Dual-Task Performance in Early Stage Dementia: Differential Effects for Automatized and Effortful Processing
Bibliographic record
Abstract
Attentional functions of individuals with early stage Alzheimer's disease (AD) and normal older adults (NC) were studied using a concurrent-task paradigm. Fourteen patients (5 men, 9 women) and 14 age- and sex-matched normal adults engaged in speeded unimanual tapping and speaking tasks during single- and dual-task trials. Speaking tasks were either relatively automatized (Speech Repetition) or relatively effortful (Speech Fluency). As single-task tapping rates were slower for the AD participants than for the NC participants, a proportional decrement score was used as an index of interference in the dual-task conditions. Interference during concurrent-task performance was greater when the cognitive task was effortful for both the NC and the AD groups. Although AD patients suffered higher levels of interference than NC participants while performing the effortful speech task, the two groups showed equivalent small changes in tapping speed while combining the automatized speaking and tapping tasks. Results suggest that a general-purpose attentional processing resource declines in the early stages of AD but dual-task performance is well-maintained when the component tasks are relatively automatized.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 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".