Search Results

Purpose: To assess the effects of a 7-wk low-volume, high-intensity training (HIT) intervention on performance parameters in national-level youth swimmers. Methods: Sixteen swimmers (age 15.8 [1.0] y, age at peak height velocity 12.9 [0.6] y, 100-m freestyle 61.4 [4.1] s) were randomly assigned to an HIT group or a low-intensity, high-volume training (HVT) group that acted as a control. The HIT group reduced their weekly training volume of zone 1 (low-intensity) training by 50% but increased zone 3 (high-intensity) training by 200%. The HVT group performed training as normal. Pretest to posttest measures of physiological performance (velocity at 2.5- and 4-mM blood lactate [velocity_2.5mM and velocity_4mM] and peak blood lactate), biomechanical performance (stroke rate, stroke length [SL], and stroke index [SI] over a 50- and 400-m freestyle), and swimming performance (50-, 200-, and 400-m freestyle) were assessed. Results: There were no significant 3-way interactions between time, group, and sex for all performance parameters (P > .05). There was a significant 2-way interaction between time and group for velocity_4mM (P = .02, ${\eta }_{\mathrm{p}}^2=.40$ ), SL₅₀ (P = .03, ${\eta }_{\mathrm{p}}^2=.37$ ), and SI₅₀ (P = .03, ${\eta }_{\mathrm{p}}^2=.39$ ). Velocity_4mM decreased in the HIT group but increased in the HVT group while SL₅₀ and SI₅₀ decreased in the HVT group. Conclusions: A 7-wk HIT intervention was neither beneficial nor detrimental to performance parameters; however, the HIT group completed 6 h (17.0 km) of swimming per week compared with 12 h (33.4 km) per week for the HVT group.

Balance and anaerobic performance are key attributes related to horse-racing performance, but research on the impact of making weight for racing on these parameters remains unknown. The purpose of this study was to investigate the effects of rapid weight loss in preparation for racing on balance and anaerobic performance in a group of jockeys.

Purpose: Insufficient recovery can lead to a decrease in performance and increase the risk of injury and illness. The aim of this study was to evaluate salivary cortisol as a marker of recovery in elite rugby union players. Method: Over a 10-wk preseason training period, 19 male elite rugby union players provided saliva swabs biweekly (Monday and Friday mornings). Subjective markers of recovery were collected every morning of each training day. Session rating of perceived exertion (sRPE) was taken after every training session, and training load was calculated (sRPE × session duration). Results: Multilevel analysis found no significant association between salivary cortisol and training load or subjective markers of recovery (all P > .05) over the training period. Compared with baseline (wk 1), Monday salivary cortisol significantly increased in wk 4 (14.94 [7.73] ng/mL; P = .04), wk 8 (16.39 [9.53] ng/mL; P = .01), and wk 9 (15.41 [9.82] ng/mL; P = .02), and Friday salivary cortisol significantly increased in wk 5 (14.81 [8.74] ng/mL; P = .04) and wk 10 (15.36 [11.30] ng/mL; P = .03). Conclusions: The significant increase in salivary cortisol on certain Mondays may indicate that players did not physically recover from the previous week of training or match at the weekend. The increased Friday cortisol levels and subjective marker of perceived fatigue indicated increased physiological stress from that week’s training. Regular monitoring of salivary cortisol combined with appropriate planning of training load may allow sufficient recovery to optimize training performance.

Context: Stress responses in athletes can be attributed to training and competition, where increased physiological and psychological stress may negatively affect performance and recovery. Purpose: To examine the relationship between training load (TL) and salivary biomarkers immunoglobulin A (IgA), alpha-amylase (AA), and cortisol across a 16-wk preparation phase and 10-d competition phase in Paralympic swimmers. Methods: Four Paralympic swimmers provided biweekly saliva samples during 3 training phases—(1) normal training, (2) intensified training, and (3) taper—as well as daily saliva samples in the 10-d Paralympic competition (2016 Paralympic Games). TL was measured using session rating of perceived exertion. Results: Multilevel analysis identified a significant increase in salivary immunoglobulin A (sIgA: 94.98 [27.69] μg·mL⁻¹), salivary alpha-amylase (sAA: 45.78 [19.07] μg·mL⁻¹), and salivary cortisol (7.92 [2.17] nM) during intensified training concurrent with a 38.3% increase in TL. During the taper phase, a 49.5% decrease in TL from the intensified training phase resulted in a decrease in sIgA, sAA, and salivary cortisol; however, all 3 remained higher than baseline levels. A further significant increase was observed during competition in sIgA (168.69 [24.19] μg·mL⁻¹), sAA (35.86 [16.67] μg·mL⁻¹), and salivary cortisol (10.49 [1.89] nM) despite a continued decrease (77.8%) in TL from the taper phase. Conclusions: Results demonstrate that performance in major competition such as Paralympic games, despite a noticeable reduction in TL, induces a stress response in athletes. Because of the elevated stress response observed, modifications to individual postrace recovery protocols may be required to enable athletes to maximize performance across all 10 d of competition.

The purpose of this study was to explore the sources of stress reported by professional jockeys. In total, 15 jockeys participated in semistructured interviews that included apprentice, conditional, and senior jockeys. Reflexive thematic analysis was used to analyze qualitative data that included inductive and deductive approaches. Jockeys reported a wide range of stress sources. Four core themes were identified and categorized as competitive (current form or being in a slump, pressure, horse, injury, opponents, tactical, and race day), racing industry (weight, workload, travel demands, injury concerns, suspension, and facilities), interpersonal (trainer, other jockeys, expectations of others, support networks, and communication), and career stressors (career uncertainty, career opportunities, and transitions). The findings highlight unique stressors to the jockey population, as well as stressors common with other athlete groups. Practical applied recommendations and future research directions are provided.