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Int J Sports Phys Ther
Int J Sports Phys Ther
2159
International Journal of Sports Physical Therapy
2159-2896
NASMI Website: International Journal of Sports Physical Therapy

34631241
27634
10.26603/001c.27634
Systematic Review/Meta-Analysis
Systematic Review and Meta-Analysis of the Y-Balance Test Lower Quarter: Reliability, Discriminant Validity, and Predictive Validity
Plisky Phillip 1
Schwartkopf-Phifer Katherine 2
Huebner Bethany 1
Garner Mary Beth 3
Bullock Garrett 4
1 Physical Therapy, University of Evansville; ProRehab-PC
2 Physical Therapy, University of Evansville; Rehabitlitation & Performance Institute
3 Physical Therapy, University of Evansville
4 Department of Orthopaedic Surgery, Wake Forest School of Medicine; Centre for Sport, Exercise and Osteoarthritis Research Versus Arthritis, University of Oxford
Corresponding author: Garrett S. Bullock PT, DPT, DPhil Department of Orthopaedic Surgery Wake Forest School of Medicine Winston-Salem, NC gbullock@wakehealth.edu
1 10 2021
2021
16 5 11901209
10 12 2020
15 6 2021
© The Author(s)
https://creativecommons.org/licenses/by-nc-sa/4.0/ This is an open access article distributed under the terms of the Creative Commons Attribution-NonCommercial-ShareAlike License (4.0) which permits non-commercial use, distribution, and reproduction in any medium, provided the original author and source are credited. If you remix, transform, or build upon this work, you must distribute your contributions under the same license as the original.

Background

Deficits in dynamic neuromuscular control have been associated with post-injury sequelae and increased injury risk. The Y-Balance Test Lower Quarter (YBT-LQ) has emerged as a tool to identify these deficits.

Purpose

To review the reliability of the YBT-LQ, determine if performance on the YBT-LQ varies among populations (i.e., sex, sport/activity, and competition level), and to determine the injury risk identification validity of the YBT-LQ based on asymmetry, individual reach direction performance, or composite score.

Study Design

Systematic Review

Methods

A comprehensive search was performed of 10 online databases from inception to October 30, 2019. Only studies that tested dynamic single leg balance using the YBT-LQ were included. Studies were excluded if the Y-Balance Test kit was not utilized during testing or if there was a major deviation from the Y-Balance test procedure. For methodological quality assessment, the modified Downs and Black scale and the Newcastle-Ottawa Scale were used.

Results

Fifty-seven studies (four in multiple categories) were included with nine studies assessing reliability, 36 assessing population differences, and 16 assessing injury prediction were included. Intra-rater reliability ranged from 0.85-0.91. Sex differences were observed in the posteromedial direction (males: 109.6 [95%CI 107.4-111.8]; females: 102.3 [95%CI 97.2-107.4; p = 0.01]) and posterolateral direction (males: 107.0 [95%CI 105.0-109.1]; females: 102.0 [95%CI 97.8-106.2]). However, no difference was observed between sexes in the anterior reach direction (males: 71.9 [95%CI 69.5-74.5]; females: 70.8 [95%CI 65.7-75.9]; p=0.708). Differences in composite score were noted between soccer (97.6; 95%CI 95.9-99.3) and basketball (92.8; 95%CI 90.4-95.3; p <0.01), and baseball (97.4; 95%CI 94.6-100.2) and basketball (92.8; 95%CI 90.4-95.3; p=0.02). Given the heterogeneity of injury prediction studies, a meta-analysis of these data was not possible. Three of the 13 studies reported a relationship between anterior reach asymmetry reach and injury risk, three of 10 studies for posteromedial and posterolateral reach asymmetry, and one of 13 studies reported relationship with composite reach asymmetry.

Conclusions

There was moderate to high quality evidence demonstrating that the YBT-LQ is a reliable dynamic neuromuscular control test. Significant differences in sex and sport were observed. If general cut points (i.e., not population specific) are used, the YBT-LQ may not be predictive of injury. Clinical population specific requirements (e.g., age, sex, sport/activity) should be considered when interpreting YBT-LQ performance, particularly when used to identify risk factors for injury.

Level of Evidence

1b

y-balance test lower quarter
dynamic balance
single leg balance
star excursion balance test
==== Body
pmcINTRODUCTION

Despite increased evidence on injury prevention and identification, injuries ranging from minor to career-limiting continue to rise.1,2 Deficits in lower extremity dynamic neuromuscular control have been implicated as an injury risk factor and have been observed after lower extremity injury.3–6 Interventions to improve lower extremity dynamic neuromuscular control have been utilized as a component in multiple injury prevention programs. Specifically, researchers have observed that athletes who participated in an injury prevention program displayed improved lower extremity dynamic neuromuscular control.7,8 One study observed that the intervention group who was most compliant demonstrated the greatest lower extremity dynamic neuromuscular control improvement, and sustained lower extremity injuries at decreased rates.8 Additionally, health care practitioners frequently utilize dynamic neuromuscular control as an outcome measure for return to sport criterion. Thus, there is a need for a lower extremity dynamic neuromuscular control test that identifies athletes at increased injury risk, captures changes that may occur with intervention, and evaluates return to sport readiness (i.e., ensure motor control deficits that occur after injury have normalized). In order to be useful in a sports setting the test would need to be valid and easy to use.

The Star Excursion Balance Test (SEBT) and Y-Balance Test Lower Quarter (YBT-LQ) have been studied and used extensively for the determination of physical readiness and injury risk identification, return to sport testing, and pre-post intervention measurement.6,9 The SEBT, through a systematic review, has been found to be reliable, valid, and responsive to specific dynamic neuromuscular control training for injured and healthy athletic populations.6 The advantage of the SEBT and YBT-LQ is that they test neuromuscular control at the limits of stability, which may allow for identification and magnification of subtle deficits and asymmetry.6

The YBT-LQ was developed from the SEBT in order to improve the reliability and field expediency of the SEBT.9 The YBT-LQ was simplified to use only the most reliable three reach directions (compared to eight reach directions with the SEBT). While both tests require dynamic neuromuscular control at the limits of stability, there are differences between the tests. The YBT-LQ uses a standardized approach via a testing kit and revised protocol to improve the reliability and testing speed. Protocol revisions include: heel of stance foot is allowed to raise, no touch down is allowed with reaching limb, and kit incorporates a standard reach height off the ground is used.9

While the efficiency of the test may have been improved, these differences in test procedures can alter performance, leading researchers to conclude that the SEBT and YBT-LQ are not interchangeable.10,11 Coughlan et al.10 compared the performance on the SEBT and YBT-LQ, and found that healthy males reached farther on the SEBT in the anterior direction, but had similar reach distances in the posterior directions.10 Fullam et al.11 examined the kinematic differences between the SEBT and YBT-LQ. It was confirmed that healthy males reached farther in the anterior direction, and from a kinematic perspective, the YBT-LQ anterior reach had greater hip flexion.11 These differences may be due to procedural differences or the use of a standardized YBT-LQ test kit. In addition to the differences in results between the YBT-LQ and SEBT, researchers have found that there may be differences in performance based on sex, sport and competition level in both tests.3,4 Differences have been reported between subject performance on the YBT-LQ based on country of origin,12 as well as, competition level.13,14 However, it is uncertain whether these findings are isolated to these populations or represent a true difference in performance among populations.

While a systematic review has been performed on the reliability and discriminant validity of the SEBT, the YBT-LQ has not undergone a similar rigorous analysis regarding its effectiveness regarding injury risk identification.6 In the SEBT systematic review, the YBT-LQ was described as reliable, but only one study was available; thus, there is a need to investigate and summarize the YBT-LQ literature.6 The purpose of this systematic review and meta-analysis was to review the reliability of the YBT-LQ, determine if performance on the YBT-LQ varies among populations (i.e., sex, sport/activity, and competition level), and to determine the injury risk identification validity of the YBT-LQ based on asymmetry, individual reach direction performance, or composite score.

METHODS

Study design

A systematic review was performed on the reliability, validity, and population differences of the YBT-LQ. The Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were utilized to conduct and report this review.15 This review was prospectively registered with Prospero CRD42018090102.

