Acute stress and performance in police recruits
Bibliographic record
Abstract
Abstract Emergency personnel consistently work under high‐stress situations, and thus, the question about whether this stress affects performance is critical to the safety of both themselves and the public. However, considerable controversy exists about the influence of stress on performance. This study investigates the association between both biological and psychological manifestations of stress and performance. The study was conducted with 84 police recruits using a high‐fidelity simulation of a policing event in order to try to determine performance in a life‐like workplace environment. Measures included both biological (heart rate and salivary cortisol levels) and psychological (subjective anxiety) indicators of stress. Performance was videotaped and was later evaluated by three expert raters. The results of this study are promising in that neither physiological nor psychological responses impaired performance in a simulated acutely stressful policing situation. On the other hand, those individuals with greater cortisol release showed higher levels of performance, supporting the notion that cortisol can enhance ability in high‐stress situations. Recruits were also asked to subjectively evaluate their performance. A small group of individuals ranked themselves as poor performers while evaluators ranked them highly. These individuals experienced significantly higher increase in subjective distress and significantly higher cortisol levels at baseline and peak. Copyright © 2008 John Wiley & Sons, Ltd.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".