Comparison of traditional and body height-adjusted assessment method for standing long jump

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Traditionally, body height (hereinafter referred to as height) is not considered in the assessment (i.e., traditional SLJ or SLJ_T) and this may significantly disadvantage smaller children. Data on SLJ, pole climbing (APCT) and push-up (PU) were collected from boys and girls in Austrian regular primary, secondary, and high school as well as in secondary and high school in elite sports classes. For SLJ, we computed an alternative score by dividing jumping distance by height as correction (height-adjusted SLJ or SLJ_H). In a linear mixed model, the regression slopes of SLJ_T on height were significantly different from that of APCT and PU in the five different contexts defined by school and type of class. In contrast, corresponding regression slopes of SLJ_H differed only in minor ways from those of APCT and PU. Thus, SLJ_H removed a bias due to height in the assessment of body strength and led to a fairer assessment of participants across different schools comprising regular and elite sports classes. Health Policy Pediatrics General Practice Gender Studies Statistical Theory Physiology standing long jump standing broad jump fitness assessment test battery fitness testing Figures Figure 1 Figure 2 Figure 3 Figure 4 Introduction The standing long jump (SLJ) - also called standing broad jump - is considered a suitable parameter for assessing the strength of the lower body musculature and may also be used to assess overall body strength. [ 1 ] In the ancient Olympic Games (five sequential SLJ´s) and the modern Olympic Games, the SLJ was part of the program as a sporting discipline until 1912. [ 2 , 3 ] Currently, the SLJ is used as one of seven fitness parameters in the screening process for a sports career in the American National Football League (NFL) and, together with other psychological parameters, is used to rank players in the annual NFL Draft. [ 4 ] Furthermore, the SLJ is used in many national and international fitness test batteries [ 5 – 14 ], talent screenings [ 15 – 18 ] and selections for jobs with physical requirements [ 19 – 21 ] because the test is easy to conduct, cost-effective and provides a valid assessment of muscle strength. [ 1 ] In SLJ, the body's center of gravity (from an optimal body angle) must be catapulted forward with the highest possible take-off velocity and an optimal take-off angle along a jumping path. During the flight phase, the lower limbs are moved forward as much as possible underneath the center of gravity in order to achieve the widest possible distance, under the requirement that the center of gravity continues to move forward during landing. [ 22 – 24 ] The SLJ is a complex specific test, and its results are influenced by a several factors. [ 25 ] Physiological factors include the strength of the upper and lower body limbs [ 26 , 27 ], flexibility as a relevant factor for jumping height. [ 28 ] Psychological factors such as concentration and motivation also affect SLJ performance. [ 29 – 31 ] Technical elements in the execution of the jump are considered key performance factors and are divided into three phases: body movements immediately before take-off (take-off phase), behavior while in the air (flight phase), and landing technique (landing phase). [ 22 – 25 , 32 ] In addition, body weight has a significant influence on SLJ performance - obese and overweight participants perform significantly worse than those of normal weight. [ 33 , 34 ] All performance-influencing variables described above (physical, mental and technical factors) have something in common: they can be optimized through training [ 25 , 35 ] and healthy nutrition. [ 36 , 37 ] Another factor influencing achievement in SLJ is height [ 22 , 24 ], which naturally varies between individuals and is determined genetically, and cannot be adjusted by exercise or diet intervention. [ 38 ] Regarding children and adolescents, biological age and height have a non-modifiable influence on performance in SLJ. [ 39 ] The SLJ is assessed primarily by measuring the maximum jump distance to the nearest centimeter and, in specific cases, by biomechanical analysis of the individual phases of movement. [ 22 – 24 ] In contrast to the biomechanical and kinematic assessments, participants' height is not considered when assessing and classifying their performance in SLJ. Consequently, smaller children are assessed significantly worse even if they have the same take-off speed and jumping technique (i.e., the same level of motor performance), because take-off and landing distances are directly related to their height. [ 40 ] Therefore, alternative assessment methods are desirable to enable a fair, equitable and performance-differentiated assessment of SLJ achievement, particularly during growth. The aim of our study was to analyze the effects of including height as an anthropometric parameter when assessing SLJ. Materials and Methods Design and selection of participants Findings from this study are based on a cross-sectional study conducted at one school campus in Klagenfurt, Austria, to develop a novel strength [ 41 ] and balance test [ 42 ]. Three different types of schools (primary school (age 6 to 10 years), secondary school (age 11 to 14 years) and high school (age 15 to 19 years)) are located in a single building complex. Students in secondary and high school were drawn from regular and elite sports classes. The study was approved by the Research Ethics Committee of the University of Graz, Styria, Austria (GZ. 39/68/63 ex 2021/22). After approval by all school directors, a total of 1069 children, adolescents and young adults were invited to participate in the study. The legal guardians of children aged 14 years and younger were informed in writing about the content of the study and asked to consent to their children's participation. A total of 1048 (98.0%) participants or their legal guardians agreed to participate in the study and provided additional information (age, gender, and sport club membership). After excluding children younger than 6 years, adolescents 19 years or older, and those who did not participate in the SLJ or at least two of the comparative tests), 810 children and adolescents (mean age 13.2 ± 3.3 years, 43.7% female) remained for analysis; 569 were from regular and 241 from elite sport classes. All participants took part in SLJ and APCT; children in primary and secondary school (N = 450) also completed the PU (Fig. 1 ). Procedure and outcomes All anthropometric and fitness-related measurements were conducted by trained sports scientists and sports teachers under the direction of the corresponding author between September 2023 and January 2024. The primary outcome of this study are differences between traditional SLJ performance assessment (i.e., jumping distance in cm; SLJ_T) and its modified assessment method of dividing SLJ jumping distance in cm divided by height in cm (SLJ_H). Specifically, we compare their alignments with measures of pole climbing and push-ups, two alternative measures of body strength. Anthropometrics Body weight (kg) was measured to the nearest 0.1 kg using a Bosch PPW4202/01 body scale (Bosch Hausgeräte, Vienna, Austria), Height was measured to the nearest 0.1 cm using a SECA 213 stadiometer (Seca GmbH&Co, Hamburg, Germany). Using a wall-mounted measuring tape, grip height was measured to the nearest centimeter. Participants stood barefoot on the floor, hands stretched vertically upwards, and the maximum distance between the floor and the fingertips of the upward-stretched hand was measured. Body mass index (BMI) was calculated by dividing the body weight by the height in meters squared. Physical fitness assessments Standing long jump (SLJ). Standing on a long jump mat at the starting line, the participants jumped as far as possible with both feet. The shortest distance between the starting line and landing of the heels on the ground was measured to the nearest centimeter. Three attempts were carried out, and the widest was included in the analysis. Push-ups (PU). The test was carried out based on the German motor test manual [ 5 ]. Lying on their stomachs on the floor, the participants touched one hand with the other (above the gluteal muscles close to the spine.) in the starting position. To do a push-up correctly, the participants had to place their hands next to their shoulders and push their bodies up into a completely straight push-up position. In this position, they had to take one hand off the floor and touch the back of the other hand. After that, they had to put their hand back on the floor and return their body to the starting position in a controlled manner. The participants had to complete as many push-ups as possible within 40 seconds; the number of correctly performed push-ups was included in the analysis. Austrian Pole Climbing Test (APCT). The test was carried out based on the test manual by Jarnig et al. [ 41 ]. Participants climbed continuously on a round, smooth climbing pole (steel pole ST35, ⌀ (42.5 ± 0.5) mm × (3.3 ± 0.1) mm) fixed at the top and bottom. Norm markings at heights of 2.0, 2.5, 3.0, 3.5 and 4.0 m above the ground were marked on the climbing pole. It was mandatory to climb over as many norm marks as possible; norm marks were considered to be climbed over when the participant's chin was placed over them. Within a period of 2 minutes, any number of climbing attempts could be started and breaks could be taken between climbing attempts according to individual needs. The last climbing attempt started within the two-minute period could be completed by each participant without time limit. The highest norm marking climbed was documented for each climbing attempt, and the overall climbing performance was calculated by adding up the heights of each climbing attempt, taking into account the grip height and the thickness of the fall protection mat. Validity and reliability of these fitness tests are well documented and considered suitable for use in field studies [ 41 , 43 ]. Standardization For SLJ_T and height z-scores (i.e., SLJ_Tz & zHeight) were calculated based on age- and gender-specific reference values. Since thus far no national reference values are available for SLJ or height, the mean ( M ) and standard deviation ( SD ) were derived based on the latest international percentiles [ 44 ] (Table S1 & S2). To derive reference values for SLJ_H, M of SLJ ( M SLJ ) and height ( M height ) as well as the SD for SLJ ( SD SLJ ) (derived in Table S1 & S2) were used and age- and gender-specific M and SD values of SLJ_H were calculated (see supplementary material Table S3 - incl. calculation formula) to enable the calculation of z-scores for the novel assessment method (SLJ_Hz). Age- and gender-adjusted PU and APCT z-scores were based on age- and gender-specific reference values [ 5 , 41 ]. BMI z-scores were based on the International Obesity Task Force (IOTF) reference values [ 45 ]. Statistical Analysis For data analyses and graphics, we used mainly tidyverse (version 2.0.0) [ 46 ] and easystats (version 0.7.5) [ 47 ] package suites in the R language (version 4.5.1 [ 48 ]). Inferential statistics were based on linear mixed models (LMMs). They were estimated and post-processed with the lme4 package (version 1.1-37a; Bates et al., 2015a [ 49 ]). Model selection followed the recommendations of Bates et al. (2015b) [ 50 ]. Due to the small number of observations only varying intercepts could be estimated with child as random factor. Inferential statistics were based on two LMMs. The first one tested the hypothesized misalignment of traditional SLJ_T and alignment of height-adjusted SLJ_H with APCT. In the first set, we regressed APCT, SLJ_T, and SLJ_H (specified as three levels of a repeated-measure factor assessment) on height z-scores, adjusted for gender and age using gender as covariate nested within five contexts defined by elite/regular sports class and primary/secondary/high school. The slope for regressions of APCT on height was expected to be misaligned (i.e., ideally of a different sign) with the slope for SLJ_T, but aligned (i.e., ideally not significantly different) with the slope of SLJ_H. The second LMM replicated this analysis using PU in place of APCT. As PU was not assessed in high school, interactions of assessment contrasts with height were tested only in three contexts. As a further check of the relative merits of SLJ_H and SLJ_T, we predicted APCT and PU fitness by adding SLJ_T and SLJ_H to hierarchical multiple regression models with BMI, gender, and age in the five school/class contexts as covariates. Results Descriptives Girls and boys from five heterogeneous “contexts” (i.e., elite/regular sports classes from secondary and high school as well as from regular primary school) participated in the study. Supplement Table S4 reports breakdowns of means (M), standard deviations (SD), and number of observations (N) of standardized SLJ_H, SLJ_T, APCT, and PU scores as well as of age and BMI by gender and school. Linear regressions of the four assessments on height for girls and boys in the five contexts are shown in Fig. 2. Children in elite sports classes are clearly performing at a much higher level. More importantly, there is a clear qualitative misalignment of SLJ_T and a qualitative alignment of SLJ_H with APCT and PU in most groups, with the exception of boys in primary school and girls in regular high school, respectively. Misalignment of SLJ_T and alignment of SLJ_H with APCT and PU Statistical confirmation of SLJ_T misalignment and SLJ_H alignment was based on two LMMs that estimated (1) for each of five contexts the slopes for the regression of SLJ_T, SLJ_H, and APCT on zHeight and (2) for each of three contexts the slopes for the regression of SLJ_T, SLJ_H, and PU on zHeight whether the slopes of SLJ_T and SLJ_H were significantly different from those for APCT and PU, respectively. Table 1 shows the selection of relevant fixed effects for these assessment-by-height interactions from the final LMMs. Table 1 Selection of fixed effects for interactions of (1) APCT, SLJ_T and SLJ_H and zHeight for five contexts (top) and (2) PU, SLJ_T and SLJ_H and height for three contexts. APCT vs. SLJ_T × zHeight Coeff SE z p Regular_PS 0.13 0.04 3.06 0.002 Regular_SS 0.23 0.04 5.78 < .001 Regular_HS 0.14 0.04 3.27 0.001 Elite_SS 0.22 0.06 3.73 < .001 Elite_HS 0.41 0.08 5.28 < .001 APCT vs. SLJ_H × zHeight Regular_PS -0.04 0.04 -0.88 0.377 Regular_SS 0.06 0.04 1.43 0.152 Regular_HS -0.03 0.04 -0.64 0.520 Elite_SS 0.01 0.06 0.21 0.831 Elite_HS 0.21 0.08 2.74 0.006 PU vs. SLJ_T × zHeight Regular_PS 0.12 0.04 2.64 0.008 Regular_SS 0.24 0.04 5.86 < .001 Elite_SS 0.18 0.06 3.12 0.002 PU vs. SLJ_H × zHeight Regular_PS -0.05 0.04 -1.15 0.251 Regular_SS 0.07 0.04 1.68 0.093 Elite_SS -0.03 0.06 -0.56 0.577 Notes. For complete list of APCT-related fixed effects see Table S5 and for complete list of PU-related fixed effects see Table S6 in Supplement. zHeight = gender-age adjusted zHeight. Figure 3 visualizes the qualitative difference between zero-order regression slopes of SLJ_T on height z-scores and those of the other three assessments in the five school/class contexts. All interactions testing the difference of height-slope between SLJ_T and APCT/PU were significant. Moreover, with one exception, none of these interactions were significant for SLJ_H. The exception was APCT for children in high-school elite sports class, in this case the slope difference was only about half the size of the difference for SLJ_T (0.21 vs. 0.41). The tables of fixed effects, including also significant main effects, the effect of gender, and other interactions, are documented in Supplement Table S5 for APCT and Table S6 for PU. Prediction of PU and APCT Adjusting SLJ by children’s height did not change their correlations with each other (r = .91; partial r = .95 adjusted for age and gender) and the similarity of their correlations with APCT (r = .71 for both) and PU (r = .63 and r = .67 for SLJ_T and SLJ_H, respectively). Therefore, for example, when we regressed the two measures of body strength PU (Fig. 4A) or APCT (Fig. 4B) on SLJ_T and SLJ_H z-scores there was no loss of information associated with the adjustment. The predictions of SLJ_H scores were always very similar to the predictions of SLJ_T scores in multiple regressions including agender, age, and BMI as covariates in three or five school/class contexts; small divergences were always in the direction of steeper slopes (i.e., better fits) for SLJ_H. Changes in R 2 due to the unique effects of SLJ_H and SLJ_T were larger for SLJ_H than for SLJ_T ((APCT: 12.6% vs. 10.3%; PU: 15.6. % vs. 13.0%). Moreover, adding SLJ_H in a third step to models already including SLJ_T, significantly increased goodness of fit; APCT: F(1, 788) = 34.9, p < .001; PU: F(1, 436) = 25.9, p < .001. Conversely, adding SLJ_T to models with SLJ_H did not; F(1, 788) = 3.3, p = .07; PU: F(1, 436) = 1.2, p = .27. Discussion Toward a fair and appropriate assessment of physical fitness Anthropometric parameters and biological age directly influence fitness test results.