Training and support for nursing home staff reduced neuroleptic drug use and did not increase aggression in residents with dementia
Bibliographic record
Abstract
Fossey J, Ballard C, Juszczak E, et al. Effect of enhanced psychosocial care on antipsychotic use in nursing home residents with severe dementia: cluster randomised trial. BMJ 2006;332:756–61.[OpenUrl][1][Abstract/FREE Full Text][2] Q Does a training and support intervention for nursing home staff reduce use of neuroleptic drugs in elderly residents with dementia? ### ![Graphic][3]</img>Design: cluster randomised controlled trial. ### ![Graphic][4]</img>Allocation: concealed. ### ![Graphic][5]</img>Blinding: blinded (outcome assessor). ### ![Graphic][6]</img>Follow up period: 12 months. ### ![Graphic][7]</img>Setting: 12 nursing homes registered to accept people with dementia in London, Newcastle, and Oxford, UK. ### ![Graphic][8]</img>Patients: 349 residents (median age 82 y, 63% men) of nursing homes that had ⩾25% of residents with dementia who were taking neuroleptic drugs. ### ![Graphic][9]</img>Intervention: drug prescriptions of residents were reviewed at baseline. The consulting psychiatrist wrote to prescribing physicians at each home, recommending cessation of psychotropic drugs prescribed for >3 … [1]: {openurl}?query=rft.jtitle%253DBMJ%26rft_id%253Dinfo%253Adoi%252F10.1136%252Fbmj.38782.575868.7C%26rft_id%253Dinfo%253Apmid%252F16543297%26rft.genre%253Darticle%26rft_val_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Ajournal%26ctx_ver%253DZ39.88-2004%26url_ver%253DZ39.88-2004%26url_ctx_fmt%253Dinfo%253Aofi%252Ffmt%253Akev%253Amtx%253Actx [2]: /lookup/ijlink?linkType=ABST&journalCode=bmj&resid=332/7544/756&atom=%2Febnurs%2F9%2F4%2F122.atom [3]: /embed/inline-graphic-1.gif [4]: /embed/inline-graphic-2.gif [5]: /embed/inline-graphic-3.gif [6]: /embed/inline-graphic-4.gif [7]: /embed/inline-graphic-5.gif [8]: /embed/inline-graphic-6.gif [9]: /embed/inline-graphic-7.gif
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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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".