Bibliographic record
Abstract
This thesis contains two studies which examined the cognitive functioning of the aging brain. Specifically, age-related changes in processing speed and its remediation via cognitive training were studied. In study 1, younger adults (n = 34) and older adults (n = 39) were recruited to investigate the age-related differences in the relationships between processing speed and general cognitive status (GCS). Their performance in GCS (as measured by The Montreal Cognitive Assessment, Hong Kong Version), cognitive processing speed (as measured by Processing Speed Index, Wechsler Adult Intelligence Scale), cognitive inhibition (as measured by Stroop Color-Word Test), and divided attention (as measured by Color Trails Test) was examined. Current findings indicated that processing speed predicted GCS in older but not younger adults. In older adults, processing speed as a predictor accounted for an additional 13% of variance in GCS. This study further verified the relationship between processing speed and prefrontal abilities, including verbal fluency, cognitive inhibition and divided attention in aging. Findings revealed that despite the abovementioned prefrontal abilities were significantly correlated with processing speed, verbal fluency had remained the strongest predictor, accounting for 21% of variance in processing speed in older adults. Based on findings in study 1, it was anticipated that training cognitive skills including processing speed and prefrontal abilities in older adults would improve cognitive functioning in general. Therefore, in study 2, elderly people at risk of progressive cognitive decline (n = 70) were recruited to investigate the training effect of computerized cognitive training programs that aimed to improve cognitive processing speed, cognitive inhibition and divided attention. Findings indicated that cognitive processing speed and divided attention improved post-training. Results obtained from the two studies implied potential intervention through training cognitive processing speed in elderly people at risk of progressive cognitive decline. Future studies should focus on training specific effect and examining the optimal effect by modification of the training paradigms, particularly the design of the contents and level of difficulty.
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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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.003 | 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".