The Effect of Training Intensity on VO2max in Young Healthy Adults: A Meta-Regression and Meta-Analysis
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Bibliographic record
Abstract
International Journal of Exercise Science 9(2): 230-247, 2016. Exercise training at a variety of intensities increases maximal oxygen uptake (VO2max), the strongest predictor of cardiovascular and all-cause mortality. The purpose of the present study was to perform a systematic review, meta-regression and meta-analysis of available literature to determine if a dose-response relationship exists between exercise intensity and training-induced increases in VO2max in young healthy adults. Twenty-eight studies involving human participants (Mean age: 23±1 yr; Mean VO2max: 3.4±0.8 l·min−1) were included in the meta-regression with exercise training intensity, session dose, baseline VO2max, and total training volume used as covariates. These studies were also divided into 3 tertiles based on intensity (tertile 1: ~60-70%; 2: ~80-92.5%; 3: ~100-250%VO2max), for comparison using separate meta-analyses. The fixed and random effects meta-regression models examining training intensity, session dose, baseline VO2max and total training volume was non-significant (Q4=1.36; p=0.85; R2=0.05). There was no significant difference between tertiles in mean change in VO2max (tertile 1:+0.29±0.15 l/min, ES (effect size) =0.77; 2:+0.26±0.10 l/min, ES=0.68; 3:+0.35±0.17 l/min, ES=0.80), despite significant (p<0.05) reductions in session dose and total training volume as training intensity increased. These data suggest that exercise training intensity has no effect on the magnitude of training-induced increases in maximal oxygen uptake in young healthy human participants, but similar adaptations can be achieved in low training doses at higher exercise intensities than higher training doses of lower intensity (endurance training).
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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 | 0.005 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.006 | 0.005 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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 it