Effects of exercise training on the cognitive function of older adults with different types of dementia: a systematic review and meta-analysis
Bibliographic record
Abstract
Objectives To assess the effect of exercise training on the cognitive function of older adults living with different types of dementia, as well as potential moderators of exercise efficacy. Design Systematic review and meta-analysis. Data sources Cochrane Central, PsycINFO, Embase, Medline and CINAHL. Eligibility criteria Peer-reviewed, randomised controlled trials, in English (1990–present), which examined the effects of exercise training on the cognitive function of older adults living with dementia. Study appraisal and synthesis Risk of bias and study quality were assessed (Cochrane Risk of Bias Tool 2.0 and Physiotherapy Evidence Database Scale). We performed random-effects models using robust variance estimation and tested moderators using the approximate Hotelling-Zhang test. Results Twenty-eight studies (n=2158) were included in the qualitative review and 25 in the meta-analysis. For all-cause dementia, a small effect of exercise training on cognitive function was observed ( g =0.19; 95% CI 0.05 to 0.33; p=0.009). Type of dementia and exercise training characteristics did not moderate the effects of exercise training on cognitive function (p>0.05). Adherence to the intervention moderated the cognitive outcome effect size such that greater mean adherence was associated with greater cognitive outcome effect sizes ( b =0.02; SE =0.01; p=0.005). Conclusion Exercise training showed small benefits for the cognitive function of older adults living with all-cause dementia. More research and standardised reporting of exercise training characteristics can strengthen the evidence for what works best for which types of dementia. PROSPERO registration number CRD42020198716.
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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 | 0.015 | 0.037 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.033 |
| Bibliometrics | 0.009 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.002 | 0.002 |
| 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".