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Determining Variables of Plyometric Training for Improving Vertical Jump Height Performance: A Meta-Analysis

de Villarreal, Eduardo Saéz-Saez1; Kellis, Eleftherios2; Kraemer, William J3; Izquierdo, Mikel4

Author Information
Journal of Strength and Conditioning Research: March 2009 - Volume 23 - Issue 2 - p 495-506
doi: 10.1519/JSC.0b013e318196b7c6
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Abstract

Introduction

Plyometrics refers to exercises that are designed to enhance muscle, mainly through the use of jump training. Plyometric exercises constitute a natural part of most sport movements because they involve jumping, hopping, and skipping (i.e., such as high jumping, throwing, or kicking) (4,5,7). Plyometric exercises come in various forms depending on the purposes of a training program. Typical plyometric exercises include the countermovement jump (CMJ), the drop jump (DJ), and the squat jump (SJ). These exercises either can be combined within a training program or can be applied independently. Furthermore, plyometrics can be performed at various intensity levels, ranging from low-intensity double-leg hops to high unilateral-intensity drills. As far as the lower body is concerned, plyometrics includes the performance of various types of body-weight jumping exercises, such as DJ, CMJ, alternate-leg bounding, hopping, and other stretch-shortening cycle (SSC) jumping exercises (12,15,20,24). These exercises are characterized by SSC actions; that is, they start with a rapid stretch of a muscle (eccentric phase) and are followed by a rapid shortening of the same muscle (concentric phase) (12,16,18,19,24,54).

Plyometric training improves strength, muscle power, coordination, and athletic performance (1,6,8,13,21,27,50). Numerous studies on plyometric training have demonstrated improvements in vertical jump height (VJH) (1,11,21,25,30,33,38,45,50,55,61,63,96,97) ranging from 4.7 to 15% that could be attributed to the enhanced coordination and muscle power after training (1,94). In contrast, a number of authors failed to report significant positive effects of plyometric on VJH (47,66,87), and some even have reported negative effects (58). However, the characteristics of a training program that achieves better gains are not clear (5,10,21,30,38).

The effects of plyometric training may differ depending on various subjects' characteristics, such as training level (21,48,56,63,67), gender (17,95), age (17,44,68), sport activity, or familiarity with plyometric training (11,20,21,26,27,35,90,91). Research studies that combine these variables in different ways sometimes lead to conflicting results (30,33,58,60,63,64,66,75,82,83,87,98). Other factors that seem to determine the effectiveness of plyometric training are program duration and training volume. Research studies have used numerous combinations of duration, intensity, and volume characteristics (1,11,21,26,42,48,52,56,59,60,66,72,74,75,83,84,88,92,96,97); therefore, the optimal combination of these factors for maximum achievement remains unclear.

Research findings on the ideal box height to optimize plyometric training are also conflicting (5,8,16,54,57). Some authors suggest optimum DJ heights less than (5,14,16,54) or more than 60 cm (89), because one may optimize maximal power output. Furthermore, inconclusive results also arise from studies that have used additional weight during plyometric exercises to maximize muscle power gains (21,33,50,60,63,66,70,72,82,83,84). Plyometric exercises also have been successful when combined with other types of training such as electrostimulation or aerobics (25,47,60,72,83).

Despite the advantages of plyometric training, the principal issue of determining the optimal elements of a plyometric program remains inconclusive. Identification of the role of the various elements of a plyometric training program with regard to their effectiveness can be achieved with the use of meta-analysis: a method that allows us to overcome the problems of small sample size and low statistical power. Meta-analysis is a quantitative approach in which individual study findings addressing a common problem are statistically integrated and analyzed (46). Because meta-analysis can effectively increase the overall sample size, it also can provide a more precise estimate of the effect of plyometrics on VJH. In addition, meta-analysis can account for the factors partly responsible for the variability in treatment effects observed among different training studies (1,11,21,47,58,66,87). Thus, the purpose of this study was to examine the influence of various factors on the effectiveness of plyometric training using a meta-analysis approach.

Methods

In the present study, the meta-analysis was performed in different steps, grounded in previous recommendations (79).

Experimental Approach to the Problem

Search of Scientific Literature

A search was performed using key words in the English and French languages (e.g., jump training, drop jump, depth jump, stretch-shortening cycle, plyometric, plyometrics, training of power, plyometric training, pliometrique, entrainement pliometrique). These key words were introduced in the databases ADONIS, ERIC, SPORTSDiscus, EBSCOhost, MedLine, and PubMed. Moreover, manual searches of relevant journals and reference lists obtained from articles were conducted. The present meta-analysis includes studies published in journals that have presented original research data on healthy human subjects. No age, gender, or language restrictions were imposed during the search stage.

