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Concurrent Training for Sports Performance: The 2 Sides of the Medal

Nicolas Berryman, Iñigo Mujika, and Laurent Bosquet

The classical work by Robert C. Hickson showed in 1980 that the addition of a resistance-training protocol to a predominantly aerobic program could lead to impaired leg-strength adaptations in comparison with a resistance-only training regimen. This interference phenomenon was later highlighted in many reports, including a meta-analysis. However, it seems that the interference effect has not been consistently reported, probably because of the complex interactions between training variables and methodological issues. On the other side of the medal, Dr Hickson et al subsequently (1986) reported that a strength-training mesocycle could be beneficial for endurance performance in running and cycling. In recent meta-analyses and review articles, it was demonstrated that such a training strategy could improve middle- and long-distance performance in many disciplines (running, cycling, cross-country skiing, and swimming). Notably, it appears that improvements in the energy cost of locomotion could be associated with these performance enhancements. Despite these benefits, it was also reported that strength training could represent a detrimental stimulus for endurance performance if an inappropriate training plan has been prepared. Taken together, these observations suggest that coaches and athletes should be careful when concurrent training seems imperative to meet the complex physiological requirements of their sport. This brief review presents a practical appraisal of concurrent training for sports performance. In addition, recommendations are provided so that practitioners can adapt their interventions based on the training objectives.

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Accuracy of Heart-Rate-Recovery Parameters Assessed From a Wrist-Worn Photoplethysmography Monitor (Polar Unite)

Quentin Bretonneau, Etienne Peruque-Gayou, Etienne Wolfs, and Laurent Bosquet

Purpose: The accuracy of heart rate (HR) measured with a wrist-worn photoplethysmography (PPG) monitor is altered during rest–exercise and exercise–rest transitions, which questions the validity of postexercise HR-recovery (HRR) parameters estimated from this device. Methods: Thirty participants (50% female) randomly performed two 13-minute sequences (3′ rest, 5′ submaximal-intensity exercise, and 5′ passive recovery) on treadmill and bicycle ergometers. HR was measured concomitantly with a 10-lead electrocardiogram (ECG) and a wrist-worn PPG monitor (Polar Unite). HRR was assessed by calculating Δ60 (the difference between HR during exercise and HR 60 s after exercise cessation) and by fitting HRR data into a monoexponential model. Results: By focusing on Δ60 and τ (the time constant of the monoexponential curve), levels of association (r) of the Unite versus the 10-lead ECG were high to very high (.73 < r < .93), and coefficients of variation were >20% (in absolute value), except for Δ60 in the bicycle ergometer condition (11.7%). In 97% of cases, the decrease in HR after exercise appeared later with the Unite. By adjusting the time window used for the analysis according to this time lag, coefficients of variation of Δ60 decreased below 10% in the bicycle ergometer condition. Conclusions: If a wrist-worn PPG monitor is used to assess HRR, we recommend performing the submaximal-intensity exercise on a bicycle ergometer and focusing on Δ60. Furthermore, to obtain a more accurate Δ60, the time lag between the end of the exercise and the effective decrease in HR should also be considered before the calculation.

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Effect of Performance Level on the Prediction of Middle-Distance-Running Performances Using a Nomogram

Montassar Tabben, Laurent Bosquet, and Jeremy B. Coquart

Purpose:

This study examined the effect of performance level on the validity and accuracy of middle-distance running-performance predictions obtained from the nomogram of Mercier et al in male runners.

Methods:

Official French track-running rankings for the 3000-, 5000-, and 10,000-m events from 2006 to 2014 were examined. The performance level was determined from the official reference table of the Fédération Française d’Athlétisme, and the runners were divided in 3 groups (ie, low, moderate, and high levels). Only male runners who performed in the 3 distance events within the same year were included (N = 443). Each performance over any distance was predicted using the nomogram from the 2 other performances.

Results:

No difference was found in low- and moderate-performance-level athletes (0.02 ≤ effect size [ES] ≤ 0.06, 95% limits of agreement [LoA] ≤ 6%). By contrast, a small difference in high-performance-level athletes (P < .01, 0.23 ≤ ES ≤ 0.45, 95% LoA ≤ 11.6%) was found.

