Participants
Eight top-level Paralympic sprinters with visual impairment (6 women and 2 men; class T11) (age: 27.8 ± 6.7 years, weight: 62.2 ± 11.2 kg, and height: 165.9 ± 10.0 cm) who compete in 100- and 200-m races, from the Brazilian National Team, volunteered to participate in this study. This elite sample comprised two world champions, two Paralympic champions, one world record holder, one Paralympic record holder, seven world medalists and four Paralympic medalists. In addition, all the eight athletes are top-five in the 2015 International Paralympic Committee (IPC) world ranking, thus attesting their high level of competitiveness. The procedures were approved by an Institutional Ethics Committee. After being fully informed of the risks and benefits associated with the study, all athletes signed a written informed consent form.
Study design
This is a pilot study using a within-subject randomized cross-over experimental design to test the effectiveness of compression garments on speed–power tests performance in eight top-level Paralympic sprinters. Four of them wore the compression garments on the first testing day, while the other four athletes wore the non-compressive clothes (“control condition”). The “control condition” consisted of wearing a non-compressive Lycra® clothing, whereas the “compression condition” consisted of using garments with a functional compressive-body composed of 84 % nylon and 16 % elastane (Under Armour, Baltimore, MD, USA). The athletes performed, in the following order, unloaded squat jump (SJ), loaded jump squat (JS) and a sprint test over 20- and 70-m distances; using or not the lower body and upper body compression garment (Fig. 1). The tests were performed on the same day, with 5–10 min separating each test. Prior to the two testing sessions, the participants dressed the assigned clothes and executed a standardized warm-up protocol, including general (i.e., running at a moderate pace for 10-min followed by 5-min of active lower limb stretching) and specific exercises (i.e., sprint drills and low-intensity plyometrics). The warm-up was followed by a 3-min rest interval, after which the athletes were required to perform the actual tests. The test days were interspersed with 48-h, a period during which the athletes were oriented not to heavily train and to maintain their habitual dietary habits. In the 24-h prior to testing, the athletes were also requested not to consume alcohol or caffeine-based beverages. The study was conducted during the last semester of the final preparation phase of the cycle leading up to the 2016 Paralympic Games.
Squat jump (SJ) test
Unloaded vertical jumping ability was assessed using SJ, which started from a static position with a 90° knee flexion angle maintained for 2-s prior to a maximal jump attempt without any preparatory movement. Jumps were executed with the hands on the hips, and visually validated by one of the investigators, making sure that take-off and landing in the vertical jumps were performed at the same lower-limb position (extended knees). Otherwise, the given jump was repeated. The jumps were performed on a contact platform (Smart Jump; Fusion Sport, Coopers Plains, Australia) with the obtained flight time (t) being used to estimate the height of the rise of the body’s center of gravity (h) during the vertical jump (i.e., h = gt2/8, where g = 9.81 m s−2). Five attempts were performed interspersed with 15-s intervals. The best attempt was used for data analysis purposes. The athletes executed the SJ attempts without any help from their guides.
Mean propulsive power in loaded jump squat (JS)
Mean propulsive power was assessed using the jump squat exercise (MPP JS), performed on a Smith machine (Hammer Strength, Rosemont, IL, USA). The Paralympic sprinters executed a knee flexion until the thigh was parallel to the ground (≈100° knee angle) and, following a command, jumped as fast as possible, without their shoulder losing contact with the bar. The athletes were instructed to execute two repetitions at maximal velocity for each load, starting at 40 % of their body mass (BM), after which a load of 10 % of BM was gradually added in each set until a decrease in MPP was observed. A 5-min interval was provided between sets. To determine mean propulsive power, a linear transducer (T-Force, Dynamic Measurement System; Ergotech Consulting S.L., Murcia, Spain) was attached to the Smith machine bar. The technical specification of the MPP analysis and calculation, and the use of the MPP rather than peak power have been described previously (Loturco et al. 2015a; Sanchez-Medina et al. 2010). The maximum MPP value obtained was considered for data analysis purposes. The athletes executed the SJ attempts without any help from their guides.
Sprinting speed
Prior to the execution of the sprint speed test, three pairs of photocells (Smart Speed, Fusion Equipment, Australia) were positioned at distances of 0-, 20- and 70-m along the indoor track and field course. The Paralympic athletes sprinted twice, starting from a standing position, 0.3-m behind the start line. A 5-min interval was allowed between the two attempts and the fastest time obtained was considered for further analyses. The sprinters performed the sprint tests accompanied by their official guides.
Statistical analysis
Data are presented as mean ± SD. The comparisons of the test performances between the two conditions (placebo and compression) were analyzed using magnitude-based inference (Batterham and Hopkins 2006). The quantitative chances of finding differences in the variables tested were assessed qualitatively as follows: <1 %, almost certainly not; 1–5 %, very unlikely; 5–25 %, unlikely; 25–75 %, possible; 75–95 %, likely; 95–99 %, very likely; >99 %, almost certain. If the chances of having better and poorer results were both >5 %, the true difference was assessed as unclear. The standardized differences for the comparisons in all variables were analyzed using the Cohen’s d standardized differences based on ES (Cohen 1988). The magnitudes of the ES were qualitatively interpreted using the following thresholds: <0.2, trivial; 0.2–0.6, small; 0.6–1.2, moderate; 1.2–2.0, large; 2.0–4.0, very large and; >4.0, nearly perfect (Hopkins 2004; Hopkins et al. 2009).