Search strategy

A comprehensive computerized search was performed, employing online databases (MEDLINE, CINAHL, Cochrane, Embase, SPORTDiscus, Health Source-Consumer Edition, Health Source: Nursing/Academic Edition, SocINDEX, and Social Sciences), from inception to October 30, 2019. Medical subject headings (MeSH) and keywords were utilized for “dynamic balance,” “Y-Balance Test,” “Star Excursion Balance Test,” and “single leg balance.” The full search strategy entailed “y balance test*”[All Fields] OR “star excursion balance test*”[All Fields] OR YBT[All Fields] OR SEBT[All Fields]. References were tracked in Covidence systematic review software (Veritas Health Innovation, Melbourne, Australia).

Eligibility criteria

Studies examining the YBT-LQ were included if they met the following criteria: 1) tested dynamic single leg balance using the YBT-LQ; 2) full-text articles were written in English. Study exclusion criteria consisted of 1) studies that did not use the Y-Balance Test kit during testing; 2) major deviation from the Y-Balance Test procedure (e.g., stance foot heel kept down); 3) the Y-Balance Test Upper Quarter procedure was utilized instead of the YBT-LQ; 4) conference abstracts or non-peer-reviewed papers.

Study selection

Four reviewers (GB, MG, BH, KS) were split into pairs, and each pair independently assessed half of the selected studies. Title and abstracts were first screened using inclusion and exclusion criteria. Four reviewers independently, who were all physical therapists and specialized in sports medicine, executed full-text review following title and abstract screening. Any conflicts were first discussed within the four reviewers. If a consensus could not be reached, another reviewer (PJ), who is a physical therapist, athletic trainer, PhD, with over twenty years’ experience in sports medicine, was utilized to determine final study eligibility. Following full-text review, a hand search was performed for any studies missed within the initial search.

Data extraction

Data were extracted into a customized Excel spreadsheet (Version 2013, Microsoft, Redmond, Washington, United States) in three domains: reliability, population differences, and injury prediction. Two reviewers verified data for each domain. Disagreements concerning data domain placement were resolved by a third reviewer (PJ). Data elements included study characteristics (e.g., publication data, study design, and population), YBT-LQ methodology, and results (number of injuries, reach distance, reach asymmetry, and reliability).

Quality assessment

All three domains (reliability, population differences, and injury prediction) were each analyzed by two independent reviewers (GB, MG, BH, KS). A third reviewer (PJ) resolved any quality assessment disagreements. The Oxford Centre for Evidence-Based Medicine (OCEBM) levels of evidence (Level I to IV)16 was used to discern study design. The YBT-LQ methodology was specifically assessed for uniformity.6 The YBT-LQ protocol factors that were assessed included the use of shoes during testing, the use of the average or maximum reach for each reach direction, hand placement during testing, number of practice trials, and number of data collection trials.6 The modified Downs and Black tool was utilized for methodological assessment for studies within the reliability and population differences domains.17,18 The modified Downs and Black tool has been shown to be reliable and valid.17 This methodological tool was scored on a scale of 0 to 15. The scoring system has a stratified ranking, with a score of 12 or greater deemed high quality, a score of 10 to 11 deemed moderate quality, and a score at or below 9 deemed low quality.18 The Newcastle-Ottawa Scale (NOS) was utilized for methodological assessment for studies within the injury prediction domain. The NOS incorporates a ‘star system’ for three broad perspectives: the selection of the study groups (four questions); the comparability of the groups (one question); and the ascertainment of outcome of interest (three questions). Multiple questions can have more than one star, which may result in the number of stars totaling greater than total number of questions.19

Statistical analyses

Percentage agreement and Cohen Kappa statistics were calculated to provide absolute agreement between raters in SPSS 23 (SPSS Inc, IBM, Chicago, Illinois). The extracted data were aggregated into three domains: reliability, population differences, and injury prediction. Reliability data were summarized in a narrative fashion. The population differences domain data were analyzed by pooling the study means through a random effects inverse variance approach, originally described by DerSimonian and Laird.20 Studies that reported more than one individual cohort were each calculated as individual studies. Heterogeneity was assessed with the Cochrane Q and I2 with high heterogeneity designated by a Q p-value <0.10 and I2 >50%. Meta-analysis was used to combine and summarize the data. In outcomes related meta-analysis, high heterogeneity indicates that there is large variation in study outcomes between studies and that results should not be pooled or combined. In this meta-analysis, high heterogeneity was observed indicating that there indeed may be differences in performance on the YBT-LQ among populations (i.e., age, sex, sport, activity, occupation, and injury status). Through an abundance of caution, a random effects model was used assuming that even within populations, results fall in a normal distribution. Data subdivisions were first grouped by sex for each YBT-LQ reach and composite score then analyzed through a series of z-tests (p<0.05). Due to the differences found between sexes, and the paucity of female studies, only males were assessed for further subdivisions. Additionally, competition level was not able to be compared as there were no greater than two subgroups at each competition level. Male sports differences (for all three YBT-LQ reaches and composite scores) were analyzed through one-way ANOVA with Tukey-Kramer Q tests to localize pair-wise differences based on pooled study means and variances (p<0.05).21 All meta-analyses were performed in R version 3.5.1 (R Core Team (2013). R: A language and environment for statistical computing (R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/), using the meta package.22 Given the heterogeneity in study design and data reporting, injury prediction data were summarized in a narrative fashion.

RESULTS

Study selection

A total of 982 titles were identified through the initial database and hand searches. After removal of duplicate articles, 732 abstracts were reviewed for relevance. Substantial agreement was demonstrated in title and abstract screening (k=0.976, p<0.01). Full text eligibility assessment of the remaining 411 articles resulted in 57 articles with 4 in multiple categories (Figure 1).3,9,12–14,23–50 Nine studies9,25,33,40,46,51–54 assessed reliability, 36 studies12–14,23–30,32,35,37,38,41–45,47,49,54–67 examined differences in the performance on the YBT-LQ in different populations or reported mean performance on the YBT-LQ in a specific population, and 16 studies3,31,34,36,39,48,50,57,64,68–74 examined injury prediction (see Table 1). Substantial agreement was also observed for full text review (k=0.84, p<0.01).

69140 Figure 1. PRISMA study selection demonstrating the systematic review of the literature for reliability, validity, and population differences for the Y-Balance Test Lower Quarter. PRISMA, Preferred Reporting Items for Systematic Reviews and Meta-Analyses.