[ 39 ] In a model calculation of the SLJ, an individual’s deviation from average height leads to a significantly better or worse assessment of muscle strength, keeping other physical parameters constant. [ 40 ] Indeed, as shown here, the usual assessment of muscle strength/fitness with the SLJ results in lower scores for smaller individuals – a difference not seen in other tests of physical muscle strength such as the APCT and PU. Using the alternative assessment method, that is taking height into account, resulted in muscle strength assessments that were comparable to the other muscle strength assessments (APCT & PU). In regular school classes, no significant differences were found between the assessments by SLJ_H, APCT, and PU in terms of height, regardless of school level (primary school, secondary school, high school). The same applies to elite sports classes in secondary school, but not to elite sports classes in high school. Elite sports classes in secondary school are attended by 10- to 14-year-old regional athletes who belong to a sports club, had to pass a sports entrance exam, and complete two to three hours of additional physical education and sports per week at school, compared to regular school classes. In contrast, elite sports classes in high school are attended by supra-regional athletes who complete high intensity, sport-specific training led by sports scientists throughout the day and do not participate in general physical education classes. In this context, the significant differences between SLJ_H, APCT, and PU in the elite sports classes in high school seem less important for a general assessment of SLH_H, as some participants (e.g., ski jumpers and track and field athletes) undergo high-intensity jump trainings and therefore the results cannot be generalized. Thus, our results and trends suggest that SLJ_H is more suitable and fairer for assessing muscle strength based on the SLJ performance than SLJ_T. The practical value of the height-adjusted score for prediction of other fitness indicators such as APCT and PU may appear to be limited given larger than .90 zero-order and partial correlations with the traditional assessment. So why bother? We submit that at a minimum the high correlations show that the benefit of fairer assessment did not come at the cost of loss of predictive value when compared with the traditional score. Moreover, the two other measures of body strength, PU and APCT, were significantly better predicted with SLJ_H than SLJ_T after adjustment for gender and age across different school and types of sport classes. In common widespread international fitness monitoring systems in Europe [ 8 ], America [ 10 ], Asia [ 12 , 51 ], Africa [ 52 ] or Australia [ 53 ], age- and gender-specific normative values are used to assess participants in the children and youth sector; biological age does not play a role in these assessment models. It is however well known that biological age should be taken into account, especially in talent selection [ 54 , 55 ], and there are methods such as Tanner stages [ 56 ] or maturity offset [ 57 ] used for this purpose in long-term studies or talent selection systems regionally. Furthermore, hand-wrist scans can be used to estimate the full-growth potential of children and adolescents [ 58 ]. However, due to cost and time restrictions, these methods are not used in widespread monitoring programs, even though biological age has a significant impact on fitness test results in children and adolescents. [ 59 ] Therefore, taking SLJ as an example, we propose to develop alternative options, for instance by taking height into account, particularly regarding fitness assessments in schools. Results of fitness tests play an important role in selecting children and young people for sports schools or elite training centers. In this context, greater height is often advantageous for athletic skills and therefore often and generally welcome.[ 38 ] In sports such as basketball, athletics, or volleyball, height is an important performance-determining parameter. In contrast, however, there are also sports like soccer where height plays no major role. Male soccer stars such as Lionel Messi and Diego Maradona have won world championship, Olympic Games and many other competitions despite being shorter than 1.70 m.[ 60 ] In team sports such as soccer, action speed, mobility, athletics, technique and game intelligence are performance-determining parameters, and a high height is not essential.[ 61 ] In such sports, assessing fitness without a disadvantage for smaller individuals would be useful, and reduce chances of overlooking talent among smaller athletes. Existing fitness test assessment methods should be critically reviewed and adapted if they are replaced by more sensible, easy-to-use and practical new assessment methods that consider anthropometric differences. This can increase fairness and equality in the field of children and young people and also increase participants' motivation. The latter aspect is worth being explored in further studies. Strengths and limitations This study has several strengths, including a large sample size and the fact that all data were collected by a team of testers consisting of four people under the supervision of the corresponding author. In addition, data from children, adolescents and young adults were analyzed and correlated with additional strength tests. One limitation is that for practical reasons the assessment of jumping performance was based only on jumping distance in relation to height. Other parameters influencing performance such as jumping technique, physical conditions and motivation were not considered. Conclusion It is important to highlight the fitness parameter being tested with SLJ. It is used as a measure of the lower body muscle strength of participants, and the actual distance jumped is not the primary outcome of interest. The usual assessment of muscle strength/fitness based on the SLJ disadvantages smaller individuals; taking their height into account (like SLJ_H) is an effective and practical alternative and results in a fairer assessment. In addition, the simple method of adjustment represents a useful addition to current scientific approaches in long-term studies in children and adolescents, as it enables a more precise evaluation during the growth period by allowing growth spurts to be specifically taken into account. Further nationwide studies should be organized and carried out to create representative normal and reference values. In addition, regional studies should be carried out to investigate whether novel assessment methods of fitness tests including anthropometrics may have an impact on the motivation of participants. Abbreviations APCT Austrian Pole Climbing Test IOTF International Obesity Task Force M Mean NFL National Football League PU Push-ups SD Standard deviation SLJ Standing long jump SLJ_H Assessment method taking into account the body height of participants SLJ_T Traditional assessment method Declarations The legal guardians of the 14- to 18-year-old participants were informed at school registration that the children in their care could be invited to participate in various studies during school hours and that they could provide consent independently." Institutional Review Board Statement The study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Research Ethics Committee of the University of Graz, Styria, Austria (GZ. 39/68/63 ex 2021/22). Informed consent was obtained from all subjects involved in the study. Conflicts of Interest The authors declare no conflicts of interest. Funding This research and the Open Access publishing costs were funded by the Austrian Federal Ministry of Education, Science and Research, grant number GZ:2024 − 0.780.614 and the Austrian Federal Ministry for Arts, Culture, Civil Service and Sport, grant number GZ:2025 − 0.021.608. The Open Access was funded by the University of Graz. The University of Graz funded open access publishing. Author Contributions Conceptualization, G.J. and M.N.M.v.P.; methodology, G.J.; formal analysis, G.J. and R.Kl.; investigation, G.J.; resources, G.J.; data curation, G.J.; writing—original draft preparation, G.J. and R.Kl.; writing—review and editing, G.J., R.Ke., R.Kl. and M.N.M.v.P.; visualization, G.J. and R.Kl.; supervision, M.N.M.v.P.; project administration, G.J.; funding acquisition, G.J. All authors have read and agreed to the published version of the manuscript. Data Availability Statement The data presented in this study are available upon request from the corresponding author. 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Br J Sports Med 47:98–108. 10.1136/bjsports-2011-090218 Vaeyens R, Lenoir M, Williams AM, Philippaerts RM (2008) Talent identification and development programmes in sport: current models and future directions. Sports Med 38:703–714. 10.2165/00007256-200838090-00001 Fuchslocher J, Romann M, Gulbin J Strategies to support developing talent, 10–14 Travers SH, Jeffers BW, Bloch CA, Hill JO, Eckel RH (1995) Gender and Tanner stage differences in body composition and insulin sensitivity in early pubertal children. J Clin Endocrinol Metab 80:172–178. 10.1210/jcem.80.1.7829608 Mirwald R, Baxter-Jones AD, BAILEY DA, BEUNEN GP (2002) An assessment of maturity from anthropometric measurements. Medicine & Science in Sports & Exercise 34 Romann M, Fuchslocher J (2016) Assessment of skeletal age on the basis of DXA-derived hand scans in elite youth soccer. Res Sports Med 24:185–196. 10.1080/15438627.2016.1191490 Leyhr D, Murr D, Basten L, Eichler K, Hauser T, Lüdin D, Romann M, Sardo G, Höner O (2020) Biological Maturity Status in Elite Youth Soccer Players: A Comparison of Pragmatic Diagnostics With Magnetic Resonance Imaging. Front Sports Act Living 2:587861. 10.3389/fspor.2020.587861 Brach B (2012) Who is Lionel Messi? A comparative study of Diego Maradona and Lionel Messi. Int J Cult Stud 15:415–428. 