Importance Of Sprint Interval Training Duration And Recovery Time On Endurance And Power Performance
Bibliographic record
Abstract
Sprint interval training has become popular due to its positive effects on endurance performance. This training, characterized by repeated intense efforts (typically 30 sec maximal efforts with short recovery intervals), surprisingly induces similar muscle adaptations to traditional endurance training. PURPOSE: To determine whether shorter training bout durations and variable recovery times affect endurance and power performance. METHODS: Recreationally active subjects (n = 36, 13 females 23 males) did not train 1) control (CTRL) or completed repeated maximal cycle bouts (resistance = 10% body mass):recovery intervals as follows: 2) 30 sec:4 min, 3) 10 sec:4 min, or 4) 10 sec:2 min. Subjects trained 3/wk for 2 wk (6 total sessions), starting with 4 bouts/session and increasing to 5 on bout 3 and 6 on bout 5. Pre- and post tests included 5 km cycle time trial, cycle VO2 peak, and 30 sec Wingate. RESULTS: As expected, the ability to maintain peak power over the training bouts was greater (P<0.05) for the 10 sec:4 min (95.7±2.6%) and the 10:2 min (94.6±3.0%) vs the 30 sec:4 min group (87.4±6.1%). Similarly, training bout minimum power was greater (P<0.05) in the 10 sec:4 min (69.4±6.7%) and the 10 sec:2min (68.8±4.5%) vs the 30 sec:4 min group (38±8.0%). Endurance Performance: All training groups improved time trial performance from pre- to post (30 sec:4 min, -31.4±22.3 sec [5.5±3.4%]; 10 sec:4 min, -22.4±31.1 sec [3.9±5.2%]; 10 sec: 2min, -26.0±25.0 sec [5.0±3.7%]). VO2peak also increased (P<0.05) in the 30 sec:4 min group (2.9±3.5 ml·kg-1·min-1, 6.3±8.9%) and the 10 sec:4 min (2.9±3.9 ml·kg-1·min-1, 6.5±8.6%), but not in the 10 sec:2 min group (1.8±2.4 ml·kg-1·min-1, 3.4±5.3%). Power Performance: Wingate peak power increased in the 30 sec:4 min (+84.0±87.4 W, 7.8±8.5%) and the 10 sec: 4 min groups (+76.7±87.5 W, 5.6±7.5%) but not in the 10 sec:2 min group (+21.5±82.5 W, 1.8±7.3%). Average Wingate power improved in the 30 sec:4 min (+87.0±49.6 W, 12.2±7.4%) and the 10 sec:4 min groups (+53.4±72.6 W, 6.4±9.2%) but not the 10 sec:2 min group (+14.5±28.3 W, 1.9±3.7%). CONCLUSION: Repeat 10 and 30 sec sprint interval training bouts with 2 or 4 min recovery produce significant and similar improvements for 5 km time trial performance; but for VO2peak and power performance, 10 and 30 sec training bouts with 4 min recovery appear to be better.
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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 | 0.001 |
| 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 | 0.000 |
| 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".