Fatigue in Wildland Firefighting: Relationships Between Sleep, Shift Characteristics, and Levels of Stress and Cognitive Function.
Notice bibliographique
Résumé
Rationale: With climate change rising, the impact of wildfires is expected to increase. Wildland firefighting requires constant attention while exposed to harsh working conditions, including long working hours and sub-optimal sleep. These stressors may contribute to heightened stress and impaired cognitive function, which poses a risk to worker health and safety, respectively. Purpose: The current study’s objective was to investigate the associations between sleep, shift characteristics and levels of stress and cognitive function in Canadian wildland firefighters. Methods: Employing a within-subject observational study design, we recruited a geographically diverse sample of 25 wildland firefighters from the British Columbia Wildfire Service (BCWS). Remote data collection occurred between June and September of the 2021 and 2022 fire seasons, including in participants’ homes and at their work respective location. Wrist-worn actigraphy, heart rate variability (HRV), and the psychomotor vigilance task served as objective, mobile measures of sleep, stress, and cognitive function, respectively. Web-based methods were used to collect shift information, as well as subjective reports of stress and fatigue. Linear mixed effects modelling was used to statistically control for inter-individual differences. The influence of participant-factors such as age, biological sex, and years of firefighting experience was also explored. Results: Average sleep and shift durations on fire suppression days were 6.7 and 13.8 hours, respectively (SD: 66 mins; 108 mins). Polar sleep score was found to be the best sleep-related predictor of every outcome measure, except HRV. Poor sleep, according to sleep score, was significantly associated with increased levels of stress and fatigue across all metrics (p<0.01). Later evening bedtimes were non-significantly related to reduced HRV (p<0.1). Shift duration was found to be the best shift-related predictor of every outcome measure. Longer shift durations were significantly associated with increased levels of stress and fatigue across all metrics (p<0.001). No shift characteristic predicted HRV. Cross-level interactions were indicated for two relationships involving shift duration. Physical activity and meditation experience were found to moderate the relationship between shift duration and heart rate such that the strength of association tended to be stronger in individuals without meditation experience and individuals with low physical activity. Trait morning-eveningness, physical activity, and meditation experience all moderated the relationship between shift duration and subjective fatigue such that the association was stronger in morning type individuals, individuals with low physical activity, and individuals with meditation experience. Conclusion: Our findings show that wildland firefighters are often exposed to sub-optimal sleep and long shifts. Importantly, poor sleep and long shift durations were associated with heightened levels of stress and impaired cognitive function, which have implications for worker heath and safety. We contribute novel findings to the field of research on occupational health and safety. We also provide insight and recommendations towards improved fatigue management policy within the BCWS by supporting the development, implementation, and continuous improvement of a practical and scientifically defensible fatigue risk management system.
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Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,002 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,001 | 0,000 |
| Études des sciences et des technologies | 0,002 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,001 | 0,003 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».