A Longitudinal Evaluation of Restraint Reduction within a Multi-site, Multi-model Canadian Continuing Care Organization
Bibliographic record
Abstract
While American literature on sustaining restraint reduction is relatively robust, there is a lack of research published on the same issue in Canadian continuing care (CC) settings. Statistics from Canada's largest publicly funded and operated CC organization have revealed telling patterns in mechanical restraint use. Over a 4-year study period during a campaign to reduce mechanical restraint use, the organizational prevalence dropped from 24.68 per cent to 16.01 per cent. There was substantial variability in restraint prevalence among the organization's 11 centres (range: 0-39.86% of residents restrained) and all but 1 was able to achieve mechanical restraint reduction. Specific facilitators to achieving and sustaining restraint reduction are identified, including small facility size, provision of specialized care (e.g., Alzheimer's disease), and an on-site champion . Specific barriers, such as large facility size and an off-site champion are also discussed.
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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 | 0.009 | 0.017 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 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".