Patterns and Behavioural Outcomes of Antipsychotic Use among Nursing Home Residents: a Canadian and Swiss Comparison
Bibliographic record
Abstract
Background. Although antipsychotic medications are primarily intended to treat schizophrenia and psychotic symptoms in adults, they are commonly administered to nursing home residents as pharmacotherapy for "off-label" indications such as disruptive behaviour. However, clinical trials have demonstrated limited efficacy and serious side-effects of antipsychotics among the elderly. As previous studies have reported inappropriate use in several countries, their use in nursing home residents ought to be monitored to detect and reduce inappropriate administration. Objectives. The aim of this study was a) to determine and compare prevalence rates of antipsychotic use in Ontario and Swiss nursing homes, b) to identify determinants of antipsychotics use in these two countries, by means of a cross-sectional design, and c) to investigate the impact of antipsychotic use on behaviours over time in Ontario and Swiss residents, by means of a longitudinal design. Methods. This study involved secondary data analysis of 1932 residents from 24 nursing homes in the province of Ontario in Canada and 1536 residents from 4 nursing homes in a German-speaking canton in Switzerland. Residents were assessed with the Minimum Data Set (MDS) tool. Resident characteristics and prevalence rates were compared internationally with the chi-square test. Demographic and clinical determinants of antipsychotic use, as well as behavioural change associated with antipsychotics, were analyzed using logistic regression. Results. Although Ontario nursing home residents had an overall heavier-care profile than Swiss residents, antipsychotics were administered to 25% of the Ontario residents compared to 29. 5% of the Swiss residents. The adjusted rate among residents without appropriate conditions was also lower in Ontario (14%) than in Switzerland (24. 5%). Apart from schizophrenia, bipolar disorder and cognitive impairment, antipsychotic use was determined by a different range of characteristics in these two countries. Antipsychotic use was not predictive of behavioural improvement. Conclusion. The high adjusted rates of antipsychotic use in Ontario and Swiss nursing home residents, as well as the presence of "inappropriate indications" and "facility" as determinants of their use, raise concerns about the appropriateness of their administration in both countries. Their lack of effectiveness to improve behaviours also questions their use as long-term treatment for behaviour disturbances. Changes in practice patterns and implementation of policies are warranted to reduce inappropriate prescribing practices to enhance the quality of care provided to residents in nursing homes.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".