Five‐year effects of cognitive training in individuals with mild cognitive impairment
Bibliographic record
Abstract
INTRODUCTION: In a 5-year follow-up study, we investigated the enduring effects of cognitive training on older adults with mild cognitive impairment (MCI). METHODS: A randomized controlled single-blind trial involved 145 older adults with MCI, assigned to cognitive training (MEMO+), an active control psychosocial intervention, or a no-contact condition. Five-year effects were measured on immediate and delayed memory recall, the Montreal Cognitive Assessment screening test (MoCA), self-reported strategy use, and daily living difficulties. RESULTS: At follow-up, participants who received cognitive training showed a smaller decline in delayed memory and maintained MoCA scores, contrasting with greater declines in the control groups. Cognitive training participants outperformed controls in both delayed memory and MoCA scores at the 5-year time point. No significant group differences were observed in self-reported strategy use or difficulties in daily living. DISCUSSION: Cognitive training provides long-term benefits by mitigating memory decline and slowing clinical symptom progression in older adults with MCI. Highlights: Cognitive training reduced the 5-year memory decline of persons with MCI.Cognitive training also reduced decline on the Montreal Cognitive Assessment (MoCA).No intervention effect was found on strategy use or activities of daily living.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| 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 | 0.001 | 0.001 |
| 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".