Acceptable Workload Research Articles

Real-Time Workload Assessment to Enhance Performance.

Workforce shortages, increasing costs, decreased reimbursement, and focus on quality outcomes are crucial issues for health care leaders. To remain competitive, profitable, and productive, health care organizations need to provide structure, a safe working environment, and an acceptable leader workload to guarantee effective leader performance. Poorly designed work environments and interfaces can increase workload resulting in decreased performance and satisfaction. Excessive workload has led to reduced job satisfaction, productivity, and resilience. Due to leadership turnover and vacancy rates, leader workload was perceived to be unreasonable in the respiratory therapy (RT) department of an academic medical institution in central North Carolina. The aim of this quality initiative was to explore the workload of health care leaders in the RT department to identify the factors that influenced workload as well as implement strategies to decrease perceived workload. A workload assessment was performed, which identified inefficiencies and opportunities to partner with ancillary departments to align the workload with appropriate clinical teams. The redistribution of workload provided alignment, top of scope practice, and improved satisfaction among the RT department leaders. This article identifies the strategies utilized which can be translated to other institutions.

Convolutional neural networks to classify human stress that occurs during in‐field sugarcane harvesting: A case study

AbstractAssessing human stress in agriculture proves to be a complex and time‐intensive endeavor within the field of ergonomics, particularly for the development of agricultural systems. This methodology involves the utilization of instrumentation and the establishment of a dedicated laboratory setup. The complexity arises from the need to capture and analyze various physiological and psychological indicators, such as heart rate (HR), muscle activity, and subjective feedback to comprehensively assess the impact of farm operations on subjects. The instrumentation typically includes wearable devices, sensors, and monitoring equipment to gather real‐time data of subject during the performance of farm operations. Deep learning (DL) models currently achieve human performance levels on real‐world face recognition tasks. In this study, we went beyond face recognition and experimented with the recognition of human stress based on facial features during the drudgery‐prone agricultural operation of sugarcane harvesting. This is the first research study for deploying artificial intelligence‐driven DL techniques to identify human stress in agriculture instead of monitoring several ergonomic characteristics. A total of 20 (10 each for male and female) subjects comprising 4300 augmented RGB images (215 per subject) were acquired during sugarcane harvesting seasons and then these images were deployed for training (80%) and validation (20%). Human stress and nonstress states were determined based on four ergonomic physiological parameters: heart rate (ΔHR), oxygen consumption rate (OCR), energy expenditure rate (EER), and acceptable workload (AWL). Stress was defined when ΔHR, OCR, EER, and AWL reached or exceeded certain standard threshold values. Four convolutional neural network‐based DL models (1) DarkNet53, (2) InceptionV3, (3) MobileNetV2 and (4) ResNet50 were selected due to their remarkable feature extraction abilities, simple and effective implementation to edge computation devices. In all four DL models, training performance results delivered training accuracy ranging from 73.8% to 99.1% at combinations of two mini‐batch sizes and four levels of epochs. The maximum training accuracies were 99.1%, 99.0%, 97.7%, and 95.4% at the combination of mini‐batch size 16 and 25 epochs for DarkNet53, InceptionV3, ResNet50, and MobileNetV2, respectively. Due to the best performance, DarkNet53 was tested further on an independent data set of 100 images and found 89.8%–93.3% confident to classify stressed images for female subjects while 92.2%–94.5% for male subjects, though it was trained on the integrated data set. The comparative classification of the developed model and ergonomic measurements for stress classification was carried out with a net accuracy of 88% where there were few instances of wrong classifications.

Willingness of healthcare providers to perform population-based cancer screening: a cross-sectional study in primary healthcare institutions in Tianjin, China

ObjectiveTo evaluate the willingness of healthcare providers to perform population-based screening in primary healthcare institutions in China.MethodsHealthcare providers of 262 primary healthcare institutions in Tianjin were invited to fill out...