Study Selection

Research studies implementing plyometric training programs for lower-limb muscles were used. Investigations involving training of the upper-limb muscles as well as summaries or abstracts were rejected. A total of 70 studies were initially identified.

The next step was to select studies with respect to their internal validity. Selection was based on the recommendations of Campbell and Stanley (23) and included 1) studies involving a control group, 2) randomized control studies, 3) studies using instruments with high reliability and validity, and 4) studies with minimal experimental mortality. Fifty-six studies were selected after having completed all quality conditions (1,2,4,7,9-11,21,22,25-38,43,47,48,50,51-53,56,58-60,62-63,65-67,69-72,75,76,78,80-84,87,92,96-98) (Table 1).

Table 1
Table 1:
Summary of characteristics of all studies meeting the inclusion criteria.
Table 1
Table 1:
(Continued).
Table 1
Table 1:
(Continued).

Identification of the Independent Variables

Each study was read and coded independently by 2 investigators using different moderator variables. Because of the high number of variables that may affect training effectiveness, independent variables were grouped into the following areas: 1) subject characteristics: variables included age (years), body mass (kg), height (cm), years of experience, group size, level of fitness, sports level, and type of sport activity; 2) program exercises: variables included combination with other types of exercise, intensity of session, types of plyometric exercises, and resistance; 3) program elements: variables included duration of the session, frequency of weekly sessions, program duration, total number of sessions, drop height, number of jumps per session, number of exercises per session, and rest intervals between series of exercises; and 4) outcome measurements: the type of power test used to identify gains in SJ, CMJ, DJ, or Sargent jump. The coding agreement between investigators was determined by dividing the variables coded the same by the total number of variables. A mean agreement of 0.90 is accepted as an appropriate level of reliability in the coding procedure (74). Mean agreement was 0.91 in our study. Each coding difference was scrutinized by both investigators and was resolved before the analysis.

Calculation of Effect Size

Effect size (ES) is a standardized value that permits the determination of the magnitude of the differences between groups or experimental conditions (85). Gain ESs were calculated using Hedges and Olkin's g (46), using Formula [1]:g = (Mpost − Mpre)/SDpooled, where Mpost is the mean for the post test and Mpre is the mean for the pretest, and SDpooled is the pooled SD of the measurements. [2]:

In those cases for which mean and SD values were not available, ESs were calculated using F,t, or p values, as outlined by Rosenthal (77). For correlational studies, r values were converted to g using Formula [3]:

Correction of Effect Size

It has been suggested (77,79,85) that ES should be corrected for the magnitude of the sample size of each study. Therefore, correction was performed using Formula [4]: 1 − 3 / (4m − 9), where m = n − 1, as proposed by Hedges and Olkin (46).

Statistical Analyses

To examine the effect of the categorical independent variables on the ES, an analysis of variance (ANOVA) was used (39,77,86). In the case of quantitative independent variables (e.g., age, height, duration of the treatment in weeks, number of jumps per session) a Pearson (r) correlation test was used to examine the relationships between ESs and variable values (77). Statistical significance was set at p ≤ 0.05 for all analyses. The scale used for interpretation was the one proposed by Rhea (73), which is specific to strength training research and the training status of the subjects to evaluate the relative magnitude of an ES. The magnitudes of the ESs were considered either trivial (<0.35), small (0.35 − 0.80), moderate (0.80 − 1.50), or large (>1.5).

Results

The analysis showed that the average ES of the plyometric training group (0.84; n = 107; 3.90 cm) was significantly higher (p < 0.05) compared with the ES of controls (0.13; n = 44; 0.84 cm). The Pearson test showed a negative correlation between sample size (r = −0.221, p = 0.05) and ES.

With regard to subject characteristics, the results indicate a significant correlation coefficient for age (r = 0.240) and years of experience (r = 0.575) with the magnitude of the ES (Table 2). The ANOVA showed a significant (p < 0.05) gender effect and sport level (p < 0.05) on ES (Table 2). No other significant effects were found.

Table 2
Table 2:
Analysis for independent variables of subject characteristics.

The ANOVA showed a significant effect regarding the intensity of a session (p < 0.05) and the type of plyometric exercise (p < 0.05). According to the reported data, in these athletes, a post hoc analysis also indicated that maximal gains were obtained with the combined use of SJs, CMJs, and DJs during a training session, showing significantly higher gains (p < 0.05) compared with other plyometric exercises. No differences in ESs were found among the different combinations of plyometric training or among programs with and without added resistance (Table 3).

Table 3
Table 3:
Analysis of variance results on the differences of effect size (ES) between various elements of plyometric training independent variables of program elements.

