Investigating How A Community Peer-exercise Program Aiming To Reduce Risk Of Falls Challenges Balance
Bibliographic record
Abstract
INTRODUCTION: Older adults who engage in balance-challenging exercise programs for three hours per week are 51% less likely to fall. However, only 6% of Canadian fall prevention programs adhere to these guidelines, and accurately measuring balance-focused exercise remains a persistent challenge. OBJECTIVE: This study aimed to examine the perceived balance challenge from participants involved in Zoomers in Balance, a community peer-led fall prevention exercise program and explore if some participants’ characteristics are associated with balance intensity. METHODS: A total of 919 returning participants were sent a survey based on the Monash University Balance Intensity Scale during the 2024 winter session. The survey included questions regarding perceived balance intensity: what level of effort is needed to maintain balance during most exercises? 1-No effort at all; 2- A little effort; 3-Some effort; 4-A lot of effort; 5-Maximal effort, attendance, years of participation, the mode of delivery (e.g., in-person, online, or both called hybrid), and demographic characteristics. RESULTS: A total of 398 participants answered the survey with an average age of 69 years, 88.6% were female, 23.5% participated in person, 12.5% participated online, and 64% used both (hybrid). Participants averaged a 3.2 ± 0.7 on the intensity score with no difference among groups (p = 0.32). Age (r = 0.13; p = 0.01), but not years of participation nor sex or attendance, was associated with balance intensity. CONCLUSION: Based on this study, the average Zoomers in Balance participants report some effort (3/5) to maintain balance during the exercise programs, with increased effort with age. More studies are needed to know how much effort is needed to have a meaningful impact on the risk of falls. Canadian Institutes of Health Research
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".