Coordinating a Team Response to Behavioral Emergencies in the Emergency Department: A Simulation-Enhanced Interprofessional Curriculum
Bibliographic record
Abstract
INTRODUCTION: While treating potentially violent patients in the emergency department (ED), both patients and staff may be subject to unintentional injury. Emergency healthcare providers are at the greatest risk of experiencing physical and verbal assault from patients. Preliminary studies have shown that a team-based approach with targeted staff training has significant positive outcomes in mitigating violence in healthcare settings. Staff attitudes toward patient aggression have also been linked to workplace safety, but current literature suggests that providers experience fear and anxiety while caring for potentially violent patients. The objectives of the study were (1) to develop an interprofessional curriculum focusing on improving teamwork and staff attitudes toward patient violence using simulation-enhanced education for ED staff, and (2) to assess attitudes towards patient aggression both at pre- and post-curriculum implementation stages using a survey-based study design. METHODS: Formal roles and responsibilities for each member of the care team, including positioning during restraint placement, were predefined in conjunction with ED leadership. Emergency medicine residents, nurses and hospital police officers were assigned to interprofessional teams. The curriculum started with an introductory lecture discussing de-escalation techniques and restraint placement as well as core tenets of interprofessional collaboration. Next, we conducted two simulation scenarios using standardized participants (SPs) and structured debriefing. The study consisted of a survey-based design comparing pre- and post-intervention responses via a paired Student t-test to assess changes in staff attitudes. We used the validated Management of Aggression and Violence Attitude Scale (MAVAS) consisting of 30 Likert-scale questions grouped into four themed constructs. RESULTS: One hundred sixty-two ED staff members completed the course with >95% staff participation, generating a total of 106 paired surveys. Constructs for internal/biomedical factors, external/staff factors and situational/interactional perspectives on patient aggression significantly improved (p<0.0001, p<0.002, p<0.0001 respectively). Staff attitudes toward management of patient aggression did not significantly change (p=0.542). Multiple quality improvement initiatives were successfully implemented, including the creation of an interprofessional crisis management alert and response protocol. Staff members described appreciation for our simulation-based curriculum and welcomed the interaction with SPs during their training. CONCLUSION: A structured simulation-enhanced interprofessional intervention was successful in improving multiple facets of ED staff attitudes toward behavioral emergency care.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".