Drop jump (DJ) is one of the most used tests for assessment of jumping performances (24), and particularly, capacity for using stretch-shortening cycle that provide well-known benefits to the production of the maximal power output (19). An extensive application of DJ as a standard test has been well supported in the literature because of its proper metrics characteristics, such as validity, reliability, and sensitivity (6,24,366,24,366,24,36). In addition, over the past half century, DJ has been a very popular exercise for development of muscle power of the lower extremities (6), and the findings of numerous studies have revealed its beneficial effects on gaining jumping performances after the applied training procedures (25) or rehabilitation interventions (26). The important issue that has been raised over time is related to the optimum intensity (i.e., magnitude load) in DJ that could provide the most effective mechanical responses either in terms of production of the maximal muscular power or achievement of maximum jumping performances. The aforementioned issue is not important merely from the theoretical aspect, such as dealing with fundamental properties and design of the muscular system (10) but also from the practical aspect (11). Specifically, it has been suggested that both valid assessment of muscle power output and efficient training or rehabilitation procedures (12) require the application of the optimum load (Lopt).
It has been generally presumed that Lopt elicits maximal muscle power production in natural human movements similar to the mechanical properties of an in vitro muscle (13). However, the experimental findings have been generally inconsistent regarding Lopt for maximizing the muscle power. Namely, there was a large difference both between and within standard muscle power tests (i.e., jumping, throwing, running, or cycling tasks) with respect to Lopt (16). For instance, in the vertical jumps (i.e., squat jump, countermovement jump, and countermovement jump with arm swing), Lopt that allows maximal power production was largely varied between unloading (0.7 of body weight [BW], (38)) and loading condition (59% of 1 repetition maximum [1RM] in squat, (4)). Note, Lopt in aforementioned tests was defined in relation to the different reference values, such as maximum dynamic strength (MDS, (29)), 1RM (4), BW (38), or absolute weight (27). However, because of specificity of DJ (i.e., drop from certain height), Lopt has been commonly represented as an optimum drop depth or height (DHopt, (20,3620,36)).
Although the effect of drop height on the jumping performances in DJ has been frequently studied (5,7,20,22,31,365,7,20,22,31,365,7,20,22,31,365,7,20,22,31,365,7,20,22,31,365,7,20,22,31,36), the results remained mainly inconsistent. Specifically, findings of the previous studies have revealed that DHopt could be within range of 0.12 (22) to 0.80 m (36). The observed relatively wide range of DHopt could be a result of various methodological issues, such as the differences in the data collection (7), used calculation techniques (3,123,12), design of experimental protocols (e.g., range of applied drop heights, (33)), and, particularly, from the jumping technique specificity (i.e., bounce vs. countermovement drop jump, (6)). Note that mentioned large variability could be caused by questionable reliability (14) of applied methods for determination DHopt. In addition, selection of the dependent variables could be another factor that could affect DHopt (8). Namely, the previous researchers mainly used both jumping height (7,207,20) and reactive strength index (8) as variables for determination of DHopt, whereas other factors, such as energy expenditure ratio between breaking and propulsion phases (2), total ground contact time (32), heel ground contact (40), and power output (31), were used less often. However, it is important to note that maximal power output as one of the most important performance indicators has been almost completely neglected as variable for the detection of DHopt in DJ, so far. Despite of the large differences in the previous findings with respect to DHopt, reliability of applied methods for determination DHopt has not been explored yet.
In addition to the above-discussed factors that could affect DHopt, there is some evidence that Lopt could also be subject specific due to the factors, such as age, gender, level of maximal muscle strength (MSmax), and training history of the athlete (11,12,3011,12,3011,12,30). Consequently, as DHopt represents Lopt in DJ, therefore, it could be dependent on the aforementioned factors, especially with respect to the level of MSmax. Although previous studies have not supported this assumption in DJ task yet, there are some indications that speak in favor of this hypothesis. For example, naturally stronger adults revealed maximal jumping performances (assessed as jumping height) at higher drop height compared with boys (0.4 vs. 0.2 m, (21)). Also, higher DHopt has been found in men (i.e., 0.66 m for volleyball players and 0.63 m for male physical education students) compared with women (i.e., 0.48 m for female students, (20)). Although there is a lack of research that has implicitly studied the effect of training history on DHopt (36), to the best of our knowledge, no previous research has asked whether DHopt is influenced by MSmax (i.e., assessed as 1RM or MDS).
