Introduction: Measuring an operator's physiological state and using that data to predict future performance decrements has been an ongoing goal in many areas of transportation. Regarding Army aviation, the realization of such an endeavor could lead to the development of an adaptive automation system which adapts to the needs of the operator. However, reaching this end state requires the use of experimental scenarios similar to real-life settings in order to induce the state of interest that are able to account for individual differences in experience, exposure, and perception to workload manipulations. In the present study, we used an individualized approach to manipulating workload in order to account for individual differences in response to workload manipulations, while still providing an operationally relevant flight experience.
Methods: Eight Army aviators participated in the study, where they completed two visits to the laboratory. The first visit served the purpose of identifying individual workload thresholds, with the second visit resulting in flights with individualized workload manipulations. EEG data was collected throughout both flights, along with subjective ratings of workload and flight performance.
Results: Both EEG data and workload ratings suggested a high workload. Subjective ratings were higher during the high workload flight compared to the low workload flight ( < 0.001). Regarding EEG, frontal alpha ( = 0.04) and theta ( = 0.01) values were lower and a ratio of beta/(alpha+theta) ( = 0.02) were higher in the baseline flight scenario compared to the high workload scenario. Furthermore, the data were compared to that collected in previous studies which used a group-based approach to manipulating workload.
Discussion: The individualized method demonstrated higher effect sizes in both EEG and subjective ratings, suggesting the use of this method may provide a more reliable way of producing high workload in aviators.
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http://dx.doi.org/10.3389/fnrgo.2024.1397586 | DOI Listing |
Psychiatry Res
January 2025
SA Health, Northern Adelaide Local Health Network, Northern Community Mental Health, Salisbury, Australia; Sonder, Headspace Adelaide Early Psychosis, Adelaide, Australia; The University of Adelaide, Adelaide Medical School, Discipline of Psychiatry, Adelaide, Australia.
Community-based high intensity services for people living with severe and enduring mental illnesses face critical workforce shortages and workflow efficiency challenges. The expectation to monitor complex, dynamic patient data from ever-expanding electronic health records leads to information overload, a significant factor contributing to worker burnout and attrition. An algorithmic workforce, defined as a suite of algorithm-driven processes, can work alongside health professionals assisting with oversight tasks and augmenting human expertise.
View Article and Find Full Text PDFJ Spine Surg
December 2024
Department of Neurosurgery, Asfendiyarov Kazakh National Medical University, Almaty, Kazakhstan.
Background: Currently, there remains a high percentage of complications after lumbar discectomy, while there is no uniform tactic to prevent their development. Purpose of the study was to compare the clinical efficacy and return to work rate (RWR) after total disk replacement (TDR) and microsurgical lumbar discectomy (MLD) in railway workers with lumbar disk herniation (LDH).
Methods: We randomly assigned 75 patients out of a total of 81 patients, between 25 and 35 years of age who had one level LDH to undergo single-level TDR surgery (group I, n=37) or MLD surgery (group II, n=38) in the L4-L5 or L5-S1 segments.
BMC Med Res Methodol
January 2025
School of Management, Beijing University of Chinese Medicine, Beijing, China.
Purpose: The process of searching for and selecting clinical evidence for systematic reviews (SRs) or clinical guidelines is essential for researchers in Traditional Chinese medicine (TCM). However, this process is often time-consuming and resource-intensive. In this study, we introduce a novel precision-preferred comprehensive information extraction and selection procedure to enhance both the efficiency and accuracy of evidence selection for TCM practitioners.
View Article and Find Full Text PDFPLoS One
January 2025
Department of Clinical Physiology, Karolinska University Hospital, Stockholm, Sweden.
Background: The causes of reduced aerobic exercise capacity (ExCap) in chronic kidney disease (CKD) are multifactorial, possibly involving the accumulation of tryptophan (TRP) metabolites such as kynurenine (KYN) and kynurenic acid (KYNA), known as kynurenines. Their relationship to ExCap has yet to be studied in CKD. We hypothesised that aerobic ExCap would be negatively associated with plasma levels of TRP, KYN and KYNA in CKD.
View Article and Find Full Text PDFNeuroradiology
January 2025
Department of Radiology, Jinling Hospital, Affiliated Hospital of Medical School, Nanjing University, Nanjing, 210002, Jiangsu, China.
Purpose: We aimed to validate a clinically available artificial intelligence (AI) model to assist general radiologists in the detection of intracranial aneurysm (IA) in a multi-reader multi-case (MRMC) study, and to explore its performance in routine clinical settings.
Methods: Two distinct cohorts of head CT angiography (CTA) data were assembled to validate an AI model. Cohort 1, comprising gold-standard consecutive CTA cases, was used in an MRMC study involving six board-certified general radiologists.
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