Cognitive Fluctuations and Cognitive Test Performance Among Institutionalized Persons With Dementia
Bibliographic record
Abstract
OBJECTIVE: To examine the nature and frequency of cognitive fluctuations (CFs) among institutionalized persons with dementia. METHOD: A clinical interview and a medical chart review were conducted, and 55 patients were assigned a specific dementia diagnosis. The Severe Impairment Battery (SIB) was administered to assess cognitive function, and the Dementia Cognitive Fluctuation Scale (DCFS) was administered to each patient's primary nurse to determine the presence and severity of CFs. RESULTS: A simple linear regression model was conducted with DCFS as the predictor variable and SIB total score as the dependent variable. The overall model was significant, suggesting that score on the DCFS significantly predicted SIB total score. Additionally, greater severity of CFs predicted poorer performance in the areas of orientation, language, and praxis. CONCLUSIONS: Results suggest that CFs exert a clinically significant influence over patients' cognitive abilities and should be considered as a source of excess disability.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".