Limited Benefits of Heterogeneous Dual-Task Training on Transfer Effects in Older Adults
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVES: It has often been reported that cognitive training has limited transfer effects. The present study addresses training context variability as a factor that could increase transfer effects, as well as the manifestation through time of transfer effects. METHOD: Fifty-eight older adults were assigned to an active placebo or two dual-task training conditions, one in which the training context varies between sessions (heterogeneous training) and the other in a fixed training context (homogeneous training). Transfer was assessed with near and far-modality transfer tasks. RESULTS: Results show that heterogeneous and homogeneous training led to larger near-modality transfer effects than an active placebo (computer lessons). Transfer effects were roughly comparable in both training groups, but heterogeneous training led to a steeper improvement of the dual-task coordination learning curve within training sessions. Also, results indicated that dual-task cost did not improve in the active placebo group from the pre- to the post-training sessions. DISCUSSION: Heterogeneous training showed modest advantages over homogeneous training. Results also suggest that transfer effects on dual-task cost induced by training take place early on in the post-training session. These findings provide valuable insights on benefits arising from variability in the training protocol for maximizing transfer effects.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| 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) | 0.000 | 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 it