Should I rest or should I go now? A comparison between fixed and self-selected rest durations in high-intensity interval training cycling sessions
DOI:
https://doi.org/10.51224/SRXIV.248Keywords:
self selected rest, HIIT, sEMG, cyclists, RPEAbstract
Background: In high-intensity interval training (HIIT), the rest durations between intervals are commonly prescribed using a fixed approach (e.g., 30 seconds between intervals). An alternative is the self-selected (SS) approach, in which trainees select their resting durations. Studies comparing the two approaches report mixed results. However, in these studies, trainees in the SS condition rested for as little or as long as they wished, leading to dissimilar total rest durations between conditions. Here, for the first time, we compare the two approaches while controlling for total rest duration.
Methods: Twenty-four amateur adult male cyclists completed a familiarization session, followed by two counterbalanced cycling HIIT sessions. Each session was composed of nine, 30-second intervals, in which the goal was to accumulate as many watts as possible on an SRM ergometer. In the fixed condition, cyclists rested for 90 seconds between intervals. In the SS condition, cyclists had 720 seconds (i.e., 8x90 seconds) of rest to allocate in any way they wished. We measured and compared watts, heart rate, electromyography of the knee flexors and extensors, rating of perceived effort and fatigue, perception of autonomy and enjoyment. Additionally, a subsample of ten cyclists completed a retest of the SS condition.
Results: With the exception of perception of autonomy, which was higher in the SS condition, both aggregated and across-interval outcomes were highly similar in both conditions. For example, the average aggregated differences were: 0.57 (95% CI -8.94, 10.09) for watts; -0.85 (95% CI -2.89, 1.18) for heart rate; and 0.01 (95% CI -0.29, 0.30) for rating of perceived effort (on a 0-10 scale). Additionally, the retest of the SS condition resulted in a similar rest allocation pattern across the intervals and in similar outcomes.
Conclusion: Given the similarities between the fixed and SS conditions, both can be equally utilized based on coaches’ and cyclists’ preferences and training goals.
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References
Buchheit M, Laursen PB. High-intensity interval training, solutions to the programming puzzle: part II: Anaerobic energy, neuromuscular load and practical applications. Sports Med. 2013;43(10):927–54.
Laursen P, Buchheit M, editors. Science and application of high-intensity interval training. Champaign, IL, USA: Human Kinetics; 2019.
Billat LV. Interval training for performance: a scientific and empirical practice. Sports Med. 2001;31(1):13–31.
Laursen. Training for intense exercise performance: high-intensity or high-volume training?: High-intensity and high-volume training. Scand J Med Sci Sports. 2010 Sep 14;20:1–10.
Buchheit M, Laursen PB. High-intensity interval training, solutions to the programming puzzle: part I: cardiopulmonary emphasis. Sports Med. 2013;43(5):313–38.
Midgley AW, McNaughton LR. Time at or near VO2max during continuous and intermittent running - A review with special reference to considerations for the optimisation of training protocols to elicit the longest time at or near VO2max. J Sports Med Phys Fitness. 2006;46(1):1–14.
Parmar A, Jones TW, Hayes P R. The dose-response relationship between interval-training and VO2max in well-trained endurance runners: A systematic review. J Sports Sci. 2021;39(12):1410–27.
Wen D, Utesch T, Wu J, Robertson S, Liu J, Hu G, et al. Effects of different protocols of high intensity interval training for VO2max improvements in adults: A meta-analysis of randomized controlled trials. J Sci Med Sport. 2019;22(8):941–7.
Schoenmakers PPJM, Hettinga FJ, Reed KE. The moderating role of recovery durations in high-intensity interval-training protocols. Int J Sports Physiol Perform. 2019;14(6):859–67.
Leotti LA, Iyengar SS, Ochsner KN. Born to choose: The origins and value of the need for control. Trends Cogn Sci. 2010;14(10):457–63.
Patall EA, Cooper H, Robinson JC. The effects of choice on intrinsic motivation and related outcomes: A meta-analysis of research findings. Psychol Bull. 2008;134(2):270–300.
Fidalgo A, Joi S, Lattari E, de Oliveira B, Pilon R, Farinatti P, et al. Influence of HIIRT with fixed and self-selected recovery intervals on physiological, affective, and enjoyment responses. Res Q Exerc Sport. 2022;
Halperin I, Chapman DW, Martin DT, Lewthwaite R, Wulf G. Choices enhance punching performance of competitive kickboxers. Psychol Res. 2017;81(5):1051–8.
Dello Iacono A, Beato M, Halperin I. Self-selecting the number of repetitions in potentiation protocols: enhancement effects on jumping performance. Int J Sports Physiol Perform. 2021;16(3):353–9.
