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Strength training is an important means for performance development in young rowers. The purpose of this study was to examine the effects of a 9-week equal volume heavy-resistance strength training (HRST) versus strength endurance training (SET) in addition to regular rowing training on primary (e.g., maximal strength/power) and secondary outcomes (e.g., balance) in young rowers. Twenty-six female elite adolescent rowers were assigned to an HRST (n = 12; age: 13.2 ± 0.5 yrs; maturity-offset: +2.0 ± 0.5 yrs) or a SET group (n = 14; age: 13.1 ± 0.5 yrs; maturity-offset: +2.1 ± 0.5 yrs). HRST and SET comprised lower- (i.e., leg press/knee flexion/extension), upper-limbs (i.e., bench press/pull; lat-pull down), and complex exercises (i.e., rowing ergometer). HRST performed four sets with 12 repetitions per set at an intensity of 75–95% of the one-repetition maximum (1-RM). SET conducted four sets with 30 repetitions per set at 50–60% of the 1-RM. Training volume was matched for overall repetitions × intensity × training per week. Pre-post training, tests were performed for the assessment of primary [i.e., maximal strength (e.g., bench pull/knee flexion/extension 1-RM/isometric handgrip test), muscle power (e.g., medicine-ball push test, triple hop, drop jump, and countermovement jump), anaerobic endurance (400-m run), sport-specific performance (700-m rowing ergometer trial)] and secondary outcomes [dynamic balance (Y-balance test), change-of-direction (CoD) speed (multistage shuttle-run test)]. Adherence rate was >87% and one athlete of each group dropped out. Overall, 24 athletes completed the study and no test or training-related injuries occurred. Significant group × time interactions were observed for maximal strength, muscle power, anaerobic endurance, CoD speed, and sport-specific performance (p ≤ 0.05; 0.45 ≤ d ≤ 1.11). Post hoc analyses indicated larger gains in maximal strength and muscle power following HRST (p ≤ 0.05; 1.81 ≤ d ≤ 3.58) compared with SET (p ≤ 0.05; 1.04 ≤ d ≤ 2.30). Furthermore, SET (p ≤ 0.01; d = 2.08) resulted in larger gains in sport-specific performance compared with HRST (p < 0.05; d = 1.3). Only HRST produced significant pre-post improvements for anaerobic endurance and CoD speed (p ≤ 0.05; 1.84 ≤ d ≤ 4.76). In conclusion, HRST in addition to regular rowing training was more effective than SET to improve selected measures of physical fitness (i.e., maximal strength, muscle power, anaerobic endurance, and CoD speed) and SET was more effective than HRST to enhance sport-specific performance gains in female elite young rowers.
How We Found Our IMU
(2020)
Inertial measurement units (IMUs) are commonly used for localization or movement tracking in pervasive healthcare-related studies, and gait analysis is one of the most often studied topics using IMUs. The increasing variety of commercially available IMU devices offers convenience by combining the sensor modalities and simplifies the data collection procedures. However, selecting the most suitable IMU device for a certain use case is increasingly challenging. In this study, guidelines for IMU selection are proposed. In particular, seven IMUs were compared in terms of their specifications, data collection procedures, and raw data quality. Data collected from the IMUs were then analyzed by a gait analysis algorithm. The difference in accuracy of the calculated gait parameters between the IMUs could be used to retrace the issues in raw data, such as acceleration range or sensor calibration. Based on our algorithm, we were able to identify the best-suited IMUs for our needs. This study provides an overview of how to select the IMUs based on the area of study with concrete examples, and gives insights into the features of seven commercial IMUs using real data.
