S-VSM) paired with a Traffic Light System (TLS) to evaluate and visualize the Manufacturing Sustainability Score (MSS). Applied to a plywood manufacturing case study, the framework highlighted areas requiring improvement, particularly in worker well-being and operational safety, while demonstrating the industry's moderate overall efficiency. By offering actionable insights for improving resource use, operational processes, and employee conditions, this framework provides a practical tool for industry managers aiming to enhance sustainability. Furthermore, its adaptability makes it a valuable reference for other manufacturing sectors seeking to implement resource-efficient and sustainable practices. This research not only fills critical gaps in sustainability assessment but also contributes to advancing industry practices by emphasizing holistic and innovative approaches to manufacturing efficiency.

WORKLOAD DYNAMICS OF MEDICAL PROFESSIONALS IN BULGARIAN HEALTHCARE SYSTEM: EVIDENCES FROM AGGREGATE DATA

Purpose. This study aims to analyze the tendencies of the workload of medical professionals in Bulgaria after the liberal reforms in the national healthcare system. Material/Methods. Basic econometric methods, such as tests for structural breaks and dynamic rows modeling based on "macro-" or aggregate data, are implemented. The period covered is 1980-2023, twenty years before and twenty-four years after introducing market elements in national healthcare. Variables such as the number of patients discharged, consultations, doctors, and nurses are used to assess the workload level. Workload estimates are derived from a linear regression model of hospital output as the dependent variable with the number of doctors and nurses in the health system as factors. The model is tested for the stability of the regression coefficients (structural breaks) dated 2000. Results. A structural break was found in 2000 in all three dynamic rows of doctors, nurses, and discharges. There was a well-defined increasing trend in the number of patients passing through the hospitals after the liberalization of the national healthcare system. In this condition, the number of medical professionals follows its own dynamics – a slight reduction for the group of doctors and a sharp decline for the nurses in the after-reforms sub-period. These facts indicate the presence of an increasing trend in the workload and intensity of medical labour. The dependence is well established, especially in the case of nurses. Conclusions. This study confirms the hypothesis that the liberalization of the Bulgarian healthcare system, together with open-ended payment systems, caused an intensive growth of inpatient system output and workload. The expansion, especially for hospital facilities, which is not supported by a relevant number of medical professionals, threatens workplace performance and the quality of medical services.

Occupational injuries, mental workload and coping strategies among the nursing workforce in the Eastern Region of Ghana: a multi-centre study

BackgroundThe nursing profession plays a crucial role in the quality of healthcare services. While nurses face occupational injury challenges globally, mental workload, which is often overlooked, plays a significant role in these injuries. Understanding nurses’ coping strategies can help develop effective interventions. The study examined the influence of mental workload on occupational injuries and coping strategies among nurses.MethodsA multi-centre cross-sectional study was conducted in selected hospitals in the Eastern Region of Ghana. Using a stratified sampling technique, 317 nursing staff from 6 hospitals participated in the study. A researcher-developed occupational injury questionnaire, NASA Task Load Index and Brief COPE scale were used to measure occupational injury, mental workload and coping strategies among nurses. Descriptive statistics, Pearson moment-product correlations, and regression analysis were used to analyse the data at a statistical significance of 0.05.ResultsNeedle pricks, injuries from sharps, exposure to blood and other body fluids, and back pain and injury from patient handling tasks were shared among participants in the past year. The study also revealed a high level of mental workload among participants. A significant correlation was observed between mental workload and various occupational injuries. The participants adopted different coping strategies in dealing with the mental workload, with active coping and instrumental support being the most used coping strategies.ConclusionThe findings underscore the importance of addressing mental workload in nursing to reduce occupational injuries. To achieve this, nurses must be provided with appropriate coping strategies and support to minimise mental stress.ImplicationProviding accessible and effective coping strategies tailored to nurses’ needs can significantly improve their well-being and job performance. Healthcare administrators and policymakers should consider these results when designing interventions to support the nursing workforce.