Sonographer wellbeing in Australia: Perceptions of job demands and resources in clinical working environments

AbstractIntroductionThe concept that job characteristics can have a profound impact on employee wellbeing has been well documented. This manuscript aims to highlight the job demands and resources experienced by Australian sonographers, and those resources perceived to be the most effective at improving workplace wellbeing.MethodsUtilising the Job Demands‐Resources Model, a national survey was issued to Australian sonographers in both public and private clinical working environments. The quantitative and qualitative data collected were analysed using non‐parametric tests of association as well as inductive coding of themes.ResultsSixty‐nine participants responded to the survey with 27 participants (39%) reporting moderate levels of job satisfaction. Workplace demands of unrealistic workloads, time pressures, and inadequate scheduled breaks were reported as the most frequently experienced demand by 67 participants (97%). Twenty‐four participants (35%) reported no access to any form of resource or strategy for improving wellbeing in the workplace and a further nine indicated they utilised entirely self‐driven resources. Workload reduction strategies were perceived to be the most consistently effective yet were the least accessible strategy for sonographers. Other strategies including psychology sessions, physical therapies, and injury prevention were perceived to be more accessible, yet minimally effective.ConclusionNew legislation in the management of psychosocial hazards at work is likely to generate positive changes. Further research establishing an acceptable workload for sonographers, introducing job crafting, and improving sonographer recognition would prove to be the most fruitful.

Air traffic controller workload level prediction using conformalized dynamical graph learning

Air traffic control (ATC) is a safety-critical service system that demands constant attention from ground air traffic controllers (ATCos) to maintain daily aviation operations. The workload of the ATCos can have negative effects on operational safety and airspace usage. To avoid overloading and ensure an acceptable workload level for the ATCos, it is important to predict the ATCos’ workload accurately for mitigation actions. In this paper, we first perform a review of research on ATCo workload, mostly from the air traffic perspective. Then, we briefly introduce the setup of the human-in-the-loop (HITL) simulations with retired ATCos, where the air traffic data and workload labels are obtained. The simulations are conducted under three Phoenix approach scenarios while the human ATCos are requested to self-evaluate their workload ratings (i.e., low-1 to high-7). Preliminary data analysis is conducted. Next, we propose a graph-based deep-learning framework with conformal prediction to identify the ATCo workload levels. The number of aircraft under the controller’s control varies both spatially and temporally, resulting in dynamically evolving graphs. The experiment results suggest that (a) besides the traffic density feature, the traffic conflict feature contributes to the workload prediction capabilities (i.e., minimum horizontal/vertical separation distance); (b) directly learning from the spatiotemporal graph layout of airspace with graph neural network can achieve higher prediction accuracy, compare to hand-crafted traffic complexity features; (c) conformal prediction is a valuable tool to further boost model prediction accuracy, resulting a range of predicted workload labels. The code used is available at Link.

Double faecal immunochemical testing in patients with symptoms suspicious of colorectal cancer.

Faecal immunochemical test (FIT)-directed pathways based on a single test have been implemented for symptomatic patients. However, with a single test, the sensitivity is 87 per cent at 10 µg haemoglobin (Hb) per g faeces. This aims of this study were to define the diagnostic performance of a single FIT, compared with double FIT in symptomatic populations. Two sequential prospective patient cohorts referred with symptoms from primary care were studied. Patients in cohort 1 were sent a single FIT, and those in cohort 2 received two tests in succession before investigation. All patients were investigated, regardless of having a positive or negative test (threshold 10 µg Hb per g). In cohort 1, 2260 patients completed one FIT and investigation. The sensitivity of single FIT was 84.1 (95 per cent c.i. 73.3 to 91.8) per cent for colorectal cancer and 67.4 (61.0 to 73.4) per cent for significant bowel pathology. In cohort 2, 3426 patients completed at least one FIT, and 2637 completed both FITs and investigation. The sensitivity of double FIT was 96.6 (90.4 to 99.3) per cent for colorectal cancer and 83.0 (77.4 to 87.8) per cent for significant bowel pathology. The second FIT resulted in a 50.0 per cent reduction in cancers missed by the first FIT, and 30.0 per cent for significant bowel pathology. Correlation between faecal Hb level was only modest (rs = 0.58), and 16.8 per cent of double tests were discordant, 11.4 per cent in patients with colorectal cancer and 18.3 per cent in those with significant bowel pathology. FIT in patients with high-risk symptoms twice in succession reduces missed significant colorectal pathology and has an acceptable workload impact.