To address the above-reviewed unresolved issues, we designed an experiment with the aim to investigate the effect of MSmax on DHopt that allows production of maximal power output in DJs. First, we explored the reliability and mutual relationship of the 2 methods for determination of DHopt. Thereafter, we estimated the relationship between MSmax and DHopt and tested possible differences in DHopt between 2 groups with different level of MSmax (i.e., strong and weak individuals). As a first hypothesis, we assumed that applied methods for determination of DHopt are reliable, whereas the second hypothesis was that there exists the cause-and-effect relationship between MSmax and DHopt. The findings were expected not only to reveal some fundamental properties of the neuromuscular system and its adaptation but also to provide potentially valuable practical information regarding the load optimization in DJ. Of particular importance for strength and conditioning practitioners could be determination whether the individualization of DHopt is dependent to achieved level of MSmax.
Experimental Approach to the Problem
Although the previous findings obtained from other tasks, such as cycling (30), provide evidence that level of MSmax could affect the “optimum load” that producing the maximum power output, this effect is not explored in DJ. Hence, we designed experimental cross-sectional study with the main aims to explore the cause-and-effect relation of MSmax on DHopt in DJ. As a first step, we explored reliability of 2 methods for determination of DHopt on larger sample of participants according to recommendation by Hopkins (14) and estimated the relationship between MSmax and DHopt. In the second step, we tested possible differences in DHopt between individuals with different level of MSmax, while we control possible effects of age and gender. Note that we previously conducted a sample size estimate based on the differences in MSmax (34) among similar groups of participants. Based on Cohen's guidelines (9) with power 0.8 and an alpha level 0.05, sample sizes ≥8 seemed to be acceptable per subgroup. In addition, we recorded a few dependent kinetic and kinematic variables related to the jumping pattern and jumping performance (for details, see further text). We expect that the experimental data could significantly contribute to the understanding whether MSmax influences DHopt in DJ, what is of utmost importance for athlete's training purposes.
Thirty sport and physical education male students (age: 20.3 ± 1.3 years; body mass: 77.5 ± 10.2 kg; height: 1.83 ± 0.06 m) participated in this study. All subjects were physically active through their standard academic curriculum (average 4–7 classes per week that included a low-, moderate-, and high-intensity exercises) and some of them additionally through the regular training program in sports groups at the faculty. Although none of them was a professional athlete, note that they had a varied experience with organized resistance strength training, and therefore, a very different level of MSmax. In addition, from the total sample of subjects, 16 subjects were selected and allocated into 2 subgroups formed according to their resistance strength training background (i.e., level of MSmax): strong (n = 8) and weak (n = 8). The subjects' characteristics are depicted in Table 3.
The students who represented the strong group were selected on the basis of their experience and current activity in resistance strength training. Specifically, it involved minimum 6 months and minimum 3 training sessions a week aimed to hypertrophy (i.e., 60–80% 1RM) or strength (i.e., 85–100% 1RM). Therefore, they could qualify as “strong” for sport and physical education students due to their experience and weekly resistance strength training protocol before the experiment. The weak group involved students who were active only through their aforementioned standard academic curriculum; however, none of these subjects had had experience with regular resistance strength training.
The participants did not report any medical problem or recent injuries that could compromise the tested performance. Before the experiment, all participants received a complete explanation regarding the purpose and procedures of the study, as well as possible risks. They were also required to sign an informed consent document. The study was approved by the Institutional Review Board of the University of Belgrade.
The experiment consisted of 2 testing sessions separated by at least 3 days of rest. The first session included anthropometric measurements (body height, body mass, and percentage of body fat), lower-body strength assessments (i.e., 1RM squat test), and familiarization with DJ test at different drop heights (i.e., 3–4 practice trials performed at each drop height; 24–32 jumps in total). The second session consisted of DJs performed at 8 different drop heights: 0.12, 0.22, 0.32, 0.42, 0.50, 0.62, 0.72, and 0.82 m. The sequence of drop heights was randomized for each subject. Each session was preceded by a standard 10-minute warm-up (i.e., cycling and stretching) and 5-minute specific warm-up (i.e., single and double leg jumps) procedure, following a detailed explanation and qualified demonstration of each test. The testing was conducted in the fall between 10 AM and 14 PM in the laboratory facility that was maintained at the air temperature between 18 and 22°C. The subjects were asked to follow their normal diet and to refrain from any form of intense physical activity for the 48 hours, as well as to fast for 2 hours before each testing session.
