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Updated: Nov 29, 2025

Collecting Sleep, Circadian, Fatigue, and Performance Data in Complex Operational Environments
Published on: August 8, 2019
Trends in Strategic Napping in Surgical Residents by Gender, Postgraduate Year, Work Schedule, and Clinical Rotation
Jaime K Devine1, Lindsay P Schwartz1, Steven R Hursh2
1Institutes for Behavior Resources, Baltimore, Maryland.
Objective:
To identify surgical resident and clinical rotation attributes which predict on-shift napping through objectively measured sleep patterns and work schedules over a 2-month period.
Design:
In a cross-sectional study, participants provided schedules, completed the Epworth Sleepiness Scale (ESS), and wore sleep-tracking devices (Zulu watch) continuously for 8 weeks. Multiple linear regression predicted percent days with on-shift napping from resident and rotation characteristics.
Setting:
Greater Washington, DC area hospitals.
Participants:
Twenty-two (n = 22) surgical residents rotating in at least 1 of 5 different clinical rotation categories.
Results:
Residents slept 6 hours within a 24-hour period (370 ± 129 minutes) with normal sleep efficiency (sleep efficiency (SE): 87.13% ± 7.55%). Resident ESS scores indicated excessive daytime sleepiness (11.64 ± 4.03). Ninety-five percent (n = 21) of residents napped on-shift. Residents napped on-shift approximately 32% of their working days and were most likely to nap when working between 23:00 and 05:00 hours. Earlier shift start times predicted less on-shift napping (B = -0.08, SE = 0.04, β = -2.40, t = -2.09, p = 0.05) while working more night shifts (B = 1.55, SE = 0.44, β = 4.12, t = 3.52, p = 0.003) and shifts over 24 hours (B = 1.45, SE = 0.55, β = 1.96, t = 2.63, p = 0.01) predicted more frequent on-shift napping.
Conclusions:
Residents are taking advantage of opportunities to nap on-shift. Working at night seems to drive on-shift napping. However, residents still exhibit insufficient sleep and daytime sleepiness which could reduce competency and represent a safety risk to themselves and/or patients. These findings will help inform intervention strategies which are tailored to surgical residents using a biomathematical model of fatigue.
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