No full-text available
To read the full-text of this research,
you can request a copy directly from the authors.
Do Normative Composite Scores on the Functional Movement Screen Differ Across High School, Collegiate, and Professional Athletes? A Critical Review
Abstract
Objective:
The Functional Movement Screen (FMS) is a battery of 7 unloaded tests designed to rate human movement competency. Injury rates vary across the different level of a sport. The purpose of this critical review was to determine whether normative FMS composite scores differ across high school, collegiate, and professional athletic populations and to determine whether normative composite scores correlate with rates of severe injury across different collegiate sports.
Data sources:
PubMed, Web of Science, and EBSCO databases from inception to September 2017 with the following syntax: "functional movement screen*" OR "movement screen*". Additional records were identified by citation tracking and hand search of articles.
Study selection:
A total of 708 records identified, of which 36 were included. Studies were included if they reported a FMS composite score for one of the groups.
Data extraction:
Two reviewers (T.R.P. and F.K.) screened records for the author and year; sample size; study design; sport(s); number, age, and sex of participants; testing conditions; methodological quality; and mean or median composite score(s).
Data synthesis:
Normative FMS composite scores were invariant to level of play, with 61% of reported scores falling between 14 and 16, despite injury rates increasing by level of play. Scores for high school, college, and professional athletes were 14.1, 14.8, and 15.7, respectively. There was a significant positive relationship between composite scores and rate of severe injury in college sports (r(11) = 0.66, P = 0.014).
Conclusions:
Our findings potentially undermine the FMS's predictive validity. Although the FMS may have other applications, this critical review provides further evidence against the composite score for injury prediction in competitive athletes.
... A sports injury is a complex risk network system composed of multiple factors [7]. For student athletes, biomechanical changes [8,9], neurocognitive performance [10], physical performance, and movement pattern quality [11][12][13] have been identified as potential injury risk factors. The Functional Movement Screen (FMS) is a widely used tool to assess the quality of movement patterns. ...
... By assessing the flexibility, stability, and coordination of the body, it can analyze compensation, imbalance, and asymmetry in the subject's movement [10]. Although the validity of FMS composite scores and cutoff scores for injury prediction remains controversial [11,12], movement asymmetry or poor-quality movement patterns have proven useful in estimating injury risk [13,14]. However, individual psychosocial factors such as stress, anxiety, and high levels of life event stress [15,16] could increase injury risk, but have been less targeted in sports injury research [6]. ...
... However, in Pollen et al.'s critical review [13], the FMS composite score was positively correlated with the incidence of injury due to other risk factors that may have a greater impact on injury. A growing number of studies suggest that FMS composite scores are not related to injury [12] or should not be used in isolation to predict injuries [13]. ...
High-quality movement patterns and high levels of mindfulness are thought to be beneficial in preventing sports injuries. Yoga is recommended in the field of athlete rehabilitation. This study investigated the effects of yoga intervention on functional movement patterns and mindfulness in collegiate athletes. It is a quasi-experimental study with a pre/post-test control design. The participants were divided into a yoga group and a control group. A Functional Movement Screen and the Mindful Attention Awareness Scale were used to assess participants’ basic movement patterns and mindfulness before and after 12 weeks of yoga intervention (two classes per week, 90 min per class). The results show that the yoga group’s FMS scores improved more compared to the control group [F(1,78) = 29.08, p < 0.001, ŋp2 = 0.27], and that the scores for the deep squat (ŋp2 = 0.4), shoulder mobility (ŋp2 = 0.17), and trunk stability pushup (ŋp2 = 0.36) improved substantially. The dysfunctional score ratio for deep squats (χ2 = 18.57, p < 0.001), shoulder mobility (χ2 = 26.90, p < 0.001), trunk stability pushup (χ2 = 17.07, p < 0.001), and rotatory stability (χ2= 38.29, p <0.001) decreased significantly compared with the control group, but there was no significant improvement in asymmetric movement patterns (χ2 = 0.75, p = 0.39). The mindfulness scores in the yoga group significantly exceeded those of the control group [F(1,78) = 13.56, p < 0.001, ŋp2 = 0.15]. These results suggest that yoga intervention can improve functional movement patterns and mindfulness levels, but further evidence is needed to determine whether yoga could positively influence sports injuries.
... In the past few years, several articles Pollen et al., 2018; have seriously undermined the predictive validity of the FMS among various populations (adults, athletes, firefighters, etc.). Emphasizing that although the reliability of the test is excellent , it is not enough as FMS does not demonstrate the properties essential to be considered as a measurement scale and has neither measurement nor predictive validity . ...
... nor in athletic youth (AUC: 0.56, 95% CI: 0. 47-0.63). The results of our study are hardly surprising because in the past few years several articles (43,46,48,68) have seriously undermined the predictive validity of the FMS among various populations (adults, athletes, firefighters, etc.). ...
... All skinfold measures were taken in triplicate and median values were used for analyses. Waist and hip circumferences were measured manually with non-stretchable tape in a transverse plane at the midpoint between the last rib and the iliac crest, and at the level of the largest lateral extension of the hips, respectively(48 ...
