Efficacy of a cognitive training programme for mild cognitive impairment: Results of a randomised controlled study
Bibliographic record
Abstract
This study aimed to determine the efficacy of cognitive training in a 10-week randomised controlled study involving 22 individuals presenting with mild cognitive impairment of the amnestic type (MCI-A). Participants in the experimental group (n = 11) learned face-name associations using a paradigm combining errorless (EL) learning and spaced retrieval (SR) whereas participants in the control group (n = 11) were trained using an errorful (EF) learning paradigm. Psycho-educational sessions on memory were also provided to all participants. After neuropsychological screening and baseline evaluations, the cognitive training took place in 6 sessions over a 3-week period. The post-training and follow-up evaluations, at one and four weeks respectively, were performed by research assistants blind to the participant's study group. The results showed that regardless of the training condition, all participants improved their capacity to learn face-name associations. A significant amelioration was also observed in participant satisfaction regarding their memory functioning and in the frequency with which the participants used strategies to support memory functions in daily life. The absence of difference between groups on all variables might be partly explained by the high variability of scores within the experimental group. Other studies are needed in order to verify the efficacy of EL learning and SR over EF in MCI-A.
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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 | 0.008 | 0.011 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.003 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".