Impact of collaboration behavior among staff nurses on their quality of work life and job satisfaction

Background Nursing collaboration is a key component of promoting a good work environment in a health-care organization, as it helps to support acceptable workloads and levels of complexity, which leads to improved nurses’ quality of life and job satisfaction. Aim To assess the impact of collaboration behavior among staff nurses on their quality of work life and job satisfaction. Design A descriptive correlational study design was utilized. Setting The study was conducted in the medical critical care units at New Kasr El Aini Teaching Hospital. Subject A convenience sample of staff nurses (n=90) who are working in the previous mentioned setting. Tools Three questionnaires were used for this study: nurse collaboration behavior scale (20 items), quality of work life (38 items), and job satisfaction questionnaire (28 items). Results Results of the present study regarding collaboration behavior items revealed that around two-thirds (64.4%) of the participants agreed on listening to each other’s opinions and suggestions item, while 34.4% of them disagreed about no qualms in sharing their ideas with one another item. Also, participants were highly perceived for all-quality work life dimensions (mean%=72.1%) and most of the study participants had a moderate level of job satisfaction (78.9%). However, this study showed that there was a statistically significant positive correlation between nurse collaboration behavior and quality of work life, but no correlation was found between nurse collaboration behavior and job satisfaction (P=0.000). Conclusion The current study concluded that the majority of participants agreed about most of collaboration behavior items, participants were highly perceived for all-quality work life dimensions, and most of them had a moderate level of job satisfaction. However, there was statistically significant positive correlation between collaboration behavior and quality of work life, but no statistically significant correlation between collaboration behavior and job satisfaction as well as there was a positive statistically significant correlation between quality of work life and job satisfaction. Recommendations Nurse managers should display collaboration behaviors to construct an engaging climate, collaborative relationship with nurses and health team to preserve quality of patients’ care, and hospital administration must regularly monitor nurse job satisfaction and resolve points of dissatisfaction to encourage staff affiliation with the organization and to improve quality of work life.

Secure IoMT Pattern Recognition and Exploitation for Multimedia Information Processing using Private Blockchain and Fuzzy Logic

The Internet of Medical Things (IoMT) is a definite IoT connecting atmosphere that contracts with communication via intelligent medical equipment. Activity detection, motion tracking, information extraction, consumer retrieval, etc., have all been solved due to advances in the autonomous study of human behavior from multimedia information processing. Though the IoT connecting atmosphere enables and provisions our daily actions, it too has certain disadvantages. IoTgrieves from numerous safety and confidentiality challenges, such as reiteration, impersonation, man-in-the-middle, remote hijacking, privileged-insider attack, denial of service (DoS) attacks, password guessing, and malware bouts. Hence, in this paper, Private Blockchain and Fuzzy Logic based Attack Detection system (PBFL-ADS) has been proposed for secure IoMT disease prediction using Multimedia Information Processing techniques. The proposed method utilizes Bayesian inference-based trust administration to perceived malevolent nodes in Health Smartphone Structures (HSS) for PBFL-ADS. This paper focuses on the specific form of IoMT called HSS because smartphones have been widely used in the healthcare profession. Then, blockchains have been utilized to improve Bayesian trust management's efficacy in detecting hostile nodes in HSSs. The effectiveness of the suggested technique has been assessed, and test results show that blockchain technology helps identify fraudulent nodes with an acceptable workload. The proposed PBFL-ADS method increases the HS2 scenario 1.1, processor utilization at nodes 33.5%, pattern recognition ratio 92.1%.and server utilization 40.1%.