Multimodal Assessment of Mental Workload During Automated Vehicle Remote Assistance: Modeling of Eye-Tracking-Related, Skin Conductance, and Cardiovascular Indicators

Remote assistance for highly automated vehicles (HAVs), i.e., third-party assistance from support staff outside the vehicle in times of the need for assistance, presents a solution to extend the capabilities of HAVs by integrating a third party for decision making in uncertain situations. Similar to other control center positions, we expect the remote assistance tasks to exert high mental demands on the human operators. Therefore, we assessed impact of elevated mental workload during HAV remote assistance in a controlled environment in a user study (N = 37) with the goal of identifying cues to differentiate workload levels based on eye-tracking-related, skin conductance, and cardiovascular indicators. The results provide evidence that (A) elevated workload induced via a secondary task depreciates performance, and (B) we can identify workload levels person-independently as differences in tonic skin conductance (F(2,72) = 24.538, p < 0.001, partial η² = 0.405) and pupil dilation (F(2,72) = 13.872, p < 0.001, partial η² = 0.278), resulting in a classification accuracy of 58% in a three-class classification task. The results provide evidence that we are able to differentiate operator workload during remote assistance in a time-resolved way with the ultimate goal to provide adaptations to counteract task deficiencies.

Measurement of Mental Workload with The NASA-TLX Method on Employees of PT XYZ

PT XYZ is the largest maritime industry in Indonesia. The company focuses on producing ships and repairing ships both domestically and abroad. Human resources are the most important aspect in determining the success of a company. To increase employee work productivity, companies must pay attention to the physical workload and mental workload felt by employees. Uneven workload can cause complaints, so that productivity decreases and gets less than optimal results. Therefore, a mental workload measurement was conducted to determine the level of mental workload of employees using the National Aeronautics and space Administration Task load Index (NASA-TLX) method. The NASA-TLX questionnaire was distributed to 8 workers of the ISO, Standardisation and Calibration Department. Based on the highest WWL average value of 81.3 with a very high category. To improve the mental workload, the company is advised to evaluate labour needs in other departments or divisions to support additional employees through job rotation, provide regular job training to improve employee skills and speed in completing work, provide a storage area for tools to be calibrated so that employees are not disturbed by tools that accumulate in the workspace, procure new tools to support the increasing workload, conduct monitoring and job evaluation.

APAKAH BEBAN KERJA MENTAL BERHUBUNGAN DENGAN TINGKAT KECEMASAN PADA KARYAWAN BANDARA?

Anxiety was the anticipation of future danger accompanied by feelings of dysphoria and somatic symptoms. Anxiety often occured in employees within the early adults (ages 26-35). Risk factors of anxiety in employees included genetics, social and family environmental factors, and mental workload. The impact of mental workload on employees could affect mental health, specifically the level of anxiety, that could implicate the job performance. The aim of this study was to assess the relationship between gender, age, and mental workload with the anxiety levels of airport employees. The design of the study was observational analytic cross-sectional approach. A sample size of 125 subjects were obtained through cluster random sampling. Primary data was collected using the HARS and NASA-TLX questionnaires. Data were analyzed with SPSS using the Kolmogorov-Smirnov and Kendall's Tau tests. There were 69 male employees and 53 individuals were in the early adulthood (26-35 years). For mental workload, 51 employees had a slightly high workload and 47 employees had severe anxiety.The bivariate analysis indicated that there was no relationship between gender and anxiety levels (p=0.709) as well as age and anxiety levels (p=0.142). However, there was a relationship between mental workload and anxiety levels (p=0.005). Mental workload is related with anxiety levels in airport workers.

Effects of Mental Workload Manipulation on Electroencephalography Spectrum Oscillation and Microstates in Multitasking Environments.

Multitasking during flights leads to a high mental workload, which is detrimental for maintaining task performance. Electroencephalography (EEG) power spectral analysis based on frequency-band oscillations and microstate analysis based on global brain network activation can be used to evaluate mental workload. This study explored the effects of a high mental workload during simulated flight multitasking on EEG frequency-band power and microstate parameters. Thirty-six participants performed multitasking with low and high mental workloads after 4 consecutive days of training. Two levels of mental workload were set by varying the number of subtasks. EEG signals were acquired during the task. Power spectral and microstate analyses were performed on the EEG. The indices of four frequency bands (delta, theta, alpha, and beta) and four microstate classes (A-D) were calculated, changes in the frequency-band power and microstate parameters under different mental workloads were compared, and the relationships between the two types of EEG indices were analyzed. The theta-, alpha-, and beta-band powers were higher under the high than under the low mental workload condition. Compared with the low mental workload condition, the high mental workload condition had a lower global explained variance and time parameters of microstate B but higher time parameters of microstate D. Less frequent transitions between microstates A and B and more frequent transitions between microstates C and D were observed during high mental workload conditions. The time parameters of microstate B were positively correlated with the delta-, theta-, and beta-band powers, whereas the duration of microstate C was negatively correlated with the beta-band power. EEG frequency-band power and microstate parameters can be used to detect a high mental workload. Power spectral analyses based on frequency-band oscillations and microstate analyses based on global brain network activation were not completely isolated during multitasking.