69141 Table 1: Study demographics, design, and risk of bias

Author	Level of Evidence (Study Design)	Study Domain	Sport	Competition Level	# of subjects M:F	Risk of Bias (Downs and Black)	
Alnahdi et al. 2014	4 (Case series)	Population differences	-	-	30:31	13/15	
Avery et al. 2017	4 (Case series)	Reliability and Population differences	Ice Hockey	Youth	36:0	12/15	
Benis et al. 2016	1 (Randomized controlled trial)	Reliability and Population differences	Basketball	Elite	0:28	13/15	
Bonato et al. 2017	1 (Randomized controlled trial)	Population differences	Basketball	Elite	0:160	13/15	
Booysen et al. 2015	4 (Case series)	Population differences	Soccer	University & Elite	50:0	12/15	
Bullock et al. 2016	4 (Case series)	Population differences	Basketball	Middle School High School Collegiate Professional	88:0 105:0 46:0 41:0	12/15	
Butler et al. 2012	4 (Case series)	Population differences	Soccer	High School Collegiate Professional	38:0 37:0 44:0	12/15	
Butler et al 2013	4 (Case series)	Population differences	Soccer	Adolescent	26:0	12/15	
Butler et al. 2016	4 (Case series)	Population differences	Baseball	High School Collegiate Professional	88:0 78:0 90:0	13/15	
Chaouachi et al. 2017	1 (Randomized control trial)	Population differences	Soccer	Adolescent Elite	26:0	12/15	
Chimera et al. 2015	3 (Case control)	Population differences	Basketball Basketball Cheer & Dance Cross Country Cross Country Football Golf Soccer Swimming & Diving Tennis Tennis Track & Field Track & Field Volleyball	Division I Collegiate	9:0 0:2 0:4 13:0 0:17 69:0 0:3 0:28 0:17 5:0 0:5 7:0 0:3 0:8	12/15	
Chimera et al. 2016	4 (Case series)	Population differences	Rowing	Adolescent Varsity Adolescent Novice	0:31 0:21	11/15	
Engquist et al. 2015	4 (Case series)	Population differences	-	Division I Collegiate General College students	88:79 31:72	12/15	
Faigenbaum et al. 2014	2 (Randomized control trial)	Reliability	-	-	97:91	10/15	
Gorman et al. 2012	3 (Case control)	Population differences	Single Sport Multi-Sport	High School	68:24	12/15	
Greenberg et al. 2019	2 (Prospective cohort)	Reliability	Athletes	Adolescent	0:21	11/15	
Hoch et al. 2017	3 (Case control)	Population differences	Field Hockey	Collegiate	0:20	11/15	
Hudson et al. 2017	4 (Case series)	Population differences	Volleyball	Collegiate	0:90	11/15	
Johnston et al. 2019	2 (Prospective cohort)	Population differences	Rugby	Under 20 Senior	50:0 211:0	11/15	
Kenny et al. 2018	2 (Prospective cohort)	Reliability	Dance	Pre-professional	3:35	9/15	
Krysak et al. 2019	2b (Cross-sectional cohort)	Population differences	Golf	Middle High School College Professional	53:0 129:0 207:0 29:0	11/15	
Lacey et al. 2019	4 (Observa-tional repeated measures)	Reliability	Gaelic Football, Hurling, Camogie, Soccer, Rugby	Local sports clubs	11:8	10/15	
Linek et al. 2017	2 (Randomized control trial)	Reliability	Soccer	Adolescent semi-professional	38:0	9/15	
Lisman et al. 2018	4 (Cross-sectional)	Population differences	Football	Middle High School	29 52	12/15	
Miller et al. 2017	3 (Case control)	Population differences	-	High School	117:178	12/15	
de la Motte et al. 2016 A	4 (Case series)	Population differences	US Marines	-	356:0	13/15	
de la Motte et al. 2016 B	4 (Case series)	Population differences	US Military applicants	-	837:147	10/15	
Linek et al. 2019	2b
(Cross-sectional)	Population differences	Soccer	Elite Adolescents	43:0	12/15	
Lopez-Valenciano et al. 2019	3
(Cross-sectional)	Population differences	Soccer	Professional	88:79	10/15	
Muehlbauer et al. 2019	4 (Cross-sectional)	Population differences	Soccer	Sub-Elite	76:0	11/15	
O’Malley et al. 2016	4 (Case series)	Population differences	Gaelic Football	Collegiate	78:0	13/15	
Plisky et al. 2009	2 (Randomized control trial)	Reliability	Soccer	Collegiate	15:0	7/15	
Rossler et al. 2015	1 (Randomized control trial)	Population differences	Soccer	Elementary/ Middle School	157	12/15	
Ryu et al. 2019	3
(Case control)	Population differences	Baseball	Professional	42:0	10/15	
Schafer et al. 2013	2 (Randomized control trial)	Reliability	Service Members	-	53:11	10/15	
Schlingermann et al. 2017	1 (Randomized control trial)	Population differences	Gaelic Football	Collegiate	131:0	11/15	
Slater et al. 2018	4 (Descriptive)	Population differences	Ice Skating	Senior Level	17:15	10/15	
Smith (Laura) et al. 2018	2b (Cross-sectional)	Reliability	Football Basketball Lacrosse Softball Soccer	High School	30:0 12:34 8:0 0:10 1:15	12/15	
Smith (Joseph) et al. 2018	2b (Cross-sectional)	Population differences	Basketball Soccer	High School	94:91	13/15	
Teyhen et al. 2014	4 (Case series)	Population differences	Military	Army	53:11	12/15	
Teyhen et al. 2016	3 (Case control)	Population differences	Military	Army	1380:86	13/15	
Author	Level of Evidence (Study Design)	Study Domain	Sport	Competition Level	# of subjects M:F	Risk of Bias (Newcastle)	
Brumitt et al. 2018	2 (Prospective cohort)	Predictive	Basketball	Collegiate	169:0	8	
Butler et al. 2013	2 (Prospective cohort)	Predictive	Football	Collegiate	59:0	9	
Cosio-Lima et al. 2016	2 (Prospective cohort)	Predictive	Military	Coast Guard Maritime Security Response Team Candidates	31:0	7	
de la Motte et al. 2019	2 (Prospective cohort)	Predictive	Military	-	1433:281	10	
Gonell et al. 2015	2 (Prospective cohort)	Predictive	Soccer	Professional Amateur	34:0 40:0	6	
Gonzalez et al. 2018	2 (Prospective cohort)	Predictive	Rowing	Division I Collegiate	0:31	11	
Hartley et al. 2017	2 (Prospective cohort)	Predictive	Baseball Basketball Football Lacrosse Soccer Softball Tennis Volleyball Other	Division II/NAIA Collegiate	54:0 67:35 161:0 19:0 62:48 0:30 10:0 0:30 11:24	6	
Johnston et al. 2019	2 (Prospective cohort)	Predictive	Rugby	Elite	109:0	9	
Lai et al. 2017	3 (Case control)	Predictive	-	Division I Collegiate	177:117	6	
Lisman et al. 2019	2 (Prospective cohort)	Predictive	Football, Lacrosse, Baseball	High School	156:0	10	
Ruffe et al	2 (Prospective Cohort)	Predictive	Cross Country	High School	68:80	10	
Siupsinskas et al. 2019	2 (Prospective cohort)	Predictive	Basketball	Professional	0:169	10	
Smith et al. 2015	2 (Prospective cohort)	Predictive	Basketball Cross Country Track & Field Tennis Football Golf Volleyball Soccer Swimming & Diving	Division I Collegiate	9:2 13:17 7:3 5:5 68:0 0:3 0:8 0:27 0:17	8	
Teyhen et al. 2015	2 (Prospective prognostic)	Predictive	Military	Army Rangers	188:0	9	
Vaulerin et al. 2019	2 (Prospective cohort)	Predictive	Fire-fighters	-	39:0	10	
Wright et al. 2017	2 (Prospective cohort)	Predictive	Volleyball Cross Country Track & Field Lacrosse Soccer	Division I Collegiate	14 47 43 34:48 0:3	6	
*A higher score on the Downs and Black and the Newcastle-Ottawa Scale indicates lower risk of bias

Quality assessment

The NOS was used to assess quality of the included cohort studies (n=16). For the remaining 41 articles, the Downs and Black tool was used to assess quality. The scores of the included studies on the NOS ranged from 6-9 out of a possible 9, while the scores on the Downs and Black tool ranged from 7-13 out of a possible 15 (see summary in Table 1).

Reliability

Nine studies9,25,33,40,46,51–54 assessed reliability of YBT-LQ (see Table 1). Intraclass correlation coefficients (ICCs) for intrarater reliability ranged from 0.57-0.82 in adolescent populations,40 and 0.85-0.91 in adult populations.9 Interrater reliability ICCs ranged from 0.81-1.00.9,33,46,51 Test-retest reliability was assessed in five studies with ICCs ranging from 0.63-0.93.25,33,52–54

Sex differences

When sex was considered alone, differences were observed in the posteromedial direction (Male: 109.6 95% CI 107.4-111.8; Female: 102.3 95% CI 97.2-107.4; p < 0.01) and posterolateral direction (Male: 107.0 95% CI 105.0-109.1; Female: 102.0 95% CI 97.8-106.2; p=0.036).12–14,25,27,37,43,44,58–61,63–66 However, no difference was observed between sexes in the anterior reach direction (Male: 71.9 95% CI 69.5-74.5; Female: 70.8 95% CI 65.7-75.9; p=0.708)12–14,25,27,37,44,54,57–61,63,65–67 or in composite score (Male: 95.8 95% CI 94.5-97.2; Female: 95.3 95% CI 92.9-97.8; p=0.75) (Figure 2).12–14,24–30,32,37,38,42–44,55–57,59–66 However, there were significant differences based on sex, competition level, and sport throughout Figure 2. To illustrate, male Rwandan high school soccer players have a mean composite reach of 105.6 (95% CI 102.99-108.21),12 while male professional basketball players have a mean composite reach of 92.0 (95% CI 90.16-93.84).27 These scores also differ from female collegiate athletes, where a mean composite reach of 100.0 (95% CI 98.87-101.13) was observed.30

69142 Figure 2: Pooled Y-Balance Test Composite Score, Grouped by Sex. MS = Middle School, HS = High School, Col = College, Pro = Professional, ADU = Adult