The aim of this study was to establish maturation-, age-, and sex-specific anthropometric and physical fitness percentile reference values of young elite athletes from various sports. Anthropometric (i.e., standing and sitting body height, body mass, body mass index) and physical fitness (i.e., countermovement jump, drop jump, change-of-direction speed [i.e., T-test], trunk muscle endurance [i.e., ventral Bourban test], dynamic lower limbs balance [i.e., Y-balance test], hand grip strength) of 703 male and female elite young athletes aged 8–18 years were collected to aggregate reference values according to maturation, age, and sex. Findings indicate that body height and mass were significantly higher (p<0.001; 0.95≤d≤1.74) in more compared to less mature young athletes as well as with increasing chronological age (p<0.05; 0.66≤d≤3.13). Furthermore, male young athletes were significantly taller and heavier compared to their female counterparts (p<0.001; 0.34≤d≤0.50). In terms of physical fitness, post-pubertal athletes showed better countermovement jump, drop jump, change-of-direction, and handgrip strength performances (p<0.001; 1.57≤d≤8.72) compared to pubertal athletes. Further, countermovement jump, drop jump, change-of-direction, and handgrip strength performances increased with increasing chronological age (p<0.05; 0.29≤d≤4.13). In addition, male athletes outperformed their female counterpart in the countermovement jump, drop jump, change-of-direction, and handgrip strength (p<0.05; 0.17≤d≤0.76). Significant age by sex interactions indicate that sex-specific differences were even more pronounced with increasing age. Conclusively, body height, body mass, and physical fitness increased with increasing maturational status and chronological age. Sex-specific differences appear to be larger as youth grow older. Practitioners can use the percentile values as approximate benchmarks for talent identification and development.
Background: The regular assessment of hormonal and mood state parameters in professional soccer are proposed as good indicators during periods of intense training and/or competition to avoid overtraining.
Objective: The aim of this study was to analyze hormonal, psychological, workload and physical fitness parameters in elite soccer players in relation to changes in training and match exposure during a congested period of match play.
Methods: Sixteen elite soccer players from a team playing in the first Tunisian soccer league were evaluated three times (T1, T2, and T3) over 12 weeks. The non-congested period of match play was from T1 to T2, when the players played 6 games over 6 weeks. The congested period was from T2 to T3, when the players played 10 games over 6 weeks. From T1 to T3, players performed the Yo-Yo intermittent recovery test level 1 (YYIR1), the repeated shuttle sprint ability test (RSSA), the countermovement jump test (CMJ), and the squat jump test (SJ). Plasma Cortisol (C), Testosterone (T), and the T/C ratio were analyzed at T1, T2, and T3. Players had their mood dimensions (tension, depression, anger, vigor, fatigue, confusion, and a Total Mood Disturbance) assessed through the Profile of Mood State questionnaire (POMS). Training session rating of perceived exertion (sRPE) was also recorded on a daily basis in order to quantify internal training load and elements of monotony and strain.
Results: Significant performance declines (T1 < T2 < T3) were found for SJ performance (p = 0.04, effect size [ES] ES₁₋₂ = 0.15−0.06, ES₂₋₃ = 0.24) from T1 to T3. YYIR1 performance improved significantly from T1 to T2 and declined significantly from T2 to T3 (p = 0.001, ES₁₋₂ = 0.24, ES₂₋₃ = −2.54). Mean RSSA performance was significantly higher (p = 0.019, ES₁₋₂ = −0.47, ES₂₋₃ = 1.15) in T3 compared with T2 and T1. Best RSSA performance was significantly higher in T3 when compared with T2 and T1 (p = 0.006, ES₂₋₃ = 0.47, ES₁₋₂ = −0.56), but significantly lower in T2 when compared with to T1. T and T/C were significantly lower in T3 when compared with T2 and T1 (T: p = 0.03, ES₃₋₂ = −0.51, ES₃₋₁ = −0.51, T/C: p = 0.017, ES₃₋₂ = −1.1, ES₃₋₁ = −1.07). Significant decreases were found for the vigor scores in T3 when compared to T2 and T1 (p = 0.002, ES₁₋₂ = 0.31, ES₃₋₂ = −1.25). A significant increase was found in fatigue scores in T3 as compared to T1 and T2 (p = 0.002, ES₁₋₂ = 0.43, ES₂₋₃ = 0.81). A significant increase was found from T1 < T2 < T3 intension score (p = 0.002, ES₁₋₂ = 1.1, ES₂₋₃ = 0.2) and anger score (p = 0.03, ES₁₋₂ = 0.47, ES₂₋₃ = 0.33) over the study period. Total mood disturbance increased significantly (p = 0.02, ES₁₋₂ = 0.91, ES₂₋₃ = 1.1) from T1 to T3. Between T1-T2, significant relationships were observed between workload and changes in T (r = 0.66, p = 0.003), and T/C ratio (r = 0.62, p = 0.01). There were significant relationships between performance in RSSAbest and training load parameters (workload: r = 0.52, p = 0.03; monotony: r = 0.62, p = 0.01; strain: r = 0.62, p = 0.009). Between T2-T3, there was a significant relationship between Δ% of total mood disturbance and Δ% of YYIR1 (r = −0.54; p = 0.04), RSSAbest (r = 0.58, p = 0.01), SJ (r = −0,55, p = 0.01), T (r = 0.53; p = 0.03), and T/C (r = 0.5; p = 0.04).
