Purpose: To survey soccer practitioners’ recovery strategy: (1) use, (2) perceived effectiveness, and (3) factors influencing their implementation in professional soccer. Methods: A cross-sectional convenience sample of professional soccer club/confederation practitioners completed a web-based survey (April to July 2020). Pearson chi-square and Fisher exact tests with Cramer V (φ − c) assessed relationships and their strength, respectively, between the perceived effectiveness and frequency of strategy use. Results: A total of 80 soccer practitioners (13 countries) completed the survey. The 3 most important recovery objectives were “alleviating muscle damage/fatigue,” “minimizing injury risk,” and “performance optimization.” The most frequently used strategies were active recovery, structured recovery day, extra rest day, massage, cold-water therapy, and carbohydrate provision (predominantly on match day and match day + 1). Relationships were identified between perceived effectiveness and frequency of strategy use for sleep medication (P < .001, φ − c = 0.48), carbohydrate provision (P = .007, φ − c = 0.60), protein provision (P = .007, φ − c = 0.63), an extra rest day (P < .001, φ − c = 0.56), and a structured recovery day (P = .049, φ − c = 0.50). Conclusions: The study demonstrates that professional soccer practitioners have a range of objectives geared toward enhancing player recovery. A disconnect is apparent between the perceived effectiveness of many recovery strategies and their frequency of use in an applied setting. Novel data indicate that strategies are most frequently employed around match day. Challenges to strategy adoption are mainly competing disciplinary interests and resource limitations. Researchers and practitioners should liaise to ensure that the complexities involved with operating in an applied environment are elucidated and apposite study designs are adopted, in turn, facilitating the use of practically effective and compatible recovery modalities.
Adam Field, Liam D. Harper, Bryna C.R. Chrismas, Peter M. Fowler, Alan McCall, Darren J. Paul, Karim Chamari, and Lee Taylor
Sylwia Bartkowiak, Jan M. Konarski, Ryszard Strzelczyk, Jarosław Janowski, Małgorzata Karpowicz, and Robert M. Malina
Background: The objective of the study was to evaluate secular changes in the physical fitness of rural school youth, 7–15 years, in west-central Poland between 1986 and 2016. Methods: The fitness of cross-sectional samples of school youth resident in the same 10 communities was evaluated in 4 decennial surveys: 1986—1417 boys/1326 girls; 1996—979 boys/947 girls; 2006—871 boys/843 girls; and 2016—1189 boys/1105 girls. Five tests evaluated speed (5-m run), agility (figure 8 run), explosive power (vertical jump), flexibility (stand and reach), and cardiovascular fitness (modified Harvard step test). Age- and sex-specific descriptive statistics were calculated by survey, while differences among surveys were compared in 3 broad age groups (7–9, 10–12, and 13–15 y) using analysis of variance with age and age squared as covariates. Results: Speed and flexibility declined, while the jump and step test index changed variably across surveys. Although agility improved across surveys, the major improvement occurred between 1986 and 1996. Conclusions: Performances of rural school youth on 5 tests of physical fitness changed significantly, but, variably, between 1986 and 2016. The results were generally consistent with other studies of Polish school youth that spanned a similar interval.
Erianne A. Weight, Molly Harry, and Heather Erwin
Background: The Walking Classroom is an education program that provides students with an opportunity to accumulate physical activity without losing instructional time. Method: This research tests Kuczala’s application of kinesthetic learning theory through measuring knowledge retention, postactivity information processing, and mood in students who engage in a short bout of physical activity while listening to Walking Classroom podcasts about language arts, science, and history, and those who remain seated during a podcast, compared with baseline levels. Students from 9 high-poverty fourth- and fifth-grade classrooms (n = 319) in a North Carolina county comprised the sample. Results: Utilizing multivariate analysis of covariance, the results demonstrate significantly higher levels of learning while walking compared with learning while sitting. Measures of mood utilizing the 10-item version of the Positive and Negative Affect Scale also demonstrated a significant effect in predicted directions. Conclusion: The results support that coupling physical activity with instruction leads to increased performance and mood for elementary school students.
