Associations Between Psychotic Symptoms and Dependence in Activities of Daily Living Among Older Adults With Alzheimer’s Disease
Bibliographic record
Abstract
BACKGROUND: Alzheimer's disease (AD) is associated with dependence in activities of daily living (ADL). In addition to the cognitive impairment resulting from AD, the presence of psychotic symptoms may further increase this dependence. The objective of this study was to quantify the additional contribution of psychotic symptoms to dependence in ADL. METHOD: We analyzed data from 558 individuals with AD referred to a memory clinic. Information on ADL, psychotic symptoms, depression symptoms, and cognition was collected with standardized instruments. RESULTS: The frequency of psychotic symptoms was correlated with dependence in ADL (r = -.44, p < .001). The independent contribution of psychotic symptoms to ADL (basic and instrumental) after consideration for cognitive impairment and depression symptoms was assessed with hierarchical regression models. Twenty-five percent of basic ADL variance was explained by cognition; psychotic symptoms accounted for an additional 7% of the variance (b = -0.12, p < .001). Cognitive impairment explained 31% of instrumental ADL variance; psychotic symptoms accounted for an additional 6% (b = -0.21, p < .001). DISCUSSION: Psychotic symptoms are associated with dependence in ADL after controlling for cognitive impairment and depression symptoms. Future research should investigate possible causal linkages between psychotic symptoms and dependence in ADL. This may have implications regarding interventions to maintain independent living in people with 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 | 0.003 |
| 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) | 0.001 | 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".