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Ashleigh M. Johnson, Kelley Pettee Gabriel, Nalini Ranjit, Harold W. Kohl III, and Andrew E. Springer

Background: In response to conflicting findings for activity levels across sociodemographic groups, this study examined differences in adolescents’ in-school, out-of-school, and weekend physical activity (PA) by sociodemographic subgroups using representative US data. Methods: Data were obtained from the Family Life, Activity, Sun, Health, and Eating study. Multiple regression models compared in-school, out-of-school, and weekend PA by gender and race/ethnicity, and examined potential modification of associations by grade (middle vs high school) and socioeconomic status (lower vs higher). Results: Final analytic sample was 1413 adolescents (Mean age = 14.5 y, 51.3% female, 64.5% white). Compared with whites, in-school PA was significantly higher among blacks and those classified as other race/ethnicity for middle school (69.8 and 71.0, respectively, vs 66.4 min/d), and among Hispanics for high school (52.7 vs 48.4 min/d). Hispanics’ (vs whites’) out-of-school PA was significantly lower for middle school (63.7 vs 66.6 min/d), but higher for high school (54.0 vs 51.8 min/d). In-school PA was significantly higher among adolescents of lower (vs higher) socioeconomic status among males and Hispanics (all Ps < .05). Conclusions: The relation of race/ethnicity with PA varies by grade and time of day/week. Socioeconomic status findings contradict previously reported findings. Efforts to increase PA based on sociodemographic disparities should consider potential interaction effects.

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Shaun Abbott, Goshi Yamauchi, Mark Halaki, Marcela Torres Castiglioni, James Salter, and Stephen Cobley

Purpose: The study aimed to (1) accurately examine longitudinal relationships between maturity status and both technical skill indices and performance in Australian male (N = 64) age-group Front-crawl swimmers (10–15 y) and (2) determine whether individual differences in maturation influenced relationships between technical skill level and swimming performance. Methods: A repeated-measures design was used to assess maturity status and performance on 200-m Front-crawl trial across 2 competition seasons (2018–2020). Assessments were made on 3 to 5 occasions (median = 3) separated by approximately 4 months. Average horizontal velocity and stroke frequency were used to calculate technical skill indices, specifically stroke index, and arm propelling efficiency. Relationships between variables were assessed using linear mixed models, identifying fixed, and random effect estimates. Results: Curvilinear trends best described significant longitudinal relationships between maturity status with horizontal velocity (F = 10.33 [1, 233.77]; P = .002) and stroke index (F = 5.55 [1, 217.9]; P = .02) during 200-m Front-crawl trials. Maturity status was not significantly related to arm propelling efficiency (P = .08). However, arm propelling efficiency was an independent predictor of Front-crawl velocity (F = 55.89 [1, 210.45]; P < .001). Conclusions: Maturity status predicted assessment of swimmer technical skill (stroke index) and swimming performance. However, technical skill accessed via arm propelling efficiency was independent of maturation and was predictive of performance. Maturity status influences performance evaluation based on technical skill and velocity. Findings highlight the need to account for maturation and technical skill in age-group swimmers to better inform swimmer evaluation.

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Jaime Fernandez-Fernandez, Alejandro Lopez-Valenciano, Jose Vicente Garcia-Tormo, David Cabello-Manrique, and Juan García-López

Purpose: To analyze the influence of playing 2 consecutive prolonged badminton matches on the shoulder strength and range of motion (ROM) of young players. Methods: Sixteen elite junior badminton players (12 males and 4 females; mean (SD): age 16.2 [0.8] years, body mass 63.5 [6.6] kg, height 173.2 [6.3] cm) participated in a cross-sectional study. Shoulder internal (IR)/external rotation (ER) ROM and IR/ER strength measures were conducted before and after 2 consecutive prolonged (ie, 35 min) matches and 12 hours after the second match. Results: After consecutive matches, IR strength of the dominant side and ER strength of the dominant and nondominant sides (effect size [ES] = 0.20–0.57) were reduced. Shoulder total ROM of the dominant side was decreased (ES = 0.80), while on the nondominant side, IR (ES = 0.66) was also decreased. After 12 hours, results showed decreased values in the IR/ER strength of the dominant side (ES = 0.36–1.00), as well as ER of both dominant and nondominant sides (ES = 0.30–0.59). IR ROM of the nondominant side (ES = 0.69) was also decreased. Conclusion: Present results showed that 2 consecutive matches on the same day with brief rest periods led to significant impairments in shoulder strength and ROM levels. These data can potentially elucidate the need for shoulder-specific training and recovery strategies prior to or during competitions.

