Recreational Ballet Practice Is Associated with Improved Fall Risk Factors in Older Adults
Bibliographic record
Abstract
Introduction: Falls are a serious health concern with severe consequences in older adults. Various physical and cognitive functions are related to falls in older adults. Although studies have indicated that well-controlled ballet-based interventions could lead to physical and cognitive improvements in older adults, it remains unknown if and how recreational ballet practice in an unstandardized environment could also reap health benefits. This cross-sectional study examined the fall risk among recreational older ballet dancers relative to their non-dancer counterparts. Methods: Forty-three older adults aged 55 and older were recruited: 20 ballet dancers and 23 age- and sex-matched non-dancers. Fall risk was assessed through fall history (over the previous 12 months), physical function (Five-Time Sit-to-Stand test, Timed-Up-and-Go test, leg muscle strength, and physical activity level), and cognition (Montreal Cognitive Assessment). Results: The retrospective falls were similar between groups ( P = 0.704). However, dancers were faster than non-dancers to perform the Five-Time Sit-to-Stand ( P < 0.001) and Timed-Up-and-Go ( P = 0.003) tests. They also exhibited stronger knee extensors ( P = 0.010) and ankle plantarflexors ( P = 0.031) than non-dancers. Dancers were more physically active ( P < 0.001). No group difference was detected for cognition score ( P = 0.205). Conclusions: The results suggest that older adults who practice ballet recreationally show better dynamic balance with stronger and more powerful leg muscles compared to non-dancers. Dancers were also more physically active than non-dancers. The findings augment our understanding of ballet’s effects on improving physical functions in different environments and could help apply ballet as an intervention to prevent falls 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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".