10.1177/1367877911422859 Bate R, Jeffreys I (2014) Soccer Speed; Human Kinetics, ISBN 9781492584803 Additional Declarations The authors declare no competing interests. Supplementary Files Supplementarymaterial.docx Cite Share Download PDF Status: Posted Version 1 posted You are reading this latest preprint version Research Square lets you share your work early, gain feedback from the community, and start making changes to your manuscript prior to peer review in a journal. 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00:54:07","extension":"html","order_by":12,"title":"","display":"","copyAsset":false,"role":"acdc-reference","size":261792,"visible":true,"origin":"","legend":"","description":"","filename":"earlyproof.html","url":"https://assets-eu.researchsquare.com/files/rs-8108094/v1/1dca351a2f6d6762fee7960a.html"},{"id":96365833,"identity":"8b3a2509-a05f-4e1c-b942-0128170f93da","added_by":"auto","created_at":"2025-11-20 10:10:50","extension":"jpg","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":94868,"visible":true,"origin":"","legend":"\u003cp\u003eFlow diagram of subject selection.\u003c/p\u003e","description":"","filename":"1.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8108094/v1/b0230fbc77a219f007cde862.jpg"},{"id":96331158,"identity":"42a22891-4da5-4849-a177-4751214bb56d","added_by":"auto","created_at":"2025-11-20 00:54:06","extension":"jpg","order_by":2,"title":"Figure 2","display":"","copyAsset":false,"role":"figure","size":47826,"visible":true,"origin":"","legend":"\u003cp\u003eZero-order regressions of SLJ_T, SLJ_H, APCT and PU on height for girls and boys in five different contexts defined by the study design: Elite and regular secondary (SS) and high schools (HS) and regular primary school (PS). Lines are linear regressions on observations.\u003c/p\u003e","description":"","filename":"2.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8108094/v1/ef82a330cd604de5b5c2f7f6.jpg"},{"id":96367353,"identity":"5735a1e3-f746-42f4-8599-cf75df0a0401","added_by":"auto","created_at":"2025-11-20 10:12:37","extension":"jpg","order_by":3,"title":"Figure 3","display":"","copyAsset":false,"role":"figure","size":40763,"visible":true,"origin":"","legend":"\u003cp\u003eZero-order regressions of SLJ_T, SLJ_H, APCT and PU on height z-scores adjusted for gender and age for five different contexts defined by the study design: Elite and regular secondary (SS) and high schools (HS) and regular primary school (PS). Lines are linear regressions on observations with 95% band of confidence intervals.\u003c/p\u003e","description":"","filename":"3.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8108094/v1/88beb82a902fbed1aa508b6b.jpg"},{"id":96331162,"identity":"2f698485-889b-4537-b034-01a94fa79de8","added_by":"auto","created_at":"2025-11-20 00:54:07","extension":"jpg","order_by":4,"title":"Figure 4","display":"","copyAsset":false,"role":"figure","size":47768,"visible":true,"origin":"","legend":"\u003cp\u003eZero-order regressions of (A) push-ups (PU) and (B) APCT on traditional and height-adjusted SLJ z-scores (i.e., SLJ_Tz and SLJ_Hz, respectively). Lines are linear regressions on observations with 95% band of confidence intervals for three (PU) and five (APCT) different school/class contexts.\u003c/p\u003e","description":"","filename":"4.jpg","url":"https://assets-eu.researchsquare.com/files/rs-8108094/v1/ef9b25f0982ea0c2c2758a2e.jpg"},{"id":96453461,"identity":"2dd654b0-95d1-4ff2-8931-fc069c5457b0","added_by":"auto","created_at":"2025-11-21 10:00:00","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":935599,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8108094/v1/255dffcf-4e35-4275-8e2e-a70666d58b8e.pdf"},{"id":96331156,"identity":"b0720a4f-5547-46e9-8d9a-5f94b9da77df","added_by":"auto","created_at":"2025-11-20 00:54:06","extension":"docx","order_by":1,"title":"","display":"","copyAsset":false,"role":"supplement","size":54528,"visible":true,"origin":"","legend":"","description":"","filename":"Supplementarymaterial.docx","url":"https://assets-eu.researchsquare.com/files/rs-8108094/v1/7d617edb934170872671f197.docx"}],"financialInterests":"The authors declare no competing interests.","formattedTitle":"\u003cp\u003e\u003cstrong\u003eComparison of traditional and body height-adjusted assessment method for standing long jump\u003c/strong\u003e\u003c/p\u003e","fulltext":[{"header":"Introduction","content":"\u003cp\u003eThe standing long jump (SLJ) - also called standing broad jump - is considered a suitable parameter for assessing the strength of the lower body musculature and may also be used to assess overall body strength. [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e] In the ancient Olympic Games (five sequential SLJ\u0026acute;s) and the modern Olympic Games, the SLJ was part of the program as a sporting discipline until 1912. [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e] Currently, the SLJ is used as one of seven fitness parameters in the screening process for a sports career in the American National Football League (NFL) and, together with other psychological parameters, is used to rank players in the annual NFL Draft. [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e] Furthermore, the SLJ is used in many national and international fitness test batteries [\u003cspan additionalcitationids=\"CR6 CR7 CR8 CR9 CR10 CR11 CR12 CR13\" citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR14\" class=\"CitationRef\"\u003e14\u003c/span\u003e], talent screenings [\u003cspan additionalcitationids=\"CR16 CR17\" citationid=\"CR15\" class=\"CitationRef\"\u003e15\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR18\" class=\"CitationRef\"\u003e18\u003c/span\u003e] and selections for jobs with physical requirements [\u003cspan additionalcitationids=\"CR20\" citationid=\"CR19\" class=\"CitationRef\"\u003e19\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR21\" class=\"CitationRef\"\u003e21\u003c/span\u003e] because the test is easy to conduct, cost-effective and provides a valid assessment of muscle strength. [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]\u003c/p\u003e\u003cp\u003eIn SLJ, the body's center of gravity (from an optimal body angle) must be catapulted forward with the highest possible take-off velocity and an optimal take-off angle along a jumping path. During the flight phase, the lower limbs are moved forward as much as possible underneath the center of gravity in order to achieve the widest possible distance, under the requirement that the center of gravity continues to move forward during landing. [\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] The SLJ is a complex specific test, and its results are influenced by a several factors. [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e] Physiological factors include the strength of the upper and lower body limbs [\u003cspan citationid=\"CR26\" class=\"CitationRef\"\u003e26\u003c/span\u003e, \u003cspan citationid=\"CR27\" class=\"CitationRef\"\u003e27\u003c/span\u003e], flexibility as a relevant factor for jumping height. [\u003cspan citationid=\"CR28\" class=\"CitationRef\"\u003e28\u003c/span\u003e] Psychological factors such as concentration and motivation also affect SLJ performance. [\u003cspan additionalcitationids=\"CR30\" citationid=\"CR29\" class=\"CitationRef\"\u003e29\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR31\" class=\"CitationRef\"\u003e31\u003c/span\u003e] Technical elements in the execution of the jump are considered key performance factors and are divided into three phases: body movements immediately before take-off (take-off phase), behavior while in the air (flight phase), and landing technique (landing phase). [\u003cspan additionalcitationids=\"CR23 CR24\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR32\" class=\"CitationRef\"\u003e32\u003c/span\u003e] In addition, body weight has a significant influence on SLJ performance - obese and overweight participants perform significantly worse than those of normal weight. [\u003cspan citationid=\"CR33\" class=\"CitationRef\"\u003e33\u003c/span\u003e, \u003cspan citationid=\"CR34\" class=\"CitationRef\"\u003e34\u003c/span\u003e] All performance-influencing variables described above (physical, mental and technical factors) have something in common: they can be optimized through training [\u003cspan citationid=\"CR25\" class=\"CitationRef\"\u003e25\u003c/span\u003e, \u003cspan citationid=\"CR35\" class=\"CitationRef\"\u003e35\u003c/span\u003e] and healthy nutrition. [\u003cspan citationid=\"CR36\" class=\"CitationRef\"\u003e36\u003c/span\u003e, \u003cspan citationid=\"CR37\" class=\"CitationRef\"\u003e37\u003c/span\u003e]\u003c/p\u003e\u003cp\u003eAnother factor influencing achievement in SLJ is height [\u003cspan citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e, \u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e], which naturally varies between individuals and is determined genetically, and cannot be adjusted by exercise or diet intervention. [\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] Regarding children and adolescents, biological age and height have a non-modifiable influence on performance in SLJ. [\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e]\u003c/p\u003e\u003cp\u003eThe SLJ is assessed primarily by measuring the maximum jump distance to the nearest centimeter and, in specific cases, by biomechanical analysis of the individual phases of movement. [\u003cspan additionalcitationids=\"CR23\" citationid=\"CR22\" class=\"CitationRef\"\u003e22\u003c/span\u003e\u0026ndash;\u003cspan citationid=\"CR24\" class=\"CitationRef\"\u003e24\u003c/span\u003e] In contrast to the biomechanical and kinematic assessments, participants' height is not considered when assessing and classifying their performance in SLJ. Consequently, smaller children are assessed significantly worse even if they have the same take-off speed and jumping technique (i.e., the same level of motor performance), because take-off and landing distances are directly related to their height. [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e]\u003c/p\u003e\u003cp\u003eTherefore, alternative assessment methods are desirable to enable a fair, equitable and performance-differentiated assessment of SLJ achievement, particularly during growth. The aim of our study was to analyze the effects of including height as an anthropometric parameter when assessing SLJ.