Mars Mission Communication Delays and Impact on Mission Controller Performance, Workload, and Stress.

Mission Controllers (MCs) are the main point of contact for space crews and are vital for successful human spaceflight. On a mission to Mars, there will be as long as 22-min one-way communication delays between the ground and the crew, causing major changes to current communication infrastructures. This exploratory study assessed the impact of a 20-min one-way communication delay on MCs' task performance, workload, and stress levels under nominal and off-nominal conditions, conducted during a 21-d analog mission. Decrements in performance were noted on both nominal and off-nominal task completion in time-delay conditions [100% of real-time (rt) tasks complete, 16.7% of time-delay (td) tasks incomplete; 12.50% of nominal tasks and 33.33% of off-nominal tasks were incomplete]; more errors on task record forms (td = 6 forms, rt = 1 form); higher ratings of workload burden (nominal, td workload = 38.64; off-nominal, td workload = 58.72; nominal, rt workload = 34.00, off-nominal, rt workload = 52.78). No significant changes in MC stress levels were detected in rt compared to td, but MCs did report greater stress during off-nominal tasks compared to nominal tasks. The crew, however, were unable to detect these changes in MC stress levels. Overall, these findings point to the importance of future research focused on MC training and adapting MC's operations for time-delayed missions. Further studies of time-delayed analog missions could help determine additional solutions focused on technology advances. Diamond M, Leon GR, de León P. Mars mission communication delays and impact on mission controller performance, workload, and stress. Aerosp Med Hum Perform. 2025; 96(1):67-70.

Adaptive power management for multiaccess edge computing‐based 6G‐inspired massive Internet of Things

AbstractMultiaccess edge computing (MEC) is a dynamic approach for addressing the capacity and ultra‐latency demands caused by the pervasive growth of real‐time applications in next‐generation (xG) wireless communication networks. Powerful computational resource‐enriched virtual machines (VMs) are used in MEC to provide outstanding solutions. However, a major challenge with using VMs in xG networks is the high overhead caused by the excessive energy demands of VMs. To address this challenge, containers, which are generally more energy‐efficient and less computationally demanding, are being advocated. This paper proposes a containerised edge computing model for power optimisation in 6G‐inspired massive Internet‐of‐Things applications. The problem is formulated as a central processing unit energy consumption cost function based on quasi‐finite system observations. To achieve practicable computational complexity, an approach that uses a search heuristic based on Lyapunov techniques is employed to obtain near‐optimal solutions. Important performance metrics are successfully predicted using the online look‐ahead technique. The predictive model used achieves an accuracy of 97% prediction compared to actual data. To further improve resource demand, an adaptive controller is used to schedule computational resources on a time slot basis in an adaptive manner while continuing to receive workload levels to plan future resource provisioning. The proposed technique is shown to perform better compared to a competitive baseline algorithm.

Reducing workplace accidents in a cement company by assessment of physical and mental workload: A case study

As one of the leading cement companies in Indonesia, PT Semen Padang is known for its extensive distribution network. As the largest cement factory, the employees at this company engage in work that requires a high level of physical and mental effort. Although the tasks performed by the employees may be similar, the experience of psychological workload can vary greatly among them. The TPM (Total Productive Maintenance) and AFR (Alternative Fuel and Raw Material) departments in the company have several routine activities carried out daily. The numerous job demands that require physical exertion within limited time constraints can lead to a high workload level for employees in TPM and AFR. This workload is not limited to physical aspects but also includes psychological impacts that can disrupt employees’s concentration and performance. In this study, questionnaires were given to 7 employees from TPM and 7 employees from AFR. Based on the research conducted on physical workload using the CVL method, AFR employees experienced more physical workload compared to TPM employees. In terms of mental workload, using the NASA-TLX method, both TPM and AFR employees had 2 employees each with very high mental workload.

