The sleep behaviour and fatigue trends of wildland firefighters during non-fire and fire deployments
Notice bibliographique
Résumé
Ontario wildland firefighting is a hazardous and safety-critical operation with relatively high injury rates. This is indicated by the 10-year average of 4.46 lost-time injuries per 100 workers in Ontario wildland firefighting compared to 0.95-1.88 lost-time injuries in other occupations, as reported by the Workplace Safety and Insurance Board (WSIB). There is anecdotal evidence that fatigue is a major contributor to injury; however, evidence to support this is limited. Understanding fatigue trends, potential causes, and areas for intervention within the wildland firefighting profession were the main goals of the study. \nAccordingly, contributors to fatigue were assessed during non-fire and fire deployments by collecting objective sleep (Actigraphy) and vigilance (Psychomotor Vigilance Test) measures, as well as subjective measures of fatigue and recovery (questionnaires). Data were collected from wildland firefighters during the high-risk months of the fire season within the province of Ontario. \nSleep duration less than six hours, sleep efficiency below 85%, and wake after sleep onset greater than 30 min were more frequently observed during high intensity, Initial Attack deployments. Sleep duration less than six hours were routinely observed in non-fire work periods, placing workers at risk of pre-deployment sleep-debt. Self-reported morning fatigue scores were low-to-moderate and were best predicted by Initial Attack deployment work conducted the day prior. Reaction times were slightly worse in morning periods during Initial Attack deployments, but scores were generally within acceptable ranges. Self-reported recovery scores were generally good regardless of work performed. \nThe current study highlights suboptimal sleep behaviours during both non-fire and fire suppression work, with sleep measures below recommended standards. High-intensity fire suppression periods (i.e. Initial Attacks) were predictably associated with the worst sleep and fatigue levels; but it is worth noting that the data were collected during a record low-hazard, firefighting season and may not reflect the sleep behaviours and fatigue levels encountered during a high-hazard fire season. Interventions for sleep/fatigue hygiene and awareness should be explored and are further discussed in this paper. The research methodology employed in the current study could be used in future investigations to determine the sleep behaviours and fatigue levels of wildland firefighters during a high hazard fire season.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
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 | 0,000 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,003 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| 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 ».