A Cross-Sectional Survey of Patients and Staff on Inpatient Forensic Psychiatric Units During COVID-19 Outbreak.
Bibliographic record
Abstract
Outbreaks of COVID-19 on inpatient forensic units present a unique challenge as early release is not possible and some facilities were not designed to achieve sustained social distancing [1]. The enforcement of droplet and contact (D&C) precautions required during an outbreak creates further confines and restrictions for patients that are typically subject to considerable constraint during their care. From December 2020 to January 2021 43 clinicians and 12 patients on inpatient forensic units under unit-wide D&C precautions during COVID-19 outbreaks completed a cross-sectional survey regarding their experience. Virtual focus groups were also conducted to triangulate the qualitative feedback from clinicians. The survey and focus groups found the themes of enablers, barriers, and desired changes to care provision during an outbreak. Findings are discussed within the broader context of outbreak interventions and the provision of services to those living and working on forensic inpatient units experiencing outbreaks requiring the unit-wide implementation of D&C precautions.
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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 | 0.000 | 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".