Effects of Aerobic Dance on Cognition in Older Adults with Mild Cognitive Impairment: A Systematic Review and Meta-Analysis
Bibliographic record
Abstract
BACKGROUND: Regular aerobic exercises could improve global cognition in older adults with mild cognitive impairment (MCI), such as aerobic dance a type of commonly practiced aerobic exercises. However, its effects remain debatable in improving the cognitive function in patients with MCI. OBJECTIVE: The aim of this systematic review and meta-analysis is to evaluate the effects of aerobic dance on cognitive function among older adults with MCI. METHODS: We searched articles in the MEDLINE, PubMed, Embase, and The Cochrane Library databases from inception to 28 February 2019, with the following criteria: 1) randomized controlled trials; 2) older adults with MCI; 3) aerobic dance intervention. RESULTS: Five studies of 842 participants were identified. This meta-analysis showed that aerobic dance can significantly improve global cognition (Mini-Mental State Examination: MD = 1.43; 95% CI:[0.59, 2.27]; p = 0.0009; Alzheimer's Disease Assessment Scale-Cognitive Subscale: MD=-2.30; 95% CI:[-3.60, -1.00]; p = 0.0005), and delayed recall ability (SMD = 0.46;95% CI: [0.30, 0.62]; p < 0.00001) in older adults with MCI. In addition, have positive effects on improving executive function (Trial-Making Test A: MD = -2.37;95% CI:[-4.16, -0.58]; p = 0.010; Trial-Making Test B: MD = -16.0; 95% CI: [-30.03, -2.11]; p = 0.020) and immediate recall ability (SMD = 0.24;95% CI: [0.01, 0.46]; p = 0.04). CONCLUSION: Aerobic dance significantly improves global cognitive function and memory in older adults with MCI. In addition, it also benefits executive function. However, due to the limitations as the review states, more randomized controlled trials with better study design and larger sample sizes should be conducted in the future research to make it much clearer.
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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 | 0.006 | 0.018 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.016 | 0.028 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".