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TZID:America/New_York
X-LIC-LOCATION:America/New_York
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DTSTART:20241103T020000
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DTSTART:20250309T020000
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DESCRIPTION:Program: Occupational Health and Safety Session: Poster Compet
 ition for Research and Practice in Occupational Health & Safety (I) Autho
 rs : Michael Wininger\, Kaakpema Yelpaala\, Debbie Humphries\, Alyse Sabi
 na See all authors and presenters → Abstract Introduction Firefighters fa
 ce extended shifts and frequent night calls\, placing them at elevated ri
 sk of sleep disruption and fatigue. This prospective observational projec
 t investigated how demanding shift schedules and operational workloads in
 fluence sleep architecture and recovery. Methods Firefighters from a sing
 le fire department (n=200) were recruited to continuously wear a biometri
 c device tracking heart rate\, sleep stages\, and additional physiologica
 l indicators for 39 days. Biometric data was then merged with 911 call da
 ta and staffing records. Correlation matrices were developed to compare r
 elationships between workload and measured biometric data. Subsequently\,
  a random forest model was developed and validated to predict firefighter
 s’ biometric response to given workload. Results Findings revealed substa
 ntial deficits in slow wave and REM sleep during consecutive duty nights\
 , with the greatest reductions observed in personnel assigned to high-vol
 ume ambulance units. There were significant differences in restorative sl
 eep (Slow wave and REM) between on-shift (157.0 ± 58.2 minutes) versus of
 f-shift (192.0 ± 60.9 minutes)\, P < 0.001.) There were also significant 
 correlations between elevated night 911 call frequency\, diminished resto
 rative sleep (r = -0.75)\, increased resting heart rate (r = 0.68) reduce
 d heart rate variability (r =-0.53) - factors closely tied to cognitive p
 erformance and overall well-being. Conclusions and Recommendations The pr
 edictive modeling framework validated the ability to forecast fatigue lev
 els from real-time operational conditions\, enabling data-driven interven
 tions that target workload redistribution and strategic scheduling. Recom
 mended solutions include later shift start times\, alternative work cycle
 s\, and dynamic resource deployment. These measures aim to preserve firef
 ighter health\, maximize operational effectiveness\, and promote sustaina
 ble workforce policies by mitigating the harmful consequences of chronic 
 sleep disruption.\n\nSpeakers:\nMichael Wininger\; Kaakpema Yelpaala\; De
 bbie Humphries\; Alyse Sabina\n\nAdmission:\nRegistrationFees: APHA Event
  Registration is Required\n\nDetails URL:\nhttps://medicine.yale.edu/even
 t/operational-fatigue-and-sleep-loss-in-the-fire-service/\n
DTEND;TZID=America/New_York:20251102T140000
DTSTAMP:20260515T001630Z
DTSTART;TZID=America/New_York:20251102T130000
GEO:38.903500;-77.022987
LOCATION:801 Allen Y Lew Pl NW\, Washington\, DC\, United States
SEQUENCE:0
STATUS:Confirmed
SUMMARY:2036.0 - Operational Fatigue and Sleep Loss in the Fire Service: P
 hysiological Findings from Wearable Biometric Monitoring
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