Anthropometric measures were taken according to the procedures recommended by the International Society for the Advancement of Kinanthropometry (28). Body height and body mass were measured to the nearest 0.5 cm and 0.1 kg, respectively. Body composition (percentage of body fat content) was assessed using a bioelectric impedance method (In Body 720; Biospace, Seoul, Korea).
Maximal Strength Testing
After the anthropometric measurements, a standard procedure (27) was applied to assess the leg extensor strength through 1RM squat test on the standard Smith machine. Before the start of the warm-up procedure, a manual goniometer was used to visually establish the attainment of a 90° knee flexion angle while squatting. The applied loading and the number of the associated warm-up sets and repetitions were as follows: 30% (8 repetitions), 50% (4–6 repetitions), 70% (2–4 repetitions), and 90% (1 repetition) of an estimated 1RM either based on the subjects recommendation or on calculated 1.5 times the subject's body mass (Logan et al. 2000). The test included 2–3 trials to assess 1RM. Each subject was asked to move the weight upward in a controlled but forceful fashion, back to the upright position. Adequate rest was allowed between trials (3–5 minutes).
Drop Jump Testing
The force plate (AMTI, Inc., Newton, MA, USA) was mounted and calibrated according to the manufacturer's specifications, while sampling frequency was set at 1000 Hz. The guidelines provided by Vanrenterghem et al. (35) were used for the assessment of muscle power in vertical jumping. For DJ testing, participants were instructed to jump as high and as quickly as possible (40). Subjects had to keep their hands on their hips to eliminate any contribution of arm swing (36). Visual feedback was provided by 2 experienced experimenters in terms of controlling potential lowering of subject center of mass when stepping forward before the drop (18) and inspecting ground contact time duration (i.e., <400 milliseconds) to ensure that an appropriate technique was being used (32). Subjects performed 2 practice and 3 experimental trials per each of the applied drop heights. The rest period among jump trials was 30 seconds and among different drop heights was about 3 minutes. In line with previous studies performed according to a similar procedure, as well as according to the participants' reports, fatigue was never an issue.
Data Processing and Analysis
Independent variable defined as MSmax was expressed as a maximum dynamic strength (MDS) as assessed by the sum of 1RM squat and subject's body mass minus shank mass (for details see Ref. (29)), and as a 1RM squat appropriately normalized for body size using the body mass (BM) raised to the power of 0.67 (15).
The custom-designed software (LABVIEW, version 11.0; National Instruments, Austin, TX, USA) was used to record and process the vertical component of the ground reaction force. Vertical center of mass velocity during the support phase was calculated through integration of the vertical ground reaction force (3):
where VZ = vertical center of mass velocity; VTD = vertical center of mass velocity at touchdown; FZ = vertical ground reaction force; m = mass of the subject; g = acceleration of gravity; dt = delta time. Although we were primarily interested in the muscle power output, we also recorded a few dependent kinetic and kinematic variables related to the jumping pattern and jumping performance that could potentially reveal the mechanisms of the group-specific adaptation to the applied drop heights. In particular, we calculated peak ground reaction force during the eccentric and concentric jump phases (PFecc and PFcon, respectively), and time duration of both support jump phases (Tecc and Tcon). Finally, the power output was assessed based on the peak power obtained from both eccentric (PPecc) and concentric (PPcon) jump phases. The mechanical power was calculated by multiplying the vertical ground reaction force (FZ) with the velocity of the center of mass (VZ):
For each condition, the trial with higher PPcon was used for further analyses. The peak force and peak power variables were appropriately normalized for body size using BM0.67.
As a next step of analysis, DHopt that provides the maximal power output in DJ was determined as the main dependent variable. The 2 methods were applied for this purpose. The first method takes into account the highest power value across the applied drop heights (named as the method of picking) as the individual DHopt, whereas the second method was used for prediction of individual DHopt. Specifically, a second-order polynomial (i.e., parabolic) regression was fitted through the individual sets of peak power data obtained from 8 drop heights (named as the method of fitting). Presuming the regression equation:
where DH is the applied drop height and a, b, and c parameters, the first derivative allowed for calculation of the DHopt corresponding to the maximum of the fitted individual curve:
while the corresponding correlation coefficient and 95% confidence intervals (CIs) revealed the strength of the tested drop height–power relationship. The corresponding median (range, 95% CI) correlation coefficients of the individual second-order polynomial regressions were r = 0.81 (0.59–0.97, CI = 0.04). Note that despite a limited number of data points, all individual relationships seemed to be significant (p ≤ 0.05), except one which remained somewhat below the level of significance (r ≥ 0.63).