Conclusion:

The study confirms the validity of the nomogram to predict track-running performance with a high level of accuracy, except for male runners with high performance level (ie, national or international). Consequently, the predictions from the nomogram may be used in training programs (eg, to prescribe tempo runs with realistic training velocities) and competitions (eg, to plan realistic split times to reach the best performance).

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Tapering and Repeated High-Intensity Effort Ability in Young Elite Rugby Union Players: Influence of Pretaper Fatigue Level

Adrien Vachon, Nicolas Berryman, Iñigo Mujika, Jean-Baptiste Paquet, and Laurent Bosquet

Purpose: To assess the effects of a short-term taper on the ability to perform repeated high-intensity efforts, depending on players’ fatigue level following an intensive training block. Method: After a 3-day off-season camp, 13 players followed the same 3-week preseason training block followed by a 7-day exponential taper. Performance was assessed by a repeated high-intensity effort test before and after the taper. Total sprint time, percentage of decrement, and the number of sprints equal to or higher than 90% of the best sprint were retained for analysis. Players were a posteriori classified in normal training or acute fatigue groups based on their readiness to perform prior to the taper, assessed through the magnitude of difference in psychological (Profile of Mood State Questionnaire), cardiovascular (submaximal constant-duration cycling), and neuromuscular (countermovement jump) tests between the preintensive and postintensive training blocks. Results: Training load declined by 55% (9%) during the taper (P = .001, g = −2.54). The overall group showed a small improvement in total sprint time (−3.40% [3.90%], P = .04, g = −0.39) following the taper. Relative changes tended to be higher in the acute fatigue compared with the normal training group (−5.07% [4.52%] vs −1.45% [1.88%], respectively; P = .08; d = 1.01). No taper-induced improvement was observed in percentage of decrement or number of sprints equal to or higher than 90% of the best sprint. Conclusion: A 7-day taper consisting of 55% training load reduction improved repeated high-intensity effort performance in young elite rugby union players. Pretaper level of fatigue seems to be a key determinant in the taper supercompensation process, as acutely fatigued players at the end of the intensive training block tended to benefit more from the taper.

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Fitness Determinants of Repeated High-Intensity Effort Ability in Elite Rugby Union Players

Adrien Vachon, Nicolas Berryman, Iñigo Mujika, Jean-Baptiste Paquet, and Laurent Bosquet

Purpose: To investigate the relationship between physical fitness and repeated high-intensity effort (RHIE) ability in elite rugby union players, depending on playing position. Method: Thirty-nine players underwent a fitness testing battery composed of a body composition assessment, upper-body strength (1-repetition maximum bench press and 1-repetition maximum bench row), lower-body strength (6-repetition maximum back squat), and power (countermovement jump, countermovement jump with arms, and 20-m sprint), as well as aerobic fitness (Bronco test) and RHIE tests over a 1-week period. Pearson linear correlations were used to quantify relationships between fitness tests and the RHIE performance outcomes (total sprint time [TST] and percentage decrement [%D]). Thereafter, a stepwise multiple regression model was used to verify the influence of physical fitness measures on RHIE ability. Results: TST was strongly to very strongly associated to body fat (BF, r = .82, P < .01), the 20-m sprint (r = .86, P < .01), countermovement jump (r = −.72, P < .01), and Bronco test (r = .90, P < .01). These fitness outcomes were related to %D, with moderate to strong associations (.82 > ∣r∣ > .54, P < .01). By playing position, similar associations were observed in forwards, but RHIE ability was only related to the 20-m sprint in backs (r = .53, P < .05). The RHIE performance model equations were TST = 13.69 + 0.01 × BF + 0.08 × Bronco + 10.20 × 20 m and %D = −14.34 + 0.11 × BF +0.18 × Bronco − 9.92 × 20 m. These models explain 88.8% and 68.2% of the variance, respectively. Conclusion: Body composition, lower-body power, and aerobic fitness were highly related with RHIE ability. However, backs expressed a different profile than forwards, suggesting that further research with larger sample sizes is needed to better understand the fitness determinants of backs’ RHIE ability.

