Modified sprint interval training protocols: physiological and psychological responses to 4 weeks of training
Bibliographic record
Abstract
Sprint interval training (SIT) protocols involving brief (≤15 s) work bouts improve aerobic and anaerobic performance, highlighting peak speed generation as a potentially important adaptive stimulus. To determine the physiological and psychological effects of reducing the SIT work bout duration, while maintaining total exercise and recovery time, 43 healthy males (n = 27) and females (n = 16) trained for 4 weeks (3 times/week) using one of the following running SIT protocols: (i) 30:240 (n = 11; 4-6 × 30-s bouts, 4 min rest); (ii) 15:120 (n = 11; 8-12 × 15-s bouts, 2 min rest); (iii) 5:40 (n = 12; 24-36 × 5-s bouts, 40 s rest); or (iv) served as a nonexercising control (n = 9). Protocols were matched for total work (2-3 min) and rest (16-24 min) durations, as well as the work-to-rest ratio (1:8 s). Pre- and post-training measures included a graded maximal oxygen consumption test, a 5-km time trial, and a 30-s maximal sprint test. Self-efficacy, enjoyment, and intentions were assessed following the last training session. Training improved maximal oxygen consumption (5.5%; P = 0.006) and time-trial performance (5.2%; P = 0.039), with a main effect of time for peak speed (1.7%; P = 0.042), time to peak speed (25%; P < 0.001), and body fat percentage (1.4%; P < 0.001) that appeared to be driven by the training. There were no group effects for self-efficacy (P = 0.926), enjoyment (P = 0.249), or intentions to perform SIT 3 (P = 0.533) or 5 (P = 0.951) times/week. This study effectively demonstrated that the repeated generation of peak speed during brief SIT work bouts sufficiently stimulates adaptive mechanisms promoting increases in aerobic and anaerobic capacity.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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".