Antipsychotic drug use in Canadian long-term care facilities: prevalence, and patterns following resident relocation
Bibliographic record
Abstract
BACKGROUND AND AIMS: Data on antipsychotic use were collected in two Canadian long-term care (LTC) facilities. During the one-year study, residents in one facility were relocated to a new facility, allowing examination of the changes in antipsychotic use associated with relocation. METHOD: A comparative descriptive design was used. Pharmacy and chart data on antipsychotic use were gathered for three separate one-month periods during one year. Data were collected both in a facility experiencing relocation of all residents to a new facility, and in a facility not undergoing relocation. The three one-month data collection periods covered a one-month period before the relocation, immediately after the relocation, and six months after the relocation. RESULTS: In the facility not experiencing relocation, an average of 31.3% of all residents were receiving antipsychotics. Residents in this facility received antipsychotics for an average length of 0.81 years, and 20.8% of all antipsychotic prescriptions reflected dose reductions within six months of the start of the prescription. Only 8.1% of prescriptions had accompanying documentation on the behavioral indication for the use of antipsychotics. A total of 73.4% of all antipsychotics were 'atypical' antipsychotics, and 13.5% of all antipsychotic prescriptions were written as 'p.r.n.' (as needed). While the use of antipsychotics remained relatively constant in the non-relocation facility (between 30.3% and 33.1% of all residents), the percentage of residents receiving antipsychotics in the facility experiencing a relocation climbed significantly; from 21.5% six months before the move, to 32.6% immediately after the move, to 36.9% six months after the move. CONCLUSION: These findings, when compared with the U.S. standards on antipsychotic use (OBRA), suggest the need for additional research on antipsychotic use in Canadian LTC facilities.
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 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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".