The main purpose of this doctoral thesis is to determine in which way are level of physical activity (PA), adiposity, and injury related to the quality of movement patterns among adolescent population. Within this doctoral thesis, there are three distinct studies with related research questions and aims (Study 1, Study 2, and Study 3). Study 1 examined relationship between functional movement and PA in an urban adolescent population, while study 2 strive to identify association between adiposity and quality of movement patterns among the adolescent population. Finally, in Study 3, machine learning (ML) was used to predict injuries among adolescents by functional movement testing. Participants in all three studies were part of the Physical Activity in Adolescence Longitudinal Study (CRO-PALS) cohort. In Study 1 we included 725 adolescents (aged between 16 and 17 years) from CRO-PALS cohort. Movement quality was evaluated via Functional Movement ScreenTM (FMSTM) while PA was assessed with the School Health Action, Planning and Evaluation System (SHAPES) questionnaire. From SHAPES questionnaire, vigorous PA (VPA) and moderate-to-vigorous PA (MVPA) was calculated. Confounders included chronological age, body fat and socioeconomic status (SES). Results of Study 1 indicated that after adjusting for age, body fat and SES, both VPA and MVPA showed minor but significant effects on total FMS score among girls (β=0.011, p=0.001, β=0.005, p=0.006, respectively), but not in boys (β=0.004, p=0.158; β=0.000, p=0.780). Regarding PA type, volleyball and dance improved total FMS score (β=1.003, p=0.071; β=0.972, p=0.043, respectively), while football was associated with lower FMS score (β=-0.569, p=0.118). Conclusively, results of Study 1 showed that PA level is positively associated with the functional movement in adolescent girls, but not in boys, where the type of PA moderates these associations. Because girls are more engaged in aesthetic sports activities that improve functional movement, and unlike boys are in the final stages of maturation, this could affect sexual dimorphism in the quality of movement among the adolescent population. In Study 2 participants were 652 urban adolescents (aged between 16 and 17 years). Body mass index (BMI), a sum of four skinfolds (S4S), waist and hip circumference were measured, and movement quality (i.e. functional movement – FM) was assessed via FMSTM. Furthermore, total FMSTM screen was indicator of FM with the
composite score ranged from 7 to 21, with higher score indicating better FM. Multilevel analysis was employed to determine the relationship between different predictors and total FMS score. Results of the Study 2 demonstrate that, in boys, after controlling for age, MVPA, and SES, total FMS score was inversely associated with BMI (β=-0.18, p<0.0001), S4S (β=-0.04, p<0.0001), waist circumference (β=-0.08, p<0.0001), and hip circumference (β=-0.09, p<0.0001). However, among girls, in adjusted models, total FMS score was inversely associated only with S4S (β=-0.03, p<0.0001), while BMI (β=-0.05, p=0.23), waist circumference (β=-0.04, p=0.06), and hip circumference (β=-0.01, p=0.70) failed to reach statistical significance. Findings of Study 2 point out that the association between adiposity and FM in adolescence is sex-specific, suggesting that boys with overweight and obesity could be more prone to develop dysfunctional movement patterns. Therefore, exercise interventions directed toward correcting dysfunctional movement patterns should be sex-specific, targeting more boys with overweight and obesity rather than adolescent girls with excess weight. Analyses for the Study 3 were based on nonathletic (n=364) and athletic (n=192) subgroups of the cohort (16–17 years). Sex, age, BMI, body fatness, MVPA, training hours per week, FMS, and SES were assessed at baseline. A year later, data on injury occurrence were collected. The optimal cut-point of the total FMS score for predicting injury was calculated using receiver operating characteristic curve. These predictors were included in ML analyses with calculated metrics: area under the curve (AUC), sensitivity, specificity, and odds ratio (95% confidence interval [CI]). Results of the receiver operating characteristic curve analyses with associated criterium of total FMS score >12 showed AUC of 0.54 (95% CI: 0.48–0.59) and 0.56 (95% CI: 0.47–0.63), for the nonathletic and athletic youth, respectively. However, in the nonathletic subgroup, ML showed that the Naïve Bayes exhibited highest AUC (0.58), whereas in the athletic group, logistic regression was demonstrated as the model with the best predictive accuracy (AUC: 0.62). In both subgroups, with given predictors: sex, age, BMI, body fat percentage, MVPA, training hours per week, SES, and total FMS score, ML can give a more accurate prediction then FMS alone. Results of the Study 3 indicate that nonathletic boys who have lower-body fat could be more prone to suffer from injury incidence, whereas among athletic subjects, boys who spend more time training are at a higher risk of being injured. Conclusively, total FMS cut-off scores for each
subgroup did not successfully discriminate those who suffered from those who did not suffer from injury, and, therefore, this study does not support FMS as an injury prediction tool.
... Furthermore, several controversies exist regarding the predictive validity of the FMS and its underlying factors, e.g., sport type, which may be related to elevate injury risk [16][17][18]. More evidence is needed to identify the utility of FMS in professional athletes and its associations for those are at high risk of injury and high motor skill level [19]. To date, no studies have utilized FMS in Wushu routine sports, even though Wushu athletes are at high injury risk. ...
... The strength of correlation was interpreted as weak (<0. 19), low (0.20-0.39), moderate (0.40-0.59), strong (0.60-0.79), or very strong (>0.80) [22]. ...
... The majority of Wushu routine athletes (about 70%) were able to get three points from the in-line lunge, shoulder mobility, active straight leg raise and trunk stability push-up, which are related to the movement characteristics of Wushu routine. Thus, the FMS scores were relatively high in the most Wushu athletes as compared to previously published results in other sports [19], which highlights the need to identify sport-specific FMS score threshold for these athletes. ...
The functional movement screen (FMS) is commonly used to evaluate sports injury risks, but no study has been reported for Wushu athletes. The aim of this study was to identify optimal FMS cut-off points for previously injured Wushu athletes and to examine the associations with other possible factors. In this study, a total of 84 Chinese Wushu athletes (15.1 ± 4.5 years old, 51% male) with a minimum of two years of professional training background in either Taiji, Changquan, or Nanquan were assessed by the FMS. Video recordings were used to confirm the scoring criteria, and previous injuries were assessed based on face-to-face interviews. An optimal cut-off of the FMS score was investigated by receiver operating characteristic curves with sensitivity and specificity. We found that FMS score of less than 16 (sensitivity = 80%, specificity = 56%) was related to an increased occurrence of injuries (odds ratio = 5.096, 95%CI: 1.679–15.465) for the current study sample. The training type and training levels were related with FMS scores. More than half of the athletes (58%) had FMS asymmetry and 21% of athletes reported pain while performing the FMS protocol. Future prospective studies are recommended to use FMS with cut-off of 16 points in Wushu athletes.
... The results of our study are hardly surprising because in the past few years several articles (43,46,48,68) have seriously undermined the predictive validity of the FMS among various populations (adults, athletes, firefighters, etc.). Emphasizing that although reliability of the test is excellent (68), it is not enough as FMS does not demonstrate the properties essential to be considered as a measurement scale and has neither measurement nor predictive validity (46). ...