Conclusion: An intensive period of congested match play significantly compromised elite soccer players’ physical and mental fitness. These changes were related to psychological but not hormonal parameters; even though significant alterations were detected for selected measures. Mood monitoring could be a simple and useful tool to determine the degree of preparedness for match play during a congested period in professional soccer.
Background/objective
Dry land-training (e.g., plyometric jump training) can be a useful mean to improve swimming performance. This study examined the effects of an 8-week plyometric jump training (PJT) program on jump and sport-specific performances in prepubertal female swimmers.
Methods
Twenty-two girls were randomly assigned to either a plyometric jump training group (PJTG; n = 12, age: 10.01 ± 0.57 years, maturity-offset = -1.50 ± 0.50, body mass = 36.39 ± 6.32 kg, body height = 146.90 ± 7.62 cm, body mass index = 16.50 ± 1.73 kg/m2) or an active control (CG; n = 10, age: 10.50 ± 0.28 years, maturity-offset = -1.34 ± 0.51, body mass = 38.41 ± 9.42 kg, body height = 143.60 ± 5.05 cm, body mass index = 18.48 ± 3.77 kg/m2). Pre- and post-training, tests were conducted for the assessment of muscle power (e.g., countermovement-jump [CMJ], standing-long-jump [SLJ]). Sport-specific-performances were tested using the timed 25 and 50-m front crawl with a diving-start, timed 25-m front crawl without push-off from the wall (25-m WP), and a timed 25-m kick without push-off from the wall (25-m KWP).
Results
Findings showed a significant main effect of time for the CMJ (d = 0.78), the SLJ (d = 0.91), 25-m front crawl test (d = 2.5), and the 25-m-KWP (d = 1.38) test. Significant group × time interactions were found for CMJ, SLJ, 25-m front crawl, 50-m front crawl, 25-m KWP, and 25-m WP test (d = 0.29–1.63) in favor of PJTG (d = 1.34–3.50). No significant pre-post changes were found for CG (p > 0.05).
Conclusion
In sum, PJT is effective in improving muscle power and sport-specific performances in prepubertal swimmers. Therefore, PJT should be included from an early start into the regular training program of swimmers.
This study aimed to investigate the relationship between the acute to chronic workload ratio (ACWR), based upon participant session rating of perceived exertion (sRPE), using two models [(1) rolling averages (ACWRRA); and (2) exponentially weighted moving averages (ACWREWMA)] and the injury rate in young male team soccer players aged 17.1 ± 0.7 years during a competitive mesocycle. Twenty-two players were enrolled in this study and performed four training sessions per week with 2 days of recovery and 1 match day per week. During each training session and each weekly match, training time and sRPE were recorded. In addition, training impulse (TRIMP), monotony, and strain were subsequently calculated. The rate of injury was recorded for each soccer player over a period of 4 weeks (i.e., 28 days) using a daily questionnaire. The results showed that over the course of the study, the number of non-contact injuries was significantly higher than that for contact injuries (2.5 vs. 0.5, p = 0.01). There were also significant positive correlations between sRPE and training time (r = 0.411, p = 0.039), ACWRRA (r = 0.47, p = 0.049), and ACWREWMA (r = 0.51, p = 0.038). In addition, small-to-medium correlations were detected between ACWR and non-contact injury occurrence (ACWRRA, r = 0.31, p = 0.05; ACWREWMA, r = 0.53, p = 0.03). Explained variance (r²) for non-contact injury was significantly greater using the ACWREWMA model (ranging between 21 and 52%) compared with ACWRRA (ranging between 17 and 39%). In conclusion, the results of this study showed that the ACWREWMA model is more sensitive than ACWRRA to identify non-contact injury occurrence in male team soccer players during a short period in the competitive season.