Recognition of Philadelphia chromosome‐like acute lymphoblastic leukemia as part of routine diagnostic work‐up

Philadelphia chromosome (Ph)-like acute lymphoblastic leukemia (ALL) is a biologically and clinically challenging subtype of B-cell ALL which has been incorporated into the 2016 revision of the World Health classification of acute leukemia. It is independently associated with poor outcome. As it can only be reliably detected by expression profiling, it is difficult to diagnose with routine methods. Its recognition has become of greater importance due to prognostication and even more due to the new diagnostic options given by targeted therapies. There is still no standardized diagnostic test enabling its prompt recognition. Here, we introduce our approach how to detect it by combination of widely available techniques. 179 ALL patients diagnosed in our center during the last 8years were included. Data on immunophenotype and cytogenetics were used to select patients with potentially Ph-like ALL (65/179). CRLF2 gene rearrangement (CRLF2-r) was tested by FISH in 59/65 patients, and next-generation sequencing was done by Archer FusionPlex ALL kit in 34 patients. TSLPR expression was determined in 20 patients. Philadelphia chromosome-like aberrations were confirmed in 9 patients. In 10% of tested samples, CRLF2-r was confirmed. Due to a lack of material, NGS was done only in a half of potentially Ph-like cases. In 10%, other Ph-like fusions were found by NGS. The obtained frequencies, and genetic and patients' characteristics are in concordance with the literature data, ensuring a reliable detection of this challenging ALL subtype. The proposed algorithm allows detection of Ph-like ALL at reasonable cost and acceptable workload.

Numerical workflow for scale-resolving computations of space launcher afterbody flows with and without jets

Scale resolving numerical methods are necessary to accurately predict the afterbody flows of space launchers. Numerical workflows built for such computations have to be designed in order to obtain a minimal numerical dissipation to resolve fine turbulent structures, a sufficient robustness to capture eventual shock waves and both a reasonable computational cost and an acceptable user workload enabling comparative design studies. This article presents the development of a hybrid numerical framework based on Ducros’s sensor and designed to switch from a low-dissipation formulation in presence of vortical structures to a robust formulation around high gradients. This hybrid workflow is used with ZDES, including its latest automatic mode (ZDES mode 2 (2020)), to simulate a transonic space launcher afterbody experiment with and without a cold air propulsive jet [1,2]. The salient physical properties of the base flow are investigated and the evaluation of computed results follows the extended nomenclature for validation of simulation techniques [3] from level 0 to 5. The framework is thus validated for instantaneous and mean flow visualizations, base and extension mean pressure coefficient distribution, pressure fluctuation levels, one-point and two-point spectral analyses. Such an efficient automatic RANS/LES strategy could be well suited to study realistic launcher afterbody geometries with propulsive jet(s).

The Perception of Patient Safety Strategies by Primary Health Professionals.

Almost all European citizens rank patient safety as very or fairly important in their country. However, few patient safety initiatives have been undertaken or implemented in Poland. The aim was to identify patient safety strategies perceived as important in Poland and compare them with those identified in an earlier Dutch study. A web-based survey was conducted among primary healthcare providers in Poland. The findings were compared with those obtained from eight other countries. The strategies regarded as most important in Poland included the use of integrated medical records for communication with specialists and others, patient-held medical records, acceptable workload in general practice, and availability of information technology. However, despite being seen as important, these strategies have not been widely implemented in Poland. This is the first study to identify strategies considered by primary care physicians in Poland to be important for improving patient safety. These strategies differed significantly from those indicated in other countries.

Implementation of a Pooled Surveillance Testing Program for Asymptomatic SARS-CoV-2 Infections on a College Campus - Duke University, Durham, North Carolina, August 2-October 11, 2020.