The results show a positive relationship (p < 0.05) between program duration (r = 0.452), number of sessions (r = 0.515), and number of jumps per session (r = 0.391) with plyometric training effect (Table 4). No differences in ES (p > 0.05) were found among the different power tests (Table 5).

Table 4
Table 4:
Pearson correlation coefficients (r) between various program elements and training gains.
Table 5
Table 5:
Analysis for independent variables of outcome measurement.

Discussion

The results of this investigation support previous narrative reviews (12,61) that have concluded that plyometric training seems to be an effective training method for the improvement of vertical jumping ability (ES = 0.84; i.e., plyometric group). Thus, the reported VJH enhancement of >7% (i.e., 3.90 cm) resulting from plyometric training could be of practical relevance for trained athletes in sports aiming at achieving optimum jumping performance. In addition, several studies focusing on plyometrics have demonstrated that a significant increase in VJH of 10% was accompanied by a respective increase in sport-specific jumping (12,61). The present meta-analysis offers robust quantitative evidence to this conclusion, together with a precise estimate of the effects of plyometric training on jump height in particular types of vertical jumps. Furthermore, the results of this study provide valuable information concerning the importance of controlling some determinant variables for the improvement of jumping performance.

It is well known that sample size influences the power to detect real and significant effects (46). The typical sample size in almost all previous studies on plyometrics ranged from 8 to 12 subjects per group. The present results show a low negative correlation between sample size and training gains. It seems that the greater the sample size, the worse the ES. Most studies used small sample sizes, and therefore a generalization of their findings would be inappropriate. Therefore, one may suggest that studies using large sample sizes are necessary to better illustrate the effects of plyometric training.

Plyometric training requires appropriate technical ability as well as optimum levels of muscle strength and joint coordination. For this reason, subjects with low fitness levels or less experienced individuals are expected to benefit less from such training (3,49). However, the results of the present meta-analysis indicate equal ESs for subjects of various fitness levels (Table 2). These results might indicate that when subjects can adequately follow plyometric exercises, the training gains are independent of fitness level.

Furthermore, our results suggest that higher enhancements after plyometric training can be observed in athletes competing at the international level compared with those gains reached in athletes at the regional level (Table 2). This is further supported by a moderate correlation coefficient between years of experience and ES (Table 2) and suggests that plyometric training is essential for top-level and experienced athletes. Plyometrics improve SSC use with reduced energy consumption and higher power output, and they require high levels of coordination. These features are essential aspects of top-level athletes and optimal performance.

An interesting finding in this study is that men demonstrated higher gains compared with women (Table 2). The reasons for this difference are not clear. It could be suggested that men demonstrate higher power output and better coordination than women. However, the large difference in sample sizes between men and women and the small number of ESs available may account for this observation.

The results show similar ESs for various sport activities. Each sport has its own characteristics, and therefore specific plyometric training exercises have been applied. This confirms previous suggestions (81) that plyometric training should be performed in conditions very similar to competition to achieve sport-specific gains.

In the present study, VJH improvements are not higher when plyometrics are combined with other types of exercise (Table 3). This emphasizes the unique characteristics of plyometric training in terms of improving VJH. However, it should be mentioned that when plyometrics were combined with electrostimulation, higher ESs were observed.

The results of this investigation suggest that when the intensity is high during a session, there is a greater improvement in VJH performance (Table 3). The present results show that a combination of SJs, CMJs, and DJs demonstrates a higher ES compared with the use of a single type of exercise (Table 3). It is well documented (17,54,65,81,89,99) that VJH is higher during DJs, followed by CMJs and then SJs. This is mainly because of the different characteristics of movement and, thus, different use of SSC characteristics. For these reasons, the combination of various exercises may result in higher VJH gains compared with the performance of each exercise alone.

The specific effects of plyometrics on VJH in the different types of vertical jumps could be of particular importance. It has been suggested that plyometric training is more effective in improving vertical jump performance in SSC jumps because it enhances the ability of subjects to use the elastic and neural benefits of the SSC (95). This also could be attributed to differences in the use of SSC characteristics (17,54). An SJ mainly consists of a concentric (push-off) phase, whereas a CMJ involves an eccentric and concentric phase (15). The results of our study support these suggestions. Specifically, our data indicate that plyometrics produce somewhat greater (although not significantly) positive effects in the fast SSC jumps (i.e., DJ) than in the concentric-only jumps (i.e., SJ) or even the slow SSC jumps (i.e., CMJ). Keeping the specificity of contraction-type training in mind (i.e., SSC muscle function), greater positive effects of plyometric training on DJs and CMJs than on SJs can be expected. However, to explain the difference in the effects of plyometric training between DJs and CMJs, we should take into account the biomechanical differences between the slow and fast SSC jumping exercises (12). Several authors (12,99) have shown a substantial difference in the mechanical output and jumping performance between slow SSC vertical jumps such as CMJs and fast SSC vertical jumps such as DJs. For these authors, the jumping technique (i.e., corporal position, movement amplitude, and ground-contact time) represents one of the most important factors to be considered when designing plyometric programs. However, in many of the studies included in this review, the researchers did not consider the above-mentioned factors when describing their plyometric programs. Therefore, it remains unclear whether the jumping technique is responsible for the somewhat greater gains observed in VJH.

