Neuropsychological mediators of the links among age, chronic illness, and everyday problem solving.
Bibliographic record
Abstract
Reductions in everyday problem solving (EPS) are often reported in older age, although the underlying mechanisms remain unclear. The authors examined the role of 2 variables predicted to mediate (neuropsychological abilities and health status) or moderate (health status) the relationship between age and EPS performance. Toward these ends, they compared EPS and neuropsychological performance in 50 functionally independent adults with chronic kidney disease (CKD) and 64 control participants matched on age and education. Both older age and CKD were associated with worse performance on measures of EPS and memory/executive abilities. Neuropsychological abilities were positively associated with EPS performance. In both the full sample and control participants only, memory/executive functioning mediated the association between presence of chronic illness and EPS. Furthermore, memory/executive functioning partially mediated the link between age and EPS. Findings indicate that relations among age, health status, and EPS are not straightforward. Although performance on neuropsychological measures appeared to underlie EPS declines in chronic illness, increasing age remained independently associated with reduced EPS. The authors discuss implications for models of adult developmental changes in everyday cognition.
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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 | 0.007 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".