Symptoms of anxiety and depression in young athletes using the Hospital Anxiety and Depression Scale
(2018)
Elite young athletes have to cope with multiple psychological demands such as training volume, mental and physical fatigue, spatial separation of family and friends or time management problems may lead to reduced mental and physical recovery. While normative data regarding symptoms of anxiety and depression for the general population is available (Hinz and Brahler, 2011), hardly any information exists for adolescents in general and young athletes in particular. Therefore, the aim of this study was to assess overall symptoms of anxiety and depression in young athletes as well as possible sex differences. The survey was carried out within the scope of the study "Resistance Training in Young Athletes" (KINGS-Study). Between August 2015 and September 2016, 326 young athletes aged (mean +/- SD) 14.3 +/- 1.6 years completed the Hospital Anxiety and Depression Scale (HAD Scale). Regarding the analysis of age on the anxiety and depression subscales, age groups were classified as follows: late childhood (12-14 years) and late adolescence (15-18 years). The participating young athletes were recruited from Olympic weight lifting, handball, judo, track and field athletics, boxing, soccer, gymnastics, ice speed skating, volleyball, and rowing. Anxiety and depression scores were (mean +/- SD) 4.3 +/- 3.0 and 2.8 +/- 2.9, respectively. In the subscale anxiety, 22 cases (6.7%) showed subclinical scores and 11 cases (3.4%) showed clinical relevant score values. When analyzing the depression subscale, 31 cases (9.5%) showed subclinical score values and 12 cases (3.7%) showed clinically important values. No significant differences were found between male and female athletes (p >= 0.05). No statistically significant differences in the HADS scores were found between male athletes of late childhood and late adolescents (p >= 0.05). To the best of our knowledge, this is the first report describing questionnaire based indicators of symptoms of anxiety and depression in young athletes. Our data implies the need for sports medical as well as sports psychiatric support for young athletes. In addition, our results demonstrated that the chronological classification concerning age did not influence HAD Scale outcomes. Future research should focus on sports medical and sports psychiatric interventional approaches with the goal to prevent anxiety and depression as well as teaching coping strategies to young athletes.
Purpose
We quantified the acute and chronic effects of whole body vibration on athletic performance or its proxy measures in competitive and/or elite athletes.
Methods
Systematic literature review and meta-analysis.
Results
Whole body vibration combined with exercise had an overall 0.3 % acute effect on maximal voluntary leg force (−6.4 %, effect size = −0.43, 1 study), leg power (4.7 %, weighted mean effect size = 0.30, 6 studies), flexibility (4.6 %, effect size = −0.12 to 0.22, 2 studies), and athletic performance (−1.9 %, weighted mean effect size = 0.26, 6 studies) in 191 (103 male, 88 female) athletes representing eight sports (overall effect size = 0.28). Whole body vibration combined with exercise had an overall 10.2 % chronic effect on maximal voluntary leg force (14.6 %, weighted mean effect size = 0.44, 5 studies), leg power (10.7 %, weighted mean effect size = 0.42, 9 studies), flexibility (16.5 %, effect size = 0.57 to 0.61, 2 studies), and athletic performance (−1.2 %, weighted mean effect size = 0.45, 5 studies) in 437 (169 male, 268 female) athletes (overall effect size = 0.44).
Conclusions
Whole body vibration has small and inconsistent acute and chronic effects on athletic performance in competitive and/or elite athletes. These findings lead to the hypothesis that neuromuscular adaptive processes following whole body vibration are not specific enough to enhance athletic performance. Thus, other types of exercise programs (e.g., resistance training) are recommended if the goal is to improve athletic performance.