Descriptive statistics were calculated for all experimental data as mean and standard deviation (SD). To explore absolute and relative reliability of all dependent variables (i.e., PFecc, PFcon, Tecc, Tcon, PPecc, and PPcon), as well as, the 2 methods for determination of DHopt, intraclass correlation coefficients (ICCs, model 3,1) were used to determine between-subject reliability (39), whereas within-subject variation was determined by calculating coefficient of variation (CV, (14)) and standard error of measurement (SEM) (39). Ninety-five percent confidence intervals (95% CI) were determined for ICC, CV, and SEM. In addition, we used a repeated-measure 1-way analysis of variance (ANOVA) and Tukey post hoc multiple comparison test for the detection of possible systematic bias between 3 consecutive trials (33). Also, the assumption of linearity was confirmed (p ≤ 0.05). Pearson's correlations and dependent-samples t-test was used for the detection of possible relationship and systematic difference between the 2 applied methods. Also, relationships between DHopt and corresponding subject maximal strength characteristics (MDS, and 1RM/BM0.67) were determined by Pearson's correlations. The magnitude of the relationship was considered either small (r > 0.1), moderate (r > 0.3), or large (r > 0.5) in line with standard Cohen's suggestions (9), although even the “large magnitude” could leave up to 75% of the variance unexplained. Note that applied Shapiro-Wilks test confirmed the normality of the distribution (p ≥ 0.09) for the both MSmax variables (i.e., MDS and 1RM/BM0.67).
Independent-samples t-test was used for the between-group analyses (strong vs. weak) of the subject characteristics (i.e., height, weight, percentage of body fat, MDS, and 1RM/BM0.67). Because all sets of DJ data revealed normal distribution and homogeneity of variance between samples for all dependent variables (p > 0.05), a 2-way mixed-model ANOVA was used to evaluate the main effects of drop height (0.12, 0.22, 0.32, 0.42, 0.50, 0.62, 0.72, and 0.82) and group (strong and weak) on all dependent variables (i.e., PFecc, PFcon, Tecc, Tcon, PPecc, and PPcon), separately. A Greenhouse-Geisser adjustment was made to the degrees of freedom in case of violation of the sphericity condition. When the main effects were revealed, Tukey post hoc tests were applied. Finally, for the detection of possible differences in DHopt between groups, we used independent t-test separately for the both of applied methods.
A significant level of p ≤ 0.05 was used for all comparisons. According to Cohen (9), the magnitude of difference was tested by means of effect size, where difference was considered either small (0.2), moderate (0.5), or large (0.8) for t-test, whereas the partial eta squared (pη2) was calculated for the ANOVAs with the values of 0.01, 0.06, and above 0.15 considered to be small, medium, and large, respectively. In addition, the statistical power of difference (1 − β) was calculated (37). All statistical tests were performed using SPSS 16.0 (SPSS Inc., Chicago, IL, USA) and Office Excel 2007 (Microsoft Corporation, Redmond, WA, USA).
Kinetics and Kinematics Data Reliability
The absolute and relative reliability of the calculated dependent variables has been shown to be moderate to high across the range of the applied drop heights: PFecc (ICC = 0.49–0.83, CV = 5.4–7.8%), PFcon (ICC = 0.78–0.91, CV = 5.2–8.4%), Tecc (ICC = 0.78–0.88, CV = 6.2–9.4%), Tcon (ICC = 0.73–0.86, CV = 4.9–6.9%), PPecc (ICC = 0.57–0.92, CV = 8.4–11.4%), and PPcon (ICC = 0.90–0.95, CV = 4.2–8.6%). No significant differences were recorded among 3 consecutive trials for either of the variables (p > 0.05).
Methods for Determination of the Optimum Drop Height
Descriptive statistics and intratrial reliability coefficients of the applied method for determination of DHopt are presented in Table 1. The method of picking demonstrated poorer absolute (i.e., ICC; 0.42 vs. 0.74) and relative (i.e., CV; 37.6 vs. 17.0%) reliability compared with the method of fitting, respectively. No significant differences in DHopt were recorded among 3 consecutive trials for either of the methods (p > 0.05). Also, comparison of the 2 methods for determination of DHopt showed large mutual relationship (r = 0.61, p < 0.01), whereas DHopt identified using the method of picking was significantly (p = 0.03) higher than the DHopt identified by the method of fitting (0.47 vs. 0.43 m). An example of possible differences between the applied methods is illustrated in Figure 1.
