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Purpose: There is little known about the state of teacher education programs in this field. The aim of this article is to provide a descriptive analysis of physical education and health education teacher education programs in the United States. Method: Using published curriculums, a census of active undergraduate teacher education programs and a more in-depth analysis of one program from each state based on interviews with program coordinators was conducted. Findings: Data are reported across nine categories: (a) institution and program classifications, (b) degree designations, (c) degree and major’s hours, (d) enrollment, (e) program status and trends, (f) admission and graduation requirements, (g) curricular time, (h) faculty demographics, and (i) health education. Conclusions: The data show that there is a broad interpretation of what counts as physical and health teacher education in terms of curriculum, and there are significant and pressing challenges for the field to address moving forward.

Purpose: The aim of this study was to assess the interaction of kinematic, kinetic, and energetic variables as speed predictors in adolescent swimmers in the front-crawl stroke. Design: Ten boys (mean age [SD] = 16.4 [0.7] y) and 13 girls (mean age [SD] = 14.9 [0.9] y) were assessed. Methods: The swimming performance indicator was a 25-m sprint. A set of kinematic, kinetic (hydrodynamic and propulsion), and energetic variables was established as a key predictor of swimming performance. Multilevel software was used to model the maximum swimming speed. Results: The final model identified time (estimate = −0.008, P = .044), stroke frequency (estimate = 0.718, P < .001), active drag coefficient (estimate = −0.330, P = .004), lactate concentration (estimate = 0.019, P < .001), and critical speed (estimate = −0.150, P = .035) as significant predictors. Therefore, the interaction of kinematic, hydrodynamic, and energetic variables seems to be the main predictor of speed in adolescent swimmers. Conclusions: Coaches and practitioners should be aware that improvements in isolated variables may not translate into faster swimming speed. A multilevel evaluation may be required for a more effective assessment of the prediction of swimming speed based on several key variables rather than a single analysis.

This research provides a review of seated shot put alongside new data from the Tokyo 2020 Paralympic Games with the aim to understand the latest trends in equipment within a recently established rule set and how key equipment variables may impact performance for athletes in different classifications. First, a review of the literature found that the throwing pole is a key equipment aid that is not well understood, in part due to limitations in testing design. New data from the 2020 Paralympic Games showed inconsistent trends for the use of the throwing pole among athletes, particularly in transitionary classes (F33–34 and F54–55). A two-way analysis of variance found a main effect of classification on performance (p < .001), as well as an interaction effect between pole use and classification on performance (p < .05). Notably, pole users are seen to perform better than non–pole users in Class F32 (p < .05).

Purpose: The purpose of the current investigation was to retrospectively assess possible differences in physiological performance characteristics between junior cyclists signing a contract with an under-23 (U23) development team versus those failing to sign such a contract. Methods: Twenty-five male junior cyclists (age: 18.1 [0.7] y, stature: 181.9 [6.0] cm, body mass: 69.1 [7.9] kg, peak oxygen uptake: 71.3 [6.2] mL·min⁻¹·kg⁻¹) were assigned to this investigation. Between September and October of the last year in the junior category, each cyclist performed a ramp incremental exercise test to determine certain physiological performance characteristics. Subsequently, participants were divided in 2 groups: (1) those signing a contract with a U23 development team (JUNIOR_U23) and (2) those failing to sign such a contract (JUNIOR_NON-U23). Unpaired t tests were used to assess possible between-groups differences in physiological performance characteristics. The level of statistical significance was set at P < .05 two tailed. Results: No significant between-groups differences in submaximal (ie, gas exchange threshold, respiratory compensation point) and maximal physiological performance characteristics (ie, peak work rate, peak oxygen uptake) expressed in absolute values (ie, L·min⁻¹, W) were observed (P > .05). However, significant between-groups differences were observed when physiological performance characteristics were expressed relative to the cyclists’ body weights (P < .05). Conclusions: The current investigation showed that junior cyclists stepping up to a U23 development team might be retrospectively differentiated from junior cyclists not stepping up based on certain physiological performance characteristics, which might inform practitioners and/or federations working with young cyclists during the long-term athletic development process.

Purpose: The primary objective was to assess the performance benefits of caffeine (CAF) supplementation in habitual users. Importantly, this investigation was designed to account for the potential confounding effects of CAF withdrawal (CAF_W), which are inherent and common in previous work. Methods: Ten CAF-consuming (394 [146] mg·d⁻¹) recreational cyclists (age 39.1 [14.9] y; maximum oxygen consumption 54.2 [6.2] mL·kg^–1·min^–1) completed four 10-km time trials (TTs) on a cycle ergometer. On each trial day, 8 hours before reporting to the laboratory, subjects consumed 1.5 mg·kg^–1 CAF to prevent withdrawal (no withdrawal [N]) or a placebo (PLA; withdrawal [W]). Then, 1 hour prior to exercise, they received either 6 mg·kg^–1 CAF or PLA. These protocols were repeated 4 times, employing all combinations of N/W and CAF/PLA. Results: CAF_W did not impair TT power output (PLA_W vs PLA_N P = .13). However, preexercise CAF only improved TT performance when compared to PLA in the W condition (CAF_N vs PLA_W P = .008, CAF_W vs PLA_W P = .04), not when W was mitigated (PLA_N vs CAF_N P = .33). Conclusions: These data indicate that preexercise CAF only improves recreational cycling performance when compared to bouts preceded by CAF abstinence, suggesting that habitual users may not benefit from 6 mg·kg^–1 of CAF and that previous work may have overstated the value of CAF supplementation for habitual users. Future work should examine higher doses of CAF for habitual users.

Aim: To quantify the physiological demands and impact of muscle function t of the Fran workout, one of the most popular CrossFit benchmarks. Methods: Twenty experienced CrossFitters—16 male: 29 (6) years old and 4 female: 26 (5) years old— performed 3 rounds (with 30-s rests in between) of 21–21, 15–15, and 9–9 front squats to overhead press plus pull-up repetitions. Oxygen uptake and heart rate were measured at baseline, during the workout, and in the recovery period. Rating of perceived exertion, blood lactate, and glucose concentrations were assessed at rest, during the intervals, and in the recovery period. Muscular fatigue was also monitored at rest and at 5 minutes, 30 minutes, and 24 hours postexercise. Repeated-measures analysis of variance was performed to compare time points. Results: Aerobic (52%–29%) and anaerobic alactic (30%–23%) energy contributions decreased and the anaerobic lactic contribution increased (18%–48%) across the 3 rounds of the Fran workout. Countermovement jump height decreased by 8% (−12 to −3) mean change (95% CI), flight duration by 14% (−19 to −7), maximum velocity by 3% (−5 to −0.1), peak force 4% (−7 to −0.1), and physical performance (plank prone 47% [−54 to −38]) were observed. Conclusions: It appears that the Fran workout is a physically demanding activity that recruits energy from both aerobic and anaerobic systems. This severe-intensity workout evokes substantial postexercise fatigue and corresponding reduction in muscle function.