\u003c/p\u003e"},{"header":"Materials and Methods","content":"\u003cdiv id=\"Sec3\" class=\"Section2\"\u003e\u003ch2\u003eDesign and selection of participants\u003c/h2\u003e\u003cp\u003eFindings from this study are based on a cross-sectional study conducted at one school campus in Klagenfurt, Austria, to develop a novel strength [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e] and balance test [\u003cspan citationid=\"CR42\" class=\"CitationRef\"\u003e42\u003c/span\u003e]. Three different types of schools (primary school (age 6 to 10 years), secondary school (age 11 to 14 years) and high school (age 15 to 19 years)) are located in a single building complex. Students in secondary and high school were drawn from regular and elite sports classes. The study was approved by the Research Ethics Committee of the University of Graz, Styria, Austria (GZ. 39/68/63 ex 2021/22).\u003c/p\u003e\u003cp\u003eAfter approval by all school directors, a total of 1069 children, adolescents and young adults were invited to participate in the study. The legal guardians of children aged 14 years and younger were informed in writing about the content of the study and asked to consent to their children's participation. A total of 1048 (98.0%) participants or their legal guardians agreed to participate in the study and provided additional information (age, gender, and sport club membership).\u003c/p\u003e\u003cp\u003eAfter excluding children younger than 6 years, adolescents 19 years or older, and those who did not participate in the SLJ or at least two of the comparative tests), 810 children and adolescents (mean age 13.2\u0026thinsp;\u0026plusmn;\u0026thinsp;3.3 years, 43.7% female) remained for analysis; 569 were from regular and 241 from elite sport classes. All participants took part in SLJ and APCT; children in primary and secondary school (N\u0026thinsp;=\u0026thinsp;450) also completed the PU (Fig.\u0026nbsp;\u003cspan refid=\"Fig1\" class=\"InternalRef\"\u003e1\u003c/span\u003e).\u003c/p\u003e\u003c/div\u003e\n\u003ch3\u003eProcedure and outcomes\u003c/h3\u003e\n\u003cp\u003eAll anthropometric and fitness-related measurements were conducted by trained sports scientists and sports teachers under the direction of the corresponding author between September 2023 and January 2024. The primary outcome of this study are differences between traditional SLJ performance assessment (i.e., jumping distance in cm; SLJ_T) and its modified assessment method of dividing SLJ jumping distance in cm divided by height in cm (SLJ_H). Specifically, we compare their alignments with measures of pole climbing and push-ups, two alternative measures of body strength.\u003c/p\u003e\u003cp\u003e\u003c/p\u003e\n\u003ch3\u003eAnthropometrics\u003c/h3\u003e\n\u003cp\u003eBody weight (kg) was measured to the nearest 0.1 kg using a Bosch PPW4202/01 body scale (Bosch Hausger\u0026auml;te, Vienna, Austria), Height was measured to the nearest 0.1 cm using a SECA 213 stadiometer (Seca GmbH\u0026amp;Co, Hamburg, Germany). Using a wall-mounted measuring tape, grip height was measured to the nearest centimeter. Participants stood barefoot on the floor, hands stretched vertically upwards, and the maximum distance between the floor and the fingertips of the upward-stretched hand was measured. Body mass index (BMI) was calculated by dividing the body weight by the height in meters squared.\u003c/p\u003e\n\u003ch3\u003ePhysical fitness assessments\u003c/h3\u003e\n\u003cp\u003e\u003cem\u003eStanding long jump (SLJ).\u003c/em\u003e Standing on a long jump mat at the starting line, the participants jumped as far as possible with both feet. The shortest distance between the starting line and landing of the heels on the ground was measured to the nearest centimeter. Three attempts were carried out, and the widest was included in the analysis.\u003c/p\u003e\u003cp\u003e\u003cem\u003ePush-ups (PU).\u003c/em\u003e The test was carried out based on the German motor test manual [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Lying on their stomachs on the floor, the participants touched one hand with the other (above the gluteal muscles close to the spine.) in the starting position. To do a push-up correctly, the participants had to place their hands next to their shoulders and push their bodies up into a completely straight push-up position. In this position, they had to take one hand off the floor and touch the back of the other hand. After that, they had to put their hand back on the floor and return their body to the starting position in a controlled manner. The participants had to complete as many push-ups as possible within 40 seconds; the number of correctly performed push-ups was included in the analysis.\u003c/p\u003e\u003cp\u003e\u003cem\u003eAustrian Pole Climbing Test (APCT).\u003c/em\u003e The test was carried out based on the test manual by Jarnig et al. [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. Participants climbed continuously on a round, smooth climbing pole (steel pole ST35, ⌀ (42.5\u0026thinsp;\u0026plusmn;\u0026thinsp;0.5) mm \u0026times; (3.3\u0026thinsp;\u0026plusmn;\u0026thinsp;0.1) mm) fixed at the top and bottom. Norm markings at heights of 2.0, 2.5, 3.0, 3.5 and 4.0 m above the ground were marked on the climbing pole. It was mandatory to climb over as many norm marks as possible; norm marks were considered to be climbed over when the participant's chin was placed over them. Within a period of 2 minutes, any number of climbing attempts could be started and breaks could be taken between climbing attempts according to individual needs. The last climbing attempt started within the two-minute period could be completed by each participant without time limit. The highest norm marking climbed was documented for each climbing attempt, and the overall climbing performance was calculated by adding up the heights of each climbing attempt, taking into account the grip height and the thickness of the fall protection mat. Validity and reliability of these fitness tests are well documented and considered suitable for use in field studies [\u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e, \u003cspan citationid=\"CR43\" class=\"CitationRef\"\u003e43\u003c/span\u003e].\u003c/p\u003e\n\u003ch3\u003eStandardization\u003c/h3\u003e\n\u003cp\u003eFor SLJ_T and height z-scores (i.e., SLJ_Tz \u0026amp; zHeight) were calculated based on age- and gender-specific reference values. Since thus far no national reference values are available for SLJ or height, the mean (\u003cem\u003eM\u003c/em\u003e) and standard deviation (\u003cem\u003eSD\u003c/em\u003e) were derived based on the latest international percentiles [\u003cspan citationid=\"CR44\" class=\"CitationRef\"\u003e44\u003c/span\u003e] (Table S1 \u0026amp; S2). To derive reference values for SLJ_H, \u003cem\u003eM\u003c/em\u003e of SLJ (\u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eSLJ\u003c/em\u003e\u003c/sub\u003e) and height (\u003cem\u003eM\u003c/em\u003e\u003csub\u003e\u003cem\u003eheight\u003c/em\u003e\u003c/sub\u003e) as well as the \u003cem\u003eSD\u003c/em\u003e for SLJ (\u003cem\u003eSD\u003c/em\u003e\u003csub\u003e\u003cem\u003eSLJ\u003c/em\u003e\u003c/sub\u003e) (derived in Table S1 \u0026amp; S2) were used and age- and gender-specific \u003cem\u003eM\u003c/em\u003e and \u003cem\u003eSD\u003c/em\u003e values of SLJ_H were calculated (see supplementary material Table S3 - incl. calculation formula) to enable the calculation of z-scores for the novel assessment method (SLJ_Hz).\u003c/p\u003e\u003cp\u003eAge- and gender-adjusted PU and APCT z-scores were based on age- and gender-specific reference values [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR41\" class=\"CitationRef\"\u003e41\u003c/span\u003e]. BMI z-scores were based on the International Obesity Task Force (IOTF) reference values [\u003cspan citationid=\"CR45\" class=\"CitationRef\"\u003e45\u003c/span\u003e].