Promoting Safety: Behavioural Emergency Response during the COVID-19 Pandemic
Bibliographic record
Abstract
During the ongoing COVID-19 pandemic, patients with and without pre-existing mental health diagnoses will either be admitted to the hospital as patients under investigation for COVID-19 or patients positive for COVID-19. A safe and timely response is required for patients exhibiting escalating behaviours (e.g., responsive, agitated and/or aggressive behaviours) to prevent harm to the patient, nearby patients and staff. In this paper, we report on a new protocol that has been implemented throughout our institution to address Code White calls for escalating behaviours during the COVID-19 pandemic. This procedure uses a least restraint-based philosophy for the management of an escalating situation, involves the use of an interprofessional team of healthcare providers (including mental health clinicians) and security team members and accounts for the need for personal protective equipment. We believe that other hospitals could benefit from knowing about this approach as a strategy to improve patient care and diminish disease transmission.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 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) | 0.002 | 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 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".