The Impact of Stress on Paramedic Performance During Simulated Critical Events
Bibliographic record
Abstract
OBJECTIVES: Substantial research demonstrates that the stressors accompanying the profession of paramedicine can lead to mental health concerns. In contrast, little is known about the effects of stress on paramedics' ability to care for patients during stressful events. In this study, we examined paramedics' acute stress responses and performance during simulated high-stress scenarios. METHODS: Twenty-two advanced care paramedics participated in simulated low-stress and high-stress clinical scenarios. The paramedics provided salivary cortisol samples and completed an anxiety questionnaire at baseline and following each scenario. Clinical performance was videotaped and scored on a checklist of specific actions and a global rating of performance. The paramedics also completed patient care documentation following each scenario. RESULTS: The paramedics demonstrated greater increases in anxiety (P < .05) and salivary cortisol levels (P < .05) in response to the high-stress scenario compared to the low-stress scenario. Global rating scores were significantly lower in the high-stress scenario than in the low-stress scenario (P < .05). Checklist scores were not significantly different between the two scenarios (P = .12). There were more errors of commission (reporting information not present in the scenario) in the patient care documentation following the high-stress scenario than following the low-stress scenario (P < .05). In contrast, there were no differences in omission errors (failing to recall information present in the scenario) between the two scenarios (P = .34). CONCLUSION: Clinical performance and documentation appear vulnerable to the impact of acute stress. This highlights the importance of developing systems and training interventions aimed at supporting and preparing emergency workers who face acute stressors as part of their every day work responsibilities.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".