Cognitive Impairments Predict the Behavioral and Psychological Symptoms of Dementia
Bibliographic record
Abstract
Abstract Background: To evaluate the association between behavioral and psychological symptoms of dementia (BPSD), as assessed via the Neuropsychiatric Inventory Questionnaire (NPI-Q), and cognitive impairments in individuals with dementia and amnestic mild cognitive impairment (aMCI). Methods: 120 participants, comprising of 80 aMCI and 40 Alzheimer’s disease (AD) subjects, were included in the study. aMCI was diagnosed using Petersen’s criteria, whilst AD was diagnosed using the National Institute of Neurological and Communicative Disorders and Stroke/AD criteria. Results: Pure exploratory bifactor analysis revealed that a general factor and a single-group factor (with high loadings on delusions, hallucinations, apathy, and appetite) underpinned the NPI-Q domains. Significant negative correlations between the Montreal Cognitive Assessment (MoCA) total score and the general and single-group NPI-Q scores were found in all subjects (aMCI + AD combined) and AD, but not in aMCI. Cluster analysis allocated subjects with BPSD (10% of aMCI and 50% of AD participants) into a distinct ‘AD + BPSD’ class. Conclusion: The NPI-Q total score, which is an appropriate index of BPSD, is largely predicted by cognitive deficits. It is plausible that aMCI subjects with severe NPI-Q symptoms (10% of our sample) may have a poorer prognosis and constitute a subgroup of aMCI patients who will likely convert into AD.
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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 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".