Emanuel A, Har-Nir I, Rozen Smukas II, Halperin I. The effect of self-selecting the number of repetitions on motor performance and psychological outcomes. Psychol Res. 2021 Sep;85(6):2398–407.
Watson K, Halperin I, Aguilera-Castells J, Dello Iacono A. A comparison between predetermined and self-selected approaches in resistance training: Effects on power performance and psychological outcomes among elite youth athletes. PeerJ. 2020;8:e10361.
Wingfield G, Marino F, Skein M. The influence of knowledge of performance endpoint on pacing strategies, perception of effort, and neural activity during 30-km cycling time trials. Physiol Rep. 2018;6(21):1–13.
Wulf G, Adams N. Small choices can enhance balance learning. Hum Mov Sci. 2014;38:235–40.
Seiler S, Hetlelid KJ. The impact of rest duration on work intensity and RPE during interval training. Med Sci Sports Exerc. 2005;37(9):1601–7.
Gibson N, Brownstein C, Ball D, Twist C. Physiological, perceptual and performance responses associated with self-selected versus standardized recovery periods during a repeated sprint protocol in elite youth football players: A preliminary study. Pediatr Exerc Sci. 2017;29(2):186–93.
McEwan G, Arthur R, Phillips SM, Gibson NV, Easton C. Interval running with self-selected recovery: physiology, performance, and perception. Eur J Sport Sci. 2018;18(8):1058–67.
Brownstein CG, Ball D, Micklewright D, Gibson NV. The effect of maturation on performance during repeated sprints with self-selected versus standardized recovery intervals in youth footballers. Pediatr Exerc Sci. 2018;30(4).
Engel FA, Altmann S, Chtourou H, Woll A, Neumann R, Yona T, et al. Repeated sprint protocols with standardized versus self-selected recovery periods in elite youth soccer players: can they pace themselves? A replication study. Pediatr Exerc Sci. 2022;34(4).
Rodríguez-Barbero S, Rodrigo-Carranza V, Santos-García DJ, Ravé JMG, González-Mohíno F. Acute effects of long interval training with varied recovery periods in trained runners. In Review; 2022.
Schoenmakers PPJM, Reed KE. The effects of recovery duration on physiological and perceptual responses of trained runners during four self-paced HIIT sessions. J Sci Med Sport. 2019;22(4):462–6.
Mujika I, Padilla S. Physiological and performance characteristics of male professional road cyclists. Sports Med. 2001;31(7):479–87.
Hebisz P, Hebisz R, Zatoń M, Ochmann B, Mielnik N. Concomitant application of sprint and high-intensity interval training on maximal oxygen uptake and work output in well-trained cyclists. Eur J Appl Physiol. 2016 Aug 1;116(8):1495–502.
Laursen PB, Shing CM, Peake JM, Coombes JS, Jenkins DG. Interval training program optimization in highly trained endurance cyclists. Med Sci Sports Exerc. 2002;34(11):1801–7.
Halperin I, Emanuel A. Rating of Perceived Effort: Methodological Concerns and Future Directions. Sports Med. 2020 Apr;50(4):679–87.
Micklewright D, St Clair Gibson A, Gladwell V, Al Salman A. Development and validity of the rating-of-fatigue scale. Sports Med. 2017;47(11):2375–93.
Ostrow KS, Heffernan NT. Testing the validity and reliability of intrinsic motivation inventory subscales within ASSISTments. In: Penstein Rosé C, Martínez-Maldonado R, Hoppe HU, Luckin R, Mavrikis M, Porayska-Pomsta K, et al., editors. Artificial Intelligence in Education. Cham: Springer International Publishing; 2018. p. 381–94.
Kooiman DBJ, Li DW, Michael D, Kim DH. Validation of the relatedness scale of the intrinsic motivation inventory through factor analysis. Int J Multidiscip Res Mod Educ. 2016;1(2):302–11.
Wood SN. Generalized additive models - An introduction with R. 2nd ed. New York: Chapman and Hall/CRC; 2017.
Hernán MA, Robins JM. Causal Inference: What If. 1st ed. Boca Raton: Chapman & Hall/CRC; 2020.
Patterson JT, Carter M. Learner regulated knowledge of results during the acquisition of multiple timing goals. Hum Mov Sci. 2010;29(2):214–27.
Aiken CA, Fairbrother JT, Post PG. The effects of self-controlled video feedback on the learning of the basketball set shot. Front Psychol. 2012;3(338):1–18.
Glaister M, Witmer C, Clarke DW, Guers JJ, Heller JL, Moir GL. Familiarization, reliability and evaluation of a multiple sprint running test using self-selected recovery periods. J Strength Cond Res. 2010;24(12):3296–301.
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Copyright (c) 2023 Eyal Colorni, Evyatar Ohayon, Julie N Côté, Uri Obolski, Israel Halperin
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