Build Better Bones With Exercise: Protocol for a Feasibility Study of a Multicenter Randomized Controlled Trial of 12 Months of Home Exercise in Women With a Vertebral Fracture
Bibliographic record
Abstract
BACKGROUND: Our goal is to conduct a multicenter randomized controlled trial (RCT) to investigate whether exercise can reduce incident fractures compared with no intervention among women aged ≥65 years with a vertebral fracture. OBJECTIVES: This pilot study will determine the feasibility of recruitment, retention, and adherence for the proposed trial. DESIGN: The proposed RCT will be a pilot feasibility study with 1:1 randomization to exercise or attentional control groups. SETTING: Five Canadian sites (1 community hospital partnered with an academic center and 4 academic hospitals or centers affiliated with an academic center) and 2 Australian centers (1 academic hospital and 1 center for community primary care, geriatric, and rehabilitation services). PARTICIPANTS: One hundred sixty women aged ≥65 years with vertebral fracture at 5 Canadian and 2 Australian centers will be recruited. INTERVENTION: The Build Better Bones With Exercise (B3E) intervention includes exercise and behavioral counseling, delivered by a physical therapist in 6 home visits over 8 months, and monthly calls; participants are to exercise ≥3 times weekly. Controls will receive equal attention. MEASUREMENTS: Primary outcomes will include recruitment, retention, and adherence. Adherence to exercise will be assessed via calendar diary. Secondary outcomes will include physical function (lower extremity strength, mobility, and balance), posture, and falls. Additional secondary outcomes will include quality of life, pain, fall self-efficacy, behavior change variables, intervention cost, fractures, and adverse events. Analyses of feasibility objectives will be descriptive or based on estimates with 95% confidence intervals, where feasibility will be assessed relative to a priori criteria. Differences in secondary outcomes will be evaluated in intention-to-treat analyses via independent Student t tests, chi-square tests, or logistic regression. The Bonferroni method will be used to adjust the level of significance for secondary outcomes so the overall alpha level is .05. LIMITATIONS: No assessment of bone mineral density will be conducted. The proposed definitive trial will require a large sample size. CONCLUSIONS: The viability of a large-scale exercise trial in women with vertebral fractures will be evaluated, as well as the effects of a home exercise program on important secondary outcomes.
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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 | 0.068 | 0.055 |
| Meta-epidemiology (narrow) | 0.007 | 0.004 |
| Meta-epidemiology (broad) | 0.012 | 0.006 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.006 | 0.005 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.005 | 0.004 |
| Research integrity | 0.009 | 0.012 |
| Insufficient payload (model declined to judge) | 0.064 | 0.013 |
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".