Drowsy and dangerous? Fatigue in paramedics: an overview
Bibliographic record
Abstract
Background Fatigue is a complex phenomenon that has effects on physical characteristics, cognition, behaviours, and physical and mental health. Paramedicine crosses the boundaries of many high-risk industries, namely medicine, transport and aviation. The effects of fatigue on paramedics thus need to be explored and considered in order to begin to identify appropriate interventions and management strategies. Aim The aim of this article was to provide an overview of fatigue in paramedics and its potential effects on various areas of paramedic practice and paramedic health, and to outline potential solutions to assess and manage the risk of fatigue in paramedics as suggested by the literature. Methods We conducted unstructured, non-systematic searches of the literature in order to inform an overview of the literature. An overview is a summary of the literature that attempts to survey the literature and describe its characteristics. We thematically structured the review under the following headings: defining occupational activity and health status; clinical performance and patient safety; shift length and time at work; effects on paramedic health; effects on driving abilities; fatigue risk management; and, fatigue proofing. Discussion Fatigue should be considered in the context of overall paramedic health status and paramedic occupational activity. The nature of paramedic shift work, and the associated occupational activity place paramedics at increased risk from fatigue. Shift work may also contribute to sleep disorders among paramedics. Fatigue is associated with increased errors and adverse events, increased chronic disease and injury rates, depression and anxiety, and impaired driving ability. Conclusion The issue of fatigue in paramedicine is complex and has serious consequences for patients and paramedics. Paramedic services and paramedics need to work collaboratively to identify and action appropriate measures to reduce the effects of fatigue on the wellbeing of the workforce and mitigate its effects on clinical performance and safety.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.013 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".