Finding the Optimal Resistance Training Intensity for Your Bones: Protocol for a Randomized Controlled Trial
Bibliographic record
Abstract
OBJECTIVE: The purpose of this trial is to evaluate the effect of twice-weekly, moderate-to-high intensity progressive resistance training (PRT) for 1 year on lumbar spine bone mineral density (BMD) in individuals with low BMD, compared to attention control. Secondary analyses will examine if resistance training improves other health outcomes; if high intensity is more effective than moderate intensity resistance training for all outcomes; the cost of intervention versus benefit; the willingness to pay; and harms. METHODS: For this study, 324 men or postmenopausal women aged ≥50 years with a femoral neck, total hip, or lumbar spine BMD T-score of ≤-1, or a Fracture Risk Assessment Tool probability of ≥20% for major osteoporotic fracture or ≥ 3% for hip fracture are being recruited to participate in a randomized controlled trial with 1:1:1 randomization. Participants will be stratified by site (3 centers) to twice-weekly, supervised PRT at moderate intensity (about 10 repetitions maximum), to high intensity PRT (≤6 repetitions maximum), or to a home posture and balance exercise program (attention control) for 1 year (resistance training to comparator allocation ratio of 2:1). The primary outcome is lumbar spine BMD via dual-energy X-ray absorptiometry. Secondary outcomes include trabecular bone score, proximal femur and total hip BMD and structure, bone-free and appendicular lean mass, physical functioning, falls, fractures, glucose metabolism, cost per life-year gained, adverse events, and quality of life. Between-group differences will be tested in intention-to-treat and per-protocol analyses using analysis of covariance, chi-square tests, or negative binomial or logistic regression, adjusting for site and baseline values. IMPACT: The Finding the Optimal Resistance Training Intensity For Your Bones trial will support decision making on resistance training for people at risk of fracture.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 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) | 0.000 | 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 teacher head, 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".