Assessment of Behavioural and Psychological Symptoms Associated with Dementia
Bibliographic record
Abstract
Neuropsychiatric symptoms (mood, psychotic, and behavioural) are very common in dementia and do not necessarily correlate well with other measures of cognition. However, these symptoms are of great importance, as they are a major source of excess disability, patient distress and caregiver burden and have great impact on the level of care required, and the associated costs. This paper is a review of the most useful outcome measures for behaviour and mood symptoms. Investigators who require a comprehensive instrument to measure neuropsychiatric symptoms in studies of patients with dementia should consider using the Neuropsychiatric Inventory (NPI), the Behavior Rating Scale for Dementia of the Consortium to Establish a Registry for Alzheimer's Disease (CERAD-BRSD) or, possibly, the Behavioral Pathology in Alzheimer's Disease Scale (BEHAVE-AD). The Cornell Scale for Depression in Dementia and the Dementia Mood Assessment Scale (DMAS) are recommended for evaluating depressive symptoms and the Cohen-Mansfield Agitation Inventory (CMAI) is very useful for evaluating the full range of agitation symptoms.
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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) | 0.004 | 0.001 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".