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Parameters Influencing the Accuracy of a Wrist Photoplethysmography Heart-Rate Monitor (Polar Unite) During Exercise

Quentin Bretonneau, Etienne Peruque-Gayou, Etienne Wolfs, and Laurent Bosquet

Purpose: The accuracy of heart rate measured with a wrist photoplethysmography monitor can be influenced by the tightening of the wristband, movement of arms, or kinetics of the signal (eg, steady-state exercise vs on- and off-transients). To test these hypotheses, photoplethysmographic and electrocardiographic (ECG) signals were compared. Methods: Thirty participants (50% female) randomly performed two 13′ sequences (3′ rest, 5′ submaximal-intensity exercise, and 5′ passive recovery) on a motorized treadmill and a bicycle ergometer. Heart rate was measured concomitantly with a 10-lead ECG, a chest-strap monitor, and 2 wrist photoplethysmography monitors (Polar Unite) with different tightening (free vs imposed at the maximum tolerable). Results: The level of association (r) and coefficient of variation (CV; ie, the error of measurement) of the Polar Unite versus the 10-lead ECG is affected by the tightness of the wristband (normal vs high; r = .83 and .96, CV = 16.1 and 8.1% for the treadmill, respectively; r = .71 and .97, CV = 20.3% and 6.2% for the bicycle, respectively) by the phase of the signal (transition vs steady state; r = .90 and .97, CV = 9.0% and 7.6% for the treadmill, respectively; r = .93 and .99, CV = 7.5% and 3.1% for the bicycle, respectively) and movement of arms (treadmill vs bicycle; r = .90 and .93, CV = 9.0% and 7.5% during the transition phase, respectively; r = .97 and .99, CV = 7.6% and 3.1% during the steady-state phase, respectively). Conclusion: The accuracy of heart rate measured with a wrist photoplethysmography monitor is affected by the tightness of the wristband and the phase of the signal. A high tightening is required when high accuracy is expected.

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Preconditioning Activities to Enhance Repeated High-Intensity Efforts in Elite Rugby Union Players

Adrien Vachon, Nicolas Berryman, Iñigo Mujika, Jean-Baptiste Paquet, and Laurent Bosquet

Purpose: To assess the effect of a rugby-specific high-intensity interval-training (HIITRugby) protocol on the repeated high-intensity-effort ability of young elite rugby union players and to verify the influence of 2 preconditioning sequences composed either of physical contacts (ie, tackles) or of additional runs on the magnitude of improvement. Method: Fourteen players (19 [1] y; 183.5 [8.6] cm; 95.6 [15.6] kg) underwent an HIITRugby protocol, consisting of 7 supervised training sessions over 4 weeks, each session including 3 or 4 sets of 1 to 2 minutes with 1-minute recovery. Prior to HIITRugby training, players underwent a preconditioning contact sequence or a preconditioning running sequence, to assess their influence on subsequent interval-training sessions. Results: The overall group showed a moderate improvement in total sprint time, sprints ≥90% of the best, and 20-m sprint (−3.91% [2.68%], P = .0002; 74.6% [123.7%], P = .012; −3.22% [3.13%], P = .003, respectively) and a large improvement in percentage decrement (−23.1% [20.5%], P = .005) following the 4-week training block. Relative improvements were similar between groups in total sprint time, 20-m sprint, and perceived difficulty, but the preconditioning running-sequence group exhibited a larger magnitude of gains in percentage decrement (−28.6% [20.2%] vs −17.6% [20.7%]; effect size = −1.01 vs −0.73). Conclusion: An HIITRugby training block was effective to improve repeated high-intensity-effort ability. A preconditioning contact sequence prior to HIITRugby can reduce subsequent long-interval running activity, which may attenuate the improvement of repeated high-intensity-effort indices related to the aerobic system.