\u003c/p\u003e\u003cdiv id=\"Sec8\" class=\"Section2\"\u003e\u003ch2\u003eStatistical Analysis\u003c/h2\u003e\u003cp\u003eFor data analyses and graphics, we used mainly \u003cem\u003etidyverse\u003c/em\u003e (version 2.0.0) [\u003cspan citationid=\"CR46\" class=\"CitationRef\"\u003e46\u003c/span\u003e] and \u003cem\u003eeasystats\u003c/em\u003e (version 0.7.5) [\u003cspan citationid=\"CR47\" class=\"CitationRef\"\u003e47\u003c/span\u003e] package suites in the R language (version 4.5.1 [\u003cspan citationid=\"CR48\" class=\"CitationRef\"\u003e48\u003c/span\u003e]). Inferential statistics were based on linear mixed models (LMMs). They were estimated and post-processed with the \u003cem\u003elme4\u003c/em\u003e package (version 1.1-37a; Bates et al., 2015a [\u003cspan citationid=\"CR49\" class=\"CitationRef\"\u003e49\u003c/span\u003e]). Model selection followed the recommendations of Bates et al. (2015b) [\u003cspan citationid=\"CR50\" class=\"CitationRef\"\u003e50\u003c/span\u003e]. Due to the small number of observations only varying intercepts could be estimated with child as random factor.\u003c/p\u003e\u003cp\u003eInferential statistics were based on two LMMs. The first one tested the hypothesized misalignment of traditional SLJ_T and alignment of height-adjusted SLJ_H with APCT. In the first set, we regressed APCT, SLJ_T, and SLJ_H (specified as three levels of a repeated-measure factor assessment) on height z-scores, adjusted for gender and age using gender as covariate nested within five contexts defined by elite/regular sports class and primary/secondary/high school. The slope for regressions of APCT on height was expected to be misaligned (i.e., ideally of a different sign) with the slope for SLJ_T, but aligned (i.e., ideally not significantly different) with the slope of SLJ_H. The second LMM replicated this analysis using PU in place of APCT. As PU was not assessed in high school, interactions of assessment contrasts with height were tested only in three contexts. As a further check of the relative merits of SLJ_H and SLJ_T, we predicted APCT and PU fitness by adding SLJ_T and SLJ_H to hierarchical multiple regression models with BMI, gender, and age in the five school/class contexts as covariates.\u003c/p\u003e\u003c/div\u003e"},{"header":"Results","content":"\u003cdiv id=\"Sec10\"\u003e\n \u003ch2\u003eDescriptives\u003c/h2\u003e\n \u003cp\u003eGirls and boys from five heterogeneous \u0026ldquo;contexts\u0026rdquo; (i.e., elite/regular sports classes from secondary and high school as well as from regular primary school) participated in the study. Supplement Table S4 reports breakdowns of means (M), standard deviations (SD), and number of observations (N) of standardized SLJ_H, SLJ_T, APCT, and PU scores as well as of age and BMI by gender and school. Linear regressions of the four assessments on height for girls and boys in the five contexts are shown in Fig.\u0026nbsp;2. Children in elite sports classes are clearly performing at a much higher level. More importantly, there is a clear qualitative misalignment of SLJ_T and a qualitative alignment of SLJ_H with APCT and PU in most groups, with the exception of boys in primary school and girls in regular high school, respectively.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec11\"\u003e\n \u003ch2\u003eMisalignment of SLJ_T and alignment of SLJ_H with APCT and PU\u003c/h2\u003e\n \u003cp\u003eStatistical confirmation of SLJ_T misalignment and SLJ_H alignment was based on two LMMs that estimated (1) for each of five contexts the slopes for the regression of SLJ_T, SLJ_H, and APCT on zHeight and (2) for each of three contexts the slopes for the regression of SLJ_T, SLJ_H, and PU on zHeight whether the slopes of SLJ_T and SLJ_H were significantly different from those for APCT and PU, respectively. Table\u0026nbsp;1 shows the selection of relevant fixed effects for these assessment-by-height interactions from the final LMMs.\u003c/p\u003e\n \u003cdiv\u003e\n \u003ctable id=\"Tab1\" border=\"1\"\u003e\n \u003ccaption language=\"En\"\u003e\n \u003cdiv\u003eTable 1\u003c/div\u003e\n \u003cdiv\u003e\n \u003cp\u003eSelection of fixed effects for interactions of (1) APCT, SLJ_T and SLJ_H and zHeight for five contexts (top) and (2) PU, SLJ_T and SLJ_H and height for three contexts.\u003c/p\u003e\n \u003c/div\u003e\n \u003c/caption\u003e\n \u003cthead\u003e\n \u003ctr\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eAPCT vs. SLJ_T \u0026times; zHeight\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eCoeff\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003eSE\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ez\u003c/p\u003e\n \u003c/th\u003e\n \u003cth align=\"left\"\u003e\n \u003cp\u003ep\u003c/p\u003e\n \u003c/th\u003e\n \u003c/tr\u003e\n \u003c/thead\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRegular_PS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.13\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRegular_SS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.23\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; .001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRegular_HS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.14\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.27\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eElite_SS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; .001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eElite_HS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.28\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; .001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eAPCT vs. SLJ_H \u0026times; zHeight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRegular_PS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.377\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRegular_SS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.43\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.152\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRegular_HS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.520\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eElite_SS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.01\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.831\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eElite_HS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.21\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.08\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.006\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePU vs. SLJ_T \u0026times; zHeight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRegular_PS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e2.64\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.008\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRegular_SS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e5.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e\u0026lt; .001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eElite_SS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.18\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e3.12\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003ePU vs. SLJ_H \u0026times; zHeight\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003ctd align=\"left\"\u003e\u0026nbsp;\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRegular_PS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.05\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-1.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.251\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eRegular_SS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.07\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.04\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e1.68\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.093\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd align=\"left\"\u003e\n \u003cp\u003eElite_SS\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.03\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.06\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e-0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd align=\"char\"\u003e\n \u003cp\u003e0.577\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n \u003ctfoot\u003e\n \u003ctr\u003e\n \u003ctd colspan=\"5\"\u003e\u003cem\u003eNotes.\u003c/em\u003e For complete list of APCT-related fixed effects see Table S5 and for complete list of PU-related fixed effects see Table S6 in Supplement. zHeight\u0026thinsp;=\u0026thinsp;gender-age adjusted zHeight.\u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tfoot\u003e\n \u003c/table\u003e\n \u003c/div\u003e\n \u003cdiv\u003e\u003c/div\u003e\n \u003cdiv\u003e\u003c/div\u003e\n \u003cdiv\u003e\u003c/div\u003e\n \u003cdiv\u003e\u003c/div\u003e\n \u003cdiv\u003e\u003c/div\u003e\n \u003cdiv\u003e\u003c/div\u003e\n \u003cp\u003eFigure 3 visualizes the qualitative difference between zero-order regression slopes of SLJ_T on height z-scores and those of the other three assessments in the five school/class contexts. All interactions testing the difference of height-slope between SLJ_T and APCT/PU were significant. Moreover, with one exception, none of these interactions were significant for SLJ_H. The exception was APCT for children in high-school elite sports class, in this case the slope difference was only about half the size of the difference for SLJ_T (0.21 vs. 0.41). The tables of fixed effects, including also significant main effects, the effect of gender, and other interactions, are documented in Supplement Table S5 for APCT and Table S6 for PU.