Some research studies have shown that plyometric training with additional weights (vests, bars on the back, etc.) demonstrated higher gains (11,35,40,41,52), whereas others (21,34,50,60,63,66,70,72,82-84) have reported the opposite. The results of the meta-analysis indicate no differences among training conditions (Table 3). This suggests that using additional weights in training does not cause significant gains in performance. It could be suggested, then, that training with additional loads might increase not only resistance but also contact time. However, the longer the contact time, the less effective the SSC (13). Therefore, training effects using additional weights are not guaranteed.

Volume and frequency are very important parameters to take into account for an optimum plyometric training program design. The results showed that training for 10 weeks is more beneficial than similar programs of shorter duration. Similarly, treatment with more than 20 sessions increases VJH, whereas performance of more than 50 jumps per session seemed to result in the most beneficial volume (Table 4). These figures are compatible with previous recommendations (30,35,89,98). However, in agreement with previous studies (78), a short-term plyometric training program with a moderate training frequency and volume of jumps (2 d·wk−1, 840 jumps) produced similar enhancements in jumping performance but greater training efficiency compared with high training frequency (4 d·wk−1, 1680 jumps). Conceptually taken on the whole, the present data indicate that increasing the number of jumps in previously moderately trained men does not seem to be the best stimulus for improving vertical jump performance during short-term training periods compared with high jump-training volumes. These results also suggest that there is a minimum training volume threshold over which further increases in volume are no longer advantageous. It is also likely that in previously physically active subjects within the context of a short-term plyometric training cycle of 7 weeks, jumping performance training can be improved only by 50% or by a high-volume jumping program (e.g., 28 sessions of plyometric training [1680 DJs] performed for 4 sessions per week during a 7-week training period).

The results indicate a nonsignificant ES for drop height on VJH gains (Table 4). This agrees with previous studies (8,14,93) suggesting that the height of the jump is not crucial for improving power in jump training. Therefore, jumping from a lower height allows performance of more repetitions per session and improves trainability of jumping performance with less injury risk.

In conclusion, the present study demonstrates that plyometric training significantly improves VJH. The estimated improvements in VJH as a result of plyometrics could be considered as practically relevant-for example, an improvement in VJH of >7% (i.e., 3.90 cm) could be of high importance for trained athletes in sports relying on jumping performance. According to our results, subjects with more experience in sport obtained the greatest enhancements in VJH. On the other hand, subjects in both good and bad physical condition benefit equally from plyometric work, although men obtain better power results than women after plyometric training. A training volume of more than 10 weeks (with more than 20 sessions), using high intensities (with more than 50 jumps per session), is the strategy that will maximize one's probability of obtaining significant improvements in performance. It is also probable that there is a minimum training volume threshold over which further increases in volume may no longer be advantageous. Another important conclusion is that it is more beneficial to combine different types of plyometrics than to use only 1 form, whereas the best combination is SJs + CMJs + DJs. However, there are no extra benefits gained from doing plyometrics with added weight.

Practical Applications

Plyometric training can be recommended as an effective form of physical conditioning for augmenting vertical jump performance; yet, the effects of plyometric training could vary because of a large number of variables, such as training program design, subject characteristics (gender, age), training level, the specific sport activity, familiarity with plyometric training, program duration, and training volume or intensity. These conclusions are essential and should be taken into account by strength and conditioning professionals, who must consider the most appropriate plyometric training approach based on the fundamental movement patterns, technique, volume, frequency, intensity, energy system requirements, and potential injury analysis for a given sport. Furthermore, for an individual athlete, initial training status and training experience must be considered, and specific fitness limitations should be stressed. The strength and conditioning coach may take into account the dose-response trends identified in this analysis to prescribe the appropriate level of training.

Acknowledgments

The authors have no professional relationships with companies or manufacturers that might benefit from the results of this study. The results of this study do not constitute endorsement of any product by the authors or the NSCA.

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Keywords:

power; effect size; lower limb; training volume; intensity

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