Cognitive and social intervention with Go and chess in early and subjective cognitive decline: The COGniChESs study results, with an updated meta-analysis
Bibliographic record
Abstract
Background There is a growing interest in dementia prevention and scalable cognitive enhancement strategies for individuals at-risk, with or without Alzheimer's disease. Board games have shown potential cognitive and mood benefits, but randomized controlled evidence remains limited and heterogeneous. Objective We aimed at assessing whether chess and/or Go could improve cognition, mood, and quality of life in individuals with mild cognitive impairment (MCI) and subjective cognitive decline (SCD). Methods Individuals with MCI or SCD aged ≥55 years were randomized to one of three arms: chess, Go (each consisting of 12 weekly group sessions), or a waitlist control group. Montreal Cognitive Assessment, digit span, trail making test, categorical fluency, Geriatric Depression Scale, and the World Health Organization Quality of Life scale were administered at baseline and follow-up. We also updated our previously published meta-analysis including these new results. Results 69 subjects completed the study. Categorical fluency improved significantly in the games groups (p < 0.05). No between-group differences were found in overall cognition. A significant group × diagnosis × time interaction showed improved quality of life in MCI participants in the games groups (p = 0.002). A group × gender × time interaction revealed reduced depression in females in the games groups (p = 0.013). The updated meta-analysis confirmed a significant effect on depression (standardized mean differences −0.48, p = 0.013), but not on cognition. Conclusions The improvements in mood and quality of life, particularly among females and MCI subjects, underscore the psychological value of board games interventions, possibly through their social component. These activities may foster emotional well-being in older adults at risk for Alzheimer's disease, even without cognitive benefits. Clinicaltrials.gov Identifier: NCT06281652
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.010 | 0.025 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".