COLD WATER IMMERSION FOLLOWING INTENSE INTERVAL RUNNING IMPROVES SUBSEQUENT RUNNING PERFORMANCE
Bibliographic record
Abstract
Immersing in cold water (i.e. cold tub) following strenuous exercise is a technique used by many athletes because it is believed to promote recovery and improve subsequent training and performance. Despite extensive research on the use of cryotherapy to reduce inflammation and promote recovery from soft-tissue injury, its validation in the athletic model to improve performance is largely unproven. PURPOSE The purpose of this study was to determine if cold-water immersion (submerse up to the waist for 10 min in 8°C water: TUB) following intense interval running can maintain orimprove performance compared to what can be achieved without TUB. METHODS 16 recreationally active individuals (9M, 7F) completed two sessions consisting of performance assessment (vertical jump, VJ; treadmill run, 6 min level and then 6% grade to fatigue, FT) followed by an intense 6 km interval run (IR) that included 72 flights of stairs (avg. time to complete 43.5 min). 10min following IR, subjects were randomly assigned to TUB or to a control period (CON: 10 min light stretching) (Day 1). Two days following the original assessment day, subjects completed both the performance tests (VJ, FT) and IR again (Day 3). RESULTS Performance time on the treadmill (FT) was reduced in CON (9.04 ± 0.5 min vs 8.19 ± 0.8 min) and increased in TUB (11.99 ± 6.77 min vs 12.82 ± 6.84 min) from Day 1 to Day 3 (interaction: P < 0.001). There was no change in vertical jump in either group. Submax and maximal heart rates, ratings of perceived exertion and soreness were not different between groups for either the FT or IR. There was a trend for lower lactate in during FT and IR on Day 3 in the TUB group. CONCLUSION The use of cold tub following intense exercise may reduce the effects of fatigue and improve subsequent performance in submaximal, but not maximal exercise, by mechanisms yet unknown. Supported by Natural Sciences Engineering Research Council of Canada and the Nova Scotia Health Research Foundation.
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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 | 0.000 |
| 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".