Topic 8: Mental Workload (Written Report) PDF

 **REPUBLIC OF THE PHILIPPINES** **RIZAL TECHNOLOGICAL UNIVERSITY**\ Brgy. Malamig, Boni Avenue, Mandaluyong City **College of Engineering\ **Department of Industrial Engineering **WRITTEN REPORT** IE16: Ergonomics 2 Mental Workload Oral Presentation: [February 2025] Cam...

 **REPUBLIC OF THE PHILIPPINES** **RIZAL TECHNOLOGICAL UNIVERSITY**\ Brgy. Malamig, Boni Avenue, Mandaluyong City **College of Engineering\ **Department of Industrial Engineering **WRITTEN REPORT** IE16: Ergonomics 2 Mental Workload Oral Presentation: [February 2025] Camposano, Eunice B. Caparas, Jade Anne M. Estacio, Czeralline Zita P. Guias, Joan B. Manalo, Bhea G. Mengolio, Angelo Tabag, Jherico G. **Dr. Nestor Mirhan Japis, PIE**\ IE16: Ergonomics 2 **Second Semester** *Academic Year 2024 - 2025* **OUTLINE** **Title Page** **i** **Outline** **ii** **Objectives** **1** **Introduction** **2** I. II. A. B. C. D. E. III. A. B. IV. A. B. C. D. **Summary** **(#_heading=h.1t3h5sf)6** **Conclusion** **(#_heading=h.1t3h5sf)7** **Bibliography** **49** **OBJECTIVES** Enhancing worker well-being, boosting productivity and efficiency, improving workplace safety, and optimizing human-system interaction are the main goals of ergonomics\' assessment of mental workload. Ergonomists can detect and lessen elements like information overload, time constraints, and task complexity by comprehending the cognitive demands of tasks. This enables the creation of work systems that are not only effective but also lower the possibility of mistakes, increase worker comfort and general well-being, and improve technology usage. In the end, this strategy helps create a more secure and efficient workplace where people can complete their responsibilities efficiently and safely while reducing cognitive stress. The ultimate objective is to provide a workplace where people can carry out their duties safely and productively while reducing cognitive stress and optimizing their wellbeing. **INTRODUCTION** The idea of mental workload in ergonomics arose as a crucial topic of study in the mid-20th century, owing to the growing complexity of human--machine systems. Initially, the area was largely concerned with physical labor and the mechanical demands made on workers. However, as technology improved, particularly during World War II, the necessity to comprehend the cognitive demands placed on operators of sophisticated equipment such as radar systems and airplanes became clear. This signaled the start of a movement toward investigating mental workload as a critical component in human performance. In the postwar era, researchers began to formalize the study of mental workload, noting that excessive cognitive demands could impede decision-making, reaction speeds, and general efficiency. The development of aircraft, computing, and other technology-driven industries emphasized the significance of matching task demands with human cognitive capabilities. This period saw the emergence of early mental workload metrics, such as subjective rating scales and physiological tests, which established the framework for present evaluation methods. By the 1970s and 1980s, the field had grown greatly as ergonomists included psychological theories into their research. Concepts such as information processing and attentiveness became critical in understanding how humans interacted with complex systems. The field also benefited from interdisciplinary collaboration, which included discoveries from psychology, neuroscience, and engineering. This growth enabled the development of tools and environments that might optimize mental workload and prevent errors in high-stakes situations. Today, the study of mental workload remains an important aspect of ergonomics, with applications ranging from healthcare to space exploration. Modern research is constantly refining ways for monitoring and managing mental workload, ensuring that systems are intended to be compatible with human cognitive capacity. This historical development highlights the importance of ergonomics in improving safety, performance, and well-being in increasingly complicated work situations. I. Mental workload (MWL) is an intricate as well commonly used concept in ergonomics and human factors, although it is difficult to accurately describe (Young et al., p. 4). The word is sometimes defined as an analogy to physical workload, with mental workload consisting of two basic components: stress (job demands) and strain (the impact on the human operator) (Schlegel, 1993). Task demands can vary depending on time constraints and complexity, whereas strain can be altered by available resources such as team support or technology aids (Bevan & Macleod, 1994). MWL is commonly defined as the balance of attentional resources and task demands, with exceeding available resources resulting in performance degradation (Welford, 1978; Wickens, 1980, quoted in Young et al., p. 5). If demands exceed an individual\'s cognitive capability, competent operators may try to cope by changing their techniques; but, beyond a certain point, performance is likely to deteriorate. This perspective aids in predicting how mental workload may fluctuate in different scenarios and how it can be quantified using various performance metrics. Young and Stanton (2005) give a comprehensive definition of mental workload as \"the level of attentional resources required to meet both objective and subjective performance criteria, which may be mediated by task demands, external support, and past