Mental Workload Analysis Using NASA-TLX Method at Bank XYZ - Medan Balaikota Consumer Loan Unit

All human activities, whether light, medium, or heavy, must have or contain a workload. Basically, every human being has a varied workload capacity, thus it's not inconceivable that the workload experienced by one worker differs from that of another, because there are a variety of elements that influence the difference in workload capacity. Sales and processing teams are under a lot of pressure to meet credit disbursement targets, which puts them under a lot of mental strain. A worker will experience work stress if he is given an excessive workload. When it comes to work, the influence of stress will result in a decline in performance, efficiency, and productivity of the work in question. To address this issue, a study based on the National Aeronautics and Space Administration Task Load Index (NASA-TLX) approach will be conducted to measure the mental strain of personnel in the Medan Balaikota consumer loan unit. NASA-TLX is a way for analyzing the mental workload of workers who must do a variety of tasks at work. Mental demand, physical demand, temporal demand, performance, effort, and frustration dimensions are among the six variables to be measured. Thirty workers of PT Bank XYZ Consumer Loan Unit Medan Balaikota Branch were surveyed. The NASA-TLX survey method is a quantitative descriptive methodology that was utilized to test in this study. According to the findings of the study, the NASA-TLX average score of PT Bank XYZ Consumer Loan Unit Medan Balaikota Branch employees obtained through research had a modest value. The result is a score of 77. Keywords: Mental Workload, NASA-TLX.

A new measure of group decision-making efficiency

It has widely been accepted that aggregating group-level decisions is superior to individual decisions. As compared to individuals, groups tend to show a decision advantage in their response accuracy. However, there has been a lack of research exploring whether group decisions are more efficient than individual decisions with a faster information-processing speed. To investigate the relationship between accuracy and response time (RT) in group decision-making, we applied systems’ factorial technology, developed by Townsend and Nozawa (Journal of Mathematical Psychology 39, 321–359, 1995) and regarded as a theory-driven methodology, to study the information-processing properties. More specifically, we measured the workload capacity CAND(t), which only considers the correct responses, and the assessment function of capacity AAND(t), which considers the speed-accuracy trade-off, to make a strong inference about the system-level processing efficiency. A two-interval, forced-choice oddball detection task, where participants had to detect which interval contains an odd target, was conducted in Experiment 1. Then, in Experiment 2, a yes/no Gabor detection task was adopted, where participants had to detect the presence of a Gabor patch. Our results replicated previous findings using the accuracy-based measure: Group detection sensitivity was better than the detection sensitivity of the best individual, especially when the two individuals had similar detection sensitivities. On the other hand, both workload capacity measures, CAND(t) and AAND(t), showed evidence of supercapacity processing, thus suggesting a collective benefit. The ordered relationship between accuracy-based and RT-based collective benefit was limited to the AAND(t) of the correct and fast responses, which may help uncover the processing mechanism behind collective benefits. Our results suggested that AAND(t), which combines both accuracy and RT into inferences, can be regarded as a novel and diagnostic tool for studying the group decision-making process.

Crafting Care That Fits: Workload and Capacity Assessments Complementing Decision Aids in Implementing Shared Decision Making

About 42% of adults have one or more chronic conditions and 23% have multiple chronic conditions. The coordination and integration of services for the management of patients living with multimorbidity is important for care to be efficient, safe, and less burdensome. Minimally disruptive medicine may optimize this coordination and integration. It is a patient-centered approach to care that focuses on achieving patient goals for life and health by seeking care strategies that fit a patient’s context and are minimally disruptive and maximally supportive. The cumulative complexity model practically orients minimally disruptive medicine–based care. In this model, the patient workload-capacity imbalance is the central mechanism driving patient complexity. These elements should be accounted for when making decisions for patients with chronic conditions. Therefore, in addition to decision aids, which may guide shared decision making, we propose to discuss and clarify a potential workload-capacity imbalance.

Model analysis and optimization of operating rates of enterprises with small-series production type

The article deals with issues surrounding the production management of enterprise with small-series production type. Specific features of small-series production are determined. Task complex defined by initial production phase comes under review. Problem of calculation, analysis and optimization of machine load is covered in depth. It is assumed that machine load calculating task will minimize potencial stress of production plan and maximize workplace capacity. Calculations are carried out for each type of work for the required period (year, month, week, etc.) for the whole enterprise, workshops, production areas, workplaces. The labor intensity for each workplace and usage coefficient are calculated. The analysis of obtained indexes is the basis for redistribution of the workload capacity.