Julian Alcazar, Pedro J. Cornejo-Daza, Juan Sánchez-Valdepeñas, Luis M. Alegre, and Fernando Pareja-Blanco
Purpose: This study aimed to compare the adaptations provoked by various velocity loss (VL) thresholds used in resistance training on the squat force–velocity (F–V) relationship. Methods: Sixty-four resistance-trained young men were randomly assigned to one of four 8-week resistance training programs (all 70%–85% 1-repetition maximum) using different VL thresholds (VL0 = 0%, VL10 = 10%, VL20 = 20%, and VL40 = 40%) in the squat exercise. The F–V relationship was assessed under unloaded and loaded conditions in squat. Linear and hyperbolic (Hill) F–V equations were used to calculate force at zero velocity (F0), velocity at zero force (V0), maximum muscle power (Pmax), and force produced at mean velocities ranging from 0.0 to 2.0 m·s−1. Changes in parameters derived from the F–V relationship were compared among groups using linear mixed models. Results: Linear equations showed increases in F0 (120.7 N [89.4 to 152.1]) and Pmax (76.2 W [45.3 to 107.2]) and no changes in V0 (−0.02 m·s−1 [−0.11 to 0.06]) regardless of VL. Hyperbolic equations depicted increases in F0 (120.7 N [89.4 to 152.1]), V0 (1.13 m·s−1 [0.78 to 1.48]), and Pmax (198.5 W [160.5 to 236.6]) with changes in V0 being greater in VL0 and VL10 versus VL40 (both P < .001). All groups similarly improved force at 0.0 to 2.0 m·s−1 (all P < .001), although in general, effect sizes were greater in VL10 and VL20 versus VL0 and VL40 at velocities ≤0.5 m·s−1. Conclusions: All groups improved linear and hyperbolic F0 and Pmax and hyperbolic V0 (except VL40). The dose–response relationship exhibited an inverted U-shape pattern at velocities ≤0.5 m·s−1 with VL10 and VL20 showing the greatest standardized changes.
Isabella Russo, Paul A. Della Gatta, Andrew Garnham, Judi Porter, Louise M. Burke, and Ricardo J.S. Costa
Purpose: This study aimed to determine the effects of an acute “train-low” nutritional protocol on markers of recovery optimization compared to standard recovery nutrition protocol. Methods: After completing a 2-hour high-intensity interval running protocol, 8 male endurance athletes consumed a standard dairy milk recovery beverage (CHO; 1.2 g/kg body mass [BM] of carbohydrate and 0.4 g/kg BM of protein) and a low-carbohydrate (L-CHO; isovolumetric with 0.35 g/kg BM of carbohydrate and 0.5 g/kg BM of protein) dairy milk beverage in a double-blind randomized crossover design. Venous blood and breath samples, nude BM, body water, and gastrointestinal symptom measurements were collected preexercise and during recovery. Muscle biopsy was performed at 0 hour and 2 hours of recovery. Participants returned to the laboratory the following morning to measure energy substrate oxidation and perform a 1-hour distance test. Results: The exercise protocol resulted in depletion of muscle glycogen stores (250 mmol/kg dry weight) and mild body-water losses (BM loss = 1.8%). Neither recovery beverage replenished muscle glycogen stores (279 mmol/kg dry weight) or prevented a decrease in bacterially stimulated neutrophil function (−21%). Both recovery beverages increased phosphorylation of mTORSer2448 (main effect of time = P < .001) and returned hydration status to baseline. A greater fold increase in p-GSK-3βSer9/total-GSK-3β occurred on CHO (P = .012). Blood glucose (P = .005) and insulin (P = .012) responses were significantly greater on CHO (618 mmol/L per 2 h and 3507 μIU/mL per 2 h, respectively) compared to L-CHO (559 mmol/L per 2 h and 1147 μIU/mL per 2 h, respectively). Rates of total fat oxidation were greater on CHO, but performance was not affected. Conclusion: A lower-carbohydrate recovery beverage consumed after exercise in a “train-low” nutritional protocol does not negatively impact recovery optimization outcomes.