experience\". This definition emphasizes the limited nature of attentional resources, emphasizing how excessive demand can lead to performance degradation. At the same time, investing cognitive resources is an effortful and voluntary process, which means that performance can be maintained at the expense of increased strain on the individual (Hancock & Warm, 1989). I. A. A workload measuring technique must be linked directly to the cognitive demands imposed on an individual. This means that it should accurately record the mental processes involved in task execution without being impacted by unrelated physiological or environmental factors. A useful metric should provide information about cognitive strain, attentional demands, and decision-making complexity. **Example:** Heart rate variability (HRV) is one example of an indirect indication of workload; however, if stress or physical activity also influences HRV, its relevance to purely mental workload may be questioned. As a result, workload measures must be carefully chosen to ensure that they accurately reflect the mental effort necessary for a particular task. B. Sensitivity relates to a measurement technique\'s capacity to identify changes in mental workload under diverse task situations. A sensitive measure should respond clearly and consistently to different degrees of cognitive exertion. Sensitivity also implies that the measure has a high test power, which means it can successfully distinguish between little variations in workload without being impacted by external variables or ambient noise. Furthermore, a sensitive measure should be able to track workload changes in real time, making it useful in dynamic and complex operational environments. **Example:** When task difficulty rises, a sensitive workload measure should reflect it via physiological changes, performance indicators, or subjective ratings. C. Concordance assures that a workload measurement produces consistent patterns among different individuals in the target population. This means that when the same workload assessment method is used on several users performing comparable jobs, the findings should follow a consistent pattern, regardless of individual variations such as skill level, training, or experience. A workload measure that lacks concordance may produce inconsistent or contradictory data, making it difficult to determine vital workload thresholds. **Example:** If one group of participants assesses a task to be challenging while another group views it as easy under the same conditions, the measure may not be consistent. To achieve concordance, workload assessment approaches often demand substantial validation across several demographics and task contexts. D. Reliability is another important consideration; consistent outcomes over time are ensured by shown test-retest repeatability. Additionally, it should show differential stability, which means that even as people get more proficient at a task, workload patterns should stay consistent. To make meaningful comparisons between studies and populations, variance statistics and validated means are required. **Example:** Measurements of heart rate variability (HRV) can show dependability in a number of ways. First, they demonstrate \"differential stability\" if the trends in change over time are the same for each person. Differential stability is demonstrated, for instance, when people routinely demonstrate an increase in HRV with experience on a particular task. Second, it is essential to generate verified means and variance statistics for HRV measurements in varied populations and situations. E. Workload measures should be straightforward to understand and use without requiring complicated procedures or a lot of training. Portability measures should work well in a variety of settings, such as field tests and practical assessments. Another important consideration is cost-effectiveness, which makes it possible to acquire accurate readings without incurring undue expenses. **Example:** In terms of convenience, physiological measurements like heart rate have several benefits. Portable heart rate monitors are appropriate for real-world applications since they are widely accessible and simple to use in field situations. Additionally, a lot of wearable heart rate monitors are easily available and reasonably priced, which lowers the cost of data collecting. Last but not least, these tools are generally simple to use and require little training, which makes them adaptable to a variety of practical and research contexts. There are two types of measurements, objective and subjective. Workload measurements should be used for every test or evaluation, and it is frequently necessary to use more than one form of measure. A. Heart rate variability, or HRV, is one type of psychophysiological indicator. eye blink rate, galvanic skin response (GSR), and other developments in brain activity measurements. Changes in brain activity that may help diagnose brain disorders, particularly epilepsy or another seizure disorder, can be detected by an EEG. B. Online Reports of Mental Workload Levels (Verbal): These are real-time verbal assessments, whereby participants indicate the amount of mental work they experience while doing the tasks. This provides them with immediate feedback about their mental state. Post-Test Evaluations (Questionnaires, Rating Scales): Post-task mental workload is assessed using standardized questionnaires measuring different aspects, including mental demand and frustration, with a well-known