Relationship Between Maximal Strength and Optimum Drop Height
Table 2 depicts correlation analysis between DHopt, assessed using the both methods, and corresponding subject's MSmax characteristics. The obtained results indicate moderate relationship between both the absolute and relative MSmax, and DHopt (determined through the method of fitting). Note that the method of picking failed to show any significant relationships between observed variables.
Effect of Maximal Strength on Kinetic, Kinematic, and Power Output Pattern
The subject's characteristics of the strong and weak groups are summarized in Table 3. Independent t-test revealed significant group differences in absolute and body mass–normalized maximum squat strength only (p < 0.001), where the effect sizes were exceptionally high (i.e., Cohen's d > 0.8), as well as statistical power of difference (1 − β = 97–100%).
The following figures show the averaged across-the-subject values of the variables depicting the corresponding kinetic and kinematic patterns (Figure 2), and the produced muscle power output (Figure 3) observed under the different drop height applied on the 2 groups in tested DJs. The main effects of group, drop height, and their interactions, as well as the corresponding post hoc tests of the main effects are presented in Table 4. The statistical power of difference for the all detected effects were acceptable (1 − β = 52–100%). Of particular importance could be a decrement in muscle power output during propulsion phase observed across the applied drop heights (i.e., PPcon) with respect to DHopt. As a result, the subjects lost on average 2–13% (strong group) and 4–20% (weak group) of maximal power depending on the drop height. Note also the observed 2-way interactions for both PPecc and PPcon. The interactions reflected that the stronger individuals at lower drop heights (i.e., at 0.22 m; pairwise comparisons, p ≤ 0.05) generate higher power output during braking phase (i.e., PPecc) compared with the weaker individuals, whereas in propulsion phase (i.e., PPcon), the strong group demonstrated higher production of muscle power at higher drop heights (i.e., 0.62, 0.72, and 0.82 m; pairwise comparisons, p ≤ 0.05) in relation to the weak group.
Effect of Maximal Strength on Optimum Drop Height
Table 5 shows the main finding of this study. On average, the stronger individuals demonstrated higher DHopt values than individuals from the weaker group in the both methods (i.e., 0.15–0.17 m). Independent t-test confirmed significant difference between groups for the both of applied methods (p ≤ 0.05), whereas the effect size showed large differences (i.e., Cohen's d > 0.8). In addition, statistical power of difference was exceptionally high (1 − β = 87–90%).
In this study, we evaluated the effect of MSmax on DHopt that maximizes power output in DJs, and also we tested the 2 hypotheses. In addition to the acceptable reliability of the 2 applied methods for determination of DHopt (hypothesis 1), we also expected the relationship between MSmax and DHopt, as well as differences in DHopt between the individuals with distinctively different strength levels (hypothesis 2). Consistently with our hypotheses, we found that both the acceptable reliability of DHopt and that DHopt was related to MSmax. Note that observed findings were valid for the method of fitting only, and not for the method of picking used in determining DHopt. However, one of the main findings was that higher DHopt was in the stronger compared with the weaker individuals. In the following text, we will focus on the methodological, theoretical, and practical interpretation of these main findings.
The standard several indices of reliability were used to evaluate the 2 applied methods for determination of DHopt in DJ. Note that there are no data about indices of reliability of the determined DHopt in the previous studies. However, of particular importance could be that the obtained results revealed that there was a noticeable difference between the tested methods in terms of reliability. Specifically, the method of fitting showed better characteristics over the method of picking in both the absolute (i.e., assessed by ICC) and relative (i.e., assessed by CV and SEM) reliability. Overall, the method of fitting revealed acceptable reliability (ICC >0.7, (37)), and satisfactory sensitivity in terms of detecting the expected relationship with MSmax variables. Conversely, the method of picking proved as unreliable and insensitive. Although the previous studies usually reported DHopt as the highest values averaged across conditions (22,3622,36), from the methodological point of view, using the applied methods for individual determination of DHopt could be more convenient. However, the method of picking was used in a few studies only (20,3120,31), whereas the method of fitting was neglected for determination of DHopt in DJs. This could be of particular importance, considering the large variability in DHopt observed across the numerous studies (5,20,22,31,365,20,22,31,365,20,22,31,365,20,22,31,365,20,22,31,36). Hence, the previous data should be taken with caution because low reliability could affect the final results (14). Also, this can potentially lead to incorrectly formulated conclusions. In addition, the applied methods revealed large mutual correlation (9), whereas the method of picking showed the significantly higher (i.e., overestimated) values of DHopt. Also, it is noteworthy that the method of fitting demonstrates better properties for describing the casual relationship between DHopt and the corresponding predictor (i.e., MSmax) variables. The observed advantages of the method of fitting over the method of picking could be found in fact that all experimental data have some errors in them, and unless the errors are negligible, it could be methodologically more appropriate to smooth the data, that is, to fit a curve approximating the data appropriately (1). Therefore, it is important to emphasize that the method of fitting used in this study allows both a reliable determination of the DHopt and detection of the expected causal relationships with MSmax variables.