Competition Level Differences

When competition level was considered alone (middle school, high school, college, professional), no differences were observed for the anterior (p = 0.05), posteromedial (p = 0.69), posterolateral (p = 0.62), or composite score (p = 0.15) (Figure 3, 4, 5, 6).12–14,23–30,32,35,37,38,41–45,47,49,54–67

69143 Figure 3: Pooled Y-Balance Test, Anterior Reach, Grouped by Sex. MS = Middle School, HS = High School, Col = College, Pro = Professional, ADU = Adult

69144 Figure 4: Pooled Y-Balance Test, Anterior Reach, Compared by Sport. MS = Middle School, HS = High School, Col = College, Pro = Professional

69145 Figure 5: Pooled Y-Balance Test, Posteromedial Reach, Compared by Sport. MS = Middle School, HS = High School, Col = College, Pro = Professional

69146 Figure 6: Pooled Y-Balance Test, Posterolateral Reach, Compared by Sport. MS = Middle School, HS = High School, Col = College, Pro = Professional

Sport differences

In the anterior reach direction, a significant difference was observed between soccer and basketball athletes (Soccer: 76.0 95% CI 73.6-78.4; Basketball: 70.5 95% CI 67.7-73.2; p < 0.01).12–14,27 In the posteromedial reach direction, a significant difference was observed between soccer and basketball athletes (Soccer: 114.8 95% CI 111.6-118.3; Basketball: 105.6 95% CI 101.9-109.4; p < 0.01), and baseball and basketball athletes (Baseball: 113.8 95% CI 109.5- 118.1; Basketball 105.6 95% CI 101.9-109.4; p < 0.01).12–14,27 In the posterolateral reach direction, a significant difference was observed between soccer and basketball athletes(Soccer: 111.8, 95%CI 108.5-115.0; Basketball: 102.0 95% CI 101.3-104.4; p < 0.01), and baseball and basketball athletes (Baseball: 107.7 95% CI 105.7-106.1; Basketball: 102.0 95% CI 101.3-104.4; p < 0.01).12–14,27 For composite score, there was a significant difference between soccer and basketball athletes (Soccer: 97.6 95% CI 95.9-99.3; Basketball: 92.8 95% CI 90.4-95.3; p < 0.01) and baseball and basketball athletes (Baseball: 97.4 95% CI 94.6-100.2; Basketball: 92.8 95% CI 90.4-95.3; p = 0.02).12–14,27

Injury prediction

A total of 16 studies3,31,34,36,39,48,50,57,64,68–74 investigated the association between YBT-LQ performance and injury risk: 12 investigated anterior reach asymmetry, 10 investigated asymmetries in the posteromedial and posterolateral directions, five studied individual reach directions, and 13 utilized composite scores. Populations studied include collegiate athletes3,36,39,50,57,68,70 (n=1,493), elite female basketball players73 (n=169), male high school athletes72 (n=156), professional and amateur soccer athletes34 (n=74), rugby players71 (n=109), high school cross country runners64 (n=148), military personnel31,48,69 (n=1919), and firefighters74 (n=39).

Anterior Reach Asymmetry

Twelve studies34,36,39,48,50,57,64,68,69,72–74 investigated the injury prediction ability of the YBT-LQ anterior reach asymmetry (Subjects: n=3,986). Five of these studies34,50,57,64,68 examined anterior reach asymmetry using a cut off of ≥4 cm; three34,57,64 reported raw numbers of subjects falling above and below this cut off score. Due to the high level of methodological and reporting discrepancies in the available data, a meta-analysis was not able to be completed.

Smith et al.68 utilized the 4 cm threshold and found a relationship with future injury risk, reporting an OR of 2.20 (95% CI 1.09-4.46). The remaining seven studies varied in interpretation of anterior reach performance. Five studies39,48,69,72,74 utilized anterior asymmetry cut off values varying from 2-3cm; of these, Valuerin et al.74 found an asymmetry of ≥2cm was predictive of ankle sprains. Siupsinksaks et al.73 reported only limb difference scores and did not find an association to injury in elite female basketball players. Hartley et al.36 created a reach distance cut off of 54.5 %LL for the anterior reach and found a significant difference between injured and uninjured collegiate athletes. Populations and definition of injury and asymmetry varied between studies, however, the three studies identifying a relationship between injury risk and anterior reach all included collegiate or professional athletes.

Posteromedial and Posterolateral Asymmetry

Ten studies3,34,36,39,57,64,68,72–74 examined the relationship between posteromedial and/or posterolateral reach asymmetry and future injury risk. Gonell et al.34 reported an OR of 3.86 (95%CI 1.46-10.95) for male soccer players with a posteromedial asymmetry of 4cm or greater. No relationship was observed with posterolateral asymmetry. Four studies57,64,68,72 used the same 4cm or greater asymmetry threshold for both the posteromedial and posterolateral directions, and found no relationship to future non-contact injuries in collegiate basketball players, high school cross country runners, collegiate athletes, or musculoskeletal injuries in male high school athletes, respectively. Hartley et al.36 also reported a significant difference in posteromedial reach asymmetry, with injured female athletes having a significantly reduced asymmetry compared to uninjured counterparts. Lai et al.39 reported asymmetries of 9cm in the posteromedial reach direction and 3cm in the posterolateral direction resulted in a sensitivity of 17.1% and 54.9% (respectively), while specificity was reported as 89.9% and 54.6% (respectively). Valuerin et al.74 and Siupsinskas et al.73 reported varying values for asymmetry in reach directions or limb differences, though no relationships to future injury risk were noted. Finally, Butler et al.3 did not observe significant differences in reach asymmetry between injured and uninjured football players.

Individual Reach Directions Distance

Five studies34,36,50,69,71 described the relationship between injury and individual reach directions. Four of these studies34,36,50,69 reported normalized reach distances for all reach directions, with no significant difference noted between injured and uninjured subjects.

Johnston et al.71 examined the relationship between the anterior reach and future concussions. Using an inertial sensor, rugby players with increased sample entropy when reaching in the anterior direction were found to be 3 times more likely to sustain a concussion. No association between posteromedial and posterolateral reaches to concussion was noted.

Composite

One3 of 13 studies3,31,34,39,48,50,57,64,68,69,72–74 found a relationship between composite score and future injury. Butler et al.3 reported an odds ratio of 3.5 (95%CI 2.4-5.3) when using a cutoff of 89.6% (SN=100%, SP=71.7%) in football players. Wright et al.50 and Brumitt et al.57 utilized different composite cutoffs for athletic teams, ranging from 89-94%, all yielding non-significant likelihood ratios (ranges 0.55-1.32 and 0.50-1.70, respectively). Nine studies31,34,39,48,68,69,72–74 did not report significant relationships between composite scores and future injury.

Three studies34,64,69 examined the relationship between composite score asymmetry and future injury. Gonell et al.34 and Ruffe et al.64 both utilized 12cm or greater threshold for asymmetry and no relationship to injury was noted. De la Motte et al.69 found no significant differences in composite asymmetry between injured and uninjured military personnel (p=0.50).

DISCUSSION

Testing is an important function for researchers, health care providers, and performance professionals. Many decisions hinge on test results, and it is essential to have validated tests in this process. While commonly used, the YBT-LQ has not been rigorously studied via systematic review and meta-analysis. This systematic review observed that the YBT-LQ is a highly reliable test. Dynamic balance differences were observed between sex, sport, and competition level, and asymmetry in the anterior reach demonstrated increased risk of lower extremity injury.