example being the NASA Task Load Index (NASA-TLX). Other examples include the Subjective Workload Assessment Technique (SWAT). Explanations of High-strain Events: These are qualitative assessments of some situations or events that could lead to increasing mental strain as they often pinpoint aspects such as task difficulty and external stressors. **IV. Properties of Workload Assessment Techniques** Techniques for workload measurement are assessed in terms of properties that affect their utility for specific applications, with sensitivity and intrusiveness being particularly critical properties. The properties may be affected by factors such as the type and level of information processing demands placed on operators. **A. Sensitivity** Sensitivity is a complicated attribute that depends on many variables, such as the amount of capacity used to complete a task and the specific demands placed on each resource in the human processing system. To make workload measuring methods more useful, one must be aware of these factors. **Example**: High Sensitivity Scenario: A storm causes the flight plans of several aircraft to be disrupted, and the controller needs to reroute them. Within seconds, they have to constantly monitor radar screens, call pilots to inform them of new instructions, and maintain safe separations between aircraft. Their sensitivity is stretched to its limits by heavy cognitive load and temporal constraints. **Sensitivity as a Function of Level of Capacity Expenditure** **Non-overload Region**: In this region, the operator constraints are not exceeded by capacity spending, and hence the performance is steady with minimal errors and reaction times. Performance is not immediately affected by increased effort. **Region of Overload**: When demand increases, the capacity expenditure in this zone exceeds its bounds, and errors and reaction times increase. Variations in capacity expenditure affect performance. **B. Intrusiveness** This refers to the unintended interference by a workload measurement technique on the primary task performance. The concern here is that intrusiveness could distort estimates on capacity expenditure. It would be hard, for instance, to discern the actual mental or physical demands of a task independent of interference. Whereas a certain degree of intrusion may be acceptable in a controlled laboratory setting, it becomes an important issue in operational environments where performance and safety should not be compromised. If a measurement technique interferes with the primary task, the data collected may not reflect real conditions, and therefore the wrong conclusions may be drawn about workload and capacity allocation. The degree of intrusiveness is determined by many factors, ranging from the kind of primary task involved to the type of measurement technique adopted. Research reveals that intrusiveness is not an inherent property; instead, it varies with how much the measurement task overlaps the cognitive or physical resources required to carry out the primary task. As an example, secondary tasks that overlap with estimates of time, such as estimating the time between events, can significantly interfere with central processing tasks such as navigation in a flight simulator but have relatively little impact on motor tasks or auditory monitoring tasks. This suggests that performance degradation is more likely when a measurement technique draws upon the same cognitive resources as the primary task. Intrusiveness also can be attributed to general distractions unrelated to resource overlap, further making it difficult to assess workload. There are different techniques of measuring workload and varying intrusiveness levels. The most intrusive is secondary task methods because they require much cognitive effort, often coinciding with the execution of the primary task. In addition, they can bring about peripheral interference from physical constraints, such as being unable to use the same hand for carrying out more than one task at once. On the other hand, subjective techniques, which rate workload after task completion, and physiological techniques, which measure bodily responses with minimal processing demands, are less intrusive. In general, research findings support these expectations, and it is crucial to select the appropriate workload measurement methods based on the operational context to minimize interference and obtain accurate assessments. **Intrusion With Secondary Task Techniques** Secondary task techniques introduce significant intrusion into laboratory settings, especially in the commonly used subsidiary task paradigm in which participants have to maintain their primary task performance at baseline levels. This has led to several strategies to mitigate the effects of such intrusion. One method is to reduce peripheral interference by designing secondary tasks that require fewer perceptual inputs or response outputs. The IPT, or Internal Process Task, is one such approach, in that it consists of continuous motor responses independent of external stimuli, thereby reducing the chances of interference. Research has indicated that this method successfully measures the motor output load of a primary task while limiting the amount of disruptions caused by the requirements of a secondary task. The other approach is the procedure for embedded tasks, which consists of secondary tasks that naturally occur in operational settings, such as radio communications for aviation. This aims at maintaining primary tasks while the performance of