Although the numerous authors previously cited the potential impact of MSmax on Lopt that maximizes maximal power output in standard power tests (11,12,1711,12,1711,12,17), there was no explicit evidence supporting this assumption in DJ regarding to DHopt. However, this study provides a new line of important evidence that MSmax as a subject-specific factor has influence on DHopt. Specifically, the existence of this cause-and-effect relationship was confirmed (for details, see Table 2 and 5), based on the fact that the moderate relationship between MSmax (assessed as 1RM squat and MDS) and DHopt was established and that the stronger individuals demonstrated the higher DHopt compared with the weaker individuals (hypothesis 2). Also, of particular importance could be the fact that level of strength differently affects kinetic and kinematic patterns of jumping and provides some benefits. Overall, it seems that the stronger individuals are more “explosive” because they demonstrated shorter ground contact duration in both the braking (Tecc) and propulsion phases (Tcon), whereas the generated force was similar. Note also that the strong group showed maximal values of muscle power output during propulsion phase (i.e., PPcon) on the higher drop height compared with the weak group (i.e., 0.62 vs. 0.32 m, respectively; Figure 3A). Although the similar effects of MSmax on Lopt for maximization of the muscle power output were showed in the other standard tasks for assessment of the muscle power output, such as cycling (e.g., 6-second maximal cycling sprint test, (30)), there are no studies that explore this effect on DHopt (i.e., Lopt in DJ test). Indeed, there were some indications that the observed effects could be expected. For instance, it was shown that stronger adults revealed maximal jumping performances (assessed as maximal jumping height) at higher drop height compared with the boys (21). On the contrary, there were no differences in DHopt between jumpers and controls (36). As in both studies, only 2 drop heights were applied (i.e., either too narrow or wide ranges), that could compromise the acceptable range in terms of describing the real maximum of jumping performances. Regarding the gender effect, DHopt seems to be larger in naturally stronger men (i.e., volleyball players and physical education students) compared with female students (20). However, the authors did not provide appropriate statistical support except descriptive comparisons of DHopt among subgroups, hence, any interpretations without statistical analysis could be questionable. The results provided by Pietraszewski and Rutkowska-Kucharska (31) showed that in heterogeneous samples, individual maximal value of relative power is obtained from a wide spectrum of applied drop heights (i.e., DHopt varied from 0.15 to 0.60 m). Because the maximal power output was used as an indicator of DHopt in only 1 study so far, the present findings are important from both the theoretical and practical perspectives.
From the theoretical perspective, of primary interest could be strength-induced properties and adaptation mechanisms of the neuromuscular system that could play a role in the recorded differences in DHopt. A relatively simple explanation of the observed phenomenon could be based on the classical force-velocity relationship of individual muscles (23). Specifically, relatively stronger muscles (such as in individuals of the strong group) may require a higher external load to reach the speed of shortening that maximizes muscle power output in the propulsion phase (16). On the contrary, for the weaker individuals, the higher (than optimal) drop height possibly affects the actin-myosin interaction in cross-bridges that could be detached when the force exceeds a certain level during the breaking phase (10). Hence, aforementioned arguments support DHopt as an important strength-dependent phenomenon from both mechanical and physiological perspective. Although the difference in MSmax was relatively large between the defined groups, the limitation of this study could be related to the sample selection (i.e., physically active students). Specifically, it would be an advantage if the selected sample included the individuals with more prominent differences with respect to the level of MSmax. In addition, a cross-sectional design applied in this study could be potentially another source of limitation. Therefore, in the future, appropriate either cross-sectional or longitudinal design should be applied to further confirm the observed effects, with ultimate goal—to propose the simple and valid regression model for prediction DHopt based on MSmax assessed as 1RM squat.