Reliability

The YBT-LQ demonstrated high reliability over time and between raters. The high YBT-LQ reliability is comparable to the SEBT, which highlights the ability of the YBT-LQ to accurately measure dynamic neuromuscular control.9 Higher variability in single session performance on the YBT-LQ in children may be due to the greater variability of balance performance seen in children.75

Difference in YBT-LQ by sex, sport, and competition level

Sex differences

When sex was considered alone, differences were observed in the posteromedial and posterolateral directions, but no differences were observed between sexes in the anterior reach direction or in composite score. While it may appear that there was not a difference between sexes in composite score, it is important to note that there was large variability in each sex, sport, and age/competition level in YBT-LQ performance. This was confirmed by the high heterogeneity observed indicating that there indeed may be differences in performance on the YBT-LQ among populations (i.e., age, sex, sport, activity, occupation, and injury status). This overall heterogeneity helped confirm that sex, sport, and competition level differences may exist. Thus, when the pooled means were analyzed, no differences were noted. Composite reach scores varied by as much as 13 %LL depending on the sex, sport, and competition level. These differences may point to the differences seen in injury rate and type by sex.76

Sport differences

There were significant differences observed between baseball and basketball in the posteromedial, posterolateral reach directions, and overall composite reach, with baseball demonstrating greater reach distances normalized to limb length. There were also differences observed between soccer and basketball in the anterior, posteromedial, posterolateral reach directions, and overall composite reach, with soccer demonstrating greater reach distances normalized to limb length. This may be due to sport specific adaptations in dynamic balance based on the demands and environment of the sport. For example, while both sports spend time running, soccer spends more time in unilateral stance at the limit of stability (e.g., kicking the ball) compared to basketball.77 While these differences may be due to sport specific adaptations, or limb dominance, specifically greater dynamic balance strategies on the stance leg during the kicking motion, it is also worth noting that dynamic neuromuscular control differences could be due to disparate anthropometric body types in athletes. For example, basketball players may in general have longer femurs than soccer players, which may make single limb squatting (i.e., anterior reach) biomechanically more difficult for basketball players.

Population differences summary

There were significant differences across populations by sex and sport in YBT-LQ reach distance. There were not enough studies to analyze all the possible sex, sport, competition level permutations; however, it was clear that differences exist. For example, when male Rwandan high school soccer players were compared to male high school soccer players from the United States, the posteromedial and posterolateral reach distances were not different.12 However, there was a significant difference in anterior reach and composite score. This shows YBT-LQ performance can potentially be affected by environment factors (e.g., in Rwanda there is less frequent wearing of athletic shoes and more frequent deep squatting for activities of daily living compared to the United States).12

It is interesting to note, that not only sex, sport, and environment might influence YBT-LQ performance, but also biological maturation. Researchers have found that YBT-LQ reach distance was significantly associated with the total Balance Error Scoring System score as YBT-LQ anterior and posteromedial reach distances.78

Injury prediction validity of the YBT-LQ

Since there were sport and gender differences in YBT-LQ, predictive studies could only be analyzed if they used a population specific cut point or examined homogeneous populations (e.g., male collegiate football players). Cut points for asymmetry and composite score varied

between studies. Due to these differences, composite score was found to be predictive of future injury in one study.3 More research is needed to develop these population-specific cut points to more accurately determine future injury risk.

Lehr et al.5 used population specific cut points across multiple sports. The researchers found that accurate injury risk identification was possible when multiple risk factors, including the YBT-LQ, were combined. The authors used age, sex, and sport specific risk cut points to place athletes in risk categories. These cut points were based on previously published injury prediction studies and normative databases.5 Thus, it is important to include age, sex, and sport cut points for injury risk identification. This study was not included in the meta-analysis since the researchers included multiple risk factors and the YBT-LQ was not able to be isolated as a risk factor. Further, Teyhen et al.79 found using a multifactorial model in soldiers that included YBT-LQ: Anterior Reach ≤ 72% limb length as one of the risk factors in the model. This study further illustrates the point that YBT cut points are population specific but also that the YBT should be used as part of a multifactorial model rather than a single risk factor in isolation.

Six studies34,36,39,48,50,68 examined reach asymmetry as a predictor of injury. Four of the studies found a positive relationship between injury risk and reach asymmetry. However, there was variability in the definition of “asymmetry” with a wide cut point range and different risk reporting methods (e.g., odds ratios, likelihood ratio, sensitivity, and specificity). Thus, there may be an association with reach asymmetry and injury risk, but this was difficult to quantify given the variability of data reporting and analysis. Given that sport and sex differences were observed, it is likely that tolerance for asymmetry and direction of asymmetry may differ by sport or population. While asymmetry is an absolute value that is relative to the individual, it also may need population specific cut points, like composite score. A meta-analysis was not performed and definitive conclusions could not be drawn.

Limitations

While 57 articles were included in this review, there were not enough studies (even when combined) to provide enough power to compare populations by the different combinations of sex, sport, and competition levels. A meta-analysis on the YBT-LQ predictive ability was not completed because only two studies were found that used homogeneous methodology and reporting measures. YBT-LQ reach asymmetry as a predictive factor was not analyzed due to the highly variable reported risk cut points. Two studies9,40 were low quality, while the rest were moderate and high quality. Furthermore, some of the studies had high heterogeneity in the specific YBT-LQ methodology (hands free versus hands on hip, maximum versus average reach, etc.). Due to the study risk of bias stratification, and the methodological heterogeneity, these findings need to be taken with some caution. The YBT-LQ is a controlled dynamic balance test. As many sport injuries are sustained at high velocities and forces, the YBT-LQ does not mimic some sport mechanisms of injury, which decreases the transferability of these results to the sport setting. Finally, this systematic review investigated athletic and active populations; thus, these findings cannot be generalized to all adult populations (inactive adults, geriatrics, etc.).

RECOMMENDATIONS FOR FUTURE RESEARCH

From this meta-analysis, it is clear that populations when stratified by sex and sport perform significantly differently on the YBT-LQ. This has two large implications. First, future research needs to establish normative data for a wide range of populations that utilize this test. Second, injury predictive studies need to use population specific (e.g., age, sex, sport/activity) cut points for composite score and reach asymmetry. For asymmetry, these cut points should be greater than the standard error of measure (3.2cm),9 so that meaningful asymmetry, beyond the error of measure, can be identified. Further, given the findings of Lehr et al.5 and Teyhen et al.79 it may be most appropriate to combine the YBT-LQ asymmetry and composite score specific to age, sex, and sport, along with other testing to accurately determine injury risk. Interestingly, country of origin seemed to impact performance; thus, cut points may need to specify beyond the aforementioned factors to include geographical location. Future research should use adequately powered and homogenous age, sex, and sport/activity specific analysis to determine if composite score is related to injury risk.

CONCLUSION

The YBT-LQ is a reliable tool for capturing dynamic single leg neuromuscular control at the limits of stability. Performance on the YBT-LQ differs based on age, sex, and sport, therefore clinicians should consider these factors when interpreting results to ensure accurate clinical decision-making. The relationship between the YBT-LQ and future injury risk remains unclear; future studies should utilize population specific cut points and homogenous samples to determine utility in injury prediction.

Data sharing statement

This study is registered with PROSPERO, and the protocol can be found at https://www.crd.york.ac.uk/prospero/ with the identifier Prospero CRD42018090102.

Conflicts of Interest

Funding for payment of a graduate research assistant was made possible through the Ridgeway 488 Student Research Award from the University of Evansville.

