title: The effect of low- vs high-cadence interval training on the freely chosen cadence and performance in endurance-trained cyclists.
abstract: The aim of this study was to determine the effects of high- and low-cadence interval training on the freely chosen cadence (FCC) and performance in endurance-trained cyclists. Sixteen male endurance-trained cyclists completed a series of submaximal rides at 60% maximal power (Wmax) at cadences of 50, 70, 90, and 110 r·min(-1), and their FCC to determine their preferred cadence, gross efficiency (GE), rating of perceived exertion, and crank torque profile. Performance was measured via a 15-min time trial, which was preloaded with a cycle at 60% Wmax. Following the testing, the participants were randomly assigned to a high-cadence (HC) (20% above FCC) or a low-cadence (LC) (20% below FCC) group for 18 interval-based training sessions over 6 weeks. The HC group increased their FCC from 92 to 101 r·min(-1) after the intervention (p = 0.01), whereas the LC group remained unchanged (93 r·min(-1)). GE increased from 22.7% to 23.6% in the HC group at 90 r·min(-1) (p = 0.05), from 20.0% to 20.9% at 110 r·min(-1) (p = 0.05), and from 22.8% to 23.2% at their FCC. Both groups significantly increased their total distance and average power output following training, with the LC group recording a superior performance measure. There were minimal changes to the crank torque profile in both groups following training. This study demonstrated that the FCC can be altered with HC interval training and that the determinants of the optimal cycling cadence are multifactorial and not completely understood. Furthermore, LC interval training may significantly improve time-trial results of short duration as a result of an increase in strength development or possible neuromuscular adaptations.
authors.affiliation: a School of Exercise and Health Science, Australian Catholic University, Locked Bag 4115, Fitzroy, VIC, Australia.|b Faculty of Health, University of Technology Sydney, Moore Park, Australia.
authors.forename: Anthony G
authors.initials: AG
authors.lastname: Whitty
authors.affiliation: b Faculty of Health, University of Technology Sydney, Moore Park, Australia.|c School of Science and Technology, University of New England, Armidale, Australia.
authors.forename: Aron J
authors.initials: AJ
authors.lastname: Murphy
authors.affiliation: b Faculty of Health, University of Technology Sydney, Moore Park, Australia.
authors.forename: Aaron J
authors.initials: AJ
authors.lastname: Coutts
authors.affiliation: b Faculty of Health, University of Technology Sydney, Moore Park, Australia.
authors.forename: Mark L
authors.initials: ML
authors.lastname: Watsford
mesh_terms: D000222:Adaptation, Physiological; D000328:Adult; D056352:Athletes; D001642:Bicycling; D015992:Body Mass Index; D016552:Ergometry; D006339:Heart Rate; D006801:Humans; D008297:Male; D010101:Oxygen Consumption; D064797:Physical Conditioning, Human / Q000379:methods*; D010807:Physical Endurance; D010809:Physical Fitness; D019415:Torque
keywords: central pattern generators; efficience métabolique; exigences musculaires; générateurs centraux de mouvement; metabolic efficiency; muscular demands