Sprint performance plays a vital role in many athletic performances. Specific components such as acceleration (the initial 10 m) and maximum speed, which is reached at approximately 40 m (16), are especially pertinent to sports such as track and field, football, and soccer. Considering the vital role sprinting plays in various sports, enhancing sprint performance should be a concern to athletes and sport scientists alike. Bret et al. (3) claim that both acute and chronic sprint performance can be augmented through mechanisms such as resistance training, which most commonly takes the form of Olympic lifts, such as power cleans (PC), snatches, and jerks. Additional methods, such as whole-body vibration (WBV), have also been shown to elicit improvements in dynamic performances related to jump height, lower-limb strength, and flexibility (2,18,23). Chiu et al. (4) claim that such muscle performance augmentations, referred to as postactivation potentiation (PAP), can be elicited by several different means, many of which have been mentioned above.
Sale (21) describes the phenomenon of PAP as an increase in muscle isometric twitch and low-frequency tetanic force after a preconditioning activity. In lay terms, PAP refers to a “heightened” or “excited” state experienced by the neuromuscular system (11). Several studies have shown an increase in posttest performance after a preconditioning activity focused on inducing PAP via WBV and other means. Specific enhancements have been seen in variables such as strength and power (6,7) as well as electromyographic activity (2). Additional studies have shown augmented performances within dynamic events, such as drop and vertical jumps, after a PAP-focused warm-up (11,17).
Despite the numerous studies linking PAP with enhanced dynamic exercise performance (9,11,17), there seems to be little literature available on the influence of PAP on sport-specific performances, such as sprinting. Much of the current literature agrees that PAP can positively influence activities thought to be explosive in nature. Therefore, it seems appropriate to assume that sprinting, which through the initial acceleration phase is highly explosive, would also benefit from a mechanism such as PAP. Current warm-up recommendations for dynamic exercise suggest increasing muscle temperature while focusing on task-specific range of motion (1,12,19); thus, it seems appropriate that PAP could be integrated into warm-up procedures, provided it can positively impact sprint performance. If the possibility exists that a warm-up eliciting PAP could enhance acute sprint performance, research concerning such a prospect is warranted. As such, it was the purpose of this study to examine the effectiveness of 2 specific preconditioning activities, WBV and PC, on eliciting PAP, and inspecting the corresponding effects of these activities on acute sprint performance.
Experimental Approach to the Problem
To determine the effectiveness of eliciting PAP through different means, 2 separate but similar studies were conducted. In both studies the dependent variable, acute sprint performance, remained the same, despite differences in the corresponding interventions. During the first study, the effects of WBV were measured on sprint performance, whereas the second study examined the impact of PC on sprint performance. In the initial study, sprint splits were recorded at 10, 20, and 40 m after WBV exposure. After analyzing the data from that particular study, the research focus was shifted for the second study to include the shorter, more ballistic components of sprint performance, such as reaction time (RXN) and 5-m split times (as well as 10 and 40 m). As a result, the 20-m split, which was present in the first study, was eliminated from the second study.
Split and RXN times were measured using battery-powered timing gates (Brower Timing System, Salt Lake City, Utah). In both studies, subjects were asked to start all trials from the blocks. Timing was initiated at the release of a pressure sensitive pad placed on the rear starting block. Those subjects taking part in the PC study were encouraged to react as quickly as possible to the starting beep emitted from the timing system, thus measuring RXN. The RXN was the amount of time it took the athlete to release pressure from the rear block after the initial starting beep. During the WBV study, split times were recorded at 10, 20, and 40 m. For the PC study, split times were taken at 5, 10, and 40 m, after the initial measure of RXN. Split times were recorded from the breaking of a light beam existing between gates placed at each of the designated distances. To control for environmental variability, all testing was done on a rubberized track in an indoor facility used regularly for collegiate track and field competitions.
Participants in both studies were trained male collegiate track and field athletes recruited from an NCAA Division I team. The athlete pool consisted of ballistic trained athletes: sprinters, jumpers, and throwers. Fourteen subjects participated in the WBV study (21 ± 3.0 years, 1.80 ± 0.046 m, 80.1 ± 9.5 kg), and 9 subjects participated in the PC study (20 ± 1.5 years, 1.81 ± 0.06 m, 84.57 ± 17.15 kg). In both cases, data collection occurred in-season during the month of October to best assimilate the peak physical condition of the athletes. Before the study, all participants were informed of the experimental risks and completed a university-approved informed consent form.
Subjects were screened according to their familiarity with the testing procedures being implemented in each of the studies. It was mandatory that all athletes in both studies have 5 years of experience with high-intensity sprinting, whereas those participating in the second study were also required to have at least 3 years of experience with the PC lift being used. The warm-up protocol employed for both studies consisted of exercises commonly used by the athletes as part of their regular preperformance activities.