Tim J. Mosey and Lachlan J.G. Mitchell
Objectives: The purpose of this study was to document the longitudinal strength and power characteristic changes and race performance changes of a skeleton athlete. Method: Longitudinal strength and power changes were assessed with strength and power diagnostic testing over a 9-year period. Trends over 9 years for relative strength were analyzed using a linear model. Push-start time was recorded across multiple tracks. Trends over 9 years for start performance at each track were assessed using a mixed-effects linear model to account for the impact of different tracks. Lower-body strength and power changes were assessed via a 1-repetition-maximum squat and a body-weight countermovement jump. The relationship between strength and power changes was assessed over time. The relationship between strength changes and start performance was determined by assessing the fixed effect of relative strength changes on push-start time. Results: Relative lower-body strength ranged from 1.6 kg per body weight to 1.9 kg per body weight and showed a significant mean improvement of 0.05 kg per body weight per year (R 2 = .71, P < .01). A negative correlation (R 2 = .79) between relative strength changes and push-start performance across multiple tracks was found. The mixed-effects model indicated that push-start time improved significantly year to year (0.02 s; P < .001; R 2 = .74) when controlling for the effect of track. Conclusions: The longitudinal analysis of push-start time and the associations with changes in strength suggest that training this quality can have a positive effect on push-start performance.
Even Brøndbo Dahl, Eivind Øygard, Gøran Paulsen, Bjarne Rud, and Thomas Losnegard
Purpose: Preconditioning exercise is a widely used strategy believed to enhance performance later the same day. The authors examined the influence of preconditioning exercises 6 hours prior to a time-to-exhaustion (TTE) test during treadmill running. Methods: Ten male competitive runners (age = 26  y, height = 184  cm, weight = 73  kg, maximum oxygen consumption = 72  mL·kg−1·min−1) did a preconditioning session of running (RUN) or resistance exercise (RES) or no morning exercise (NoEx) in a randomized order, separated by >72 hours. The RUN consisted of 15 minutes of low-intensity running and 4 × 15 seconds at race pace (21–24 km·h−1) on a treadmill; RES involved 5 minutes of low-intensity running and 2 × 3 repetitions of isokinetic 1-leg shallow squats with maximal mobilization. Following a 6-hour break, electrically evoked force (m. vastus medialis), countermovement jump, running economy, and a TTE of approximately 2 minutes were examined. Results: Relative to NoEx, no difference was seen for RUN or RES in TTE (mean ± 95% CI: −1.3% ± 3.4% and −0.5% ± 6.0%) or running economy (0.2% ± 1.6% and 1.9% ± 2.7%; all Ps > .05). Jump height was not different for the RUN condition (1.0% ± 2.7%]) but tended to be higher in RES than in the NoEx condition (1.5% ± 1.6%, P = .07). The electrically evoked force tended to reveal low-frequency fatigue (reduced 20:50-Hz peak force ratio) only after RES compared to NoEx (−4.5% ± 4.6%, P = .06). Conclusion: The RUN or RES 6 hours prior to approximately 2 minutes of TTE running test did not improve performance in competitive runners.
