Effects of Mindfulness Training on Depression and Cognition in Older People With Mild Cognitive Impairment: A Systematic Review and Meta‐Analysis
Bibliographic record
Abstract
BACKGROUND: This systematic review and meta-analysis aimed to evaluate the efficacy of mindfulness-based treatments for older people with mild cognitive impairment (MCI) who also experience depression and cognitive difficulties. METHODS: Seven databases were searched: PubMed, EBSCOhost, CINAHL Complete, Cochrane Library, ProQuest, Scopus, and Web of Science, up to July 2025. PRISMA guidelines, the Oxford Centre for Evidence-Based Medicine scale, the RoB 2 tool, and GRADEpro were employed to evaluate the methodological quality and evidence reliability. The review plan was pre-registered in the PROSPERO database (CRD420251080874). RESULTS: Initially, 1738 records were identified in the databases. Thirteen studies that met the inclusion criteria were included in the analysis. The PICOS framework was employed for the subsequent analysis. The meta-analysis indicated that participants receiving mindfulness therapies experienced a significant reduction in depression symptoms, as assessed by the Geriatric Depression Scale (GDS, p = 0.045). In contrast, the Montreal Cognitive Assessment (p = 0.061) and the Mini-Mental State Examination (p = 0.713) did not demonstrate statistically significant changes in cognitive ability. CONCLUSIONS: The findings suggest that mindfulness-based training may reduce depressive symptoms in older individuals with MCI; however, the impact on cognitive abilities remains inconclusive.
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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 | 0.012 | 0.028 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.014 | 0.023 |
| Bibliometrics | 0.007 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 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".