Age and Verbal Fluency: The Mediating Effect of Speed of Processing
Bibliographic record
Abstract
BACKGROUND AND PURPOSE: Cognitive decline is a function of normal aging; however, the effect of age on various domains is differential. This study examined the effect of age on verbal fluency and showed how speed of processing modifies fluency performance in healthy older adults compared to younger individuals. METHODS: Three age groups, 62 young (17-40 years), 30 middle-aged (41-59 years), and 38 older adults (60-78 years), were studied using the Controlled Oral Word Association Test, National Adult Reading Test, and speed-of-processing composite score. The study examined the effect of age on fluency before and after controlling for processing speed and intelligence quotient. RESULTS: The young group performed better than the older group on category fluency as measured by animal category (p < .001) and on processing speed composite score (p < .001). However, the older group performed better than the young group on the National Adult Reading Test (p < .05) and on letter fluency after controlling for the decline in processing speed (p < .05). Processing speed had a significant effect on both category and letter fluency (p < .01) in older adults. CONCLUSIONS: This study suggests that aging adversely affects some but not all cognitive domains and that age-related decline in processing speed contributes to age-related changes in fluency.
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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 | 0.002 |
| 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 | 0.000 | 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".