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Simone Dohle, Mitch J. Duncan, and Tamara Bucher

Many exercise-based weight-loss interventions result in considerably less weight loss than predicted. One possible explanation could be that people have certain beliefs about the interplay of exercise and food that also influence their eating behavior, such as the belief that food is a reward for exercise. The current research outlines a systematic multiphase process to develop a psychometrically sound scale to assess these beliefs. In Study 1, regular exercisers (N = 520) completed an exploratory questionnaire on their beliefs related to diet and exercise. In Study 2 (N = 380), the factor structure of the newly developed scale was corroborated by confirmatory factor analysis. In addition, a test–retest (N = 166) was used to confirm reliability and stability. In sum, the Diet-Related Beliefs of Exercisers Scale with its four subscales (“Refrain from Eating,” “Food as Reward,” “Healthy Eating,” and “Nutritional Replenishment”) represents a valid and reliable measure of exercisers’ diet-related beliefs.

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Daniel Crago, John B. Arnold, and Christopher Bishop

Purpose: To determine the effect of manipulating foot longitudinal arch motion with different-stiffness foot orthoses on running economy (RE) in runners with flat-arched feet and if changes in arch deformation and recoil were associated with changes in RE. Methods: Twenty-three recreational distance runners performed 5-minute submaximal treadmill runs at 12 km·h−1, in the following 3 conditions in a randomized order: (1) footwear only, (2) flexible orthoses (reduced arch thickness), and (3) standard orthoses. The RE (submaximal steady-state oxygen consumption [VO2submax]) and sagittal arch range of motion were compared among conditions using a repeated-measures analysis of variance and effect sizes (Cohen d). Pearson correlation coefficients were used to determine the association between the change in the sagittal arch range of motion and VO2submax. Results: Compared with standard orthoses, the mean VO2submax was significantly lower in both the flexible orthoses (−0.8 mL·kg−1·min−1, P < .001, d = 0.35) and footwear-only conditions (−1.2 mL·kg−1·min−1, P < .001, d = 0.49). The change in VO2submax between the flexible orthoses and footwear-only conditions was significantly positively correlated with the change in sagittal arch range of motion (r = .591, P = .005). Conclusion: Conventional foot orthoses were associated with poorer RE compared with flexible orthoses and footwear alone. Changes in arch deformation were positively correlated to changes in oxygen consumption, indicating that foot orthoses that limit arch deformation and recoil degrade RE. Foot orthoses that facilitate energy storage and release in the foot longitudinal arch may be advisable for athletes prescribed these devices for clinical purposes to maintain optimal running performance.

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Tomás T. Freitas, Lucas A. Pereira, Valter P. Reis, Victor Fernandes, Pedro E. Alcaraz, Paulo H.S.M. Azevedo, and Irineu Loturco

Purpose: To investigate the effects of a match-congested period on straight and curve sprint performance, change of direction (COD) speed and deficit, vertical jumping ability, and half-squat (HS) mean propulsive power (MPP) output in young soccer players. Methods: A total of 15 under-20 elite male soccer players participated in 14 matches over 8 weeks. The following assessments were performed before and after the congested fixture period: squat and countermovement jumps, 17-m linear sprint, curve sprint test for the “good” (CSGS) and “weak” (CSWS) sides, modified 17-m Zigzag test, and HS MPP. Magnitude-based inferences and a paired t test were used to analyze pre–post changes in the assessed variables. Results: Very likely (P < .05) decreases were noticed in 17-m sprint velocity (effect size [ES] [90% confidence limit; CL], −0.56 [−0.32 to −0.81]) and CSGS (ES [90% CL], −0.72 [−0.40 to 1.03]) after the 8-week period. A possible but nonsignificant impairment was revealed in CSWS (ES [90% CL], −0.18 [0.03 to −0.39]), and countermovement jump (ES [90% CL], −0.21 [−0.54 to 0.12]). Zigzag velocity (ES [90% CL], −2.90 [−2.45 to −3.36]) and COD deficit (ES [90% CL], 0.86 [0.52 to 1.20]) were almost certainly and significantly (P < .05) reduced and increased, respectively, after the match-congested period. An almost certain and significant (P < .05) reduction was found in HS MPP (ES [90% CL], −1.18 [−0.76 to −1.61]). Conclusions: Straight and curve sprint velocity, COD speed and deficit, and HS MPP were impaired after the match-congested period. Vertical jump height was possibly decreased. Seasonal phases comprising high volumes of soccer-specific training and competition seem to be detrimental to speed–power qualities in under-20 elite soccer players.