Subjects were required to participate in a familiarization session 1 week before testing regardless of their previous experience with the designated procedures. During the familiarization session, subjects were given instructions on the specific performance variables required of them for the WBV and/or the PC interventions as well as the 40-m sprint. Participants were also given an opportunity to ask any questions they had regarding testing protocol for both WBV and PC treatments. In addition, the familiarization session was used to collect information regarding the physical characteristics of the subjects (i.e., age, weight, and height). Each of the subjects was then tested to determine his respective 1RM PC, which was used to determine the 3RM PC used for his PC intervention.
During the familiarization session, subjects were taken through the warm-up procedure that would be used before data collection on the days of testing. The warm-up was designed to mimic an abbreviated version of a typical warm-up that the athletes would conduct themselves before a workout. Specifically, it consisted of 10 minutes of general warm-up, including jogging, ballistic stretches, and dynamic drills, followed by 10 minutes of dynamic stretching and sprint-specific running drills. The warm-up concluded after the completion of a single 50-m sprint at approximately 90% intensity. Both studies comprised treatment (i.e., WBV and PC) and nontreatment (i.e., no WBV and no PC) trials, which were conducted 1 d·wk-1. Subjects completed the respective treatment trials in a random sequence to eliminate potential ordering effects.
Study 1: Whole-Body Vibration
For the study using WBV, subjects participated in 4 separate days of testing in which 4 different vibration frequencies (0, 30, 40, and 50 Hz) were compared. All testing was done using a 0.82 × 1.02-m Pneu-Vibe Pro vibrating platform (Pneumex, Sandpoint, Idaho) at the low amplitude setting (1-2 mm). The above frequencies have been factory validated at ± 2 Hz. Data were collected during 4 consecutive weeks in which the subjects were asked to remain “normally” active. During all trials, subjects were given a rest period of 3 minutes after the warm-up, during which they were asked to “stay warm” without conducting any further dynamic activity.
Regardless of their grouping, subjects were asked to perform a single 40-m sprint, after which they received 2 minutes of rest. Upon completion of the 2-minute rest period, participants took part in 4 bouts of “high knee” running on the vibration platform under 1 of 4 conditions: 0, 30, 40, or 50 Hz. Each bout of high knees lasted approximately 5 seconds, and subjects were instructed to take 30 seconds of rest between sets. After the vibration exposure, subjects completed 2 × 40-m sprints after 1 and 4 minutes of rest, respectively.
Study 2: Power Clean
For the PC study, data were collected on 2 separate sessions. Subjects were asked to participate in both the treatment and nontreatment trials in random order, thus allowing for comparisons between treatment conditions to be made. The intervention consisted of 3 reps of the PC at 90% 1RM intensity. After the same warm-up used in the WBV study, subjects were given 3 minutes of rest in which they were inactive. All subjects were then asked to complete 2 × 40-m sprints with 3 minutes of rest between (no PC); or 1 minute of rest, 3 × 90% 1RM, and 1 minute of rest between consecutive sprints.
In both studies, subjects completed all treatment and nontreatment trials, which allowed for comparisons to be made between different group mean values for each condition. For the WBV study, a double multivariate analysis of variance was used to calculate differences between conditions (frequencies) and sprint trials (time). With the PC study, a repeated-measures (RM) analysis of variance (ANOVA) was used to test for significant differences between resting sprint and RXN times and those times after the experimental treatment. Significance was determined using an alpha level of 0.05.
Test-retest reliability was assessed using Hopkins' (13) spreadsheet, which provides values for typical error and the coefficient of variation (CV), as well as intraclass correlation coefficients (ICCs) for pairwise comparisons. In addition, smallest worthwhile change, which refers to the practical impact of relatively small differences between values, was calculated using the product of sprint time, CV, and a coefficient of 0.20. Typical error, CV, and ICC pertain to the amount of variability present between consecutive trials. Specifically, the CV for a particular trial can be expressed as the percentage of the mean accounted for by typical error. The ICC values represent the consistency between trials and illustrate the extent to which subject trials are homogenous. Higher ICC values suggest that more variance can be explained between consecutive sprint trials.
Study 1: Whole-Body Vibration
No significant differences were found between the first and second sprints for 10-, 20-, and 40-m split times across all frequencies. In addition, no significant differences were found between the different vibration conditions for 10-, 20-, and 40-m splits. Specific values for sprint times can be found in Table 1. It should be noted that for all sprints after treatment, corresponding ICCs were above 0.8. Despite the lack of significant differences between control and treatment trials, an apparent trend existed within the 30-Hz condition when compared with corresponding control times. However, the large variances corresponding to these values make it difficult to attribute the differences to treatment rather than error.
Study 2: Power Clean
Results taken from the RM ANOVA revealed no significant differences between the control and treatment trials for any of the recordings taken at 5, 10, and 40 m. Additionally, no significant differences were found between the measures of RXN during the nontreatment trial vs. the treatment trial. Corresponding performances suggested a lack of any apparent trend across the 9 subjects and their respective responses to the treatment (Table 2). Although ICC values were above 0.80 for the 40-m sprints, these values deteriorated within the shorter sprint trials.
