Observational studyFrontiers in public health2025
High risk, low rest: a new framework for monitoring sleep vulnerability in emergency medicine.
Observational study in Frontiers in public health, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
Corrections and comments
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Authors and funding
9 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Shift work in emergency care settings disrupts circadian rhythms and sleep, increasing health risks and performance. A key aspect of addressing these challenges lies in predicting the burden of shift work to develop safer schedules. This study introduces the Shift Load Index (SLI) as an advanced and sensitive metric for quantifying recovery constraints and examined its association with objective sleep outcomes in emergency healthcare professionals. Methods: A two-phase observational field study was conducted with 72 nurses and physicians from two French emergency departments. In the theoretical validation phase, 140 work shifts were analyzed using the SLI and compared to validated FAID Quantum fatigue scores. In the behavioral validation phase, weekly actigraphy data from 35 participants were analysed to assess time in bed, total sleep time, and Sleep Regularity Index (SRI). We employed generalized linear mixed-effects models to assess the association of SLI with sleep outcomes. Results: SLI scores significantly predicted FAID Quantum scores (all Discussion: Higher shift load is associated with both reduced sleep quantity and regularity. The SLI provides a useful tool to assess recovery burden, with potential applications in optimizing shift schedules and informing fatigue risk management strategies for emergency healthcare professionals.
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