INTERACTIONS BETWEEN EMERGENCY MEDICINE AND RESPIRATORY THERAPY, PSYCHOLOGICAL AND SOCIAL STRESS, ECG MONITORING, IN NURSING CARE: A SYSTEMATIC REVIEW
Bibliographic record
Abstract
Abstract Background: Emergency departments and other acute-care environments depend on tight coordination between nurses, respiratory therapists (RTs), and physicians while simultaneously managing high cognitive load, staff stress, and continuous physiologic monitoring. These domains interact teamwork affects protocol execution, monitoring alarms contribute to workload and stress, and stress can undermine communication and response reliability. We aimed to synthesize PMC full-text evidence on nurse RT emergency medicine interactions around acute respiratory, psychological stress in these teams, and ECG monitoring relevant to nursing care. Methods: We conduct a PRISMA guided systematic review. We searched the PubMed Central full-text archive using structured keywords for emergency, respiratory therapy, inter-professional collaboration, stress, ECG monitoring, and alarm fatigue. We included original studies reporting outcomes relevant to nursing care in acute settings. We narratively synthesized results because outcomes and designs were heterogeneous. Results: Ten original studies met inclusion criteria across three clusters inter-professional emergency and acute respiratory and critical-care processes, psychological stress, burnout in nurses, RTs, and ECG competence and alarm management. Inter-professional on-floor education in ED settings was feasible and perceived as beneficial. A nurse, RT-driven asthma pathway reduced PICU length of stay, while an ED asthma decision-support approach did not improve time to disposition in a trial. Rapid response team implementation was associated with reduced hospital mortality and cardiopulmonary arrest rates in a large pre. RT-driven lung-protective ventilation protocol implementation increased guideline adherence and was associated with reduced ARDS incidence, but also raised concerns about communication for a subset of RTs. ECG education increased nurses’ confidence but did not reduce psychological stress about ECG monitoring; ED work experience was associated with higher ECG-related stress. Alarm-management training improved behaviors and reduced alarm fatigue. Conclusion: PMC evidence supports that protocolized, team-based interventions can improve process and some patient outcomes, but social dynamics and workload must be addressed. Monitoring competence and alarm behaviors are modifiable, yet stress may persist even when confidence increases. Implementation strategies should explicitly target communication, staffing, and alarm ecology alongside clinical protocols.
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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 | 0.000 | 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 | 0.000 |
| 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".