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Benefits of Training the Iron Cross With Herdos Devices and External Load Added to Body Weight for Young Nonachiever Gymnasts

Michel Marina, Priscila Torrado, Blai Ferrer-Uris, and Albert Busquets

Purpose: To verify whether training the iron cross (IC) with assistive devices (herdos; HIC) and added external load (LHIC) to equate the moments of force developed on the rings could be considered an intermediate step between the nonoverloaded herdos situation (HIC) and the IC performed on the rings. Methods: Relative levels of surface electromyography (sEMG) activity were normalized with respect to a standing IC before comparing gymnasts who can perform the IC on the rings (achievers) and gymnast who cannot (nonachievers) in the 2 herdos conditions (HIC and LHIC). Seven muscles were chosen for sEMG analysis, namely, pectoralis major (PM), latissimus dorsi, teres major, lower trapezius, serratus anterior, biceps brachii (BB), and triceps brachii. Additionally, 3 indices were calculated to measure levels of coactivation: Elbowidx, Scapulaidx, and Shoulderidx. Results: The bigger magnitude of differences in sEMG activity among situations was found for the PM and BB (F ≥ 30.7; P < .001). When comparing the global and the PM, teres major, BB, and triceps brachii activity across groups, nonachievers activated their musculature to a greater extent than the achievers independently of the herdos situation (P ≤ .046). Achievers’ Elbowidx was the only index that was significantly higher (P ≤ .005) in the IC in comparison to LHIC and HIC. Conclusion: sEMG activity of PM and BB was particularly sensitive between situations, independently of the level of achievement. We recommend training the IC by adding external load in the herdos situation to increase muscle activity to levels closer to the rings situation but avoiding the potential factor of injuries.

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Erratum. Determinants of 1500-m Front-Crawl Swimming Performance in Triathletes: Influence of Physiological and Biomechanical Variables

International Journal of Sports Physiology and Performance

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Recreational Runners Gain Physiological and Biomechanical Benefits From Super Shoes at Marathon Paces

Giorgos P. Paradisis, Elias Zacharogiannis, Athanassios Bissas, and Brian Hanley

Purpose: Advanced footwear technology is prevalent in distance running, with research focusing on these “super shoes” in competitive athletes, with less understanding of their value for slower runners. The aim of this study was to compare physiological and biomechanical variables between a model of super shoes (Saucony Endorphin Speed 2) and regular running shoes (Saucony Cohesion 13) in recreational athletes. Methods: We measured peak oxygen uptake (VO2peak) in 10 runners before testing each subject 4 times in a randomly ordered crossover design (ie, Endorphin shoe or Cohesion shoe, running at 65% or 80% of velocity at VO2peak [vVO2peak]). We recorded video data using a high-speed camera (300 Hz) to calculate vertical and leg stiffnesses. Results: 65% vVO2peak was equivalent to a speed of 9.4 km·h−1 (0.4), whereas 80% vVO2peak was equivalent to 11.5 km·h−1 (0.5). Two-way mixed-design analysis of variance showed that oxygen consumption in the Endorphin shoe was 3.9% lower than in the Cohesion shoe at 65% vVO2peak, with an interaction between shoes and speed (P = .020) meaning an increased difference of 5.0% at 80% vVO2peak. There were small increases in vertical and leg stiffnesses in the Endorphin shoes (P < .001); the Endorphin shoe condition also showed trivial to moderate differences in step length, step rate, contact time, and flight time (P < .001). Conclusions: There was a physiological benefit to running in the super shoes even at the slower speed. There were also spatiotemporal and global stiffness improvements indicating that recreational runners benefit from wearing super shoes.

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Development and Interplay of Metabolic and Mechanical Performance Determinants Over an Annual Training Period in Adolescent National-Level Squad Swimmers

Sebastian Keller, Sanghyeon Ji, Joshua F. Feuerbacher, Boris Dragutinovic, Moritz Schumann, and Patrick Wahl