This study used machine learning (ML) to predict injuries among adolescents by functional movement testing. This research is a part of the CRO-PALS study conducted in a representative sample of adolescents and analyses for this study are based on nonathletic (n = 364) and athletic (n = 192) subgroups of the cohort (16-17 years). Sex, age, body mass index (BMI), body fatness, moderate-to-vigorous physical activity (MVPA), training hours per week, Functional Movement Screen (FMS), and socioeconomic status were assessed at baseline. A year later, data on injury occurrence were collected. The optimal cut-point of the total FMS score for predicting injury was calculated using receiver operating characteristic curve. These predictors were included in ML analyses with calculated metrics: area under the curve (AUC), sensitivity, specificity, and odds ratio (95% confidence interval [CI]). Receiver operating characteristic curve analyses with associated criterium of total FMS score >12 showed AUC of 0.54 (95% CI: 0.48-0.59) and 0.56 (95% CI: 0.47-0.63), for the nonathletic and athletic youth, respectively. However, in the nonathletic subgroup, ML showed that the Naïve Bayes exhibited highest AUC (0.58), whereas in the athletic group, logistic regression was demonstrated as the model with the best predictive accuracy (AUC: 0.62). In both subgroups, with given predictors: sex, age, BMI, body fat percentage, MVPA, training hours per week, socioeconomic status, and total FMS score, ML can give a more accurate prediction then FMS alone. Results indicate that nonathletic boys who have lower-body fat could be more prone to suffer from injury incidence, whereas among athletic subjects, boys who spend more time training are at a higher risk of being injured. Conclusively, total FMS cut-off scores for each subgroup did not successfully discriminate those who suffered from those who did not suffer from injury, and, therefore, our research does not support FMS as an injury prediction tool.
... However, as the result of univariate and multivariate analyses in our study, the cut-off points in the FMS composite of ≤14, ≤15, ≤16, ≤17 and ≤18 were not associated with any of the parameters for number of injury, lower limb injury, traumatic injury or the time to return to play. Although 61% of reported scores represented were between 14 and 16, the injury rates were increased depending upon the level of play 24) . Additionally it was suggested that the FMS composite score does not predict injuries in youth academy soccer players 25) . ...
[Purpose] This study aimed to assess the reliability of the Functional Movement Screen and explore whether this evaluation tool can predict the risks of personal injuries in Japanese soccer players. [Participants and Methods] Seventy-five Japanese college soccer players who participated in our 1 year prospective cohort study underwent a Functional Movement Screen assessment. Demographic data, athletic characteristics, and types and frequency of injuries sustained, were analyzed with the assessment results. [Results] There was no significant difference in the mean Functional Movement Screen composite scores between genders. Although the Functional Movement Screen showed excellent inter-rater reliability (0.92), low overall internal consistency (0.35) was observed. A maximum score of 3 in straight leg raise occurred in 94% of the females and was considered a ceiling effect. None of the cut-off point scores of the Functional Movement Screen were associated with the number of overall injuries, lower limb injuries, and traumatic injuries, or time to return to play. The Functional Movement Screen composite score of ≤15 represented the maximum sensitivity of 76.92% and specificity of 34.78% with 0.56 in the area under the curve. [Conclusion] Functional Movement Screen composite scores do not have sufficient sensitivity and specificity for predicting injuries in Japanese college soccer players.
... However, the scientific evidence for the FMS is less clear regarding its validity for predicting injuries across sports [27][28][29], which is the purported aim of this screening tool. Scientists have invested the FMS in populations ranging from youth sport participants to recreational athletes and across high school, collegiate, and professional athletes [30][31][32][33][34]. However, no studies using the FMS have been published on professional basketball players to date. ...
Background and objectives: Striking a balance between maximizing performance and preventing injury remains elusive in many professional sports. The purpose of this study was to assess the relative risk of non-contact injuries in professional basketball players based on predictive cut scores on the Functional Movement Screen™ (FMS). Materials and Methods: Thirty-two professional basketball players from the National Basketball Association (NBA) and Women’s National Basketball Association (WNBA) participated in this study. This observational pilot cohort study assessed and scored each participant using the FMS during training camp. Each athlete was then tracked throughout the season while recording the number, type, and time lost due to injuries. Possible exposures, actual exposures, and exposures missed due to non-contact injury (NCI) for each athlete were calculated and then used to determine the crude and specific incident rates for exposures missed due to NCI per 1000 exposures. Results: Linear regression models were used to evaluate the predictive ability of the FMS score for total missed exposures, NCI, and CI missed exposures. In all models, the FMS total score failed to attain significance as a predictor (p > 0.05). FMS scores ranged from 5 to 18. The recommended cut score of 14 showed a sensitivity of 0.474 and a specificity of 0.750. The cut score of 15 showed the best combination, exhibiting a sensitivity of 0.579 and specificity of 0.625. A total of 5784 exposures to NCI were possible for the men and women combined, and 681 possible exposures were missed. Of these, 23.5% were due to NCI, 16.5% were due to contact injuries (CI), and 60% were due to illnesses and personal reasons. Conclusions: The FMS proved to be a measure that was not associated with any injury measure in this sample of professional basketball players, suggesting the instrument lacks predictive validity in this population.
... Th ese tests are also used to assess pain in athletes, muscle strength, joint stability in the lower limbs, muscle fl exibility, balance and proprioception [25]. Th e FMS is considered a comprehensive tool evaluating motor control ISSN: 2640-0936 through functional movement and dynamic coordination analysis [26,27]. Th e FMS has also been used as an injury prediction tool in competitive athletes. ...
Objective: The Functional Movement Screening (FMS) measures the range of motion, balance, and stability in different situations. So performing exercises that increase the (FMS) scores may be helpful in reducing the number of exercise injuries. Therefore, the aim of this study was to assess does TRX training reduce injury rates in futsal athletes, as measured by the Functional Movement Screening Test? Methods: Twenty-four futsal players (CON mean age: 22.40 ± 1.24 years and INT Mean age: 2.44 ± 21.80 years, age range: 18-28) were randomly assigned to a CON (n = 12) or an INT (n = 12) group. The intervention group carried out three times a week over six weeks during the same period, the control group continued its routine training that includes futsal specialist training and Tactical training. Both groups performed functional movement screening before and after the exercise program. Paired t-test was used to analyze the data via SPSS software at the significance level of P < 0.050.Results: The Paired t-test analysis showed significant improvements in Deep squat (p = 0.01), Hurdle step (p = 0.01), In-line lunge (p = 0.04), Trunk rotary stability (p = 0.021) and total score of the FMS (p = 0.002) from the pre- to post-test in the INT group, But no significant changes were observed in control group performance.Conclusion: According to the results, the suspension training seems to increase the FMS by strengthening the body’s core region and modifying the patterns of utilizing motor units and it can reduce the injury rates to futsal players. So, it is recommended for athletic trainers and athletes to use this training to prevent sports injuries.
Objective: The aim of the study was to examine whether the proportion of young elite football players with high functional movement screening (FMS) scores and reaching professionalism differs from the proportion of young elite football players with low FMS scores and non-professionals.