On university campuses and in similar congregate environments, surveillance testing of asymptomatic persons is a critical strategy (1,2) for preventing transmission of SARS-CoV-2, the virus that causes coronavirus disease 2019 (COVID-19). All students at Duke University, a private research university in Durham, North Carolina, signed the Duke Compact (3), agreeing to observe mandatory masking, social distancing, and participation in entry and surveillance testing. The university implemented a five-to-one pooled testing program for SARS-CoV-2 using a quantitative, in-house, laboratory-developed, real-time reverse transcription-polymerase chain reaction (RT-PCR) test (4,5). Pooling of specimens to enable large-scale testing while minimizing use of reagents was pioneered during the human immunodeficiency virus pandemic (6). A similar methodology was adapted for Duke University's asymptomatic testing program. The baseline SARS-CoV-2 testing plan was to distribute tests geospatially and temporally across on- and off-campus student populations. By September 20, 2020, asymptomatic testing was scaled up to testing targets, which include testing for residential undergraduates twice weekly, off-campus undergraduates one to two times per week, and graduate students approximately once weekly. In addition, in response to newly identified positive test results, testing was focused in locations or within cohorts where data suggested an increased risk for transmission. Scale-up over 4 weeks entailed redeploying staff members to prepare 15 campus testing sites for specimen collection, developing information management tools, and repurposing laboratory automation to establish an asymptomatic surveillance system. During August 2-October 11, 68,913 specimens from 10,265 graduate and undergraduate students were tested. Eighty-four specimens were positive for SARS-CoV-2, and 51% were among persons with no symptoms. Testing as a result of contact tracing identified 27.4% of infections. A combination of risk-reduction strategies and frequent surveillance testing likely contributed to a prolonged period of low transmission on campus. These findings highlight the importance of combined testing and contact tracing strategies beyond symptomatic testing, in association with other preventive measures. Pooled testing balances resource availability with supply-chain disruptions, high throughput with high sensitivity, and rapid turnaround with an acceptable workload.

Identifying the Value of an eHealth Intervention Aimed at Cognitive Impairments: Observational Study in Different Contexts and Service Models.

BackgroundValue is one of the central concepts in health care, but it is vague within the field of summative eHealth evaluations. Moreover, the role of context in explaining the value is underexplored, and there is no explicit framework guiding the evaluation of the value of eHealth interventions. Hence, different studies conceptualize and operationalize value in different ways, ranging from measuring outcomes such as clinical efficacy or behavior change of patients or professionals to measuring the perceptions of various stakeholders or in economic terms.ObjectiveThe objective of our study is to identify contextual factors that determine similarities and differences in the value of an eHealth intervention between two contexts. We also aim to reflect on and contribute to the discussion about the specification, assessment, and relativity of the “value” concept in the evaluation of eHealth interventions.MethodsThe study concerned a 6-month eHealth intervention targeted at elderly patients (n=107) diagnosed with cognitive impairment in Italy and Sweden. The intervention introduced a case manager role and an eHealth platform to provide remote monitoring and coaching services to the patients. A model for evaluating the value of eHealth interventions was designed as monetary and nonmonetary benefits and sacrifices, based on the value conceptualizations in eHealth and marketing literature. The data was collected using the Mini–Mental State Examination (MMSE), the clock drawing test, and the 5-level EQ-5D (EQ-5D-5L). Semistructured interviews were conducted with patients and health care professionals. Monetary data was collected from the health care and technology providers.ResultsThe value of an eHealth intervention applied to similar types of populations but differed in different contexts. In Sweden, patients improved cognitive performance (MMSE mean 0.85, SD 1.62, P<.001), reduced anxiety (EQ-5D-5L mean 0.16, SD 0.54, P=.046), perceived their health better (EQ-5D-5L VAS scale mean 2.6, SD 9.7, P=.035), and both patients and health care professionals were satisfied with the care. However, the Swedish service model demonstrated an increased cost, higher workload for health care professionals, and the intervention was not cost-efficient. In Italy, the patients were satisfied with the care received, and the health care professionals felt empowered and had an acceptable workload. Moreover, the intervention was cost-effective. However, clinical efficacy and quality of life improvements have not been observed. We identified 6 factors that influence the value of eHealth intervention in a particular context: (1) service delivery design of the intervention (process of delivery), (2) organizational setup of the intervention (ie, organizational structure and professionals involved), (3) cost of different treatments, (4) hourly rates of staff for delivering the intervention, (5) lifestyle habits of the population (eg, how physically active they were in their daily life and if they were living alone or with family), and (6) local preferences on the quality of patient care.ConclusionsValue in the assessments of eHealth interventions need to be considered beyond economic terms, perceptions, or behavior changes. To obtain a holistic view of the value created, it needs to be operationalized into monetary and nonmonetary outcomes, categorizing these into benefits and sacrifices.

