Long-term maintenance of multiple task inhibition practice and transfer effects in older adults: A 3.5-year follow-up.
Bibliographic record
Abstract
This study is a follow-up to our previous work (Wilkinson & Yang, 2016a), with an intention to examine the long-term maintenance of inhibition practice benefits and the associated near-near transfer effects over a 3.5-year period in older adults. Thirty-six participants from the original multiple task inhibition practice study (Wilkinson & Yang, 2016a), 18 from the practice and 18 from the control group, returned to complete a single follow-up session on the practice and the near-near transfer tasks. The results revealed that after a 3.5-year delay, older adults were able to retain practice benefits in both deletion (i.e., 2-Back) and restraint (i.e., Go-No Go) tasks. Furthermore, 44-65% of the original near-near transfer benefits were retained across all three inhibitory subfunctions at the follow-up session over baseline performance. The findings further extend the literature on the durability of practice and transfer effects of inhibition in older adults. Specifically, the current study demonstrates the long-term practice maintenance in some inhibitory subfunctions (e.g., deletion and restraint tasks) and highlights the retention of near-near transfer gains following a 3.5-year delay in older adults. (PsycInfo Database Record (c) 2020 APA, all rights reserved).
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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".