Dr Phillip Plisky developed the Y-Balance Test Protocol and Test kit and receives royalties from the sale of the Y-Balance Test kit.
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Epidemiology of severe injuries among United States high school athletes: 2005-2007 The American Journal of Sports Medicine Darrow Cory J. Collins Christy L. Yard Ellen E. Comstock R. Dawn 16 6 2009
37 9 1798 1805 0363-5465 10.1177/0363546509333015 10.1177/0363546509333015
Insurance claims data: A possible solution for a national sports injury surveillance system? An evaluation of data information against ASIDD and consensus statements on sports injury surveillance BMJ Open Aman M. Forssblad M. Henriksson-Larsén K. 12 6 2014
4 6 e005056 2044-6055 10.1136/bmjopen-2014-005056 10.1136/bmjopen-2014-005056 24928588
Dynamic balance performance and noncontact lower extremity injury in college football players: An initial study Sports Health: A Multidisciplinary Approach Butler Robert J. Lehr Michael E. Fink Michael L. Kiesel Kyle B. Plisky Phillip J. 1 8 2013
5 5 417 422 1941-7381 10.1177/1941738113498703 10.1177/1941738113498703 24427412
Star Excursion Balance Test as a predictor of lower extremity injury in high school basketball players Journal of Orthopaedic & Sports Physical Therapy Plisky Phillip J. Rauh Mitchell J. Kaminski Thomas W. Underwood Frank B. 12 2006
36 12 911 919 0190-6011 10.2519/jospt.2006.2244 10.2519/jospt.2006.2244
Field-expedient screening and injury risk algorithm categories as predictors of noncontact lower extremity injury Scandinavian Journal of Medicine & Science in Sports Lehr M. E. Plisky P. J. Butler R. J. Fink M. L. Kiesel K. B. Underwood F. B. 20 3 2013
23 4 225 232 0905-7188 10.1111/sms.12062 10.1111/sms.12062
Using the Star Excursion Balance Test to assess dynamic postural-control deficits and outcomes in lower extremity injury: A literature and systematic review J Athl Train Gribble Phillip A. Hertel Jay Plisky Phil 1 5 2012
47 3 339 357 1062-6050 10.4085/1062-6050-47.3.08 10.4085/1062-6050-47.3.08 22892416
Time-dependent postural control adaptations following a neuromuscular warm-up in female handball players: A randomized controlled trial BMC Sports Science, Medicine and Rehabilitation Steib Simon Zahn Peter Zu Eulenburg Christine Pfeifer Klaus Zech Astrid 13 10 2016
8 33 2052-1847 10.1186/s13102-016-0058-5 10.1186/s13102-016-0058-5 27757240
High adherence to a neuromuscular injury prevention programme (FIFA 11+) improves functional balance and reduces injury risk in Canadian youth female football players: A cluster randomised trial British Journal of Sports Medicine Steffen Kathrin Emery Carolyn A Romiti Maria Kang Jian Bizzini Mario Dvorak Jiri Finch Caroline F Meeuwisse Willem H 4 4 2013
47 12 794 802 0306-3674 10.1136/bjsports-2012-091886 10.1136/bjsports-2012-091886 23559666
The reliability of an instrumented device for measuring components of the star excursion balance test N Am J Sports Phys Ther Plisky P.J. Gorman P.P. Butler R.J.. 2009
4 92 99 http://www.ncbi.nlm.nih.gov/pubmed/21509114 21509114
A Comparison Between Performance on Selected Directions of the Star Excursion Balance Test and the Y Balance Test J Athl Train Coughlan Garrett F. Fullam Karl Delahunt Eamonn Gissane Conor Caulfield Brian M. Sci Med 1 7 2012
47 4 366 371 1062-6050 10.4085/1062-6050-47.4.03 10.4085/1062-6050-47.4.03 22889651
Kinematic Analysis of Selected Reach Directions of the Star Excursion Balance Test Compared with the Y-Balance Test J Sport Rehabil Fullam Karl Caulfield Brian Coughlan Garrett F. Delahunt Eamonn 2 2014
23 1 27 35 1056-6716 10.1123/jsr.2012-0114 10.1123/jsr.2012-0114
Comparison of dynamic balance in adolescent male soccer players from rwanda and the United States Int J Sports Phys Ther Butler R.J. Queen R.M. Beckman B.. 2013
8 749 755 https://www.ncbi.nlm.nih.gov/pubmed/24377061 24377061
Differences in soccer players’ dynamic balance across levels of competition J Athl Train Butler Robert J. Southers Corey Gorman Paul P. Kiesel Kyle B. Plisky Phillip J. 1 11 2012
47 6 616 620 1062-6050 10.4085/1062-6050-47.5.14 10.4085/1062-6050-47.5.14 23182008
Competition-Level Differences on the Lower Quarter Y-Balance Test in Baseball Players J Athl Train Butler Robert J. Bullock Garrett Arnold Todd Plisky Phillip Queen Robin 1 12 2016
51 12 997 1002 1062-6050 10.4085/1062-6050-51.12.09 10.4085/1062-6050-51.12.09 27849388
Preferred reporting items for systematic review and meta-analysis protocols (PRISMA-P) 2015 statement Systematic Reviews Moher David Shamseer Larissa Clarke Mike Ghersi Davina Liberati Alessandro Petticrew Mark Shekelle Paul Stewart Lesley A 1 1 2015
4 1 2046-4053 10.1186/2046-4053-4-1 10.1186/2046-4053-4-1 25554246
Oxford centre for evidence-based medicine levels of evidence BJU Int Phillips B. Ball C. Badenoch D.. 5 2001
107 870 https://insights.ovid.com/bju-international/bjui/2011/03/000/oxford-centre-evidence-based-medicine-levels-may/39/00125504
The feasibility of creating a checklist for the assessment of the methodological quality both of randomised and non-randomised studies of health care interventions Journal of Epidemiology & Community Health Downs S. H. Black N. 1 6 1998
52 6 377 384 0143-005X 10.1136/jech.52.6.377 https://www.ncbi.nlm.nih.gov/pubmed/9764259 9764259
Which factors differentiate athletes with hip/groin pain from those without? A systematic review with meta-analysis British Journal of Sports Medicine Mosler Andrea B Agricola Rintje Weir Adam Hölmich Per Crossley Kay M 6 2015
49 12 810 0306-3674 10.1136/bjsports-2015-094602 10.1136/bjsports-2015-094602 26031646
The Newcastle-Ottawa Scale (NOS) for assessing the quality of nonrandomised studies in meta-analysis Wells G. 2004
https://ci.nii.ac.jp/naid/10020590649/
Meta-analysis in clinical trials Controlled Clinical Trials DerSimonian Rebecca Laird Nan 9 1986
7 3 177 188 0197-2456 10.1016/0197-2456(86)90046-2 https://www.ncbi.nlm.nih.gov/pubmed/3802833 3802833
Introduction to Meta-Analysis Borenstein M. Hedges L.V. Higgins J.P.T.. John Wiley & Sons 2011
https://market.android.com/details?id=book-JQg9jdrq26wC
meta: An R package for meta-analysis R News Schwarzer G 2007
7 40 45 https://cran.r-project.org/doc/Rnews/Rnews_2007-3.pdf
Reference values for the Y Balance Test and the lower extremity functional scale in young healthy adults Journal of Physical Therapy Science Alnahdi Ali H Alderaa Asma A Aldali Ali Z Alsobayel Hana 2015
27 12 3917 3921 0915-5287 10.1589/jpts.27.3917 10.1589/jpts.27.3917 26834380
Seasonal Changes in Functional Fitness and Neurocognitive Assessments in Youth Ice-Hockey Players J Strength Cond Res Avery Michelle Wattie Nick Holmes Michael Dogra Shilpa 11 2018
32 11 3143 3152 1064-8011 10.1519/jsc.0000000000002399 10.1519/jsc.0000000000002399
Elite Female Basketball Players' Body-Weight Neuromuscular Training and Performance on the Y-Balance Test J Athl Train Benis Roberto Bonato Matteo La Torre Antonio L 1 9 2016
51 9 688 695 1062-6050 10.4085/1062-6050-51.12.03 10.4085/1062-6050-51.12.03 27824252
The relationships of eccentric strength and power with dynamic balance in male footballers Journal of Sports Sciences Booysen Marc Jon Gradidge Philippe Jean-Luc Watson Estelle 8 7 2015
33 20 2157 2165 0264-0414 10.1080/02640414.2015.1064152 10.1080/02640414.2015.1064152 26153432
Basketball Players' Dynamic Performance Across Competition Levels J Strength Cond Res Bullock Garrett S. Arnold Todd W. Plisky Phillip J. Butler Robert J. 12 2018
32 12 3528 3533 1064-8011 10.1519/jsc.0000000000001372 10.1519/jsc.0000000000001372