Future Engineering Curricula: Balancing Domain Competence with CPS Readiness

The integration of courses teaching CPS design into engineering curricula is very difficult, due to tight ceilings on the acceptable work load for students. This article proposes a way of integrating CPS-relevant topics into engineering curricula. The article contains valuable suggestions for such integration. — <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Peter Marwedel, TU Dortmund</i>

Social workers and recovery from stress

Summary Recovery from stress is essential for employees’ well-being, even more so in jobs where high stress is inevitable. The purpose of this study was to examine the influence of achievement goal orientation on recovery from stress (i.e. need for recovery and vigour) over several years. We followed a sample of social workers in the Netherlands (N = 238) across four years, with three measurement points (T1–T3). Data were analysed with latent growth curve modelling. Findings Results showed that need for recovery and vigour were fairly stable over time and therefore we could not examine the effects of achievement goal orientation on change in vigour and need for recovery over time. However, level of mastery goal orientation (mastery-approach and mastery-avoidance goal orientation) at T1 was positively related to the initial level of vigour at T1, even after controlling for job autonomy and workload. Our results indicate that mastery goal orientation is relevant for employees to feel energetic and vital in a job with high stress. Practical implications Our results showed that organizations can prevent depletion among social workers by ensuring an acceptable workload, while vigour can be enhanced by selecting employees with high mastery goal orientation. Organizations can also contribute to the vitality of social workers by stimulating and fostering mastery goal orientation.

An efficient screening technique for acceptable mental workload based on the NASA Task Load Index—development and application to control room validation

Workload assessment is required for human factors validation of control rooms. The NASA Task Load Index (TLX) is a popular measure for this purpose. However, acceptability of workload is difficult to interpret based on the scores, and the measure is time consuming for use in test scenario breaks. This paper reports the identification and evaluation of a one-item subjective rating for the acceptability of mental workload. Study 1 found that one item, mental demand, highly represented the multidimensional TLX and that operators rated this item to be distinct from performance and situation awareness. Study 2 investigated the acceptance scale's sensitivity to control room modification, and the study found that operators' rating of level of mental demand and rating of acceptability of mental demand were moderately related. The rating of acceptability, compared with the original scale, was more sensitive to control room modernisation and was more strongly related to subjective performance. Operators' rating of acceptable workload was significantly related to observers' assessment of team performance, while the rating of level was not. Both acceptable and non-acceptable workload were related to high levels of the original TLX scales, indicating that operators' perception of acceptable workload was not fixated on a particular level of the original TLX scale. The results supported that efficient assessment can be achieved by applying only the TLX mental demand item and by supplementing or replacing the original rating scale with an acceptability rating scale. The approach presented applies to establishing ‘redlines’ for human performance constructs beyond mental workload. Relevance to industryHigh-consequence industries are required to perform human factors validation for new and substantially modified design. While numerous human factors measures are available, approaches for establishing cut-off scores or ‘redlines’ are lacking. This paper investigates acceptability rating to address this challenge.

Networked Decisions: Decision-Making Thresholds in Child Protection

AbstractFamilies are significantly affected by decisions made in the child protection context, yet decision outcomes differ even when cases are similar. Understanding the concepts, practices and processes of differentiation that push some cases over the threshold of key decision points, but not other similar cases, is crucial. Drawing on interviews and focus groups with child protection social workers from three site offices in Aotearoa New Zealand (interviews, n = 26; focus groups, n = 25) and using thematic analysis, this study identified the case, internal organisational, inter-site organisational and external elements that contributed to threshold decisions. Case factors such as children’s age, abuse type and chronicity recorded family history and perceptions of family compliance interacted with internal organisational processes and practices, social negotiations and hierarchical power differences to produce decision outcomes. Inter-site differences in decision thresholds resulted from differences in site managers’ perceptions of acceptable case type, site workloads, resources, size and cultural commitment to family preservation. External demographic inequalities were perceived as causing differing levels of site workload. This ‘networked decision-making’ process is theorised drawing on an extended version of the decision-making ecology (DME), by using qualitative methods to examine interactions between the DME elements and their relationship with risk regimes.