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Kobe M. Vermeire, Freek Van de Casteele, Maxim Gosseries, Jan G. Bourgois, Michael Ghijs, and Jan Boone

Purpose: Numerous methods exist to quantify training load (TL). However, the relationship with performance is not fully understood. Therefore the purpose of this study was to investigate the influence of the existing TL quantification methods on performance modeling and the outcome parameters of the fitness-fatigue model. Methods: During a period of 8 weeks, 9 subjects performed 3 interval training sessions per week. Performance was monitored weekly by means of a 3-km time trial on a cycle ergometer. After this training period, subjects stopped training for 3 weeks but still performed a weekly time trial. For all training sessions, Banister training impulse (TRIMP), Lucia TRIMP, Edwards TRIMP, training stress score, and session rating of perceived exertion were calculated. The fitness-fatigue model was fitted for all subjects and for all TL methods. Results: The error in relating TL to performance was similar for all methods (Banister TRIMP: 618 [422], Lucia TRIMP: 625 [436], Edwards TRIMP: 643 [465], training stress score: 639 [448], session rating of perceived exertion: 558 [395], and kilojoules: 596 [505]). However, the TL methods evolved differently over time, which was reflected in the differences between the methods in the calculation of the day before performance on which training has the biggest positive influence (range of 19.6 d). Conclusions: The authors concluded that TL methods cannot be used interchangeably because they evolve differently.

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Amador García-Ramos, Jonathon Weakley, Danica Janicijevic, and Ivan Jukic

Purpose: To explore the effect of several methodological factors on the number of repetitions performed before and after reaching certain velocity loss thresholds (VLTs). Method: Fifteen resistance-trained men (bench press 1-repetition maximum = 1.25 [0.16] kg·kg−1) performed with maximum intent a total of 182 sets (77 short sets [≤12 repetitions] and 105 long sets [>12 repetitions]) leading to failure during the Smith machine bench press exercise. Fifteen percent, 30%, and 45% VLTs were calculated, considering 2 reference repetitions (first and fastest repetitions) and 2 velocity variables (mean velocity [MV] and peak velocity [PV]). Results: The number of repetitions performed before reaching all VLTs were affected by the reference repetition and velocity variable (P ≤ .001). The fastest MV and PV during the short sets (75.3%) and PV during the long sets (72.4%) were predominantly observed during the first repetition, while the fastest MV during long sets was almost equally distributed between the first (37.1%) and second repetition (40.0%). Failure occurred before reaching the VLTs more frequently using PV (4, 8, and 33 occasions for 15%, 30%, and 45% VLTs, respectively) than MV (only 1 occasion for the 45% VLT). The participants rarely produced a velocity output above a VLT once this threshold was exceeded for the first time (≈10% and 30% of occasions during the short and long sets, respectively). Conclusions: The reference repetition and velocity variable are important factors to consider when implementing VLTs during resistance training. The fastest repetition (instead of the first repetition) and MV (instead of PV) are recommended.

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Alexandra M. Coates, Jordan A. Berard, Trevor J. King, and Jamie F. Burr

Context: The physiological determinants of ultramarathon success have rarely been assessed and likely differ in their contributions to performance as race distance increases. Purpose : To examine predictors of performance in athletes who completed either a 50-, 80-, or 160-km trail race over a 20-km loop course on the same day. Methods: Measures of running history, aerobic fitness, running economy, body mass loss, hematocrit alterations, age, and cardiovascular health were examined in relation to race-day performance. Performance was defined as the percentage difference from the winning time at a given race distance, with 0% representing the fastest possible time. Results: In the 50-km race, training volumes, cardiovascular health, aerobic fitness, and a greater loss of body mass during the race were all related to better performance (all P < .05). Using multiple linear regression, peak velocity achieved in the maximal oxygen uptake test (β = −11.7, P = .002) and baseline blood pressure (β = 3.1, P = .007) were the best performance predictors for the men’s 50-km race (r = .98, r 2 = .96, P < .001), while peak velocity achieved in the maximal oxygen uptake test (β = −13.6, P = .001) and loss of body mass (β = 12.8, P = .03) were the best predictors for women (r = .94, r 2 = .87, P = .001). In the 80-km race, only peak velocity achieved in the maximal oxygen uptake test predicted performance (β = −20.3, r = .88, r 2 = .78, P < .001). In the 160-km race, there were no significant performance determinants. Conclusions: While classic determinants of running performance, including cardiovascular health and running fitness, predict 50-km trail-running success, performance in longer-distance races appears to be less influenced by such physiological parameters.