European journal of sport science最新文献

Physical inactivity is considered to increase depressive symptoms. There are also studies reporting that overly strenuous physical activity can negatively affect a person's mental state. Insomnia, which is associated with lower levels of physical activity and increased sleep reactivity, is also known to be associated with depression. However, the directionalities of the associations among these factors remain unclear. The aim of this study was to investigate whether both insufficient and excessive physical activity affect depressive symptoms through sleep reactivity and sleep quality. Between April 2017 and April 2018, self-administered surveys were provided to adult volunteers through our acquaintances at Tokyo Medical University. The study included 526 volunteers whose responses were considered valid. Demographic information, results of the International Physical Activity Questionnaire, the Ford Insomnia Response to Stress Test (FIRST), the Pittsburgh Sleep Quality Index, and the Patient Health Questionnaire-9 (PHQ-9) were used for analysis. Quadratic regression was performed to examine whether the PHQ-9 score was significantly explained by physical activity duration in a U-shaped curve. Path analysis was performed to identify indirect effects. Quadratic regression indicated the presence of an optimal physical activity duration (25.7 h/week) that was related to the lowest PHQ-9 score, and both insufficient and excessive physical activity could be expressed as a Difference from Optimal Physical Activity Duration (DOP). Path analysis demonstrated that DOP increased the PHQ-9 score through the FIRST score.These findings indicate that deviation from the optimal physical activity duration worsens depressive symptoms through high sleep reactivity.

This study investigated the relationships among alexithymia, impulsivity, and aggression in mixed martial arts (MMA) athletes. Participants (N = 60, 51 men, and 9 women) were recruited from MMA clubs and training centers in Lebanon. They completed self-report measures including the Toronto Alexithymia Scale-20 (TAS-20) to assess alexithymia, the Barratt Impulsiveness Scale (BIS-11) to measure impulsivity, and the Buss-Perry Aggression Scale short form (BPAS-SF) to evaluate aggression tendencies. Results indicated that alexithymia was positively correlated with impulsivity (attentional, r = 0.41, and p < 0.01; motor, r = 0.32, and p < 0.05), aggression (r = 0.49 and p < 0.001), and its various forms of aggression (physical, verbal, anger, and hostility). Mediation analyses showed that attentional impulsivity significantly mediated the link between alexithymia and aggression (β = 0.10 and 95% CI [0.02, 0.22]), whereas motor impulsivity accounted for a smaller portion of the effect (β = 0.08 and 95% CI [0.00, 0.22]). The direct effect remained significant (β = 0.28 and 95% CI [0.03, 0.52]), indicating partial mediation. These findings underscore the importance of emotional and behavioral regulation in competitive sports contexts, highlighting potential implications for athlete development programs.

Although acute exercise can have positive effects on individual's cognitive functioning, performing ultra-endurance race can diminish these benefits. No previous studies have examined if cognitive decline can be estimated by subjective perception; thus, changes in cognitive functions and their relation to subjectively reported parameters (SRPs) were evaluated. Before, immediately after, and ~20h post ultra-endurance race, 43 amateur cyclists filled out questionnaire rating SRPs and performed digit symbol test (DST), stroop test (ST), finger tapping test (FTT). Changes between three timepoints were determined by one-way repeated measures ANOVA or Friedman test. Mixed model regression was used to test relationship between cognitive functions and SRPs. DST results exhibit no changes in post-race measurement, but an improvement of performance in recovery period was observed for correct number count (increase by 8,6 taps per 2 min, p < 0.001) and mean reaction time (decrease by 190 ms, p < 0.001). In ST, average time for correct reactions post-race increased in all three stages by 22, 35, and 68 ms, respectively (p < 0.001), with no changes in accuracy. For FTT, non-dominant hand showed decline in performance post-race. Changes in several SRPs (effort to answer the questions, physical strength, sleep quality, and stress levels during the previous day) were associated with changes in participants' cognitive performance. Short-term decline in cognitive functions was observed after ultra-endurance race, indicating possible increase in accident risk for participants. SRPs assessing sleep, current effort, stress, and physical strength, but not fatigue, may be reliable predictors of these changes.

