Metabolic Effects of Reduced Volume Sprint Interval Training During and Postexercise
Bibliographic record
Abstract
Abstract McCarthy, SF, McKie, GL, Howe, GJ, Vanderheyden, LW, and Hazell, TJ. Metabolic effects of reduced volume sprint interval training during and postexercise. J Strength Cond Res 38(5): 891–897, 2024—It is unclear what dose of sprint-interval training exercise (exercise volume) is required to derive beneficial metabolic effects during and postexercise. Therefore, we examined how reducing the volume of sprint interval training (SIT) from 2 minutes of “all-out” efforts (8 bouts) to 1.5 minutes (6 bouts) and 1 minute (4 bouts) affected during and postexercise metabolism. Fourteen recreationally active males (age: 25 ± 3 years; body mass index: 25.1 ± 3.1 kg·m −2 ) had gas exchange measured during and following (3 h) 4 experimental sessions: (a) no-exercise control (CTRL), (b) 8 × 15 SIT (2 minutes exercise), (c) 6 × 15 minutes SIT (1.5 minutes exercise), and (d) 4 × 15 SIT (1 minute exercise). All SIT protocols were 15 seconds “all-out” running efforts with 2 minutes recovery (4, 6, or 8 bouts). Changes were considered important if p < 0.100 and the effect size was ≥medium. During exercise, oxygen consumption (V̇ o 2 ; L) was different between protocols ( p < 0.001, d > 2.98) and greater than CTRL ( p < 0.001, d > 2.12); however, the rate of O 2 consumption (L·min −1 ) was similar between protocols ( p = 0.479, = 0.055). Total V̇ o 2 ( L ) postexercise was elevated following all conditions compared with CTRL ( p < 0.003, d > 1.25). Overall session V̇ o 2 was different in each condition ( p < 0.001, d > 1.89). Fat oxidation was elevated postexercise following all SIT protocols compared with CTRL ( p < 0.017, d > 0.98) with no differences between protocols ( p > 0.566, d < 0.48). Our results suggest reducing the number of all-out 15 seconds bouts during a SIT session from 8 to 6 or 4 had no differential effects on postexercise metabolism and differences during exercise were due to the longer duration of exercise.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".