The effectiveness of aerobic exercise and dance interventions on cognitive function in adults with mild cognitive impairment: an overview of meta-analyses
Bibliographic record
Abstract
This review summarizes meta-analyses (MAs) of randomized controlled trials (RCTs) that assessed the effectiveness of aerobic exercise and dance interventions on cognitive functions in adults with mild cognitive impairment (MCI).Five databases, MEDLINE, EMBASE, PsycINFO, PubMed, and CENTRAL, were searched.MAs that exclusively pooled the effect sizes of aerobic exercise or dance on cognitive functions in adults aged 50 and above with MCI were included.We summarized 20 MAs, including 59 unique RCTs on aerobic exercise and 12 unique RCTs on dance.The meta-metaanalysis results demonstrated that both aerobic exercise (SMD = 0.28 [.13, .43])and dance (SMD = 0.39 [.28, .49])significantly improve overall cognition in adults with MCI.When considering specific cognitive domains, aerobic exercise significantly improves global cognition (SMD = 0.42 [.21, .64])but does not significantly impact executive function and memory.Dance significantly enhances global cognition (SMD = 0.4 [.01, .09]),executive function (SMD = 0.18 [.03, .32]),and memory (SMD = 0.46 [.32, .61]).The moderator analysis also supported dance's superior effect on memory.This finding suggests that the cognitively demanding nature of dance, which involves memorizing complex choreography and coordinating movements with accompanying music, provides additional benefits for memory.Overall, the current review supports that aerobic exercise and dance are effective non-pharmacological interventions to stabilize and even improve cognitive functions in adults with MCI.
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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 | 0.021 | 0.051 |
| Meta-epidemiology (narrow) | 0.004 | 0.002 |
| Meta-epidemiology (broad) | 0.023 | 0.041 |
| Bibliometrics | 0.008 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.002 | 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".