Paramedic Rotating Shift Schedule —1 Year Cohort
Paramedic Rotating Shift Schedule —1 Year Cohort
Measured daily tasks, self-reported fatigue, and actigraphy-reported sleep to determine schedule impacts on health, wellbeing, and performance, informing safer long-term rostering decisions.
Funding: Funded by Social Sciences and Humanities Research Council.
What did this Project Set Out to Do?
Fatigue among paramedics is a growing occupational health and safety concern due to its association with performance impairments, safety risks, and long‑term health consequences. Paramedics work in unpredictable, time‑sensitive environments characterized by rotating shift schedules, variable workloads, and high cognitive and physical demands. While fatigue has traditionally been examined through scheduling practices, less attention has been paid to within‑shift workload exposures and how they contribute to fatigue and subsequent sleep disruption.
This project sought to advance understanding of paramedic fatigue as a multidimensional and operational issue, using the CSA Z1615:22 Canadian First Responder Fatigue Risk Management System (FRMS) as a guiding framework. The objectives were to identify factors associated with excessive daytime sleepiness and poor sleep among paramedics, demonstrate how the CSA standard can be operationalized in practice, and generate evidence to inform targeted fatigue mitigation strategies in paramedic services.
How was the Research Done?
The project combined findings from several complementary studies conducted among Ontario paramedics, integrating subjective and objective data approaches consistent with FRMS and SOBANE (screening, observation, analysis, expertise) principles.
The studies used a cross‑sectional survey design to examine the prevalence and predictors of fatigue and excessive daytime sleepiness among hundreds of paramedics. Fatigue was initially screened using the Swedish Occupational Fatigue Inventory (SOFI) and further analyzed using the Epworth Sleepiness Scale (ESS). Multivariable logistic regression was used to identify factors associated with excessive daytime sleepiness.
Additionally, this study employed a longitudinal cohort design with repeated measures in a rural Ontario paramedic service. Several paramedics contributed over 250 workday observations that combined operational data from ambulance call reports (ACRs) with actigraphy‑measured sleep outcomes. Logistic regression with cluster‑robust standard errors was used to assess associations between demographics, organizational factors, workload indicators, and objectively measured episodes of poor sleep.
Together, these approaches allowed fatigue to be examined across self‑reported experience, operational exposure, and objective sleep outcomes, consistent with a comprehensive FRMS approach.
What did the Project Discover?
Across the studies, fatigue among paramedics emerged as a complex outcome influenced by scheduling, operational workload, and individual factors.
In the survey study, combined physical and mental fatigue, which was characterized as “lack of energy,” was the most prevalent fatigue dimension. More than one‑third of respondents (36%) scored above the ESS threshold for excessive daytime sleepiness. Rotating shift schedules were associated with increased odds of excessive daytime sleepiness, underscoring the well‑documented challenges of shift work in paramedic services. Interestingly, greater knowledge of the dangers of working while fatigued was also associated with higher odds of excessive daytime sleepiness, while higher self‑reported habits of working while fatigued were associated with lower odds. This highlights potential complexities related to awareness, self‑perception, and reporting behaviours.
The longitudinal study demonstrated that within‑shift operational workload plays a critical role in subsequent sleep quality. Higher workload intensity, measured as interventions per call, was significantly associated with increased odds of experiencing a poor sleep episode, independent of call volume or total interventions alone. A paramedic’s role during calls also influenced sleep outcomes, and the relationship between workload intensity and poor sleep varied by age, with younger paramedics experiencing sharper increases in risk as interventions per call increased.
Collectively, these findings show that fatigue risk is shaped not only by when paramedics work, but also by what they experience during their shifts.
Why Does This Matter?
This project provides a real‑world demonstration of applying the CSA Z1615:22 Fatigue Risk Management System within paramedic services, highlighting the importance of moving beyond scheduling‑only approaches to fatigue management. By integrating subjective fatigue screening, objective sleep measurement, and operational workload data, the findings reinforce the need for system‑level, data‑informed fatigue mitigation strategies.
The results underscore that effective fatigue management in paramedic services must account for operational workload intensity, task demands, and worker characteristics, in addition to shift design. This work lays a foundation for future research incorporating additional objective measures, refined workload indicators, and targeted interventions—supporting safer, healthier, and more sustainable paramedic service operations.
