Prescription Practices, Anti-Psychotics, and COVID-19: An Intersectional Examination of the Long-Term Care Home Setting in Canada
Bibliographic record
Abstract
Public discourse and concern over the state of long-term care homes in Canada has been ongoing over the last two decades. One of the main sources of these concerns is the off-label prescription of anti-psychotic medications to long-term care home residents. Off-label use of pharmaceuticals is common and can be beneficial in certain contexts, however, there is a risk of anti-psychotics being used as an inappropriate means of managing patients chemically in the long-term care home setting. This paper engages in three lines of inquiry: first, the regulatory landscape of on and off-label prescription in Canada; second, the off-label use of anti- psychotics in long-term care, and specifically, why they are used, why they should not be used, and the impact COVID-19 had in increasing their use; and third, the legal implications of these practices and potential alternatives avenues. This paper ultimately highlights the dangers of off-label prescription in the long-term care setting and advocates for cultural and institutional changes to protect elderly Canadians in these facilities.
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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 | 0.003 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.011 |
| Science and technology studies | 0.027 | 0.009 |
| Scholarly communication | 0.008 | 0.002 |
| Open science | 0.002 | 0.007 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".