Relationship between elevated impulsivity and cognitive declines in elderly community-dwelling individuals
Bibliographic record
Abstract
Impulse control disorders are recognized as one of the behavioral and psychological symptoms of dementia (BPSD). Majority of studies on the treatment of BPSD related to impulsivity have rather focused on the aggression and agitation. In particular, it has not been investigated how cognitive declines are associated with impulsivity in community-dwelling elderly people. Here, we have measured the cognitive and memory functions and impulsivity of 212 elderly community-dwelling people using a psychometric test battery and analyzed the correlation between their level of impulsivity and cognitive functions by multiple regression analysis. We found an elevation of impulsivity, which was evaluated by the Barratt Impulsiveness Scale-11, closely related to decline of cognitive functions, which were evaluated by the Montreal Cognitive Assessment and the Mini-Mental State Examination, and Logical Memory function, which were evaluated by the Wechsler Memory Scale-Delayed Recall. Then we have divided them into groups based on the severity of cognitive decline and conducted an analysis of each group, the result of which showed that as this tendency was particularly noticeable in the suspected dementia group. Therefore, we have concluded that heightened impulsivity is negatively associated with cognitive and memory functions in community-dwelling elderly people.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 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".