\u003c/p\u003e\n\u003c/div\u003e\n\u003cdiv id=\"Sec12\"\u003e\n \u003ch2\u003ePrediction of PU and APCT\u003c/h2\u003e\n \u003cp\u003eAdjusting SLJ by children\u0026rsquo;s height did not change their correlations with each other (r\u0026thinsp;=\u0026thinsp;.91; partial r\u0026thinsp;=\u0026thinsp;.95 adjusted for age and gender) and the similarity of their correlations with APCT (r\u0026thinsp;=\u0026thinsp;.71 for both) and PU (r\u0026thinsp;=\u0026thinsp;.63 and r\u0026thinsp;=\u0026thinsp;.67 for SLJ_T and SLJ_H, respectively). Therefore, for example, when we regressed the two measures of body strength PU (Fig.\u0026nbsp;4A) or APCT (Fig.\u0026nbsp;4B) on SLJ_T and SLJ_H z-scores there was no loss of information associated with the adjustment. The predictions of SLJ_H scores were always very similar to the predictions of SLJ_T scores in multiple regressions including agender, age, and BMI as covariates in three or five school/class contexts; small divergences were always in the direction of steeper slopes (i.e., better fits) for SLJ_H.\u003c/p\u003e\n \u003cp\u003eChanges in R\u003csup\u003e2\u003c/sup\u003e due to the unique effects of SLJ_H and SLJ_T were larger for SLJ_H than for SLJ_T ((APCT: 12.6% vs. 10.3%; PU: 15.6. % vs. 13.0%). Moreover, adding SLJ_H in a third step to models already including SLJ_T, significantly increased goodness of fit; APCT: F(1, 788)\u0026thinsp;=\u0026thinsp;34.9, p\u0026thinsp;\u0026lt;\u0026thinsp;.001; PU: F(1, 436)\u0026thinsp;=\u0026thinsp;25.9, p\u0026thinsp;\u0026lt;\u0026thinsp;.001. Conversely, adding SLJ_T to models with SLJ_H did not; F(1, 788)\u0026thinsp;=\u0026thinsp;3.3, p\u0026thinsp;=\u0026thinsp;.07; PU: F(1, 436)\u0026thinsp;=\u0026thinsp;1.2, p\u0026thinsp;=\u0026thinsp;.27.\u003c/p\u003e\n\u003c/div\u003e"},{"header":"Discussion","content":"\u003cdiv id=\"Sec14\" class=\"Section2\"\u003e\u003ch2\u003eToward a fair and appropriate assessment of physical fitness\u003c/h2\u003e\u003cp\u003eAnthropometric parameters and biological age directly influence fitness test results.[\u003cspan citationid=\"CR39\" class=\"CitationRef\"\u003e39\u003c/span\u003e] In a model calculation of the SLJ, an individual\u0026rsquo;s deviation from average height leads to a significantly better or worse assessment of muscle strength, keeping other physical parameters constant. [\u003cspan citationid=\"CR40\" class=\"CitationRef\"\u003e40\u003c/span\u003e] Indeed, as shown here, the usual assessment of muscle strength/fitness with the SLJ results in lower scores for smaller individuals \u0026ndash; a difference not seen in other tests of physical muscle strength such as the APCT and PU. Using the alternative assessment method, that is taking height into account, resulted in muscle strength assessments that were comparable to the other muscle strength assessments (APCT \u0026amp; PU).\u003c/p\u003e\u003cp\u003eIn regular school classes, no significant differences were found between the assessments by SLJ_H, APCT, and PU in terms of height, regardless of school level (primary school, secondary school, high school). The same applies to elite sports classes in secondary school, but not to elite sports classes in high school.\u003c/p\u003e\u003cp\u003eElite sports classes in secondary school are attended by 10- to 14-year-old regional athletes who belong to a sports club, had to pass a sports entrance exam, and complete two to three hours of additional physical education and sports per week at school, compared to regular school classes. In contrast, elite sports classes in high school are attended by supra-regional athletes who complete high intensity, sport-specific training led by sports scientists throughout the day and do not participate in general physical education classes. In this context, the significant differences between SLJ_H, APCT, and PU in the elite sports classes in high school seem less important for a general assessment of SLH_H, as some participants (e.g., ski jumpers and track and field athletes) undergo high-intensity jump trainings and therefore the results cannot be generalized. Thus, our results and trends suggest that SLJ_H is more suitable and fairer for assessing muscle strength based on the SLJ performance than SLJ_T.\u003c/p\u003e\u003cp\u003eThe practical value of the height-adjusted score for prediction of other fitness indicators such as APCT and PU may appear to be limited given larger than .90 zero-order and partial correlations with the traditional assessment. So why bother? We submit that at a minimum the high correlations show that the benefit of fairer assessment did not come at the cost of loss of predictive value when compared with the traditional score. Moreover, the two other measures of body strength, PU and APCT, were significantly better predicted with SLJ_H than SLJ_T after adjustment for gender and age across different school and types of sport classes.\u003c/p\u003e\u003cp\u003eIn common widespread international fitness monitoring systems in Europe [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e], America [\u003cspan citationid=\"CR10\" class=\"CitationRef\"\u003e10\u003c/span\u003e], Asia [\u003cspan citationid=\"CR12\" class=\"CitationRef\"\u003e12\u003c/span\u003e, \u003cspan citationid=\"CR51\" class=\"CitationRef\"\u003e51\u003c/span\u003e], Africa [\u003cspan citationid=\"CR52\" class=\"CitationRef\"\u003e52\u003c/span\u003e] or Australia [\u003cspan citationid=\"CR53\" class=\"CitationRef\"\u003e53\u003c/span\u003e], age- and gender-specific normative values are used to assess participants in the children and youth sector; biological age does not play a role in these assessment models. It is however well known that biological age should be taken into account, especially in talent selection [\u003cspan citationid=\"CR54\" class=\"CitationRef\"\u003e54\u003c/span\u003e, \u003cspan citationid=\"CR55\" class=\"CitationRef\"\u003e55\u003c/span\u003e], and there are methods such as Tanner stages [\u003cspan citationid=\"CR56\" class=\"CitationRef\"\u003e56\u003c/span\u003e] or maturity offset [\u003cspan citationid=\"CR57\" class=\"CitationRef\"\u003e57\u003c/span\u003e] used for this purpose in long-term studies or talent selection systems regionally. Furthermore, hand-wrist scans can be used to estimate the full-growth potential of children and adolescents [\u003cspan citationid=\"CR58\" class=\"CitationRef\"\u003e58\u003c/span\u003e]. However, due to cost and time restrictions, these methods are not used in widespread monitoring programs, even though biological age has a significant impact on fitness test results in children and adolescents. [\u003cspan citationid=\"CR59\" class=\"CitationRef\"\u003e59\u003c/span\u003e] Therefore, taking SLJ as an example, we propose to develop alternative options, for instance by taking height into account, particularly regarding fitness assessments in schools.\u003c/p\u003e\u003cp\u003eResults of fitness tests play an important role in selecting children and young people for sports schools or elite training centers. In this context, greater height is often advantageous for athletic skills and therefore often and generally welcome.[\u003cspan citationid=\"CR38\" class=\"CitationRef\"\u003e38\u003c/span\u003e] In sports such as basketball, athletics, or volleyball, height is an important performance-determining parameter. In contrast, however, there are also sports like soccer where height plays no major role. Male soccer stars such as Lionel Messi and Diego Maradona have won world championship, Olympic Games and many other competitions despite being shorter than 1.70 m.[\u003cspan citationid=\"CR60\" class=\"CitationRef\"\u003e60\u003c/span\u003e] In team sports such as soccer, action speed, mobility, athletics, technique and game intelligence are performance-determining parameters, and a high height is not essential.[\u003cspan citationid=\"CR61\" class=\"CitationRef\"\u003e61\u003c/span\u003e] In such sports, assessing fitness without a disadvantage for smaller individuals would be useful, and reduce chances of overlooking talent among smaller athletes. Existing fitness test assessment methods should be critically reviewed and adapted if they are replaced by more sensible, easy-to-use and practical new assessment methods that consider anthropometric differences. This can increase fairness and equality in the field of children and young people and also increase participants' motivation. The latter aspect is worth being explored in further studies.