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Related Concept Videos

Components of Stress01:23

Components of Stress

Stress analysis under multiple loading conditions is intricate, necessitating a comprehensive grasp of normal and shearing stresses. Consider a small cube at point O, subjected to stress on all six faces, visible or not. Normal stress components σx, σy, σz act perpendicularly to the x, y, and z axes. Shearing stress components τxy and τxz are exerted on faces perpendicular to these axes.
Interestingly, the hidden cube faces also experience these stresses, equal and opposite to those on the...
General State of Stress01:21

General State of Stress

The general state of stress within a material can be accurately depicted using a stress tensor. This tensor encapsulates the internal forces distributed within a material subjected to external forces or deformations.
Specifically, consider a tetrahedral element where one face, labeled XYZ, is perpendicular to the line OA, and the remaining faces align with the coordinate axes with point O as the origin. At any point, such as point O, the stress tensor can be used to determine the stress...
Psychological Responses to Stress01:20

Psychological Responses to Stress

Psychological responses to stress encompass the various cognitive and emotional reactions individuals experience when faced with challenging or threatening situations, such as a job loss. Prolonged exposure to stressors can disturb emotional balance, increasing negative emotions (e.g., anxiety and sadness) and diminishing positive emotions (e.g., joy and satisfaction). These persistent emotional shifts are associated with an increased risk of both physical illness and mental health issues, such...
Stress and Mental Health01:30

Stress and Mental Health

Chronic stress profoundly affects mental health, significantly influencing mood, behavior, and overall quality of life. Research closely links chronic stress with mental health conditions such as depression, anxiety, and substance use disorders. Ongoing exposure to stress can lead to physiological and psychological changes, initiating a cycle of emotional distress and maladaptive coping mechanisms.
Individuals with depression often experience challenges in both their personal and professional...
Stress Concentrations01:24

Stress Concentrations

Stress concentration is when stress intensifies near discontinuities such as holes or abrupt cross-sectional changes in a structural member. This localized stress can often surpass the average stress within the member. The stress distribution in flat bars, either with a circular hole or varying widths connected by fillets, can be determined experimentally using a photoelastic method. The results are based on ratios of geometric parameters like the ratio of the hole's radius to the smaller width...
Stress Concentrations01:13

Stress Concentrations

The concept of stress concentration is crucial for understanding how materials respond under bending stresses, particularly when there are irregularities or discontinuities in the material's geometry. Normally, stress in a symmetric member subjected to pure bending is assumed to be uniformly distributed across the entire cross-section. However, this assumption does not hold when there are variations in the cross-sectional geometry or the presence of notches and holes.
The stress concentration...

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Polar Histogram Visualization of Acute Stress Disorder Scale Scores for Comprehensive Clinical Assessment
08:25

Polar Histogram Visualization of Acute Stress Disorder Scale Scores for Comprehensive Clinical Assessment

Published on: December 6, 2024

A data-informed multidimensional composite score for stress assessment.

Virginie Perlo1, Tharindu Fernando2, Jonathan M Flintoff3

  • 1School of Biomedical Sciences, Faculty of Health, Queensland University of Technology (QUT), 2 George St, Gardens Point, Brisbane, QLD, 4000, Australia; Centre for Biomedical Technologies, QUT, 60 Musk Ave, Kelvin Grove, QLD, 4059, Australia; Centre for Data Science, QUT, 2 George St, Gardens Point, Brisbane, QLD, 4000, Australia.

Acta Psychologica
|June 3, 2026
PubMed
Summary
This summary is machine-generated.

This study developed a multidimensional approach to measure stress responses. Sleep deprivation induced the highest stress, and baseline characteristics predicted high stress with over 90% accuracy.

Keywords:
Machine learning predictionMultidimensional stress assessmentPerformance clusteringPrincipal component analysis (PCA)Statistical analysis

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Area of Science:

  • Physiology
  • Psychology
  • Data Science

Background:

  • Occupational roles like military and emergency services require significant physical, cognitive, and psychosocial effort.
  • Individuals in these demanding roles face unique stressors, leading to varied stress responses.
  • Assessing and comparing individual stress responses is complex due to intertwined physiological, cognitive, and emotional factors.

Purpose of the Study:

  • To introduce a novel, data-driven multidimensional approach for assessing stress.
  • To quantitatively integrate cognitive, psychosocial, and physiological indicators for stress evaluation.
  • To identify key predictors of high stress responses.

Main Methods:

  • Participants underwent four stress trials: exercise in heat, musculoskeletal exertion, psychosocial stress, and sleep deprivation.
  • Stress was measured via self-reports (mood, fatigue), cognitive tasks (reaction time, inhibitory control), and postural balance.
  • A three-phase analysis involved domain clustering (self-report, cognitive, physical), Principal Component Analysis for domain scores, and composite stress score derivation.

Main Results:

  • Participants in the sleep deprivation trial showed the highest composite stress scores.
  • A random forest model accurately predicted high stress responses (balanced accuracy >90% for cognitive performance).
  • Key predictors of high stress included resilience, risk-taking behavior, BMI, and participation in the sleep deprivation trial.

Conclusions:

  • Integrating multi-domain performance changes with individual baseline characteristics offers an effective method for measuring stress.
  • This data-focused approach enables accurate prediction of stress responses across diverse stressors.
  • Understanding individual variability in stress response is crucial for high-demand occupations.