Materials and Methods: Fifty-seven players were included in the study. The health files of the participants were retrospectively scanned. Physical information and FMS scores were recorded in the data form. The level of football career of the participants as of March 2022 was assessed on the website of the Turkish Football Federation. FMS scores were compared by dividing the participants into two groups as those with- and without professional football license.
Results: The proportion of participants with a score above the FMS cut-off score and reaching the professional level was higher than the rate of non-professional participants with a score above the FMS cut-off score (p˂0.05).
Conclusion: The quality of movement in young elite football players may be a determinant for being a professional football player. For this reason, starting from an early age, measuring the quality of movement regularly and trying to improve it may be important in realizing the career goals of elite young football players.
Amaç: Futsal oyuncularının cinsiyete ve yaralanma geçmişlerine göre fonksiyonel hareket, denge, sıçrama ve esneklik performanslarının karşılaştırılması amaçlanmıştır.
Gereç ve Yöntemler: Bu çalışmaya Pamukkale Üniversitesi futsal takımında oynayan 17 kadın ve 18 erkek toplam 35 gönüllü futsal oyuncusu katılmıştır. Sporcularda fonksiyonel hareket; fonksiyonel hareket taraması testi, denge; Y denge testi, sıçrama performansı tek ayak durarak uzun atlama ve dikey sıçrama testleri, esneklik ise kapalı kinetik dorsifleksiyon ROM testi ile değerlendirilmiştir.
Bulgular: Sporcuların fonksiyonel hareket taraması testi skorları ve tüm performans parametreleri arasında yaralanma geçmişine göre anlamlı bir fark olmadığı görülmüştür (p>0,05). Sporcuların sıçrama değerleri, Y denge testinin her iki ekstremite posteromedial ve posterolateral değerlerinde, sıçrama performansları ve gövde stabilite şınavı test sonucunda erkekler lehine, esneklik kapalı kinetik dorsifleksiyon açısında ise kadınlar lehine anlamlı bir fark olduğu tespit edilmiştir (p<0,05).
Sonuç : Futsal oyuncularında yaralanma hikayesi sporcuların fonksiyonel hareket, dinamik denge, sıçrama performansını etkilememektedir. Ayrıca cinsiyet, dinamik dengenin bazı parametreleri, esneklik, kor (çekirdek) kuvveti ve sıçrama performansını etkileyen önemli bir faktördür.
Background. Basketball is a popular sport around the world, the number of players is growing, the probability
to experience trauma is increasing, too. Studies have shown that women sustain 60% more injuries than men do. Pre-
season physical examination helps to establish sports specific changes in the body of the athlete and to determine risk
factors for training, competition, which cause injury to the players. Research aim was to analyse risk of non-contact
musculoskeletal injuries in elite women basketball players according to the position on the court.
Methods. The study involved 100 players in Lithuanian women basketball league who completed the questionnaire
about the level of physical fatigue, performed Lower Quarter Y Balance Test™ and Functional Movement Screen
™ tests during pre-season physical examination in 2014. Data were analysed and compared according to player’s
position on the court (guards and forwards).
Results. The level of physical fatigue during pre-season period was low in both groups. Dynamic stability of the
right leg was better in guards (composite score – 105.2 to 101.8 in forwards) while dynamic stability of the left leg
remained the same in both groups. Guards had higher total scores in Functional Movement Screen™ tests pointing
to the better quality of basic functional movement patterns.
Conclusions. The guard’s playing efficiency during the season was higher than that of forwards and it was
associated with better dynamic stability and higher level of physical fatigue at pre-season. Indirect indicators of
non-contact musculoskeletal sport injuries showed that guards should have lower risk of non-contact sport-related
injuries in women basketball.
Keywords: risk of sports trauma, female basketball players, functional movements, dynamic stability.
Context:
The Functional Movement Screen (FMS™) is used to identify movement asymmetries and deficiencies. While obesity has been reported to impede movement, the correlation between body mass index (BMI), body fat percentage (BF%), and FMS™ in athletes is unknown.
Objective:
To determine if there is a relationship between BMI, BF%, and FMS™ scores in a sample of National Collegiate Athletic Association (NCAA) Division I football athletes.
Design:
Cross-sectional study.
Setting:
Biodynamics laboratory.
Participants:
38 male freshman football players (18.0 ± 0.7 y, 185.3 ± 5.5 cm, 103.9 ± 20.3 kg).
Interventions:
Height, weight, and BF% were collected, and subjects underwent the FMS™ conducted by a certified athletic trainer.
Main outcome measures:
The dependent variables were BMI, BF%, composite FMS™ score, and seven individual FMS™ test scores. Subjects were grouped as normal BMI (BMI < 30 kg/m(2)) or obese (BMI ≥ 30 kg/m(2)). A composite FMS™ score of ≤14 and an individual FMS™ score of ≤1 were classified as cut-offs for poor movement performance.
Results:
A negative correlation between composite FMS™ score and BMI approached significance (p = 0.07, ρ = -0.296). A negative correlation between composite FMS™ score and BF% was significant (p = 0.010, ρ = -0.449). There was a significant difference in the number of obese subjects scoring below the composite FMS™ cut-off (χ(2) = 5.179, p = 0.023) and the individual FMS™ cut-off on the deep squat (χ(2) = 6.341, p = 0.012), hurdle step (χ(2) = 9.870, p = 0.002), and in-line lunge (χ(2) = 5.584, p = 0.018) when compared to normal BMI subjects.
Conclusions:
Increased BF% and BMI relate to lower composite FMS™ and individual FMS™ test scores, indicating potentially poor movement patterns in larger NCAA football athletes. Future research should focus on examining lower extremity-specific FMS™ tasks individually from composite FMS™ scores.