secondary tasks is relevant and minimally disrupting. Research by Shingledecker and colleagues tested this approach in a flight simulator in which pilots carried out radio communication tasks with a primary tracking task of varying difficulty. Fluctuations in secondary task performance were found to be correlated with tracking difficulty levels, and the feasibility of using embedded tasks for workload assessment was supported; however, more operational-based pilots and high-fidelity simulators must be used to develop the approach further and make real-world assessments of its applicability. **Intrusion With Subjective and Physiological Techniques** The reported incidence of intrusion when using subjective and physiological workload assessment techniques has been minimal, according to research (O\'Donnell & Eggemeier, 1986). Studies on subjective workload techniques (Casali & Wierwille, 1983, 1984; Eggemeier & Amell, 1987; Wierwille & Conner, 1983; Wierwille et al., 1985) indicate that when subjective ratings are collected after task completion, they do not significantly interfere with primary task performance. A classic study by Eggemeier and Amell (1987) applied the SWAT to monitoring tracking and display monitoring tasks. They found that instructing participants to rate SWAT did not influence tracking error or loss of control in an unstable tracking task. In their first study, Eggemeier and Amell (1987) investigated tracking performance at three task difficulty levels varying in lambda 1, 2, and 3. Although SWAT ratings themselves did not exert a significant impact on RMS tracking error, nor on control loss, differences in these measures based on SWAT rating level were nonexistent. Similarly, a second experiment using a display monitoring task instead of tracking confirmed that workload rating had no measurable influence on signal detection time, number of missed signals, or false alarms. However, the SWAT rating did differ between all three levels of task demand thus confirming subjective ratings could be added to the Task Load Index without interfering with performance. The overall pattern of results lends credence to the notion that subjective workload measures collected following the execution of the tasks do not provide major intrusion. But the study applies only to perceptually and motor-task-based activity. It cannot, therefore, be extended to more complex memory-demanding tasks unless similar research is undertaken for such scenarios also. Additionally, physiological measures for workload also share the low-intrusion characteristic. Since they do not demand active cognitive processing, they generally avoid interference, although there exists a slight possibility of distraction or discomfort from monitoring equipment. Up to now, studies indicate that these effects are negligible in most applications (Wierwille & Casali, 1983b). **C. Implications of Properties** The properties of sensitivity and intrusiveness of the workload measurement techniques are complex and depend on a large number of factors. A metric cannot, for example, altogether solve the spread of requirements from different applications. Therefore, desired measurements of sensitivity and intrusion patterns along with instrumentation demands guide the choice of metric. Primary task measures give the performance adequacy, but subtle capacity differences cannot be detected. Subjective techniques with minimal intrusion and instrumentation requirements are preferred in measuring workload without compromising performance. Nevertheless, subjective measures are only to a limited extent useful in indicating specific areas of overload and have to rely on secondary tasks or physiological metrics for diagnostic purposes. For instance, perceptual overloads might be addressed by modifications to display information while high motor demands might be seen as indicative of control adjustments. These are typically administered in a simulated or laboratory setting to minimize intrusion from secondary tasks. A robust workload assessment should involve several measurement methods to provide an integrated view of the assessment. The primary task measures, coupled with subjective, secondary task, or physiological measures, are all essential in gathering data about the expenditure of capacity. Primary task performance levels alone are insufficient for establishing workload equivalence between designs. A global evaluation by sensitive techniques can pinpoint potential high workload areas, followed by diagnostic methods to find sources of overload. Methodological considerations also support the concurrent use of multiple techniques. The case of assessing secondary task intrusion requires measuring primary task performance under both single-task and dual-task conditions. The combined use of these techniques can provide a more accurate and detailed workload assessment in various design and operational scenarios. Further research is necessary to refine the selection guidelines for workload measurement techniques, as comparative data on sensitivity and intrusion are still limited. Studies show that subjective techniques produce consistent results most of the time, whereas secondary tasks and physiological metrics have varying levels of sensitivity. These variations point out the need for systematic research into the effectiveness of individual techniques. A standardized methodology for workload evaluation, including a primary loading task battery, is important to compare these properties across different techniques. This