Is Dementia Special Care Really Special? A New Look at an Old Question
Bibliographic record
Abstract
OBJECTIVES: To quantify differences in care provided to nursing home (NH) residents with dementia living on and off dementia special care units (SCUs). DESIGN: Cross-sectional study using propensity score adjustment for resident and NH characteristics. SETTING: Free-standing NHs in nonrural U.S. counties that had an SCU in 2004 (N=1,896). PARTICIPANTS: Long-stay (> or = 90 days) NH residents with a diagnosis of Alzheimer's disease or dementia and at least moderate cognitive impairment (N=69,131). MEASUREMENTS: Resident-level NH care processes such as physical restraints, bed rails, feeding tubes, psychotropic medications, and incontinence care. RESULTS: There was no difference in the use of physical restraints (adjusted odds ratio (AOR)=0.94, 95% confidence interval (CI)=0.79-1.11), but SCU residents were less likely to have had bed rails (AOR=0.55, 95% CI=0.46-0.64) and to have been tube fed (AOR=0.36, 95% CI=0.30-0.43). SCU residents were more likely to be on toileting plans (AOR=1.23, 95% CI=1.08-1.39) and less likely to use pads or briefs in the absence of a toileting plan (AOR=0.73, 95% CI=0.61-0.88). SCU residents were more likely to have received psychotropic medications (AOR=1.23, 95% CI=1.05-1.44), primarily antipsychotics (SCU=44.9% vs non-SCU=30.0%). CONCLUSION: SCU residents received different care than comparable non-SCU residents. Most strikingly, SCU residents had greater use of antipsychotic medications.
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 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 | 0.018 | 0.083 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.011 |
| Scholarly communication | 0.006 | 0.019 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.009 | 0.010 |
| Insufficient payload (model declined to judge) | 0.005 | 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".