Golf demands sustained physical effort and effective fatigue management, especially in competitive play. Allowing players to ride golf carts in elite play has raised concerns about potential performance advantages, yet well-controlled studies are lacking. This study examined the effects of golf cart use on physiological, physical and cognitive outcomes in competitive golfers. Sixteen males (mean age: 21 ± 3 years; handicap: 2.3 ± 3.7) completed two randomised competitive rounds on a championship course (6587m; 19°C), either walking with a caddie or riding a golf cart. Physiological measures included activity energy expenditure (Actiheart), core temperature, heart rate and perceived exertion (0–100). Physical outcomes were step count, carry distance, clubhead speed, ball speed and muscle power. Cognitive workload (NASA-Task Load Index) was assessed post-round. The step count and activity energy expenditure were significantly higher for walking than using a golf cart (17,007 ± 1708 vs. 6274 ± 1111 steps; 880 ± 279 vs. 456 ± 155 kilocalories). Core temperature was higher for walking at holes 6, 12, and 18 (p = 0.022). The heart rate increased across the round when walking but decreased while using a cart (p < 0.01), and post-round exertion was higher for walking (41 ± 19 vs. 25 ± 14 and p < 0.001). Carry distance, clubhead and ball speed did not differ. NASA-Task Load Index subscales of physical demand and performance (reverse scored) were higher for walking. Relative to walking, golf cart use lowered internal physiological and external physical load, without impairing muscle power or shot performance. Cognitively, walking imposed higher physical strain and reduced perceived performance. Further research should explore whether these physiological, physical and cognitive outcomes impact performance across multiday tournaments.

The structure of a talent identification and development system (TIDS), in terms of its starting, entry, and exit points is an important consideration for sporting organisations. Early talent identification decisions can be ineffective due to unpredictable and individually variable talent development. Physical qualities are a key contributor to performance in rugby league. Therefore, understanding physical development differences between age groups can inform the structure of the rugby league TIDS by highlighting key phases of development. Between-player variability in physical development must also be considered to understand the generalisability of age-group trends. Consequently, this study aimed to compare rates of physical development between annual age groups (i.e., U15, 16, 17, 18) in 261 youth rugby league players from multiple clubs, considering individual differences in development rates. Latent growth curve analysis was used to model rates of physical development for size (i.e., height, mass), strength, power, speed, and cardiovascular fitness in each age group. Results showed that U15s had significantly faster rates of development for body size and strength qualities compared with all older age groups, with large between-player variability. No differences were apparent between age groups for power, speed, or cardiovascular fitness. These findings suggest that early talent identification and (de)selection decisions may ignore the potential development of body size and strength qualities, which occurs at individually variable rates. Such findings can inform the structure and design of the rugby league TIDS by highlighting expected rates of physical development based on players' age groups.

Cycling performance is strongly influenced by aerodynamics, with most resistive drag forces being attributed to the rider. The Body Rocket device (BR) is an on-bike sensor system that uses the same load cell technology as a wind tunnel, directly measuring real-time aerodynamic resistance (CdA) from the rider. This study aimed to measure the validity and reliability of CdA measures from BR in two experiments. In Experiment 1, validity of BR was assessed in wind tunnel with a rod and discs of known diameter attached to the end change CdA by a known amount. Experiment 2, examined the validity and reliability of BR in a 250m indoor velodrome. Ten cyclists performed 7 identical efforts at ∼40 km/h for 10 laps of the velodrome, the first 4 to assess validity with the same rod and discs used in the wind tunnel, with the remaining 3 without changes in resistance or the riders changing position to assess reliability. Validity results demonstrated BR measured CdA to be strongly correlated with calculated CdA from the disc addition (r = 0.99), with the smallest identified changes being 0.002 m² across wind tunnel and velodrome. Good agreement was found between theoretical and measured CdA with varying disc sizes (95% limits of agreement = −0.012 to 0.009 m²). A high level of reliability was demonstrated during Experiment 2 with strong intraclass correlation (0.99) and small coefficient of variation (1.67%). Findings of this study demonstrate BR is a valid and reliable device for measuring real-time CdA during cycling in an indoor velodrome.