Impact of Different Auditory Environments on Task Performance and EEG Activity

Impact of Different Auditory Environments on Task Performance and EEG Activity

The relationship between workload and work life balance in generation Z employees

In recent years, the world of work has seen the arrival of a new generation known as Generation Z. Generation Z has different desires from previous generations, especially in the aspect of work flexibility related to work life balance. In achieving work life balance, workload analysis is needed, because workload can indirectly lead to a decrease in work life balance. This study aims to determine the relationship of workload to work life balance in Generation Z employees at PT “X”. The research method used is quantitative method using Spearman Rank non-parametric test. The subjects of this study were 61 employees at PT “X” using saturated samples. This study uses a workload scale and a work life balance scale. The results showed a positive relationship between workload and work life balance with a correlation value of 0.352 (p < 0.05). This shows that when the level of workload is increased according to the ability of employees, the level of work life balance also tends to increase, and vice versa. This finding provides important implications for organizations to pay attention to workload so that generation Z employees can achieve their work-life balance. KEY WORDS: workload; work-life balance; employees; generation z

RE-LAYOUT SHOPFLOOR DEPARTMENT AT RETAIL COMPANY TO OPTIMIZE THE INITIAL LAYOUT, MATERIAL HANDLING REDUCTION, AND TRANSPORTATION WASTE MINIMIZATION USING BLOCPLAN ALGORITHM

Starcorss shopfloor employee (receiving and warehousing department) at headquarter stated on very high level of mental workload while high season compared while low season. Based on this consideration, the business owner asked the author personally to develop a new layout for shopfloor department as mitigation for mental workload based on previous research recommendation. Most likely 3 month the author has direct observed and proposed am optimized shopfloor layout with BLOCPLAN Algorithm approach. The proposal also considers about how to reduce waste activities on the shopfloor regarding material handling.

Eksplorasi Pengaruh Beban Kerja pada Kesetiaan Karyawan

ABSTRACT This study explores the influence of workload on employee loyalty at PT X, using a quantitative approach involving 108 employees as research subjects. The data collected were then analyzed using simple regression methods to examine the relationship between the variables of workload and employee loyalty. The results show a significant influence of workload on employee loyalty at PT X, with a correlation of 13.7% between workload and employee loyalty levels. This indicates that while workload has an impact on loyalty, there are 86.3% of other factors that also affect employee loyalty. This research is based on previous studies that highlight the importance of workload management in maintaining employee loyalty. Understanding that workload is only one of many factors influencing loyalty, PT X’s management is expected to take more comprehensive steps to improve employee loyalty, including considering other factors such as job satisfaction, recognition, and career development. The limitation of this study is its focus on the employees of PT X, with a sample size of 108 subjects. This research provides useful insights for companies in similar industries to manage workloads more effectively to increase employee loyalty. KEY WORDS: workload employee; loyalty; influence; workload impact

Effects of Full-Time Hospital Nurses' Work Schedules are Evaluated

Background: Nurses’ work schedules are known to impact their well-being and job performance. pandemic further intensified the workload and stress levels of hospital nurses, leading to potential changes in their work schedules and conditions. This study aimed to evaluate and compare the work schedules of full-time hospital nurses before and during the pandemic, focusing on shift patterns, working hours, and related factors. Methods: This study was conducted at a regional secondary care hospital. Work schedule data were collected from handwritten records and analyzed using IBM SPSS Statistics 26.0. The study included 24 nurses who met the inclusion criteria. Descriptive statistics, repeated measures t-tests, and independent t-tests were used to compare variables such as shift length, number of workdays, consecutive shifts, and sick leave. Statistical significance was set at p < 0.05. Results: Most nurses (75%) followed rotating shift patterns, though rotation direction was inconsistent. There was a significant increase in total annual working hours in 2024 compared to 2023. Nurses worked an average of three weekends per month, with fewer free weekends available in 2024. Sick leave usage nearly doubled in 2024, with 37.5% of nurses taking more than 10 sick days compared to 20.8% in 2023. Despite increased workload, quick returns between shifts were not observed. Conclusion: increase in nurses' working hours and sick leave usage, indicating heightened job demands and potential health impacts. The findings highlight the need for better scheduling strategies to support nurses’ well-being, including more consistent shift rotations, adequate rest periods, and policies to mitigate excessive workload during health crises.

The Relationship between Mental Workload and Job Satisfaction of Faculty Members with their Educational Performance

Introduction: Workload and job satisfaction are among the most influential factors affecting job performance. Therefore, this study aims to assess the cognitive workload and job satisfaction and their impact on the quality of education faculty members provide. Method: This study was conducted among 34 faculty members through a census. The NASA-TLX tool was used to assess cognitive workload, and a job satisfaction scale was employed to evaluate job satisfaction. Moreover, the training quality score was considered a criterion for assessing the educational performance of the participants. To determine the role of explanatory variables on the level of mental workload, multiple linear regression was used at a 95% confidence level. Result: The mean cognitive workload of faculty members was 52.94 ± 24.48. Efficiency and time demand scored the highest and lowest among the subscales of workload, respectively. Job satisfaction was 56.85 ± 27.61, with satisfaction with the department head and colleagues ranking highest and satisfaction with salary being the lowest in job satisfaction. The cognitive workload had a non-significant relationship with job satisfaction (P = 0.08, r = 0.56). However, the relationship between teaching quality and both cognitive workload and job satisfaction was not statistically significant. Conclusion: No significant relationship was observed between cognitive workload, job satisfaction, and teaching quality scores. However, it is recommended that measures be taken to improve the quality of work life for faculty members to enhance the quality of education they provide.