Within Session Sequence of Balance and Plyometric Exercises Does Not Affect Training Adaptations with Youth Soccer Athletes J Sports Sci Med Chaouachi M. Granacher U. Makhlouf I.. 2017
16 125 136 https://www.ncbi.nlm.nih.gov/pubmed/28344461 28344461
SportsmetricsTM training improves power and landing in high school rowers Int J Sports Phys Ther Chimera N.J. Kremer K. 2016
11 44 53 https://www.ncbi.nlm.nih.gov/pubmed/26900499 26900499
Injury history, sex, and performance on the functional movement screen and Y balance test J Athl Train Chimera N.J. Smith C.A. Warren M. 2015
50 475 485 10.4085/1062-6050-49.6.02 10.4085/1062-6050-49.6.02 25761134
Associations between functional movement screening, the Y balance test, and injuries in coast guard training Military Medicine Cosio-Lima Ludmila Knapik Joseph J. Shumway Richard Reynolds Katy Lee Youngil Greska Eric Hampton Michael 7 2016
181 7 643 648 0026-4075 10.7205/milmed-d-15-00208 10.7205/milmed-d-15-00208 27391617
Performance comparison of student-athletes and general college students on the functional movement screen and the Y balance test J Strength Cond Res Engquist Katherine D. Smith Craig A. Chimera Nicole J. Warren Meghan 8 2015
29 8 2296 2303 1064-8011 10.1519/jsc.0000000000000906 10.1519/jsc.0000000000000906 26203739
Feasibility and reliability of dynamic postural control measures in children in first through fifth grades Int J Sports Phys Ther Faigenbaum A.D. Myer G.D. Fernandez I.P.. 2014
9 140 148 https://www.ncbi.nlm.nih.gov/pubmed/24790775 24790775
Relationship between the Y balance test scores and soft tissue injury incidence in a soccer team Int J Sports Phys Ther Gonell A.C. Romero J.A.P. Soler L.M. 2015
10 955 https://www.ncbi.nlm.nih.gov/pmc/articles/pmc4675196/
Differences in dynamic balance scores in one sport versus multiple sport high school athletes Int J Sports Phys Ther Gorman P.P. Butler R.J. Rauh M.J.. 2012
7 148 153 https://www.ncbi.nlm.nih.gov/pubmed/22530189 22530189
Y-balance test performance and BMI are associated with ankle sprain injury in collegiate male athletes Journal of Science and Medicine in Sport Hartley Emily M. Hoch Matthew C. Boling Michelle C. 7 2018
21 7 676 680 1440-2440 10.1016/j.jsams.2017.10.014 10.1016/j.jsams.2017.10.014 29102301
Y-Balance Test Performance After a Competitive Field Hockey Season: A Pretest-Posttest Study J Sport Rehabil Hoch Matthew C. Welsch Lauren A. Hartley Emily M. Powden Cameron J. Hoch Johanna M. 1 9 2017
26 5 1056-6716 10.1123/jsr.2017-0004 10.1123/jsr.2017-0004
Y-balance normative data for female collegiate volleyball players Physical Therapy in Sport Hudson Christy Garrison J. Craig Pollard Kalyssa 11 2016
22 61 65 1466-853X 10.1016/j.ptsp.2016.05.009 10.1016/j.ptsp.2016.05.009
Lower quarter Y-balance test scores and lower extremity injury in NCAA Division I athletes Orthopaedic Journal of Sports Medicine Lai Wilson C. Wang Dean Chen James B. Vail Jeremy Rugg Caitlin M. Hame Sharon L. 1 8 2017
5 8 232596711772366 2325-9671 10.1177/2325967117723666 10.1177/2325967117723666 28840153
Reliability and number of trials of Y Balance Test in adolescent athletes Musculoskeletal Science and Practice Linek Pawel Sikora Damian Wolny Tomasz Saulicz Edward 10 2017
31 72 75 2468-7812 10.1016/j.msksp.2017.03.011 10.1016/j.msksp.2017.03.011
The effects of specialization and sex on anterior Y-balance performance in high school athletes Sports Health: A Multidisciplinary Approach Miller Madeline M. Trapp Jessica L. Post Eric G. Trigsted Stephanie M. McGuine Timothy A. Brooks M. Alison Bell David R. 27 4 2017
9 4 375 382 1941-7381 10.1177/1941738117703400 10.1177/1941738117703400 28447871
The relationship between functional movement, balance deficits, and previous injury history in deploying marine warfighters J Strength Cond Res de la Motte Sarah J. Lisman Peter Sabatino Marc Beutler Anthony I. O'Connor Francis G. Deuster Patricia A. 6 2016
30 6 1619 1625 1064-8011 10.1519/jsc.0000000000000850 10.1519/jsc.0000000000000850 26964060
The interrelationship of common clinical movement screens: Establishing population-specific norms in a large cohort of military applicants J Athl Train de la Motte Sarah J. Gribbin Timothy C. Lisman Peter Beutler Anthony I. Deuster Patricia 1 11 2016
51 11 897 904 1062-6050 10.4085/1062-6050-51.9.11 10.4085/1062-6050-51.9.11 27831746
The effects of the Gaelic athletic Association 15 training program on neuromuscular outcomes in Gaelic football and hurling players: A randomized cluster trial J Strength Cond Res O'Malley Edwenia Murphy John C. McCarthy Persson Ulrik Gissane Conor Blake Catherine 8 2017
31 8 2119 2130 1064-8011 10.1519/jsc.0000000000001564 10.1519/jsc.0000000000001564 27398918
A new injury prevention programme for children’s football – FIFA 11+ Kids – can improve motor performance: A cluster-randomised controlled trial Journal of Sports Sciences Rössler R Donath L Bizzini M Faude O 2016
34 6 549 556 0264-0414 10.1080/02640414.2015.1099715 https://shapeamerica.tandfonline.com/doi/abs/10.1080/02640414.2015.1099715 26508531
Y-balance test: A reliability study involving multiple raters Military Medicine Shaffer Scott W. Teyhen Deydre S. Lorenson Chelsea L. Warren Rick L. Koreerat Christina M. Straseske Crystal A. Childs John D. 11 2013
178 11 1264 1270 0026-4075 10.7205/milmed-d-13-00222 10.7205/milmed-d-13-00222
Effects of the Gaelic athletic association 15 on lower extremity injury incidence and neuromuscular functional outcomes in collegiate gaelic games J Strength Cond Res Schlingermann Brenagh E. Lodge Clare A. Gissane Conor Rankin Paula M. 7 2018
32 7 1993 2001 1064-8011 10.1519/jsc.0000000000002108 10.1519/jsc.0000000000002108 28817505
What risk factors are associated with musculoskeletal injury in US army rangers? A prospective prognostic study Clin Orthop Relat Res Teyhen Deydre S. Shaffer Scott W. Butler Robert J. Goffar Stephen L. Kiesel Kyle B. Rhon Daniel I. Williamson Jared N. Plisky Phillip J. 9 2015
473 9 2948 2958 0009-921X 10.1007/s11999-015-4342-6 10.1007/s11999-015-4342-6 26013150
Association of physical inactivity, weight, smoking, and prior injury on physical performance in a military setting J Athl Train Teyhen Deydre S. Rhon Daniel I. Butler Robert J. Shaffer Scott W. Goffar Stephen L. McMillian Danny J. Boyles Robert E. Kiesel Kyle B. Plisky Phillip J. 1 11 2016
51 11 866 875 1062-6050 10.4085/1062-6050-51.6.02 10.4085/1062-6050-51.6.02 27690529
Association of lower quarter Y-balance test with lower extremity injury in NCAA Division 1 athletes: An independent validation study Physiotherapy Wright Alexis A. Dischiavi Steven L. Smoliga James M. Taylor Jeffrey B. Hegedus Eric J. 6 2017
103 2 231 236 0031-9406 10.1016/j.physio.2016.06.002 10.1016/j.physio.2016.06.002 27665043
Interrater and test-retest reliability of the Y Balance Test in healthy, early adolescent female athletes International Journal of Sports Physical Therapy Greenberg Eric T. Barle Matthew Glassmann Erica Jung Min-Kyung 4 2019
14 2 204 213 2159-2896 10.26603/ijspt20190204 10.26603/ijspt20190204 30997273
Between-day reliability of pre-participation screening components in pre-professional ballet and contemporary dancers Journal of Dance Medicine & Science Kenny Sarah J. Palacios-Derflingher Luz Owoeye Oluwatoyosi B. A. Whittaker Jackie L. Emery Carolyn A. 15 3 2018
22 1 54 62 1089-313X 10.12678/1089-313x.22.1.54 10.12678/1089-313x.22.1.54
Does fatigue impact static and dynamic balance variables in athletes with a previous ankle injury? Int J Exerc Sci Lacey M. Donne B. 1 11 2019
12 3 1121 1137 Published 2019 Nov 1.
