A meta‐analysis of the consequences of cognitive training on the cognitive function of aged mild cognitive impairment patients
Bibliographic record
Abstract
Cognitive training has gained popularity as a means to aid older adults with mild cognitive impairment (MCI), a transitional phase between normal ageing and Alzheimer's disease (AD). MCI represents a critical and potentially reversible state that can either improve or progress to full-blown dementia. This study aims to evaluate the impact of cognitive training on cognitive function in aged patients with MCI. PubMed, Embase, Medline, Web of Science, China National Knowledge Infrastructure (CNKI), and Wanfang databases were systematically retrieved from inception until May 2024. We rigorously applied the risk-of-bias methodology recommended by the Cochrane Handbook to assess the quality of the included studies. After two rounds of screening and removing duplicates, a total of 2685 articles were initially identified, from which 28 met the inclusion criteria. The meta-analysis included 28 randomised controlled trials with 1960 participants. In this meta-analysis, Review Manager 5.4 was used for statistical analysis. Findings revealed that cognitive training significantly improved the global cognitive function in aged MCI patients, as evidenced by the results of the Montreal Cognitive Assessment (standard mean difference (SMD) = 3.26; 95% CI, 2.69-3.82; P < 0.00001) and Mini-Mental State Examination (SMD = 2.27; 95% CI, 1.52-3.01; P < 0.00001). The beneficial effects of cognitive training interventions were consistent regardless of duration, including periods of 2 months or less (SMD = 1.94; 95% CI, 1.25-2.63; P < 0.00001), 2 to 6 months (SMD = 2.53; 95% CI, 1.52-3.53; P < 0.00001), and over 6 months (SMD = 4.12; 95% CI, 0.97-7.27; P = 0.01). The analysis indicates that cognitive training significantly benefits overall cognitive function, delayed memory, orientation, attention, and language skills in aged patients with MCI. Furthermore, cognitive training interventions are effective in enhancing cognitive function, irrespective of their duration.
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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 | 0.013 | 0.026 |
| Meta-epidemiology (narrow) | 0.003 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.051 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".