Purpose: The study examined the longitudinal interplay of anthropometric, metabolic, and neuromuscular development related to performance in adolescent national-level swimmers over 12 months. Methods: Seven male and 12 female swimmers (14.8 [1.3] y, FINA [International Swimming Federation] points 716 [51]) were tested before (T0) and after the preparation period (T1), at the season’s peak (T2), and before the next season (T3). Anthropometric (eg, fat percentage) and neuromuscular parameters (squat and bench-press load-velocity profile) were assessed on dry land. Metabolic (cost of swimming [C], maximal oxygen uptake [ V ˙ O 2 peak ], and peak blood lactate [bLapeak]) and performance (sprinting speed [v sprint] and lactate thresholds [LT1 and 2]) factors were determined using a 500-m submaximal, 200-m all-out, 20-second sprint, and incremental test (+0.03 m·s−1, 3 min), respectively, in front-crawl swimming. Results: v sprint (+0.6%) and LT1 and 2 (+1.9–2.4%) increased trivially and slightly, respectively, from T0 to T2 following small to moderate strength increases (≥+10.2%) from T0 to T1 and V ˙ O 2 peak (+6.0%) from T1 to T2. Bench-press maximal strength and peak power correlated with v sprint from T0 to T2 (r ≥ .54, P < .05) and LT2 at T1 (r ≥ .47, P < .05). Changes in fat percentage and V ˙ O 2 peak (T2–T1 and T3–T2, r ≤ −.67, P < .01) and C and LT2 (T2–T0, r = −.52, P = .047) were also correlated. Conclusions: Increases in strength and V ˙ O 2 peak from preparation to the competition period resulted in improved sprint and endurance performance. Across the season, upper-body strength was associated with v sprint and LT2, although their changes were unrelated.

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Erratum. Swimming With the COSMED AquaTrainer and K5 Wearable Metabolic System in Breath-by-Breath Mode: Accuracy, Precision, and Repeatability

International Journal of Sports Physiology and Performance

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To Sleep Dreaming Medals: Sleep Characteristics, Napping Behavior, and Sleep-Hygiene Strategies in Elite Track-and-Field Athletes Facing the Olympic Games of Tokyo 2021

Jacopo A. Vitale, Stefano Borghi, Maria Francesca Piacentini, Giuseppe Banfi, and Antonio La Torre

Purpose: Few data are available on sleep characteristics of elite track-and-field athletes. Our study aimed to assess (1) differences in sleep between sexes and among different track-and-field disciplines, (2) the effect of individualized sleep-hygiene strategies on athletes’ sleep parameters, and (3) daytime nap characteristics in track-and-field athletes. Methods: Sleep characteristics of 16 elite Olympic-level track-and-field athletes (male: n = 8; female: n = 8) were assessed during the preseason period, at baseline (T0), and during the in-season period, after the adoption of individualized sleep-hygiene strategies (T1). Sleep parameters were objectively monitored by actigraphy for a minimum of 10 days, for each athlete, at both T0 and T1. A total of 702 nights were analyzed (T0 = 425; T1 = 277). Results: Female athletes displayed better sleep efficiency (88.69 [87.69–89.68] vs 91.72 [90.99–92.45]; P = .003, effect size [ES]: 0.44), lower sleep latency (18.99 [15.97–22.00] vs 6.99 [5.65–8.32]; P < .001, ES: 0.65), higher total sleep time (07:03 [06:56–07:11] vs 07:18 [07:10–07:26]; P = .030, ES: 0.26), earlier bedtime (00:24 [00:16–00:32] vs 00:13 [00:04–00:22]; P = .027, ES: 0.18), and lower nap frequency (P < .001) than male athletes. Long-distance runners had earlier bedtime (00:10 [00:03–00:38] vs 00:36 [00:26–00:46]; P < .001, ES: 0.41) and wake-up time (07:41 [07:36–07:46] vs 08:18 [08:07–08:30]; P < .001, ES: 0.61), higher nap frequency, but lower sleep efficiency (88.79 [87.80–89.77] vs 91.67 [90.95–92.38]; P = .013, ES: 0.44), and longer sleep latency (18.89 [15.94–21.84] vs 6.69 [5.33–8.06]; P < .001, ES: 0.67) than athletes of short-term disciplines. Furthermore, sleep-hygiene strategies had a positive impact on athletes’ total sleep time (429.2 [423.5–434.8] vs 451.4 [444.2–458.6]; P < .001, ES: 0.37) and sleep latency (14.33 [12.34–16.32] vs 10.67 [8.66–12.68]; P = .017, ES: 0.19). Conclusions: Sleep quality and quantity were suboptimal at baseline in Olympic-level track-and-field athletes. Large differences were observed in sleep characteristics between sexes and among different track-and-field disciplines. Given the positive effect of individualized sleep-hygiene strategies on athlete’s sleep, coaches should implement sleep education sessions in the daily routine of top-level athletes.

