This is a quantitative study, conducted as part of a larger, longitudinal screening study realized in collaboration with the FSH in Eindhoven (NL). Its primary aim was to determine the relationship between the LQ-YBT and single-leg hop performance measures. The tests were performed on a population of first-year PETE students. It was hypothesised that there would be weak correlations between the two screening measures, which was confirmed by the results of this study.
Mainly negligible to weak correlations (r=0.260–0.457; p < 0.05) have been established between bilateral LQ-YBT reach directions and single-leg hop test scores. Furthermore, there was no significant correlation between anterior right-left asymmetry on the LQ-YBT and the hop tests, nor between the anterior right-left asymmetry and the LSI of the hop tests. To the author’s knowledge this was the first study comparing the SLH and the SLTH to the LQ-YBT, when tested simultaneously. Unlike the insignificant to weak correlations found in this study, Garrison et al. (38) have recently suggested that >
4 cm asymmetry in the LQ-YBT ANT at 12 weeks post ACL reconstruction seems to identify subjects who did not attain 90% LSI on the SLH and SLTH at time of return to sport.(38) The hop tests are functional tests that assess power, strength, neuromuscular control, balance, and confidence in the limb.(23,27) Although the LQ-YBT challenges balance, strength, flexibility, neuromuscular control, range of motion, core stability, and proprioceptive abilities,(14) the results of this study indicate that it measures different constructs than the hop tests. One explanation may be the different biomechanics used during jumping and landing tasks compared to squatting tasks.(35) While the LQ-YBT mainly consists of controlling the lower extremity in the sagittal plane, the HTs additionally require that the subject’s lower extremity muscles have a greater ability to produce power and movement during take-off and landing phases.(39) During landing tasks, impact forces need to be absorbed, and pre-stretched muscles need to be utilized by the lower extremity.(35) In fact, Donohue et al. (35) noted that squat tasks, such as those performed during the LQ-YBT, may not be sufficient for assessing sagittal plane motion during landing.
Higher correlations (r=0.348–0.453; p < 0.05) were found between the composite reach scores and the HTs. These findings may be explained by the fact that similar muscle activations are noted during landing and push-off phases of a jump as during the different reach directions of the LQ-YBT. For each reach direction of the LQ-YBT, muscles of the stance-leg are activated to a different extent.(40) The m.
vastus medialis and lateralis are most active in the anterior direction, the m. biceps femoris and the m.
tibialis anterior are most active in the posterolateral reach direction, and the m. tibialis anterior is most active in the posteromedial direction.(40) In comparison, during the landing phase of a jump, the m.
tibialis anterior muscle is eccentrically activated to stabilise the ankle joint.(41) The m. vastus lateralis acts to stabilise the knee, and to decelerate the flexion movement at the knee joint. In contrast to the m.
tibialis anterior, whose action is inhibited by the activation of the triceps surae during the push-off phase of a jump, the m. vastus lateralis remains active to extend the knee joint.(41) Even though biomechanics differ between jumping and landing tasks compared to squatting tasks, the composite reach score, representing a combination of all three reach directions of the LQ-YBT, may, thus, reflect similar muscle
activation patterns as required during different phases of a jump.
As an aside, correlations between left LQ-YBT and left HTs scores were slightly higher than those between right LQ-YBT and right HTs scores. In this study, the dominant limb was defined as the preferred stance-leg used by the participant when kicking a ball. This difference may be explained by the majority of the participants’ left limb dominance.
The second purpose of this study was to investigate if there was a significant difference between participants who had < 4 cm and those who had ≥ 4 cm difference in the LQ-YBT ANT, with respect to sports participation. It was hypothesised that the distribution would be different across categories of sport. The results showed no statistically significant variance. The hypothesis was, therefore, rejected.
In the present study, the right-sided normalized mean (±SD) anterior reach distance of the total research population (66.91±7.26 cm) was lower than the scores of high school basketball players and female soccer players tested by Plisky et al. (11,12) Unfortunately, it was difficult to compare the left-sided normalized anterior scores to existing literature because they were not normally distributed. However, considering the discrepancies in anterior reach distances in literature, it seems clear that differences exist between types of sport. Bressel et al. (42) found that there were no discrepancies between gymnasts and soccer players in terms of dynamic balance, whereas basketball players presented inferior dynamic balance compared to soccer players. The same study (42) also stated that the statistical differences in dynamic balance among different sports may be more related to specific sensorimotor challenges imposed by each sport, than to simply general sports activities. The reason behind the negligible difference between sports in this study may be explained by the fact that the neuromuscular system of PETE students may have adapted to a multitude of functional tasks through their experience in engaging in a variety of intracurricular sports activities.(43) Additionally, given their participation in 7-8 hours per week of intracurricular sport lessons, a considerable number of students also indicated that they play more than one extracurricular sport. Thus, division of participants into three categories of sports may not have been appropriate for, nor representative of, this research population.
