The Relationship Between Working Conditions And Indices Of Stress And Cognitive Function In Wildland Firefighters
Bibliographic record
Abstract
Wildland firefighters are exposed to various types of strenuous activities and working conditions during their shifts. These factors may affect autonomic nervous system balance, perceived stress, and cognitive function. PURPOSE: This study examined the relationship between working conditions and variables related to stress and cognitive function. METHODS: A within-subject, observation study was conducted on 24 Wildland firefighters (9 F) across British Columbia between July to September of 2021 and 2022. A subset of participants (n = 15) measured heart rate variability (HRV) using a chest worn heart monitor. Perceived stress was measured on a 4-point scale. Cognitive function was measured subjectively, via 7-point scales and objectively, via the psychomotor vigilance task (PVT). Working conditions were measured post-shift, including whether they conducted wildfire suppression that day (Y/N), were exposed to smoke (Y/N), and fire stage of control on a 4-point scale (i.e., out of control; being held; under control; other). Pearson correlation analyses were performed to identify the largest associates between variables. RESULTS: Stage of control had the greatest number of significant correlations to cognitive function, including subjective fatigue (r = 0.28, p < 0.001) and mean reaction time (RT) (r = 0.34, p < 0.001), while also significantly correlated to perceived stress (r = 0.30, p < 0.001). The largest associates of smoke exposure were subjective fatigue (r = -0.29, p < 0.001), median RT (r = -0.25, p < 0.001), and perceived stress (r = -0.17, p < 0.01). Similarly, the largest correlations to wildfire suppression were subjective fatigue (r = -0.30, p < 0.001), median RT (r = -0.23, p < 0.01), and one of the HRV measures, HF power (n.u) (r = 0.32, p < 0.01). Table 1 Note. * = p < 0.05, ** = p < 0.01, *** = p < 0.001. CONCLUSIONS: Indices of stress and cognitive function were significantly correlated to certain working conditions, thus warranting further investigation. Table 1. Correlations Between Working Conditions, Stress, and Cognitive Function - Stage of Control Smoke Exposure (Y/N) Wildfire Suppression (Y/N) Fatigue Pearson R df Fatigue Pearson R df Fatigue Pearson R df Post Shift Subjective Fatigue (1-7) 0.28*** 286 Post Shift Subjective Fatigue (1-7) -0.29*** 318 Post Shift Subjective Fatigue (1-7) -0.30*** 278 Post Shift Mean RT 0.34*** 177 Post Shift Median RT -0.25*** 174 Post Shift Median RT -0.23** 154 Post Shift Mean 1/RT -0.33*** 177 Post Shift Sleepiness (1-7) -0.13* 318 Post Shift Mean 1/RT 0.16* 154 Post Shift Median RT 0.32*** 176 Post Shift Mean 1/RT 0.19* 175 Stress Post Shift Slowest 10% 1/RT -0.34*** 177 Stress HF Power (n.u.) 0.32** 68 Post Shift Lapses (>355 ms) + False Starts 0.34*** 177 Perceived Stress (1-4) -0.17** 313 Max HR -0.24* 68 Post Shift PVT 0.34*** 119 HF Power (ms2) -0.21* 104 Performance Score -0.35*** 119 Post Shift Sleepiness (1-7) 0.17* 218 Stress Perceived Stress (1-4) 0.30*** 220 pNN50 -0.02* 58
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".