Antipsychotic medications and disruptive behavior in long term care : a path analysis / by Annie Roy.
Bibliographic record
Abstract
"The purpose of this study was to examine the frequencies and structure of score on Minimum Data Set 2.0 (MDS 2.0) items relevant to disruptive behaviour and antipsychotic medications in Ontario LTC home residents. These items consisted of delirium, restraint use, activities of daily living (ADLs), depression, cognitive impairment and bladder incontinence. Lisrel Path analysis was used for the analysis. Significant positive effects were found between delirium and disruptive behaviour, cognitive impairment and delirium, disruptive behaviour and antipsychotic medication, depression and disruptive behaviour, depression and delirium, restraint use and delirium, cognitive impairment and antipsychotic medication, ADLs and antipsychotic medication, ADLs and restraint use, cognitive impairment and restraint use. Significant negative effects were found between antipsychotic medication and disruptive behaviour, ADLs and antipsychotic medication, and disruptive behaviour and delirium."--Abstract.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 0.001 |
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".