This has been the first research paper investigating differences in sport participation in relation to cut-off points for injury risk. Descriptive data related to scores below or above the cut-cut-off points are not available in the literature. In fact, to this day, there exists no particular consensus about sport-specific cut-off points for risk of injury in the literature. Smith et al. (16) determined a single cut-off point of ≥ 4 cm asymmetry in the LQ-YBT ANT across multiple sports to be associated with an increased risk of non-contact injury. In contrast, Butler et al. (15) found that collegiate American football players had 3.5 times more risk of encountering a noncontact lower extremity injury when scoring below 89.6% CS. A third study by Plisky et al. (11) observed that a CS of less than or equal to 94 % was associated with increased risk of injury in all players and females only and that ≥ 4 cm asymmetry was associated with increased lower extremity injury risk in all players, males only and females only. This lack of consensus suggests that it may be valuable to investigate sport-specific cut-off points, as the sensorimotor system is not triggered the same way in all sports.(42) However, this may not be sufficient differentiation considering the fact that there are even discrepancies between individual positions within certain sports.
Another goal of the present study was to determine if there was a significant difference between participants with ≥ or < 90% LSI on the hop tests, with respect to sports activity. The data did not allow for this type of analysis due to the lack of participants scoring < 90% LSI. Therefore, HTs scores could merely be described. In this study, SLH scores (right: 125.75±22.78; left: 127.76±24.39) were lower than scores found by Myers et al. (44) and Munro et al. (29), but higher than scores established by Brumitt et al. (33). Additionally, SLTH distances were considerably lower (right: 421.79±73.89; left:
424.42±77.26) than scores found in previous studies.(30,44) The differences among studies in the distances hopped may be due to the differences in their study populations. In the study conducted by Myers et al. (44), soccer and basketball players were tested, whereas only soccer players were tested in the study by Hamilton et al. (30). These sports require a considerable amount of jumping, direction changes, and speed. In comparison, the sample of the current study comprised an equal number of individuals who engaged in jumping sports, and those who engaged in sports with a minimal amount of jumping tasks or in no sports at all. This might have led to better hop distances in the studies by Myers et al. (44) and Hamilton et al. (30) compared to the current study. Different levels of competition, gender, and the lack of consensus on restrictions to arm movements in hop test protocols may also be partly responsible for the discrepancies in hop distances found in the literature.(30,33,44) In fact, previous research has shown that male athletes performed better than female athletes on all hop tests (33,44) and that free arm motions account for 21.2% more jump distance in contrast with restricted arm movements.(45)
The lack of consensus in the literature about the notion of dominant and non-dominant limbs in calculating the hop test LSIs makes it difficult to compare results of LSI scores.(29,30,44) This is further impeded by the poor agreement between LSI cut-off scores used to decide if a subject is ready to return to and/or participate in sports. (29,46,47) Noyes et al. (46) proposed a LSI of 85%, whereas Grindem et al. (47) determined a cut-off LSI of 88% as the appropriate measure of adequate limb symmetry. Munro et al. (29) even suggested the adoption of a 90% LSI during rehabilitation and conditioning.
Several strengths in this study are noted. Firstly, standardised protocols and instructions were followed throughout the testing procedure in order to ensure consistency of the measurements. This enables easy reproducibility in future studies, as well as in clinical practice. Furthermore, in contrast to a number of other studies that used the average balance score of both limbs, this study took both limbs separately into account. This is an important factor because a difference in reach distance between the two limbs is considered a potential risk factor for injury to either limb.(11) In fact, proprioceptive deficits, a lack of static and dynamic stability and a lack of muscle strength, might contribute to altered biomechanics and increased injury risk not only in the less adept leg, but also in the more adept contralateral lower extremity.(48) Due to poor balance on the less adapt limb, the athlete might put increased load on the more adept limb, which in turn will absorb excessive forces.(49) The less adept limb may not supply a stable base of support for tasks such as landing and pivoting, and consequently, it may put both limbs at increased risk for injury.(49,50) Studies that averaged the right- and left-sided reach distances did not take poor balance into consideration as a risk factor for injury.
