Mechanisms of processing speed training and transfer effects across the adult lifespan: protocol of a multi-site cognitive training study
Bibliographic record
Abstract
BACKGROUND: In recent years, cognitive training has gained popularity as a cost-effective and accessible intervention aiming at compensating for or even counteracting age-related cognitive declines during adulthood. Whereas the evidence for the effectiveness of cognitive training in general is inconsistent, processing speed training has been a notable successful exception, showing promising generalized benefits in untrained tasks and everyday cognitive functioning. The goal of this study is to investigate why and when processing speed training can lead to transfer across the adult lifespan. Specifically, we will test (1) whether training-induced changes in the rate of evidence accumulation underpin transfer to cognitive performance in untrained contexts, and (2) whether these transfer effects increase with stronger attentional control demands of the training tasks. METHODS: We will employ a multi-site, longitudinal, double-blinded and actively controlled study design with a target sample size of N = 400 adult participants between 18 and 85 years old. Participants will be randomly assigned to one of three processing speed training interventions with varying attentional control demands (choice reaction time, switching, or dual tasks) which will be compared to an active control group training simple reaction time tasks with minimal attentional control demands. All groups will complete 10 home-based training sessions comprising three tasks. Training gains, near transfer to the untrained tasks of the other groups, and far transfer to working memory, inhibitory control, reasoning, and everyday cognitive functioning will be assessed in the laboratory directly before, immediately after, and three months after training (i.e., pretest, posttest, and follow-up, respectively). We will estimate the rate of evidence accumulation (drift rate) with diffusion modeling and conduct latent-change score modeling for hypothesis testing. DISCUSSION: This study will contribute to identifying the cognitive processes that change when training speeded tasks with varying attentional control demands across the adult lifespan. A better understanding of how processing speed training affects specific cognitive mechanisms will enable researchers to maximize the effectiveness of cognitive training in producing broad transfer to psychologically meaningful everyday life outcomes. Trial registration Open Science Framework Registries, registration https://doi.org/10.17605/OSF.IO/J5G7E ; date of registration: 9 May 2022.
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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 | 0.009 | 0.006 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.003 |
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".