Fall Prevention for Older Women Using Online Dance Classes with Blood Flow Restriction
Bibliographic record
Abstract
This project examined if online dance classes could provide a safe and accessible method for older women to improve their physical activity levels and reduce their risk of falls. Women aged 65 years and above were recruited to complete 12 weeks of twice-weekly 75-minute interventions, and were evaluated pre, mid and post via 30-second trials of quiet standing, the star excursion balance test (SEBT), 30-second Sit-to-Stand (30-CST) and the Calf Raise Senior (CRS). Significance was evaluated using non-parametric statistics (p≤.05). Participants demonstrated high attendance rates (80.4 ± 13.8%), decreased mediolateral sway during eyes closed (pre-mid p=.003) and foam conditions (pre-mid p=.02), with smaller sway area for foam conditions (pre-mid p=.015), larger reaches on the SEBT (lateral: pre-mid p=.008, pre-post p=.008; posterior-lateral: pre-post p=.009) and higher number or CRS repetitions (mid-post p=.02, pre-post p=.015). A follow-up study was conducted to try and overcome intensity limitations encountered with the online environment by using blood flow restriction (BFR). Participants completed 12-weeks of online dance classes with half the group randomized to wear BFR cuffs. No improvements were found among the control group. Participants in the BFR group demonstrated increases in strength on the 30-CST (pre-mid p=.042; pre-post p=.039) and greater reaches on the SEBT in medial (mid-post p=.043) and posterior-medial directions (pre-post p=.043). Online dance classes are an effective, safe and accessible fall prevention program and the addition of low-cost BFR cuffs further enhances strength and dynamic balance, thereby increasing independence and quality of life through older age.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".