Introduction. The aim of the study was to assess the functional status of male soccer players in different age groups who played on different surfaces. Methods. The study included 45 soccer players aged 13-35 years. Among them, 15 were junior players, 15 were players of the senior Silesia-Opole 3rd league (SL), and 15 were senior players in the futsal Extra Class league (SF). The functional status and basic motor skills were assessed according to the results obtained in seven motor tasks included in the Functional Movement Screen™ (FMS) test. Results. The mean total scores in the FMS test were statistically significantly higher among both senior futsal and senior 3
Introduction. The Functional Movement Screen™ (FMS™) is one of modern functional assessment tools used, for example, for qualitative evaluation of fundamental movement patterns and potential injury risks. Aim of Study. The purpose of this study was to assess the performance of handball players with the use of Functional Movement Screen™ (FMS™) in consideration of their competitive level, position on the court and symmetry of
movement patterns. Material and Methods. Thirty 1st and 2nd division handball players participated in the study. All subjects were healthy men aged 23.23 ± 3.59 years, with body height of 184 ± 5.6 cm and body mass of 86.37 ± 8.61 kg. The players performed seven tests from the Functional Movement Screen™. Statistical analysis was made using the SPSS Statistics 21.0 software package. The level of statistical significance was set at p ≤ 0.05. Results. No significant differences in handball players’ general characteristics were found between both divisions. Student’s t-test showed no significant differences between the two groups in total FMS™ score. Statistically significant differences were noted in the Shoulder Mobility (SM) test (U =308.5; p = 0.014) between the right and the left upper extremity. Conclusions. The study revealed no statistically significant
differences in FMS™ test scores between the 1st and 2nd division handball players as well as between players in different playing positions on the court. Also no higher risk of injury was shown among the 1st and 2nd division handball players. The study confirmed, however, characteristic adaptation of the throwing arm typical for throwing sports in the form of glenohumeral internal rotation deficit.
Identifying injury risk and implementing preventive measures can assist in reducing injury occurrence and may ultimately improve athletic performance. Improper movement patterns often contribute to musculoskeletal (MSK) injuries. The validity of the Functional Movement Screen (FMS™) as an injury prediction tool for athletes remains unclear. We designed the Basketball-Specific Mobility Test (BMT) to represent the neuromuscular demands of basketball and identify deficiencies that may be indicative of greater MSK injury risk while playing this sport. The aim of this study was to examine the association of FMS™ and BMT scores with injury occurrence in collegiate basketball players. We hypothesized that the BMT would be a better predictor of injury risk than the FMS™, and that scores from both tests would have a higher association with severe MSK injuries than minor, non-MSK injuries. One-hundred nineteen male and female collegiate basketball players from four Upper Midwest universities were assessed pre- (PRE) and post-season (POST) using the FMS™ and BMT. In-season injury records were collected from the schools' athletic trainers and were classified by type and severity. During the season, 56 of 119 players were injured, resulting in 96 total injuries. Injured athletes' PRE FMS™ scores demonstrated negligible effects compared to uninjured athletes' PRE scores (d < 0.20), though some BMT scores showed potentially meaningful effects (d > 0.20). While specificity of the FMS™ and BMT to predict injury was relatively high (FMS™ 85.7-87.6; BMT 42.0-88.0), sensitivity (FMS™ 14.2-22.7; BMT 11.6-39.1), odds ratios (FMS™ 1.00-2.08; BMT 0.47-1.06), and injury prediction capacities (AUC; FMS™ 0.43-0.49; BMT 0.49-0.59) of the tests were low. Although the FMS™ and BMT may be suitable for identifying MSK deficiencies, they do not accurately determine injury risk in collegiate basketball players. Injury risk assessments may be improved by targeting specific injury mechanisms and the conditions in which they occur.
This study had two main objectives: (1) to determine if differences in Functional Movement Screen (FMS) scores exist between two levels of competition; and (2) to analyze the association between FMS individual and overall scores and physical performance variables of lower-limb power (jumps), repeated sprint ability and shot speed. Twenty-two Under 16 (U16) and twenty-six Under 19 (U19) national competitive soccer players participated in this study. All participants were evaluated according to anthropometrics, FMS, jump performance, instep kick speed and anaerobic performance. There were no significant differences in the individual FMS scores between competitive levels. There were significant negative correlations between hurdle step (right) and Running-based Anaerobic Sprint Test (RAST) power average (ρ = −0.293; p = 0.043) and RAST fatigue index (RAST FatIndex) (ρ = −0.340; p = 0.018). The hurdle step (left) had a significant negative correlation to squat jump (SJ) (ρ = −0.369; p = 0.012). Rotary stability had a significant negative correlation to RAST fatigue index (Right: ρ = −0.311; p = 0.032. Left: ρ = −0.400; p = 0.005). The results suggest that individual FMS scores may be better discriminants of performance than FMS total score and established minimal association between FMS scores and physical variables. Based on that, FMS may be suitable for the purposes of determining physical function but not for discriminating physical performance.
Objectives:
The Functional Movement Screen (FMS) is a popular screening tool, however, the postulated relationship between prospective injury and FMS scoring remains sparsely explored in adolescent athletes. The aim of the study was to examine the association between pre-season FMS scores and injuries sustained during one regular season competition in elite adolescent Australian football players.
Design:
Prospective cohort study.
Methods:
237 elite junior Australian football players completed FMS testing during the late pre-season phase and had their weekly playing status monitored during the regular season. The definition of an injury was 'a trauma which caused a player to miss a competitive match'.
Results:
The median composite FMS score was 14 (mean=13.5±2.3). An apriori analysis revealed that the presence of ≥1 asymmetrical sub-test was associated with a moderate increase in the risk of injury (hazard ratio=2.2 [1.0-4.8]; relative risk=1.9; p=0.047; sensitivity=78.4%; specificity=41.0%). Notably, post-hoc analysis identified that the presence of ≥2 asymmetrical sub-tests was associated with an even greater increase in risk of prospective injury (hazard ratio=3.7 [1.6-8.6]; relative risk=2.8; p=0.003; sensitivity=66.7%; specificity=78.0%). Achieving a composite score of ≤14 did not substantially increase the risk of prospective injury (hazard ratio=1.1 [0.5-2.1]; p=0.834).
Conclusions:
Junior Australian football players demonstrating asymmetrical movement during pre-season FMS testing were more likely to sustain an injury during the regular season than players without asymmetry. Findings suggest that the commonly reported composite FMS threshold score of ≤14 was not associated with injury in elite junior AF players.
Context:
Few researchers have described the incidence of the most severe injuries sustained by student-athletes at the collegiate level.
Objective:
To describe the epidemiology of severe injuries within 25 National Collegiate Athletic Association (NCAA) sports in the 2009-2010 through 2014-2015 academic years.
Design:
Descriptive epidemiology study.
Setting:
Aggregate injury and exposure data from 25 NCAA sports.
Patients or other participants:
Collegiate student-athletes in the 2009-2010 through 2014-2015 academic years.
Main outcome measure(s):
Injury data from the NCAA Injury Surveillance Program were analyzed. A severe injury (1) occurred during a sanctioned competition or practice, (2) required medical attention by an athletic trainer or physician, and (3) resulted in at least 21 days lost from sport activity or a premature end to the sport season. Injury counts, proportions, rates per 1000 athlete-exposures (AEs), rate ratios (RRs), and injury proportion ratios were reported with 95% confidence intervals (CIs).