Performance metrics outperform physiological indicators in robotic teleoperation workload assessment

Robotics holds the potential to streamline the execution of repetitive and dangerous tasks, which are difficult or impossible for a human operator. However, in complex scenarios, such as nuclear waste management or disaster response, full automation often proves unfeasible due to the diverse and intricate nature of tasks, coupled with the unpredictable hazards, and is typically prevented by stringent regulatory frameworks. Consequently, the predominant approach to managing activities in such settings remains human teleoperation. Teleoperation can be demanding, especially in high-stress situations, and involves a complex blend of both cognitive and physical workload. We present an experiment to explore a range of physiological and performance-related metrics for workload assessment during robotic teleoperation. Thirty-five participants performed a teleoperation task, during which we manipulated cognitive and physical workload conditions. We recorded multiple metrics, including brain activity using functional Near-Infrared Spectroscopy, galvanic skin responses, cardiovascular responses, subjective workload ratings, task and robot performance data. Our results suggest that robotic teleoperation performance may be the most robust metric for distinguishing between different levels of workload experienced during teleoperation, with most physiological measures becoming insignificant to distinguish high cognitive workload.

The Determinants of Nutritional Status of Workers in Manufacturing Sector

Background:The manufacturing industry is a sector that transforms raw materials into finished goods. Nutritional status plays a critical role in determining a worker's productivity, with poor nutritional status often associated with reduced efficiency. Objective:This study aimed to analyze the relationship between various factors and the nutritional status of workers in the manufacturing sector in Surabaya, Indonesia. Methods:This analytical observational study utilized a cross-sectional design. Data collection was conducted from January to March 2023 among manufacturing workers at PT A in Surabaya, East Java Province, Indonesia. Of the total 500 workers, 370 respondents were selected as the study sample. Independent variables included gender, marital status, education level, smoking habits, number of children, exercise habits, contraceptive method usage, and workload level. The dependent variable was nutritional status. Statistical analysis was performed using the Spearman correlation test and the contingency coefficient correlation test to evaluate the relationships between variables. Results:The majority of workers at PT A were male, had a high school education, were married, had 1–2 children, did not use contraceptive methods, were non-smokers, exercised infrequently, and had a moderate physical workload. Significant associations were found between nutritional status and variables such as gender, marital status, contraceptive method usage, smoking habits, and workload level. However, no significant relationships were observed between nutritional status and educational background or the number of children. Conclusion:Among the factors examined, workload level demonstrated the strongest association with nutritional status, likely due to its direct impact on the physical activity required during job tasks. This finding highlights the importance of considering workload in strategies aimed at improving workers' nutritional health. Keywords:determinants; nutritional status; workforce; manufacturing industry

Examining the Effects of Different Exertion Levels and Reference Standards on the Diagnostic Accuracy of Exercise ECG for Detecting Coronary Artery Disease - A Pilot Study.

Exercise electrocardiogram (ECG) is frequently used for evaluating patients with suspected coronary artery disease (CAD). However, it has been downgraded in international guidelines due to a limited sensitivity and specificity, compared with other non-invasive tests. We hypothesized, that a sufficient exertion going beyond 85% of the age predicted maximal heart rate (APMHR), by considering the achieved level of workload can improve sensitivity and specificity of the exercise ECG. Secondly, the performance of exercise ECG, when evaluated against a functional reference standard has barely been investigated, although an improved diagnostic accuracy has been reported for other non-invasive tests in this case. Therefore, in this pilot study, a total of 147 patients without known CAD who underwent exercise ECG followed by coronary angiography within 90 days were retrospectively evaluated. The combined end point of 85% of APMHR and 75% of the predicted workload showed a slight but not statistically significant benefit over APMHR alone (66.7% vs. 58.1%; p = 0.545). The sensitivity of ST-segment depression was 51.3% for detecting anatomically defined CAD and 62.5% for functionally relevant CAD (p = 0.378). Although the results of this pilot study lack statistical significance, the numeric differences clearly justify further research on this topic.