A partial correlation was conducted to determine the relationship between RXNs and corresponding split times (Table 3). These results indicated a significant correlation between RXN and both 5- and 10-m splits (0.65 and 0.63, respectively). However, the strength of this correlation deteriorated as the sprint length increased, resulting in a much lower, but still significant, value of 0.42 between RXN and 40-m split.
The results taken from these studies suggest little efficacy for the use of dynamic lifting and vibration exposure as a means of inducing PAP in an attempt to augment acute sprint performance. The lack of significant findings could be attributed to numerous mechanisms. According to Scott and Docherty (22), several factors impact the subsequent dynamic performance of a subject participating in a specific preload activity, including volume of the resistive exercise, intensity and type of resistive exercise, time between resistive exercise and ensuing activity, testing protocol, and training status of the subjects participating in the study (14). With regard to WBV, additional factors such as frequency, amplitude, intensity, load and duration of training, duration of rest, length of training period, and body position must be considered (18). Thus, it is difficult to ascertain the ideal protocol needed to facilitate maximal gains in sprint performance.
Testing protocol may also explain the results of the PC study. According to French et al. (9), the total volume of preconditioning activity plays a significant role in the activation of PAP. In the case of the current 2 studies, volume specifically refers to the number and % 1RM load used by each subject (PC) and the active time spent on the vibrating platform (WBV). Considering this, it could be suggested that the desired results from the PC study might have been obtained had the number of repetitions been increased to 3 sets of 3 reps, had the weight been decreased (from 90% 1RM to 60-70% 1RM), or, in the case of the WBV study, had the time spent on the vibration platform increased from 5 to 10 seconds or more. Thus, it could be argued that the prescribed volumes in both cases were inappropriate to elicit significant amounts of PAP.
Regarding the limitations associated with this study, some consideration should be given to the concept of statistical power. The fact that 14 subjects were recruited for the WBV study, whereas only 9 participated in the PC study, greatly reduced the power values. Limitations involving the heterogeneity of the sample (sprinters, jumpers, and throwers) may also have been prevalent. One could argue that the variance in training routines for athletes within separate groups may have had an effect on the outcomes of the sprint trials. Questions might also be asked regarding the number of trials performed. For instance, 4 separate 40-m trials may not have been adequate to produce valid, reliable results. Perhaps 8 or 10 trials would have produced the results expected from such a sample, although fatigue then becomes an issue.
As a result of the potential limitations of the current study, future research should include the use of larger samples, in addition to more trials, to potentially enhance the statistical power of any findings. Specificity of training should also be kept as consistent as possible. Athletes used as subjects within studies such as this should be participating in similar training programs before data collection to enhance the likelihood of comparable responses to the treatment.
Support for the lack of significant findings in this study is best summarized by Robbins (20), who states that “studies attempting to elicit PAP as measured by a poststimulus performance activity are much more equivocal than those examining twitch contractile properties.” In other words, PAP, assuming it is present, is much more visible in scenarios in which isolated muscles or muscle fibers are being examined rather than performance of a dynamic activity such as sprinting. Rationales for such a discrepancy are numerous, ranging from insufficient rest (10), differences in the speed of contraction (15), absolute strength of the individual subjects (8), or just the inherent variability within dynamic activities.
Subsequent research should adjust the preload activity and corresponding volumes of PC and WBV activities in an attempt to find the best means of inducing PAP to augment athletic performance. Duration of rest is also an area worth manipulation. Time taken between preload and ensuing activities must be adjusted to determine the optimal rest periods between activities. Finally, preload activities should be kept as specific as possible to best simulate the activity one is attempting to enhance. Consequently, activities that are considered dynamic in nature should be preceded by similar dynamic preload activities rather than isometric contractions or maximal voluntary contractions.
Despite limited statistical findings, the results taken from the WBV study may have worthwhile implications for athletes in sports that require sprinting. Considering the apparent trend within the 30-Hz protocol, one might suggest WBV as part of a warm-up for sprint activities greater than 40 m. Extrapolating the results from this study to distances of 100 m or more could potentially result in a decreased sprint time of nearly 1/10th of a second, which, as any track and field coach will confirm, is worth serious consideration.
Also worth reflecting on is the importance of specificity (9) and its pertinence to the physiological responses of an individual to a particular preload activity. Lack of specificity may have had an impact on the results of the 2 current studies. For instance, a preconditioning activity aimed at eliciting PAP and consisting of “overspeed” training (5) (e.g., an athlete is towed behind another runner in an attempt to achieve sprint speeds greater than those obtained via regular sprinting), as opposed to PC, might have produced results more representative of those expected, such as a decrease in sprint time.
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