Face and content validity of Xperience™ Team Trainer: bed-side assistant training simulator for robotic surgery.

In robotic surgery, the coordination between the console-side surgeon and bed-side assistant is crucial, more than in standard surgery or laparoscopy where the surgical team works in close contact. Xperience™ Team Trainer (XTT) is a new optional component for the dv-Trainer® platform and simulates the patient-side working environment. We present preliminary results for face, content, and the workload imposed regarding the use of the XTT virtual reality platform for the psychomotor and communication skills training of the bed-side assistant in robot-assisted surgery. Participants were categorized into "Beginners" and "Experts". They tested a series of exercises (Pick & Place Laparoscopic Demo, Pick & Place 2 and Team Match Board 1) and completed face validity questionnaires. "Experts" assessed content validity on another questionnaire. All the participants completed a NASA Task Load Index questionnaire to assess the workload imposed by XTT. Twenty-one consenting participants were included (12 "Beginners" and 9 "Experts"). XTT was shown to possess face and content validity, as evidenced by the rankings given on the simulator's ease of use and realism parameters and on the simulator's usefulness for training. Eight out of nine "Experts" judged the visualization of metrics after the exercises useful. However, face validity has shown some weaknesses regarding interactions and instruments. Reasonable workload parameters were registered. XTT demonstrated excellent face and content validity with acceptable workload parameters. XTT could become a useful tool for robotic surgery team training.

ANALISIS BEBAN KERJA MENTAL PEKERJA BAGIAN GROUND H ANDLING BANDARA ADISUTJIPTO UNTUK MENDUKUNG KESELAMATAN PENERBANGAN

Increased need for air transport will increase the activity of ground handling at airports. Increased activity of this will affect the mental workload received personnel who carry it out. Any increase in mental workload will affect the occurrence of human error and affect flight safety. Analysis of mental workload ofpart o f ground handling personnel is very important to ensure acceptable personnel workloads according to workload capacity available. This mental workload research using NASA-TLX method, that the procedure uses a multi-dimensional rating, and divide the workload on the basis of the average loading 6 dimensions, namely Mental Demand, Physical Demand, Temporal Demand, Effort, Own Performance, and frustation. NASA-TLX is divided into two phases, namely a comparison of each scale (Paired Comparison) and giving value to the work (Event Scoring). The research objective is to ensure the mental workload of part of ground handling Adisucipto airport in Yogyakarta, in accordance with their capacity, so as to avoid human error and to support aviation safety. The results showed that the mean score of mental workload ground handling activities by PT. Gapura Air and PT. Kokapura Avia in Yogyakarta Adisucipto airport in the mental workload optimization group, which indicates mental workload received by workers are safe (no overload).

The Relevance of Psychophysical Methods Research for the Practitioner

The use of a psychophysical methodology in conducting manual materials handling and upper extremity studies is well recognized, and the findings (e.g., the Snook and Ciriello studies and the Liberty Mutual tables) have extensive application in the assessment and design of a variety of tasks in industry. In particular, the psychophysical methodology is directed to the assessment of what workers can actually perform and as such has identified acceptable workloads for various working populations. In many cases the identification of these acceptable workloads has historically been very difficult to achieve with methods in other scientific disciplines (e.g., Biomechanics, Physiology, Epidemiology). The purpose of this discussion panel will be to explore the questions on the usefulness and continuing relevance of the psychophysical methodologies to address the needs of the practitioner community. Each panelist will explore the applications of psychophysics in several areas of research and practice. The continuing relevance and directions of psychophysical research will be explored in discussion with the panelists and audience.