To conclude, in this study, we found that the role of MSmax on DHopt in DJ could be moderate in terms of their correlation, but the corresponding effects could be large with respect to the strength level of individuals. The observed findings suggest that drop height should be adjusted based on a subject's neuromuscular capacity to produce MSmax. Hence, from the perspective of strength and condition practitioners, MSmax should be considered as an important factor that could affect the DHopt, and therefore should be used for its adjustment in terms of optimizing athlete's testing, training, or rehabilitation intervention.
Regarding the possible practical implications of this study, note that numerous authors have suggested that the plyometric training (based on DJs exercise) performed at DHopt could be effective in both improving jumping performance and preventing of athletes' injuries (6,24,266,24,266,24,26). Therefore, the present findings suggest the importance of defining and applying the accurate DHopt with respect to the individual MSmax. Namely, the strength and conditioning practitioners should adjust DHopt based on the achieved 1RM in squat, since cause-and-effect relation was established (i.e., DHopt was related to MSmax, and the stronger individuals revealed the higher DHopt, than the weaker individuals). Thus, it is important to note that reliable and accurate defining of DHopt adjusted according level of MSmax could improve not only the outcomes of future testing and training procedures based on DJ but also preventing the occurrence of soft tissue injuries.
The authors thank Mrs. Jelena Popovic and Dr. Predrag Bozic for their valuable suggestions and comments in preparation of this article. The part of this research is supported by Ministry of Education, Science and Technological Development of the Republic of Serbia, Grant No. III41007. The authors disclose professional relationships with companies or manufacturers who will benefit from the results of this study. The results of this study do not constitute endorsement of the product by the authors or the National Strength and Conditioning Association.
1. Akima H. A new method of interpolation and smooth data curve fitting based on local procedure. J Assoc Comput Machinery 17: 589–602, 1970.
2. Asmussen E, Bonde-Petersen F. Storage of elastic energy in skeletal muscles in man. Acta Physiol Scand 91: 385–392, 1974.
3. Baca A. A comparison of methods for analyzing drop jump performance. Med Sci Sports Exerc 31: 437–442, 1999.
4. Baker D, Nance S, Moore M. The load that maximizes the average mechanical power output during jump squats in power-trained athletes. J Strength Cond Res 15: 92–97, 2001.
5. Bassa EI, Patikas DA, Panagiotidou AI, Papadopoulou SD, Pylianidis TC, Kotzamanidis CM. The effect of dropping height on jumping
performance in trained and untrained prepubertal boys and girls. J Strength Cond Res 26: 2258–2264, 2012.
6. Bobbert MF. Drop jumping
as a training
method for jumping
ability. Sports Med 9: 7–22, 1990.
7. Bobbert MF, Huijing PA, van Ingen Schenau GJ. Drop jumping
. II. The influence of dropping height on the biomechanics of drop jumping
. Med Sci Sports Exerc 19: 339–346, 1987.
8. Byrne PJ, Moran K, Rankin P, Kinsella S. A comparison of methods used to identify “optimal” drop height for early phase adaptations in depth jump training
. J Strength Cond Res 24: 2050–2055, 2010.
9. Cohen J. Statistical Power Analysis for the Behavioral Sciences. Hillsdale, NJ: Lawrence Erlbaum Associates, 1988.
10. Cormie P, McGuigan MR, Newton RU. Developing maximal neuromuscular power: Part 1-biological basis of maximal power production. Sports Med 41: 17–38, 2011.
11. Cormie P, McGuigan MR, Newton RU. Developing maximal neuromuscular power: Part 2-training
considerations for improving maximal power production. Sports Med 41: 125–146, 2011.
12. Cronin J, Sleivert G. Challenges in understanding the influence of maximal power training
on improving athletic performance. Sports Med 35: 213–234, 2005.
13. Hill AV. The heat of shortening and the dynamic constants of muscle. Proc R Soc Med (Lond) 126: 136–195, 1938.
14. Hopkins WG. Measures of reliability in sports medicine and science. Sports Med 30: 1–15, 2000.
15. Jaric S. Muscle strength testing
: Use of normalisation for body size. Sports Med 32: 615–631, 2002.
16. Jaric S, Markovic G. Leg muscles design: The maximum dynamic output hypothesis. Med Sci Sports Exerc 41: 780–787, 2009.
17. Kawamori N, Haff GG. The optimal training
load for the development of muscular power. J Strength Cond Res 18: 675–684, 2004.
18. Kibele A. Technical note. Possible errors in the comparative evaluation of drop jumps from different heights. Ergonomics 42: 1011–1014, 1999.
