Cognitive rehabilitation in the elderly: Effects on memory
Bibliographic record
Abstract
This study reports the effects of a 12-week multimodular cognitive rehabilitation training program on memory performance in two groups of older adults. In the Memory Training module, participants were instructed on the nature of memory and how to improve memory performance; internal and external strategies were described and practiced over the training sessions. Memory performance was assessed by four tests: Alpha Span, Brown-Peterson, Hopkins Verbal Learning Test - Revised (HVLT-R), and Logical Stories. One group received training on entry into the study (Early Training Group, ETG), the other after a 3-month delay (Late Training Group, LTG). The results showed no training-related improvement in working memory (Alpha Span), primary memory (Brown-Peterson, HVLT-R), or recognition memory (HVLT-R). While the most direct analyses of a training effect (analyses of covariance) rarely demonstrated significant effects, exploratory analyses provided some evidence for a training benefit in several measures of secondary memory (Logical Stories; HVLT-R) and strategic processing (Brown-Peterson; Logical Stories; HVLT-R). Positive results were largely restricted to the ETG, possibly because the LTG lost motivation as a consequence of their delayed training. The results need to be treated with caution, but are promising for the rehabilitation of memory functioning in older adults.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 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".