Results:
A total of 3183 severe injuries were reported, for an injury rate of 0.64/1000 AEs. Wrestling had the highest severe injury rate (1.73/1000 AEs), followed by women's gymnastics (1.40/1000 AEs) and football (0.97/1000 AEs). Overall, the severe injury rate was higher in competition than in practice (RR = 4.25, 95% CI = 3.97, 4.56). Most severe injuries were reported during the regular season (69.3%, n = 2206); however, severe injury rates did not differ between the preseason and regular season (RR = 0.98, 95% CI = 0.91, 1.06). Common severely injured body parts were the knee (32.9%, n = 1047), lower leg/ankle/foot (22.5%, n = 715), and head/face/neck (11.2%, n = 358). Common severe injury diagnoses were sprains (32.9%, n = 1048), strains (16.9%, n = 538), and fractures (14.4%, n = 458). Common severe injury mechanisms were player contact (25.1%, n = 800), noncontact (25.1%, n = 800), and surface contact (12.0%, n = 383).
Conclusions:
Severe injuries occurred across many sports and by numerous mechanisms. By identifying these sport-specific patterns, clinicians' efforts can be tailored toward improving injury-prevention strategies and health outcomes.
The existing data indicate that the result of the Functional Movement Screen (FMS) test influences the
likelihood of subsequent injury in professional athletes. Therefore, exercises increasing test scores of the FMS may be useful at various stages of sports activity. This study evaluated the effects of the NEURAC sling exercises method on the FMS test score in teenage volleyball players. The study was conducted on 15 volleyball players aged 14 years. The FMS test was performed three times interspersed with a two-month interval. Between the first and the second assessment, neither additional treatment nor training was applied, while between the second and the third assessment, the participants performed stabilisation exercises based on the NEURAC method. Training was carried out twice a week, for eight weeks. The analysis showed that between the first and the second measurement, no significant differences occurred. The use of specific sling exercises caused a significant improvement in FMS results (p ≤ 0.01) between the first and the third, as well as the second and the third measurement. The applied stabilisation exercises based on the NEURAC method positively influenced the FMS test result in male subjects practicing volleyball. Performance of such exercises also resulted in more than 90% of the subjects having a total FMS test score ≥ 17, which may be important in
the prevention of injuries. The preliminary results indicate that this type of exercise should be included in a teenage volleyball training routine.
The aim of this study was to investigate the use of FMS TM screening for high-level university female netball players by evaluating the relationship between FMS total score and various performance tests. Out of 20 elite female netball players, 19 completed the FMS TM screen consisting of deep overhead squat, hurdle step, in-line lunge, active straight leg raise, shoulder stability, trunk stability and rotary stability; and the performance tests consisting of maximum vertical and lateral jumps, 5 and 10 meters sprints, 5-0-5 agility tests, and repeated sprints. Spearman's correlations (p ≤ 0.05) examined the relationships between the FMS TM and performance tests. Players with higher FMS TM total score were faster on the 5-0-5 agility test (ρ =-0.52, p = 0.02), and covered more distance in the repeated sprints test (ρ = 0.51, p = 0.03). Agility 5-0-5 test was also significantly associated with the repeated sprints (ρ =-0.87, p = 0.02), while no significant relationships were found with the 5 or 10 meter sprints. These results indicate that due to specific demands of the game of netball, female netball players develop physical performance characteristics that do not depict strong association with the FMS TM assessment. Coaches and trainers should use both tools for comprehensive performance evaluation of their players.
Injury aetiology models that have evolved over the previous two decades highlight a number of factors which contribute to the causal mechanisms for athletic injuries. These models highlight the pathway to injury, including (1) internal risk factors (eg, age, neuromuscular control) which predispose athletes to injury, (2) exposure to external risk factors (eg, playing surface, equipment), and finally (3) an inciting event, wherein biomechanical breakdown and injury occurs. The most recent aetiological model proposed in 2007 was the first to detail the dynamic nature of injury risk, whereby participation may or may not result in injury, and participation itself alters injury risk through adaptation. However, although training and competition workloads are strongly associated with injury, existing aetiology models neither include them nor provide an explanation for how workloads alter injury risk. Therefore, we propose an updated injury aetiology model which includes the effects of workloads. Within this model, internal risk factors are differentiated into modifiable and non-modifiable factors, and workloads contribute to injury in three ways: (1) exposure to external risk factors and potential inciting events, (2) fatigue, or negative physiological effects, and (3) fitness, or positive physiological adaptations. Exposure is determined solely by total load, while positive and negative adaptations are controlled both by total workloads, as well as changes in load (eg, the acute:chronic workload ratio). Finally, we describe how this model explains the load—injury relationships for total workloads, acute:chronic workload ratios and the training load—injury paradox.
Objectives
The purpose of this study was to describe the prevalence of dysfunctional, asymmetrical, and painful movement in junior Australian Football players using the Functional Movement Screen (FMS).
Design
Cross-sectional study.
Methods
Elite junior male Australian Football players (n = 301) aged 15-18 years completed pre-season FMS testing. The FMS consists of 7 sub-tests: deep squat, hurdle step, in-line lunge, shoulder mobility, active straight leg raise, trunk stability push-up (TSPU) and rotary stability. The shoulder mobility, TSPU, and rotary stability tests were combined with an accompanying clearing test to assess pain. Each sub-test was scored on an ordinal scale from 0-3 and summed to give a composite score out of 21. Composite scores ≤14 were operationally defined as indicating dysfunctional movement. Players scoring differently on left and right sides were considered asymmetrical. Players reported whether they missed any games due to injury in the preceding 22 game season.
Results
Sixty percent of players (n = 182) had composite scores ≤14, 65% of players (n = 196) had at least one asymmetrical sub-test, and 38% of players (n = 113) had at least one painful sub-test. Forty-two percent of players (n = 126) missed at least one game in the previous season due to injury. Previous injury did not influence composite score (p = 0.951) or asymmetry (p = 0.629). Players reporting an injury during the previous season were more likely to experience pain during FMS testing (odds ratio 1.97, 95% confidence interval 1.23 to 3.18; p = 0.005).
Conclusions
Junior Australian Football players demonstrate a high prevalence of dysfunctional, asymmetrical, and painful movement during FMS testing.