19. Komi PV. Strech-shortening cycle. In: Strength and Power in Sport. Komi P.V., ed. London, United Kingdom: Blackwell, 1992, pp. 169–179.
20. Komi PV, Bosco C. Utilization of stored elastic energy in leg extensor muscles by men and women. Med Sci Sports 10: 261–265, 1978.
21. Lazaridis SN, Bassa EI, Patikas D, Hatzikotoulas K, Lazaridis FK, Kotzamanidis CM. Biomechanical comparison in different jumping
tasks between untrained boys and men. Pediatr Exerc Sci 25: 101–113, 2013.
22. Lees A, Fahmi E. Optimal drop heights for plyometric training
. Ergonomics 37: 141–148, 1994.
23. MacIntosh BR, Holash RJ. Power output and force-velocity properties of muscle. In: Biomechanics and Biology of Movement. Nigg B.M., MacIntosh B.R., Mester J., eds. Champaign, IL: Human Kinetics, Inc., 2000, pp. 193–210.
24. Malfait B, Sankey S, Firhad Raja Azidin RM, Deschamps K, Vanrenterghem J, Robinson MA, Staes F, Verschueren S. How reliable are lower-limb kinematics and kinetics during a drop vertical jump? Med Sci Sports Exerc 46: 678–685, 2014.
25. Markovic G. Does plyometric training
improve vertical jump height? A meta-analytical review. Br J Sports Med 41: 349–355, 2007.
26. Markovic G, Mikulic P. Neuro-musculoskeletal and performance adaptations to lower-extremity plyometric training
. Sports Med 40: 859–895, 2010.
27. McBride JM, Triplett-McBride T, Davie A, Newton RU. A comparison of strength and power characteristics between power lifter, Olympic lifters, and sprinters. J Strength Cond Res 13: 58–66, 1999.
28. Norton K, Marfell-Jones M, Whittingham N, Kerr D, Carter L, Saddington K, Gore C. Anthropometric assessment protocols. In: Physiological Tests for Elite Athletes. Gore C.J., ed. Champaign, IL: Human Kinetics, 2000, pp. 66–85.
29. Nuzzo JL, McBride JM, Dayne AM, Israetel MA, Dumke CL, Triplett NT. Testing
of the maximal dynamic output hypothesis in trained and untrained subjects. J Strength Cond Res 24: 1269–1276, 2010.
30. Pazin N, Bozic P, Bobana B, Nedeljkovic A, Jaric S. Optimum loading for maximizing muscle power output: The effect of training
history. Eur J Appl Physiol 111: 2123–2130, 2011.
31. Pietraszewski B, Rutkowska-Kucharska A. Relative power of the lower limbs in drop jump. Acta Bioeng Biomech 13: 13–18, 2011.
32. Schmidtbleicher D. Training
for power events. In: Strength and Power in Sport. Komi P.V., ed. London, United Kingdom: Blackwell, 1992, pp. 381–395.
33. Thomas J, Nelson J, Silverman SJ. Research Methods in Physical Activity. Champaign, IL: Human Kinetics, 2005.
34. Ugrinowitsch C, Tricoli V, Rodacki AL, Batista M, Ricard MD. Influence of training
background on jumping
height. J Strength Cond Res 21: 848–852, 2007.
35. Vanrenterghem J, De Clercq D, Van Cleven P. Necessary precautions in measuring correct vertical jumping
height by means of force plate measurements. Ergonomics 44: 814–818, 2001.
36. Viitasalo JT, Salo A, Lahtinen J. Neuromuscular functioning of athletes and non-athletes in the drop jump. Eur J Appl Physiol Occup Physiol 78: 432–440, 1998.
37. Vincent W. Statistics in Kinesiology. Champaign, IL: Human Kinetics, 2005.
38. Vuk S, Markovic G, Jaric S. External loading and maximum dynamic output in vertical jumping
: The role of training
history. Hum Mov Sci 31: 139–151, 2012.
39. Weir JP. Quantifying test-retest reliability using the intraclass correlation coefficient and the SEM. J Strength Cond Res 19: 231–240, 2005.
40. Young W, Pryor J, Wilson GJ. Effect of instructions on characteristics of countermovement and drop jump. J Strength Cond Res 9: 232–236, 1995.
Keywords:Copyright © 2015 by the National Strength & Conditioning Association.
jumping; drop depth; stretch-shortening cycle; training; testing