Nevertheless, it is also important to note the limitations of the current study. One of its major limitations is the limited number of participants. Out of 190 potential participants, only 79 presented themselves for the testing, and only 58 could be used in the data analysis. Consequently, several specific analyses could not be appropriately conducted due to the small sample sizes that resulted when dividing the total population into groups. Furthermore, the sample was screened for injuries by means of a questionnaire, and participants were excluded if they had encountered a lower extremity or spinal injury 6 months prior to testing that they had not recovered from on the day of testing. Including those participants in the current study might have ultimately resulted in an increased number of participants with ≥ 4 cm asymmetry in the LQ-YBT ANT and with less than 90% LSIs on the HTs. In any case, despite Shaffer et al.’s (13) findings of good inter-rater reliability (ICC= 0.85-0.93) of the LQ-YBT when performed in a large group testing setting by assessors with minimal experience, the limited experience of the assessors in this study may also have influenced the efficacy and consistency of the rating. In contrast to the study by Shaffer et al. (13), the practice hours in this study were not supervised by a more experienced assessor. Furthermore, participants performed each test in pairs and the screens that were used to divide the different testing stations were not sufficient to completely shield each station. Verbal and visual input from other students may thus have influenced the participants’ concentration and motivation and, ultimately, may have led to inferior or superior scores. Another limiting factor was the inability to control the students’ schedules and, consequently, the sports activities they participated in prior to testing. Students might have had fatigued muscles, which could have led to decreased performance on both the hop tests and the YBT. Previous studies (51,52) have shown that fatigue alters landing biomechanics during single-leg hop tasks and that it can induce a decrease in motor-control performance. Furthermore, due to time constraints, participants had only one practice trial for each of the four hop tests. This may have been insufficient to account for the motor learning that takes place when first performing the tests.(23,29) However, when consulting the existing literature, there is no evidence of consensus regarding the number of practice trials that should be performed.(28,29,53) Krishnan (53) even stated that practice trials could be minimised without compromising validity, especially when only testing LSI. Additionally, the battery of hop tests used in this study covers many aspects of athletic performance, but it does not trigger the endurance element necessary to a sport-specific setting. In fact, when a volleyball player is repeatedly jumping and landing, power endurance is an important variable to take into consideration.(19) With increasing fatigue, the athlete’s flexion angles at the hip, knee, and ankle may decrease, and less energy will be absorbed by the MTCs. This, in turn, might lead to an increased risk of injury.(19) Therefore, it might be useful to include an endurance measure -such as the side hop test- in the pre-participation screening. Finally, a multitude of correlations were calculated, which might have led to type 1 errors due to alpha inflation. This could have been corrected by using the Bonferroni adjustment. However, such an adjustment is a very conservative method that may have led, in turn, to type II errors (false negatives). Thus, this method was not applied in this study.
Due to their affordability and easy administration, both tools could easily be integrated into a pre-participation screen for students at the FSH in Eindhoven. The predominantly low correlations between
the HTs and the LQ-YBT support the idea that both tests appear to measure different constructs. Thus, both tasks may be important to consider during injury risk screening and/or rehabilitation in order to cast a wider net for potential deficits that may influence an individual’s readiness to participate or return to sports activities. Furthermore, based on the results of the injury risk screening, exercise-based intervention programs could subsequently be offered in order to diminish the risk of encountering a lower extremity injury. These exercise-based training programs should consist of a variety of neuromuscular, core stability, strength, balance, and plyometric exercises, which have all been proven to effectively decrease the risk of lower extremity injuries.(54–58)
Due to their affordability and minimal requirements of material, both tests could, thus, also be used as preventive screening measures in sports clubs in order to act on a broader scale to prevent sports injuries. The two measurement instruments could also easily be performed in the physiotherapy practice, not only to screen for injury risk and readiness to return to sport, but also to objectively follow a patient’s progress throughout rehabilitation.(10,23)
To the author’s knowledge, this is one of the first studies investigating the relationship between single-leg hop performance and LQ-YBT measures. It is hoped that it will stimulate further research in this field.
Firstly, studies should be conducted to determine gender, sport, and position-specific cut-off points for injury risk on the LQ-YBT and more research should be done determining the accuracy of the HTs in predicting injury risk. Secondly, studies should seek gender specific and sport-specific normative data for the LQ-YBT and for the HTs within larger populations. These findings could be helpful for clinicians and coaches in rehabilitation and pre-participation screening when evaluating patients’ or athletes’
readiness to engage in sports activities, with minimal risk of re-injury.(10) Thirdly, future studies should also investigate the effect of the number of sporting hours and of participation in multiple sports on the two tests. Finally, it may be interesting to investigate the predictive ability of more newly developed screening tools, such as the Performance Matrix, regarding injury risk.(59) This screening tool includes sport-specific screens aimed at identifying performance-related inefficient control of movement in the kinetic chain, to allow for the development of specific training programs.(59)