will improve the reliability of the assessments and ensure that selected techniques meet the demands of sensitivity and intrusion for a variety of applications. **D. Workload Metric Evaluation Methodology** To refine present guidelines for the selection and use of workload assessment techniques, systematic research must be carried out to establish the relative sensitivity and intrusiveness associated with individual techniques. Without such information, neither a standard set of assessment techniques nor the guidelines required can be developed. Standard testing procedures and standardized set of main loading tasks as standard would have formed the elementary building blocks within any methodology geared towards allowing proper properties\' comparisons from among techniques under investigation. The inability to draw detailed comparative data from the existing literature stems largely from the fact that when individual metrics have been applied to evaluate work- load in more than one setting, there have typically been variations in the testing procedures, primary tasks, or levels of loading across studies. Therefore, apparent differences in the sensitivity and intrusiveness between techniques cannot be properly interpreted. Since it is likely that both sensitivity and intrusion will vary as a function of the locus and level of primary task demand, development of an adequate comparative data base requires that these properties be evaluated across a range of information processing functions and loading levels. A standard set of primary loading tasks with known demand levels on each of several processing functions therefore is an essential element of a methodology for evaluating workload metrics. With such a battery, loading levels can be manipulated within individual tasks designed to emphasize certain processing functions, and the ability of workload metrics to represent these manipulations can be determined. The pattern of sensitivity to the processing functions represented in the battery would provide evidence of the global versus diagnostic nature of a metric, and would specify areas of maximum sensitivity for diagnostic measures. The potential for intrusion as a function of type and level of processing demand could also be evaluated in such an approach. The Criterion Task Set (CTS) (Shingledecker, 1984; Shingledecker et al., 1983; Shingledecker, Crabtree, & Acton, 1982) is a battery of primary tasks developed to provide the required capa- bilities for comparative evaluation of workload assessment techniques. The original or baseline version of the battery has been instrumented on a microcomputer system (Acton & Crabtree, 1985), and a number of initial applications have been completed. The following sections provide more detail about the battery and its development and discuss its application to metric evaluation and other performance assessment areas. **The Criterion Task Set** The Criterion Task Set (CTS) was devised to measure the different human information processing functions needed for complex task performance. Initially devised by Shingledecker in 1984, the CTS comprises nine core tasks, each one representing a separate cognitive processing function. These were chosen on the basis of a theoretical framework that made use of multiple resource theories of information processing as described by Navon and Gopher (1979) and Wickens (1980, 1984). These tasks have been modified over time, as is evident in research by Amell, Eggemeier, and Acton (1987).  The CTS processing framework, shown in Figure 6, organizes human information processing into three major dimensions: processing stages, modalities/codes, and central processing functions. The processing stages include perceptual input, central processing, and response output, where perceptual input is further categorized into visual and auditory modalities, and responses can be manual or vocal. Central processing is further divided into working memory and central activity, which includes information manipulation (for example, mathematical processing), reasoning, and planning/scheduling. This framework allows researchers to analyze how different cognitive tasks interact with these dimensions of processing, providing insights into cognitive resource allocation and processing efficiency. Table 1. Specific CTS tasks and corresponding processing functions. The processing functions include working memory, perceptual input, symbolic information manipulation, spatial processing, reasoning, manual response accuracy, and timing. Each of the tasks has been designed to isolate and measure a particular cognitive function to ensure a full evaluation of information-processing capabilities. For instance, monitoring of visual perceptual input is taken care of by Visual Display Monitoring, while working memory functions and encoding, storage, and retrieval are the actual focus areas of Continuous Recognition & Memory Search. Likewise, symbolic information manipulation is assessed by Linguistic Processing and Mathematical Processing, while spatial information manipulation is checked by Spatial Processing. Other measures include Grammatical Reasoning, Unstable Tracking, and Interval Production, designed to measure logical reasoning, manual response accuracy, and manual response timing, respectively. These tasks provide a structured means of assessing cognitive workload and performance across different operational conditions.  