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Objective: The aim of the study is to determine if there is a correlation between perceived staff workload, measured by the NASA Task Load Index (TLX), and the National Emergency Department Overcrowding Scale (NEDOCS) in a pediatric ED.
Methods: We collected staff questionnaires in a large, urban pediatric ED to assess perceived workload on each of six different TLX subscales, which we weighted evenly to create an overall estimate of workload. We evaluated the correlation between individual TLX responses and NEDOCS overall and by staff subgroup. Additionally, we analyzed: (1) the correlation between mean TLX responses and NEDOCS within a given hour and (2) the performance of a logistic regression model, using TLX as a predictor for "severely overcrowded," as measured by NEDOCS.
Results: Four hundred one questionnaires between 6/2018 and 1/2019 demonstrated significant variation between concurrently collected TLX responses and an overall poor correlation between perceived workload and NEDOCS ( R2 0.096 [95% confidence interval, 0.048-0.16]). TLX responses by subgroups of fellows (n = 4, R2 0.96) and patient financial advisors (n = 15, R2 0.58) demonstrated the highest correlation with NEDOCS. Taking mean TLX responses within a given hour, during periods with NEDOCS >60 (extremely busy or overcrowded), a polynomial trend line matched the data best ( R2 0.638). On logistic regression, the TLX predicts "severely overcrowded" with an area under the curve of the receiver operating characteristic of 0.731.
Conclusions: NEDOCS does not have a strong correlation with individual responses on questionnaires of perceived workload for staff in a pediatric ED. NEDOCS, as a measure of overcrowding, may be better correlated with perceived workload during periods with elevated crowding or when interpreted categorically as yes/no "severely overcrowded".
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http://dx.doi.org/10.1097/PEC.0000000000003300 | DOI Listing |
Sci Rep
August 2025
Engineering Education Innovation Research Center, The Open University of Sichuan, Chengdu, 610073, China.
Matching vast online resources to individual learners' needs remains a major challenge, especially for adults with diverse backgrounds. To address this challenge, we proposed a Dynamic Knowledge Graph-enhanced Cross-Modal Recommendation model (DKG-CMR) to solve the problem. This model utilizes a dynamic knowledge graph-a structure organizing information and relationships-that continuously updates based on learner actions and course objectives.
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August 2025
Department of Occupational Health Engineering, Faculty of Medical Sciences, Tarbiat Modares University, Tehran, Iran.
BackgroundThe maritime industry, despite rigorous safety measures, remains a high-risk sector due to persistent human errors.ObjectiveThis study aims to assess mental workload, accuracy, and attention across various mental states and explore the relationships among key variables affecting cognitive performance through a Bayesian network (BN) analysis.MethodsData were collected from 51 officers at a maritime training center using demographic surveys and the NASA Task Load Index (NASA-TLX) mental workload index.
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August 2025
Department of Industrial Engineering, Telkom University, Bandung, Indonesia.
BackgroundEffective workload management in education is crucial for student well-being with nature-based Virtual Reality (VR) interventions presenting a viable solution. Most publications primarily examined high-end VR devices with immersive Head-Mounted Displays (HMDs), leading to a study gap in areas with restricted access to advanced VR technology.ObjectivesThis study explores the impact of a low-cost non-immersive VR environment on students' workload and cognitive performance in an educational context.
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July 2025
Faculty of Transportation Engineering, Kunming University of Science and Technology, Kunming, China.
Objectives: The aim of this research was to explore the changes in eye movement characteristics, driving reaction, and operation performance of older drivers under different intersection conflict scenarios and to investigate the impact of subjective workload on hazard perception performance of older drivers.
Methods: A driving simulation experiment was conducted to simulate various intersection conflict risk scenarios, and data on driving behavior and visual characteristics were collected from 47 middle-aged and older drivers. The NASA-Task Load Index (TLX) scale was utilized to assess subjective workload across six dimensions: Mental Demands, Physical Demands, Temporal Demands, Own Performance, Effort, and Frustration.
Brain Sci
May 2025
Digital Media Art, School of Fine Arts, Central China Normal University, Wuhan 430079, China.
AI code generators are increasingly used in creative contexts, offering operational efficiencies on the one hand and prompting concerns about psychological and neurophysiological strain on the other. This study employed a multimodal approach to examine the affective, autonomic, and creative consequences of AI-assisted coding in early-stage learners. Fifty-eight undergraduate design students with no formal programming experience were randomly assigned to either an AI-assisted group or a control group and engaged in a two-day generative programming task.
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