Rugby Union is a collision sport with a relatively high risk of injury. The ability of the Functional Movement Screen (FMS) or its component tests to predict the occurrence of severe (≥28 days) injuries in professional players was assessed. 90 FMS test observations from 62 players across four different time periods were compared with severe injuries sustained during 6 months following FMS testing. Mean composite FMS scores were significantly lower in players who sustained severe injury (injured 13.2 ± 1.5 vs. non-injured 14.5 ± 1.4, ES = 0.83, large), due to differences in in-line lunge (ILL) and active straight leg raise scores (ASLR). Receiver-operated characteristic (ROC) curves and 2 x 2 contingency tables were used to determine that ASLR (cut-off 2/3) was the injury predictor with the greatest sensitivity (0.96, 95%CI 0.79 to 1.0). Adding the ILL in combination with ASLR (ILL+ASLR) improved the specificity of the injury prediction model (ASLR specificity = 0.29, 95%CI 0.18 to 0.43 vs. ASLR+ILL specificity = 0.53, 95%CI 0.39 to 0.66, p < 0.05). Further analysis was performed to determine whether FMS tests could predict contact and non-contact injuries. The FMS composite score and various combinations of component tests (Deep squat (DS)+ILL, ILL+ASLR and DS+ILL+ASLR) were all significant predictors of contact injury. The FMS composite score also predicted non-contact injury, but no component test or combination thereof produced a similar result. These findings indicate that low scores on various FMS component tests are risk factors for injury in professional rugby players.
Subjective assessment of athletes' movement quality is widely used by physiotherapists and other applied practitioners within many sports. One of the beliefs driving this practice is that individuals who display 'poor' movement patterns are more likely to suffer an injury than those who do not. The aim of this review was to summarize the reliability of the movement screens currently documented within the scientific literature and explore the evidence surrounding their association with injury risk. Ten assessments with accompanying reliability data were identified through the literature search. Only two of these ten had any evidence directly related to injury risk. A number of methodological issues were present throughout the identified studies, including small sample sizes, lack of descriptive rater or participant information, ambiguous injury definitions, lack of exposure time reporting and risk of bias. These factors, combined with the paucity of research on this topic, make drawing conclusions as to the reliability and predictive ability of movement screens difficult. None of the movement screens that appear within the scientific literature currently have enough evidence to justify the tag of 'injury prediction tool'.
Sports-related injuries can have a substantial impact on the long-term health of student-athletes. The National Collegiate Athletic Association (NCAA) monitors injuries among college student-athletes at member schools. In academic year 2013-14, a total of 1,113 member schools fielded 19,334 teams with 478,869 participating student-athletes in NCAA championship sports (i.e., sports with NCAA championship competition) (1). External researchers and CDC used information reported to the NCAA Injury Surveillance Program (NCAA-ISP) by a sample of championship sports programs to summarize the estimated national cumulative and annual average numbers of injuries during the 5 academic years from 2009-10 through 2013-14. Analyses were restricted to injuries reported among student-athletes in 25 NCAA championship sports. During this period, 1,053,370 injuries were estimated to have occurred during an estimated 176.7 million athlete-exposures to potential injury (i.e., one athlete's participation in one competition or one practice). Injury incidence varied widely by sport. Among all sports, men's football accounted for the largest average annual estimated number of injuries (47,199) and the highest competition injury rate (39.9 per 1,000 athlete-exposures). Men's wrestling experienced the highest overall injury rate (13.1 per 1,000) and practice injury rate (10.2 per 1,000). Among women's sports, gymnastics had the highest overall injury rate (10.4 per 1,000) and practice injury rate (10.0 per 1,000), although soccer had the highest competition injury rate (17.2 per 1,000). More injuries were estimated to have occurred from practice than from competition for all sports, with the exception of men's ice hockey and baseball. However, injuries incurred during competition were somewhat more severe (e.g., requiring ≥7 days to return to full participation) than those acquired during practice. Multiple strategies are employed by NCAA and others to reduce the number of injuries in organized sports. These strategies include committees that recommend rule and policy changes based on surveillance data and education and awareness campaigns that target both athletes and coaches. Continued analysis of surveillance data will help to understand whether these strategies result in changes in the incidence and severity of college sports injuries.
Background:
The Functional Movement Screen (FMS™) has been suggested for use in predicting injury risk in active populations, but time constraints may limit use of the screening test battery. Identifying one component of the FMS™ that can predict which individuals may perform poorly on the entire test, and therefore should undergo the full group of screening maneuvers, may reduce time constraints and increase pre-participation screening utilization.
Purpose:
The purpose of this study was to determine if performance on the FMS™ overhead deep squat test (DS) could predict performance on the entire FMS™.
Study design:
Cohort study.
Methods:
One hundred and three collegiate athletes underwent offseason FMS™ testing. The DS and adjusted FMS™ composite scores were dichotomized into low performance and high performance groups with athletes scoring below 2 on the DS categorized as low performance, and athletes with adjusted FMS™ composite scores below 12 categorized as low performance. Scores of 2 or above and 12 or above were considered high performances for the DS test and adjusted FMS™ composite score respectively, and therefore low risk for movement dysfunction and potentially, injury.
Results:
Individuals categorized as low performance as a result of the DS test had lower adjusted FMS™ composite scores (p < 0.001). DS scores were positively correlated with adjusted FMS™ composite scores (ρ = 0.50, p < 0.001). Binomial logistic regression identified an odds ratio of 3.56 (95% CI: 1.24, 10.23, p = 0.018) between DS and FMS™ performance categories.
Conclusions:
Performance on the DS test may predict performance on the FMS™ and help identify individuals who require further musculoskeletal assessment. Further research is needed to determine if DS performance can predict asymmetries during the FMS™.
Level of evidence:
Level 3.
The aim of this study was to assess movement patterns by using Functional Movement Screen in three categories of Slovak women’s national football teams during two occasions interpressed with one year. The reason for this was to answer the questions: 1. if there is a tendency to perform better in the screen with respect to age category, and 2. if the players who did the screen more times and recieve recommendations, perform better after a year, irrespective to age category. Our results showed that every category achieved significant improvements (p
Musculoskeletal injury is the most common reason that soldiers are medically not ready to deploy. Understanding intrinsic risk factors that may place an elite soldier at risk of musculoskeletal injury may be beneficial in preventing musculoskeletal injury and maintaining operational military readiness. Findings from this population may also be useful as hypothesis-generating work for particular civilian settings such as law enforcement officers (SWAT teams), firefighters (smoke jumpers), or others in physically demanding professions.
