Systematic Review and Meta-Analysis of the Effects of Dance on Cognition and Depression in Healthy Older Adults
Bibliographic record
Abstract
PURPOSE: Aging is associated with declines in cognition and mental health that might be ameliorated by physical activity (PA). Dance integrates multiple physical, cognitive, and social elements, and might be an avenue for improving cognition and mood. This systematic review and meta-analysis examined the effects of formal and traditional dance on cognition, depression, and anxiety in older adults. METHODS: Five database searches yielded 17 randomized control trials (RCTs). RCTs were included if participants were ≥60 yr and healthy or living with mild cognitive impairment. We examined interventions of dance against any comparison group. Records were independently screened, and data were extracted by two reviewers. We performed random-effects models using robust variance estimation and tested individual treatment, study, and outcome-level moderators using the approximate Hotelling-Zhang test. RESULTS: Seventeen RCTs were included in the systematic review, but 13 RCTs were included in the meta-analysis, which included 1174 participants with a mean age of 70.7 yr, and 66.3% were female. There were 76 effect sizes (Hedges g) calculated from the 13 RCTs with a range between -0.97 and 2.88. The overall effect of dance interventions on cognition was significant, yet small (g = 0.27; 95% confidence interval, 0.05-0.50; P = 0.022), and the effect on depression was significant and nearly moderate (g = 0.43; 95% confidence interval, 0.06-0.80; P = 0.036); only one RCT examined anxiety and was not included. No moderator variables significantly explained variation in the effects of dance on cognitive function or depression (P > 0.05). CONCLUSIONS: Dance interventions can improve cognition and depression in older adults. Additional research is needed regarding the effects of dance on anxiety and depression in older adults.
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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 | 0.048 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.022 | 0.030 |
| Bibliometrics | 0.008 | 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) | 0.004 | 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".