Validation of the CTS framework has been approached through studies examining how performance changes with increasing cognitive demands. In one of the earliest studies, Eggemeier & Amell (1986) monitored probability display monitoring with varying displays (one, two, or three) in order to investigate the impact on reaction time and accuracy. Figure 7 displays the results, where increased number of displays resulted in a greater increase in reaction time and an increased percentage of missed signals. Such results verified that even simple manipulations in tasks can generate measurable differences in cognitive workload. Based on similar validation studies, standard difficulty levels have been established for most CTS tasks that allow for controlled assessment of cognitive performance under varying conditions (Acton et al., 1983; Amell et al., 1987; Shingledecker, 1984). This refined approach ensures that the CTS framework systematically evaluates task complexity, information-processing efficiency, and mental workload across various contexts. By isolating specific cognitive demands, the CTS provides a valuable tool for researchers studying cognitive workload, task performance, and human information processing in complex environments. **Applications of the CTS Battery** The Criterion Task Set has been widely used in research to assess workload measurement techniques and their sensitivity to different task demands. Several studies, such as those by Eggemeier & Amell (1987), Potter & Acton (1985), and Shingledecker et al. (1983), have used elements of the CTS to assess how well workload measurement methods capture cognitive demands. For instance, Shingledecker et al. (1983) employed modifications of the CTS task to determine IPT sensitivity and Eggemeier & Amell (1987) unstable tracking and display monitoring tasks for examining the SWAT technique\'s sensitivity to both motor output and perceptual input functions. Other researches, for example, Wilson & Heinrich (1987), used CTS display monitoring and mathematical processing tasks to compare the effectiveness of SWAT with physiological workload measures such as heart rate and cortical responses. These studies show that CTS can be useful in a systematic analysis of sensitivity and intrusion patterns of different workload assessment techniques and, thus, aid in the building of a comparative database for different methods of evaluation. In addition to workload metric research, the CTS has been applied to study stressors such as environmental conditions, drugs, and fatigue on human performance. Since some effects will only be apparent when there is higher cognitive demand, testing across levels of task loading is necessary to effectively evaluate impacts of stress. The diverse range of processing functions comprising motor output, working memory, and perceptual processing by CTS makes its ability to detect specific stress-related impairments stronger. For instance, some stressors could be affecting working memory while leaving the motor response intact, and some others could reduce manual tracking performance. Researchers can increase the sensitivity and reliability of stress evaluations by selecting multiple CTS tasks that represent different cognitive functions. Additionally, the task-specific training procedures with CTS help ensure that changes in observed performance are due to a stressor rather than from task familiarity or learning effects. Application of CTS to Stress Research: A classic example of a CTS application for stress research was Schlegel, Gilliland, and Schlegel\'s 1986 study on the impact of sleep loss and noise on performance. While noise levels did not produce significant performance changes, sleep deprivation led to slower response times in central processing tasks and impaired interval production and tracking performance. This study demonstrates how the CTS can compare different stressors\' effects across multiple cognitive domains, helping researchers identify specific patterns of stress sensitivity. Such assessments are thus ensured to be systematic and replicable due to the structured task battery. Hence, CTS is a very useful tool in understanding cognitive workload, stress effects, and human information processing in complex environments. **SUMMARY** Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum. Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum. **CONCLUSION** In conclusion, the increasing intricacy of human-machine systems, as well as the need for the optimization of human performance, have led to a significant shift in the subject of mental load in ergonomics since the middle of the 20th century. Over time, in particular during and after World War II, where technology improved by leaps and bounds, the discipline\'s initial physical labor focus slowly shifted to emphasis on cognitive demand. As time passed, researchers developed methods to measure and manage mental workload, integrating engineering, psychology, and neuroscience to develop systems that are compatible with human cognitive abilities. Ergonomics is becoming important in improving worker safety, productivity, and well-being through the elimination of mental strain and improved human-system interaction. Ergonomists help plan work environments that are not only effective but also healthy in terms of mental health and general well-being by considering factors such as information overload, time limitations, and task complexity. Improving the measurement and management of mental workload is critical to continued safe, efficient, and human-centered workplaces well into the age of advanced technologies. **REFERENCES** 1.