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The Impact of Multisession Sleep-Hygiene Strategies on Sleep Parameters in Elite Swimmers

Florane Pasquier, Robin Pla, Laurent Bosquet, Fabien Sauvet, Mathieu Nedelec, and D-Day Consortium

Purpose: Short sleep duration and poor sleep quality are common in swimmers. Sleep-hygiene strategies demonstrated beneficial effects on several sleep parameters. The present study assessed the impact of a multisession sleep-hygiene training course on sleep in elite swimmers. Methods: Twenty-eight elite swimmers (17 [2] y) participated. The sleep-hygiene strategy consisted of 3 interventions. Sleep was measured by actigraphy for 7 days before the beginning of the intervention (baseline), after the first collective intervention (postintervention), after the second collective intervention (postintervention 2), and, finally, after the individual intervention (postintervention 3). The Epworth Sleepiness Scale (ESS) was completed concurrently. Swimmers were classified into 2 groups: nonsomnolent (baseline ESS score ≤ 10, n = 13) and somnolent (baseline ESS score ≥ 11, n = 15). Results: All swimmers had a total sleep time of <8 hours per night. Sixty percent of swimmers were moderately morning type. Later bedtime, less time in bed, and total sleep time were observed in the somnolent group compared with the nonsomnolent group at baseline. An interaction between training course and group factors was observed for bedtime, with a significant advance in bedtime between baseline, postintervention 2, and postintervention 3 for the somnolent group. Conclusions: The present study confirms the importance of implementing sleep-hygiene strategies, particularly in athletes with an ESS score ≥11. A conjunction of individual and collective measures (eg, earlier bedtime, napping, and delaying morning training session) could favor the total sleep time achieved.

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The Temporal Relationship Between Exercise, Recovery Processes, and Changes in Performance

Sabrina Skorski, Iñigo Mujika, Laurent Bosquet, Romain Meeusen, Aaron J. Coutts, and Tim Meyer

Physiological and psychological demands during training and competition generate fatigue and reduce an athlete’s sport-specific performance capacity. The magnitude of this decrement depends on several characteristics of the exercise stimulus (eg, type, duration, and intensity), as well as on individual characteristics (eg, fitness, profile, and fatigue resistance). As such, the time required to fully recover is proportional to the level of fatigue, and the consequences of exercise-induced fatigue are manifold. Whatever the purpose of the ensuing exercise session (ie, training or competition), it is crucial to understand the importance of optimizing the period between exercise bouts in order to speed up the regenerative processes and facilitate recovery or set the next stimulus at the optimal time point. This implies having a fairly precise understanding of the fatigue mechanisms that contribute to the performance decrement. Failing to respect an athlete’s recovery needs may lead to an excessive accumulation of fatigue and potentially “nonfunctional overreaching” or to maladaptive training. Although research in this area recently increased, considerations regarding the specific time frames for different physiological mechanisms in relation to exercise-induced fatigue are still missing. Furthermore, recommendations on the timing and dosing of recovery based on these time frames are limited. Therefore, the aim of this article is to describe time courses of recovery in relation to the exercise type and on different physiological levels. This summary supports coaches, athletes, and scientists in their decision-making process by considering the relationship of exercise type, physiology, and recovery.

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Evaluative Threat Increases Effort Expenditure in a Cycling Exercise: An Exploratory Study

Leila Selimbegović, Olivier Dupuy, Julie Terache, Yannick Blandin, Laurent Bosquet, and Armand Chatard

Research shows that negative or threatening emotional stimuli can foster movement velocity and force. However, less is known about how evaluative threat may influence movement parameters in endurance exercise. Based on social self-preservation theory, the authors predicted that evaluative threat would facilitate effort expenditure in physical exercise. In an exploratory study, 27 young men completed a bogus intelligence test and received either low-intelligence-quotient feedback (evaluative threat) or no feedback (control). Next, they were asked to pedal on a stationary bicycle for 30 min at a constant cadence. After 10 min (calibration period), the cadence display was hidden. Findings show that participants under evaluative threat increased cadence more than control participants during the subsequent 20-min critical period. These findings underline the potential importance of unrelated evaluative threat on physical performance.