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Updated: Sep 9, 2025

A Real-World High-Intensity Interval Training Protocol for Cardiorespiratory Fitness Improvement
Published on: February 22, 2022
Six Weeks of Low-Volume Sprint Interval Training Improves Peak Oxygen Uptake Compared to a Non-Exercise Control: A
John R M Renwick1, Jeff Crukley2, Masa Kudsi1
1Department of Kinesiology, McMaster University, Hamilton, Ontario, Canada.
None:
Low-volume sprint interval training (LVSIT) increases peak oxygen uptake (VO2peak) when performed three times a week for 6 weeks. Methodological and statistical concerns, however, constrain the veracity of prior findings. We therefore reassessed the VO2peak response to LVSIT using a randomized controlled trial design to mitigate bias and augment reporting quality. A generative model of VO2peak was constructed as a function of group, baseline VO2peak, age, sex, height, and change in body mass. Simulation experiments using previous data estimated that n = 15/group would achieve 80% power to detect a difference of 1 metabolic equivalent (MET) with a credible interval (CrI) of ≤ 1-MET. Insufficiently active young adults (22 ± 3 years, body mass index: 24 ± 4 kg m-2, baseline VO2peak: 33 ± 7 mL kg-1 min-1) were randomized to perform 6 weeks of thrice weekly LVSIT (n = 17) or no exercise (CTL; n = 20). The LVSIT protocol involved 3 × 20-s "all out" sprints over a 10-min session of low-intensity cycling. Bayesian generative multivariate modeling revealed that LVSIT increased absolute [+325 mL min-1 (101-605)] and relative VO2peak [+5.6 mL kg-1 min-1 (2.2-8.1)] versus CTL. All but one LVSIT participant (94%) were deemed a responder (i.e., mean estimate ± 95% CrI for relative VO2peak > 0). In contrast, four CTL participants (20%) met this criterion. LVSIT also improved time to exhaustion by +133 s (101-160) versus CTL. We unequivocally demonstrate that 6 weeks of thrice weekly LVSIT increased VO2peak in insufficiently active young adults compared to no exercise. By incorporating a robust design that included preregistration, concealed allocation assignment, statistical best practices, and applied Bayesian methods, and open data-sharing, this study addresses prior methodological critiques of similar previous work.
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