Effect Of Sleep Duration And Bedtime On Heart Rate Variability In Wildland Firefighters
Bibliographic record
Abstract
Wildland firefighting requires continuous attention while exposed to long working hours and sub-optimal sleep. These stressors may induce higher levels of stress via autonomic imbalance, which poses a risk to worker health and safety. PURPOSE: This investigation examined the effect of sleep characteristics on heart rate (HR) and heart rate variability (HRV) before and after shift. METHODS: An observational study was conducted on 15 wildland firefighters (6F) between July and September of the 2021 and 2022 fire seasons. Resting HR and HRV were measured directly upon waking (i.e. pre-shift) and before bed (i.e. post-shift) using a chest-worn monitor (Polar H10 + Ignite Activity Tracker). Sleep variables were measured via wrist-worn actigraphy (Polar Ignite). Separate two-way ANOVAs were performed to analyze the effect of sleep duration and bedtime on levels of HRV (RMSSD) and mean resting HR. Bedtime condition was categorized as <22:30, 22:30-23:30, or > 23:30. Sleep duration condition was categorized as >6.5 hrs, 6.5-7.5 hrs, or 7.5 hrs+. Shift condition was categorized as pre-shift or post-shift. RESULTS: Simple main effects revealed bedtime condition to have a significant effect on both HR (p < 0.01) and HRV (p < 0.05). Sleep duration condition had a significant effect on HR (p < 0.0001) but not HRV (p = 0.1153). Shift condition had a significant effect on both HR (p < 0.0001) and HRV (p < 0.0001). The only significant interaction effect found was between bedtime and shift conditions in levels of HRV (F(2, 225) = 4.3815, p < 0.05), such that HRV only appeared to be affected by late bedtimes in the pre-shift condition. CONCLUSIONS: Later bedtimes and shorter sleep were significantly related to higher resting HR, while later bedtimes were also related to reduced HRV the following morning. These indicators of automatic function suggest that impaired sleep between shifts may contribute to higher levels of stress, which has implications for worker health and safety. - Results of Two-way ANOVAs Condition SS DOF F-Value P-Value Shift & Bedtime: RMSSD Shift 13589 1 52.00 <0.0001 Bedtime 1771 2 3.39 0.0355 Shift : Bedtime Interaction 2290 2 4.38 0.0136 Shift & Bedtime: HR Shift 1445 1 20.03 <0.0001 Bedtime 1006 2 6.97 0.0012 Shift & Sleep Duration: RMSSD Shift 14148 1 52.04 <0.0001 Duration 1186 2 2.1807 0.1153 Shift & Sleep Duration: HR Shift 1717 1 24.08 <0.0001 Duration 1384 2 9.71 <0.0001
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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 | 0.009 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 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".