The purpose of this study was to investigate the associations of fast maximal dynamic strength (MDS) and reactive strength capacity with physical match performance. Seventeen male semi-professional soccer players (age = 20.2 ± 1.3 years) performed the countermovement jump (CMJ), drop jump and a modified version of the single-leg triple crossover hop (CO_av) tests during the season to measure their fast MDS and reactive strength capacities. Strength capacities were compared with the physical match performance measured through Global Positioning System (GPS) in official matches ± 14 days after the test day. The significance level was set at p < 0.05. CMJ significantly predicted the relative number of high-intensity accelerations >4 m/s⁻² (ACC_>4) (R² = 42.9%; p < 0.01) and maximum acceleration (ACC_max) (R² = 30.6%; p < 0.05). The transformed modified reactive strength index (log₁₀ (mRSI)) also significantly predicted ACC_>4 (R² = 37.1%; p < 0.01) and ACC_max (R² = 26.3%; p < 0.05). CO_av significantly predicted the worst-case scenario for player load (WCS_PL) (R² = 27.0%; p < 0.05). The present results suggest that different lower-body strength capacities are associated with acceleration match performance.

This study investigated whether the responses of upper and lower limb muscle strength and size to resistance training (RT) are reproducible across two RT periods. Untrained males and females (age 32 ± 5 years) were randomly assigned to RT (n = 20) or a control group (n = 27). The RT group completed two identical 10-week RT periods separated by 10 weeks of detraining. The control group underwent a 10-week non-RT period. Before and after each period, the muscle cross-sectional area (CSA) of the vastus lateralis (VL) and biceps brachii (BB) was measured by ultrasound. One-repetition maximum (1RM) was measured in leg press (LP) and biceps curl (BC). Minimal detectable changes were determined. The RT group showed greater gains (p < 0.001) in muscle size and strength than the control group, with variability observed among individual responses. The reproducibility of responses within-participants was demonstrated by correlations (p ≤ 0.001) between the first and second RT periods in VLCSA (r = 0.697), BBCSA (r = 0.761), and LP1RM (r = 0.671), with a trend for BC1RM (r = 0.393 and p = 0.095). Nonresponders were identified, but none were detected in both RT periods for more than one variable. First RT correlated negatively (p < 0.05) with subsequent detraining in BBCSA (r = −0.673) and LP1RM (r = −0.488), with a trend for VLCSA (r = −0.422 and p = 0.072). In conclusion, responses to RT are reproducible when RT is repeated, indicating that the individuality of the training response has a physiological origin. Nonresponsiveness is rare and should not be justified solely by one variable. Responses to detraining suggest that greater RT gains may also diminish faster.

This study aimed to compare respiratory patterns and gas exchange during tennis and treadmill running at similar oxygen uptake. On three experimental days, 15 elite players (7 female, 8 male) completed a standardized tennis protocol (TP), a treadmill-based incremental running test (RT), and a metabolically matched running protocol (RP). TP (Day 1) included low or high running loads (RL, RH) and low or high stroke velocities (SL, SH) which were combined in four incremental ball-machine stages (TP₁:RL + SL; TP₂:RL + SH; TP₃:RH + SL; TP₄:RH + SH). RT (Day 2) determined running speeds matching the oxygen uptake of each TP stage. RP (Day 3) replicated TP's mean oxygen consumption and stage duration through treadmill running. Metabolic and respiratory responses (portable spirometry) and external loads (stroke velocity) were compared between TP and RP. In tennis, mean oxygen uptake (p < 0.001), energy expenditure (p < 0.001), and respiratory exchange ratio (p < 0.001) as well as respiratory responses increased significantly between Stage 1–4. No differences in metabolic responses as well as in breathing frequency (bf), ventilation ($$’E), inspiration (tI), and expiration time (tE) were observed between TP and RP. In contrast, the number of breathing plateaus per stage (NP) was significantly higher in TP compared to RP during TP₂ (5.9 ± 3.8 vs. 0.4 ± 0.5 times, p < 0.001), TP₃ (2.6 ± 2.7 vs. 0.3 ± 0.6 times, p = 0.04), and TP₄ (4.6 ± 4.1 vs. 0.3 ± 0.6 times, p < 0.001). Breathing plateaus appear characteristic for tennis when hitting hard without affecting metabolism. Exploring individual breathing patterns can be recommended in practice.