The effects of high velocity resistance training on bone mineral density in older adults: A systematic review
Bibliographic record
Abstract
OBJECTIVE: To determine the effects of high velocity resistance training (HVRT) on bone mineral density (BMD) in older adults. METHODS: A systematic review was conducted using five databases. Records were screened by two independent reviewers. INCLUSION CRITERIA: adults ≥50 years old, HVRT defined as rapid concentric and slow eccentric phase against an external load, control group and/or other intervention group, BMD measured using dual X-ray absorptiometry, and ≥6 months. RESULTS: 25 studies met the inclusion criteria. 12 were original intervention studies (8 RCTs) with n = 1203 people. 13 papers were follow up studies of these original interventions. Heterogeneity of studies meant no meta-analysis was performed. Moderate evidence suggests a small statistically significant effect of HVRT on BMD in older adults at the lumbar spine, total hip, and femoral neck ranging from 0.9 % to 5.4 %. BMD measurements significantly decreased post-intervention in follow-up studies where the interventions had ceased. Dose-response of HVRT was shown to positively impact BMD when ≥2 sessions per week are completed. CONCLUSIONS: HVRT plays a role in increasing BMD of the lumbar spine, femoral neck, and total hip. Doses of higher intensity exercise performed ≥2 sessions per week will yield the most skeletal benefits, and if exercise is stopped for >6 months, benefits achieved may be lost.
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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 | 0.004 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.008 | 0.007 |
| Bibliometrics | 0.005 | 0.005 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".