Zeinab Khodaverdi, Abbas Bahram, Hassan Khalaji, Anoshirvan Kazemnejad, Farhad Ghadiri, and Wesley O’Brien
This paper aimed to investigate different dimensions of motor competence (MC) by using four commonly administered MC assessment tools (Test of Gross Motor Development-3, Bruininks-Oseretsky Test of Motor Proficiency-2 Short Form, Körperkoordinationtest Für Kinder, and Movement Assessment Battery for Children-2) in a sample of 184 girls (Mage = 8.61 years; SD = 1.21 years). This is the first study of its kind to shed light on different dimensions of MC, identifying them through rigorous and robust statistical analysis. The Delphi method was used to select the dimensions of MC. Confirmatory factor analysis was used to assess whether the dimensions loaded onto the same construct (i.e., MC). Face and content validity identified three dimensions of MC: fundamental motor skills, gross motor coordination, and motor abilities. Confirmatory factor analysis indicated an adequate fit for the final MC model with three dimensions. In this model, fundamental motor skills, gross motor coordination, and motor abilities loaded on the MC construct. The data reported present a revised definition of holistic MC, which comprises the level of motor abilities (physical proficiency and perceptual motor abilities) as well as gross motor coordination and fundamental motor skills proficiency, which underlie the performance of a wide range of tasks, including fine and gross motor activities in daily life.
Kolbjørn Lindberg, Ingrid Eythorsdottir, Paul Solberg, Øyvind Gløersen, Olivier Seynnes, Thomas Bjørnsen, and Gøran Paulsen
Purpose: The aim of this study was to examine the concurrent validity of force–velocity (FV) variables assessed across 5 Keiser leg press devices. Methods: A linear encoder and 2 independent force plates (MuscleLab devices) were mounted on each of the 5 leg press devices. A total of 997 leg press executions, covering a wide range of forces and velocities, were performed by 14 participants (29  y, 181  cm, 82  kg) across the 5 devices. Average and peak force, velocity, and power values were collected simultaneously from the Keiser and MuscleLab devices for each repetition. Individual FV profiles were fitted to each participant from peak and average force and velocity measurements. Theoretical maximal force, velocity, and power were deduced from the FV relationship. Results: Average and peak force and velocity had a coefficient of variation of 1.5% to 8.6%, near-perfect correlations (.994–.999), and a systematic bias of 0.7% to 7.1% when compared with reference measurements. Average and peak power showed larger coefficient of variations (11.6% and 17.2%), despite excellent correlations (.977 and .952), and trivial to small biases (3.9% and 8.4%). Extrapolated FV variables showed near-perfect correlations (.983–.997) with trivial to small biases (1.4%–11.2%) and a coefficient of variation of 1.4% to 5.9%. Conclusions: The Keiser leg press device can obtain valid measurements over a wide range of forces and velocities across different devices. To accurately measure power, theoretical maximal power calculated from the FV profile is recommended over average and peak power values from single repetitions, due to the lower random error observed for theoretical maximal power.
Justin A. Haegele, Xihe Zhu, Sean Healy, and Freda Patterson
Background: The purposes of this study were to examine the proportions of youth receiving special education services in the United States who individually and jointly met physical activity, screen time, and sleep duration guidelines, and to examine the impact of meeting none, one, two, and three of the guidelines on overweight and obesity. Methods: This cross-sectional analysis utilized data from the 2016 to 2017 National Survey for Children’s Health data set on 3582 youth aged 10–17 years who received special education services. The frequency of the participants’ compliance with the 24-hour movement guidelines and body weight status (based on the age- and sex-specific percentile cutoffs) were estimated. Meeting guidelines was defined as: 9–11 hours/night (5–13 y) or 8–10 hours/night (14–17 y) of sleep, ≤120 minutes per day of screen time, and ≥60 minutes per day of moderate to vigorous physical activity. A multinomial logistic regression analysis was conducted to estimate the impact of meeting none, one, two, or three guidelines on body weight status, adjusted for potential confounders. Results: Overall, 8.1% of youth met all three guidelines, 42.0% met two guidelines, 38.0% met one guideline, and 11.9% did not meet any guideline. Meeting all three guidelines was associated with an approximately 50% decreased likelihood of overweight than meeting no guideline, or sleep or screen time guidelines independently. Conclusions: This study extends the 24-hour movement framework to children receiving special education services and should prompt the continued study of its utility for understanding health disparities experienced by this population.