\u003c/p\u003e\u003c/div\u003e\u003cdiv id=\"Sec15\" class=\"Section2\"\u003e\u003ch2\u003eStrengths and limitations\u003c/h2\u003e\u003cp\u003eThis study has several strengths, including a large sample size and the fact that all data were collected by a team of testers consisting of four people under the supervision of the corresponding author. In addition, data from children, adolescents and young adults were analyzed and correlated with additional strength tests.\u003c/p\u003e\u003cp\u003eOne limitation is that for practical reasons the assessment of jumping performance was based only on jumping distance in relation to height. Other parameters influencing performance such as jumping technique, physical conditions and motivation were not considered.\u003c/p\u003e\u003c/div\u003e"},{"header":"Conclusion","content":"\u003cp\u003eIt is important to highlight the fitness parameter being tested with SLJ. It is used as a measure of the lower body muscle strength of participants, and the actual distance jumped is not the primary outcome of interest. The usual assessment of muscle strength/fitness based on the SLJ disadvantages smaller individuals; taking their height into account (like SLJ_H) is an effective and practical alternative and results in a fairer assessment. In addition, the simple method of adjustment represents a useful addition to current scientific approaches in long-term studies in children and adolescents, as it enables a more precise evaluation during the growth period by allowing growth spurts to be specifically taken into account. Further nationwide studies should be organized and carried out to create representative normal and reference values. In addition, regional studies should be carried out to investigate whether novel assessment methods of fitness tests including anthropometrics may have an impact on the motivation of participants.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cp\u003eAPCT\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Austrian Pole Climbing Test\u003c/p\u003e\n\u003cp\u003eIOTF\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;International Obesity Task Force\u003c/p\u003e\n\u003cp\u003eM\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Mean\u003c/p\u003e\n\u003cp\u003eNFL\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;National Football League\u003c/p\u003e\n\u003cp\u003ePU\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Push-ups\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eSD\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Standard deviation\u003c/p\u003e\n\u003cp\u003eSLJ\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;\u0026nbsp;Standing long jump\u003c/p\u003e\n\u003cp\u003eSLJ_H\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Assessment method taking into account the body height of participants\u003c/p\u003e\n\u003cp\u003eSLJ_T\u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp; \u0026nbsp;Traditional assessment method \u003cstrong\u003e\u003cbr\u003e\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e"},{"header":"Declarations","content":"\u003cp\u003eThe legal guardians of the 14- to 18-year-old participants were informed at school registration that the children in their care could be invited to participate in various studies during school hours and that they could provide consent independently.\u0026quot;\u003c/p\u003e\n\u003cp\u003eInstitutional Review Board Statement\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThe study was conducted according to the guidelines of the Declaration of Helsinki and approved by the Research Ethics Committee of the University of Graz, Styria, Austria (GZ. 39/68/63 ex 2021/22).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eInformed consent\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ewas obtained from all subjects involved in the study.\u003c/p\u003e\n\u003ch2\u003eConflicts of Interest\u003c/h2\u003e\n\u003cp\u003eThe authors declare no conflicts of interest.\u003c/p\u003e\n\u003ch2\u003eFunding\u003c/h2\u003e\n\u003cp\u003eThis research and the Open Access publishing costs were funded by the Austrian Federal Ministry of Education, Science and Research, grant number GZ:2024\u0026thinsp;\u0026minus;\u0026thinsp;0.780.614 and the Austrian Federal Ministry for Arts, Culture, Civil Service and Sport, grant number GZ:2025\u0026thinsp;\u0026minus;\u0026thinsp;0.021.608. The Open Access was funded by the University of Graz. The University of Graz funded open access publishing.\u003c/p\u003e\n\u003ch2\u003eAuthor Contributions\u003c/h2\u003e\n\u003cp\u003eConceptualization, G.J. and M.N.M.v.P.; methodology, G.J.; formal analysis, G.J. and R.Kl.; investigation, G.J.; resources, G.J.; data curation, G.J.; writing\u0026mdash;original draft preparation, G.J. and R.Kl.; writing\u0026mdash;review and editing, G.J., R.Ke., R.Kl. and M.N.M.v.P.; visualization, G.J. and R.Kl.; supervision, M.N.M.v.P.; project administration, G.J.; funding acquisition, G.J. All authors have read and agreed to the published version of the manuscript.\u003c/p\u003e\n\u003ch2\u003eData Availability Statement\u003c/h2\u003e\n\u003cp\u003eThe data presented in this study are available upon request from the corresponding author. 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Int J Cult Stud 15:415\u0026ndash;428. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003e10.1177/1367877911422859\u003c/span\u003e\u003cspan address=\"10.1177/1367877911422859\" targettype=\"DOI\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e\u003cli\u003e\u003cspan\u003eBate R, Jeffreys I (2014) \u003cem\u003eSoccer Speed;\u003c/em\u003e Human Kinetics, ISBN 9781492584803\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[{"identity":"bdf4e139-8dd0-45e5-a917-631fcd2a740f","identifier":"10.13039/501100013699","name":"Bundesministerium für Bildung, Wissenschaft und Forschung","awardNumber":"GZ:2024-0.780.614 ","order_by":0},{"identity":"76406e48-fcd6-435b-8cb5-5083b22dea22","identifier":"10.13039/501100016167","name":"Bundesministeriums für Kunst, Kultur, öffentlichen Dienst und Sport","awardNumber":"GZ:2025-0.021.608","order_by":1}],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":true,"hideJournal":true,"highlight":"","institution":"University of Graz","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true},"keywords":"standing long jump, standing broad jump, fitness, assessment, test battery, fitness testing","lastPublishedDoi":"10.21203/rs.3.rs-8108094/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8108094/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003cp\u003eThe jumping distance achieved in the standing long jump SLJ is used to assess lower body strength. Traditionally, body height (hereinafter referred to as height) is not considered in the assessment (i.e., traditional SLJ or SLJ_T) and this may significantly disadvantage smaller children.\u003c/p\u003e\u003cp\u003eData on SLJ, pole climbing (APCT) and push-up (PU) were collected from boys and girls in Austrian regular primary, secondary, and high school as well as in secondary and high school in elite sports classes. For SLJ, we computed an alternative score by dividing jumping distance by height as correction (height-adjusted SLJ or SLJ_H). In a linear mixed model, the regression slopes of SLJ_T on height were significantly different from that of APCT and PU in the five different contexts defined by school and type of class. In contrast, corresponding regression slopes of SLJ_H differed only in minor ways from those of APCT and PU. Thus, SLJ_H removed a bias due to height in the assessment of body strength and led to a fairer assessment of participants across different schools comprising regular and elite sports classes.\u003c/p\u003e","manuscriptTitle":"Comparison of traditional and body height-adjusted assessment method for standing long jump","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2025-11-20 00:54:02","doi":"10.21203/rs.3.rs-8108094/v1","editorialEvents":[{"type":"communityComments","content":0}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"researchsquare","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":true,"externalIdentity":"","sideBox":"","snPcode":"","submissionUrl":"/submission","title":"Research Square","twitterHandle":"researchsquare","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"","reportingPortfolio":"","inReviewEnabled":false,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"e6a378e6-618b-49d0-9f07-350fe64d2f22","owner":[],"postedDate":"November 20th, 2025","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"posted","subjectAreas":[{"id":57954229,"name":"Health Policy"},{"id":57954230,"name":"Pediatrics"},{"id":57954231,"name":"General Practice"},{"id":57954232,"name":"Gender Studies"},{"id":57954233,"name":"Statistical Theory"},{"id":57954234,"name":"Physiology"}],"tags":[],"updatedAt":"2025-11-20T00:54:02+00:00","versionOfRecord":[],"versionCreatedAt":"2025-11-20 00:54:02","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8108094","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8108094","identity":"rs-8108094","version":["v1"]},"buildId":"8U1c8b4HqxoKbykW_rLl7","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}