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The Influence of Menstrual-Cycle Phase on Measures of Recovery Status in Endurance Athletes: The Female Endurance Athlete Project

Virginia De Martin Topranin, Tina Pettersen Engseth, Maria Hrozanova, Madison Taylor, Øyvind Sandbakk, and Dionne A. Noordhof

Purpose: To investigate the influence of menstrual-cycle (MC) phase on measures of recovery status, that is, resting heart rate, perceived sleep quality, and physical and mental readiness to train, among female endurance athletes. Methods: Daily data were recorded during 1 to 4 MCs (ie, duration ≥21 and ≤35 d, ovulatory, luteal phase ≥10 d) of 41 trained-to-elite-level female endurance athletes (mean [SD]: age 27 [8] y, weekly training: 9 [3] h). Resting heart rate was assessed daily using a standardized protocol, while perceived sleep quality and physical and mental readiness to train were assessed using a visual analog scale (1–10). Four MC phases (early follicular phase [EFP], late follicular phase, ovulatory phase, and midluteal phase [MLP]) were determined using the calendar-based counting method and urinary ovulation-prediction test. Data were analyzed using linear mixed-effects models. Results: Resting heart rate was significantly higher in MLP (1.7 beats·min−1, P = .006) compared with EFP without significant differences between the other MC phases. Perceived sleep quality was impaired in MLP compared with late follicular phase (−0.3, P = .035). Physical readiness to train was lower both in ovulatory phase (−0.6, P = .015) and MLP (−0.5, P = .026) compared with EFP. Mental readiness to train did not show any significant differences between MC phases (P > .05). Conclusions: Although significant, the findings had negligible to small effect sizes, indicating that MC phase is likely not the main determinant of changes in measures of recovery status but, rather, one of the many possible stressors.

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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 Weekly Periodization of Top 5 Tour de France General Classification Finishers: A Multiple Case Study

Gabriele Gallo, Manuel Mateo-March, Daniel Gotti, Ed Maunder, Roberto Codella, Piero Ruggeri, Emanuela Faelli, and Luca Filipas

Purpose: The aim of this study was to describe individual training characteristics, racing strategies, and periodization in preparation for the Tour de France in 2 world-class road cyclists finishing in the top 5 of the general classification. Methods: Week‐by‐week power meter training and racing data of 2 (A and B) road cyclists (age: 29 and 23 y; maximum oxygen consumption: 83 and 81 mL·min−1·kg−1; and relative 20‐min record power output: 6.9 and 6.5 W·kg−1) in the preparation phase (December–July/August) leading up to the Tour de France were retrospectively analyzed. Weekly volume and intensity distribution in power zones were considered. Results: Cyclists A and B completed 46 and 19 races, 22.5 (6.3) and 18.2 (5.1) h·wk−1, with a pyramidal intensity distribution of 81.0%–13.3%–5.7%, and 88.8%–7.9%–3.3% in zone 1–zone 2–zone 3. Cyclist B spent 14 days at altitude. Increased high-intensity volume and polarization index occurred during race weeks. During periods without racing, training intensity progressively increased. Strength training was performed during November and December but not during the following months. During tapering, total exercise volume and time at high intensity decreased. Conclusion: These data provide novel insights into the periodization of world-class road cyclists in advance of a top 5 placing in the Tour de France general classification.

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Determinants of 1500-m Front-Crawl Swimming Performance in Triathletes: Influence of Physiological and Biomechanical Variables

Óscar López-Belmonte, Jesús J. Ruiz-Navarro, Ana Gay, Francisco Cuenca-Fernández, Roberto Cejuela, and Raúl Arellano

Purpose: To analyze the associations between physiological and biomechanical variables with the FINA (International Swimming Federation) points (ie, swimming performance) obtained in 1500-m front-crawl swimming to determine whether these variables can be used to explain triathletes’ FINA points. Methods: Fourteen world-class, international and national triathletes (10 male: 23.24 [3.70] y and 4 female: 23.36 [3.76] y) performed a 1500-m front-crawl swimming test in a short-course pool. Heart rate (HR), oxygen uptake ( V ˙ O 2 ), and blood lactate concentrations were obtained before and after the test. HR was also measured during the effort. Highest V ˙ O 2 value ( V ˙ O 2 peak ) was estimated by extrapolation. Clean swimming speed, turn performance, stroke rate, stroke length, and stroke index (SI) were obtained by video analysis. Results: Average 1500-m performance times were 1088 (45) seconds and 1144 (31) seconds for males and females, respectively. HR after the effort, V ˙ O 2 peak , aerobic contributions, total energy expenditure, energy cost, and turn performance presented moderate negative associations with swimming performance (r ≈ .5). In contrast, respiratory exchange ratio, anaerobic alactic contribution, clean swimming speed, stroke length, and SI were positively related, with clean swimming speed and SI having a strong large association (r ≈ .7). A multiple stepwise regression model determined that 71% of the variance in FINA points was explained by SI and total energy expenditure, being predictors in 1500-m front-crawl swimming. Conclusions: Swimming performance in triathletes was determined by the athletes’ energy demands and biomechanical variables. Thus, coaches should develop specific technique skills to improve triathletes’ swimming efficiency.