Performance and reliability of the Y-Balance Test™ in high school athletes The Journal of Sports Medicine and Physical Fitness Smith Laura J. Creps James R. Bean Ryan Rodda Becky Alsalaheen Bara 11 2018
58 11 1671 1675 10.23736/S0022-4707.17.07218-8 10.23736/S0022-4707.17.07218-8
Normative data and the influence of age and gender on power, balance, flexibility, and functional movement in healthy service members Military Medicine Teyhen Deydre S. Riebel Mark A. McArthur Derrick R. Savini Matthew Jones Mackenzie J. Goffar Stephen L. Kiesel Kyle B. Plisky Phillip J. 4 2014
179 4 413 420 0026-4075 10.7205/milmed-d-13-00362 10.7205/milmed-d-13-00362 24690966
Neuromuscular training reduces lower limb injuries in elite female basketball players. A cluster randomized controlled trial Scandinavian Journal of Medicine & Science in Sports Bonato M. Benis R. La Torre A. 8 1 2018
28 4 1451 1460 0905-7188 10.1111/sms.13034 10.1111/sms.13034
Preseason Y Balance Test scores are not associated with noncontact time-loss lower quadrant injury in male collegiate basketball players Sports Brumitt Jason Nelson Kyle Duey Duane Jeppson Matthew Hammer Luke 24 12 2018
7 1 4 2075-4663 10.3390/sports7010004 10.3390/sports7010004 30586865
Dynamic balance performance varies by position but not by age group in elite Rugby Union players – a normative study Journal of Sports Sciences Johnston William Duignan Ciara Coughlan Garrett F Caulfield Brian 2019
37 11 1308 1313 0264-0414 10.1080/02640414.2018.1557360 10.1080/02640414.2018.1557360 30570394
Fundamental movement and dynamic balance disparities among varying skill levels in golfers International Journal of Sports Physical Therapy Krysak Sean Harnish Christopher R. Plisky Phillip J. Knab Amy M. Bullock Garrett S. 7 2019
14 4 537 545 2159-2896 10.26603/ijspt20190537 10.26603/ijspt20190537 31440406
Functional movement screen and Y balance tests in adolescent footballers with hip/groin symptoms Physical Therapy in Sport Linek Pawel Booysen Nadine Sikora Damian Stokes Maria 9 2019
39 99 106 1466-853X 10.1016/j.ptsp.2019.07.002 10.1016/j.ptsp.2019.07.002 31288214
Functional movement screen and Y-Balance test scores across levels of American football players Biology of Sport Lisman Peter Nadelen Mary Hildebrand Emily Leppert Kyle de la Motte Sarah 2018
35 3 253 260 0860-021X 10.5114/biolsport.2018.77825 10.5114/biolsport.2018.77825 30449943
Different neuromuscular parameters influence dynamic balance in male and female football players Knee Surgery, Sports Traumatology, Arthroscopy López-Valenciano A. Ayala F. De Ste Croix M. Barbado D. Vera-Garcia F. J. 2019
27 3 962 970 0942-2056 10.1007/s00167-018-5088-y 10.1007/s00167-018-5088-y
Limb differences in unipedal balance performance in young male soccer players with different ages Sports Muehlbauer Thomas Schwiertz Gerrit Brueckner Dennis Kiss Rainer Panzer Stefan 11 1 2019
7 1 20 2075-4663 10.3390/sports7010020 10.3390/sports7010020 30641997
Lower quarter- and upper quarter Y Balance Tests as predictors of running-related injuries in high school cross-country runners International Journal of Sports Physical Therapy Ruffe Natalie J. Sorce Samantha R. Rosenthal Michael D. Rauh Mitchell J. 9 2019
14 5 695 706 2159-2896 10.26603/ijspt20190695 10.26603/ijspt20190695 31598407
Differences in lower quarter Y-balance test with player position and ankle injuries in professional baseball players Journal of Orthopaedic Surgery Ryu Chang Hyun Park Jungu Kang Mina Oh Joo Han Kim You Keun Kim Yong Il Lee Ho Seong Seo Sang Gyo 1 2019
27 1 1 7 2309-4990 10.1177/2309499019832421 10.1177/2309499019832421
Sex differences in Y-Balance performance in elite figure skaters J Strength Cond Res Slater Lindsay V. Vriner Melissa Schuyten Kristen Zapalo Peter Hart Joseph M. 5 2020
34 5 1416 1421 1064-8011 10.1519/jsc.0000000000002542 10.1519/jsc.0000000000002542 29489718
The Lower Extremity Grading System (LEGS) to evaluate baseline lower extremity performance in high school athletes International Journal of Sports Physical Therapy Smith Joseph DePhillipo Nick Azizi Shannon McCabe Andrew Beverine Courtney Orendurff Michael Pun Stephanie Chan Charles 6 2018
13 3 401 409 2159-2896 10.26603/ijspt20180401 10.26603/ijspt20180401 30038826
Association of y balance test reach asymmetry and injury in division I athletes Med Sci Sports Exerc Smith CRAIG A. Chimera NICOLE J. Warren MEGHAN 1 2015
47 1 136 141 0195-9131 10.1249/mss.0000000000000380 10.1249/mss.0000000000000380
Functional movement assessments are not associated with risk of injury during military basic training Mil Med de la Motte Sarah J Clifton Daniel R Gribbin Timothy C Beutler Anthony I Deuster Patricia A 24 5 2019
184 11-12 e773 e780 0026-4075 10.1093/milmed/usz118 10.1093/milmed/usz118
Musculoskeletal screening to identify female collegiate rowers at risk for low back pain J Athl Train Gonzalez Sophia L. Diaz Aimee M. Plummer Hillary A. Michener Lori A. 1 12 2018
53 12 1173 1180 1062-6050 10.4085/1062-6050-50-17 10.4085/1062-6050-50-17 30525938
Association of dynamic balance with sports-related concussion: A prospective cohort study The American Journal of Sports Medicine Johnston William O’Reilly Martin Duignan Ciara Liston Mairead McLoughlin Rod Coughlan Garrett F. Caulfield Brian 2019
47 1 197 205 0363-5465 10.1177/0363546518812820 10.1177/0363546518812820 30501391
Association of functional movement screen and Y-balance test scores with injury in high school athletes J Strength Cond Res Lisman Peter Hildebrand Emily Nadelen Mary Leppert Kyle 4 3 2019
10.1519/JSC.0000000000003082 1064-8011 10.1519/jsc.0000000000003082 10.1519/jsc.0000000000003082
Association of pre-season musculoskeletal screening and functional testing with sports injuries in elite female basketball players Scientific Reports Šiupšinskas Laimonas Garbenytė-Apolinskienė Toma Salatkaitė Saulė Gudas Rimtautas Trumpickas Vytenis 26 6 2019
9 1 2045-2322 10.1038/s41598-019-45773-0 10.1038/s41598-019-45773-0 31243317
Ankle sprains risk factors in a sample of French firefighters: A preliminary prospective study J Sport Rehabil Vaulerin Jérôme Chorin Frédéric Emile Mélanie d’Arripe-Longueville Fabienne Colson Serge S. 1 7 2020
29 5 1 23 1056-6716 10.1123/jsr.2018-0284 10.1123/jsr.2018-0284
Effect of age and sex on maturation of sensory systems and balance control Developmental Medicine & Child Neurology Steindl R Kunz K Schrott-Fischer A Scholtz AW 15 5 2006
48 6 477 482 0012-1622 10.1017/s0012162206001022 10.1017/s0012162206001022
Sex-related injury patterns among selected high school sports The American Journal of Sports Medicine Powell John W. Barber-Foss Kim D. 5 2000
28 3 385 391 0363-5465 10.1177/03635465000280031801 10.1177/03635465000280031801 10843133
Differences in neuromuscular strategies between landing and cutting tasks in female basketball and soccer athletes J Athl Train Cowley H.R. Ford K.R. Myer G.D.. 2006
41 67 73 https://www.ncbi.nlm.nih.gov/pubmed/16619097 16619097
Influence of biological maturity on static and dynamic postural control among male youth soccer players Gait & Posture John Cornelius Rahlf Anna Lina Hamacher Daniel Zech Astrid 2 2019
68 18 22 0966-6362 10.1016/j.gaitpost.2018.10.036 10.1016/j.gaitpost.2018.10.036
Identification of risk factors prospectively associated with musculoskeletal injury in a warrior athlete population Sports Health: A Multidisciplinary Approach Teyhen Deydre S. Shaffer Scott W. Goffar Stephen L. Kiesel Kyle Butler Robert J. Rhon Daniel I. Plisky Phillip J. 5 3 2020
12 6 564 572 1941-7381 10.1177/1941738120902991 10.1177/1941738120902991 32134698