The purposes of this study were (1) to examine whether using baseline measures of self-report and physical performance can identify musculoskeletal injury risk; and (2) to determine whether a combination of predictors would enhance the accuracy for determining future musculoskeletal injury risk in US Army Rangers.
Our study was a planned secondary analysis from a prospective cohort examining how baseline factors predict musculoskeletal injury. Baseline predictors associated with musculoskeletal injury were collected using surveys and physical performance measures. Survey data included demographic variables, injury history, and biopsychosocial questions. Physical performance measures included ankle dorsiflexion, Functional Movement Screen, lower and upper quarter Y-balance test, hop testing, pain provocation, and the Army Physical Fitness Test (consisting of a 2-mile run and 2 minutes of sit-ups and push-ups). A total of 320 Rangers were invited to enroll and 211 participated (66%). Occurrence of musculoskeletal injury was tracked for 1 year using monthly injury surveillance surveys, medical record reviews, and a query of the Department of Defense healthcare utilization database. Injury surveillance data were available on 100% of the subjects. Receiver operator characteristic curves and accuracy statistics were calculated to identify predictors of interest. A logistic regression equation was then calculated to find the most pertinent set of predictors. Of the 188 Rangers (age, 23.3 ± 3.7 years; body mass index, 26.0 ± 2.4 kg/m(2)) remaining in the cohort, 85 (45.2%) sustained a musculoskeletal injury of interest.
Smoking, prior surgery, recurrent prior musculoskeletal injury, limited-duty days in the prior year for musculoskeletal injury, asymmetrical ankle dorsiflexion, pain with Functional Movement Screen clearing tests, and decreased performance on the 2-mile run and 2-minute sit-up test were associated with increased injury risk. Presenting with one or fewer predictors resulted in a sensitivity of 0.90 (95% confidence interval [CI], 0.83-0.95), and having three or more predictors resulted in a specificity of 0.98 (95% CI, 0.93-0.99). The combined factors that contribute to the final multivariable logistic regression equation yielded an odds ratio of 4.3 (95% CI, 2.0-9.2), relative risk of 1.9 (95% CI, 1.4-2.6), and an area under the curve of 0.64.
Multiple factors (musculoskeletal injury history, smoking, pain provocation, movement tests, and lower scores on physical performance measures) were associated with individuals at risk for musculoskeletal injury. The summation of the number of risk factors produced a highly sensitive (one or less factor) and specific (three or more factors) model that could potentially be used to effectively identify and intervene in those persons with elevated risk for musculoskeletal injury. Future research should establish if screening and intervening can improve musculoskeletal health and if our findings among US Army Rangers translate to other occupations or athletes.
Level II, prognostic study.
Background:
The risk of all-cause injury and concussion associated with football is significant. The National Football League (NFL) has implemented changes to increase player safety warranting investigation into the incidence and patterns of injury.
Purpose:
To document the incidence and patterns of all-cause injury and concussions in the NFL.
Study design:
Descriptive epidemiology study.
Methods:
Injury data were collected prospectively from official NFL injury reports over 2 regular seasons from 2012 to 2014, with identification of injury incidence rates and patterns. Concussion rate ratios were calculated using previously reported NFL rates.
Results:
A total of 4284 injuries were identified, including 301 concussions. The all-cause injury rate was 395.8 per 1000 athletes at risk (AAR) and concussion incidence was 27.8 per 1000 AAR. Only 2.3% of team games were injury free. Wide receivers, tight ends, and defensive backs had the highest incidence of injury and concussion. Concussion incidence was 1.61-fold higher in 2012 to 2014 compared with 2002 to 2007. The knee was injured most frequently, followed by the ankle, hamstring, shoulder, and head.
Conclusion:
The incidence of all-cause injury and concussion in the NFL is significant. Concussion injury rates are higher than previous reports, potentially reflecting an improvement in recognition and awareness. Injury prevention efforts should continue to reduce the prevalence of injury associated with football.
The purpose of this study was to investigate whether the functional movement screen (FMS) could predict running injuries in competitive runners. Eighty-four competitive male runners (average age = 20.0 ± 1.1 years) participated. Each subject performed the FMS, which consisted of 7 movement tests (each score range: 0-3, total score range: 0-21), during the pre-season. The incidence of running injuries (time lost due to injury ≤4 weeks) was investigated through a follow-up survey during the 6-month season. Mann-Whitney U tests were used to investigate which movement tests were significantly associated with running injuries. The receiver-operator characteristic (ROC) analysis was used to determine the cut-off. The mean FMS composite score was 14.1 ± 2.3. The ROC analysis determined the cut-off at 14/15 (sensitivity = 0.73, specificity = 0.54), suggesting that the composite score had a low predictability for running injuries. However, the total score (0-6) from the deep squat (DS) and active straight leg raise (ASLR) tests (DS & ASLR), which were significant with the U test, had relatively high predictability at the cut-off of 3/4 (sensitivity = 0.73, specificity = 0.74). Furthermore, the multivariate logistic regression analysis revealed that the DS & ASLR scores of ≤3 significantly influenced the incidence of running injuries after adjusting for subjects' characteristics (OR = 9.7, 95%CI [2.1 to 44.4]). Thus, the current study identified the DS & ASLR score as a more effective method than the composite score to screen the risk of running injuries in competitive male runners.
Functional movement insufficiencies may place an individual at increased risk of injury. The Functional Movement Screen (FMS) is used to identify movement deviations. Limited research has been conducted to verify the predictive value of the FMS test to identify injury risk. Our purpose was to investigate the pre-dictive usefulness of the FMS. FMS scores of 144 National Collegiate Athletic Association Division I football athletes were obtained during preseason. Participants were tracked prospectively over the course of a single season and all sport-related injuries were evaluated, documented, and tracked by an athletic trainer. A cutoff score was determined using a receiver operator characteristic curve. A maximized odds ratio of 1.425 (95% confidence interval: .6-3.2) and a positive likelihood ratio of 1.154 were found for individuals that scored a 17 or below on the FMS. Our results are contrary to previous research and indicate that the FMS is not useful for predicting musculoskeletal injury risk.
This study aimed to 1) assess the reliability of the FMS protocol and 2) to establish changes in both FMS and tests of physical performance throughout a season. The reliability of the FMS components (12 in total) was assessed via a non-parametric statistical approach, based on two trials, separated by one week. Score on the FMS, strength (3 RM full-squat, 1 RM bench press), running speed (10 & 40 m) and jump height of 12 elite male under-19 rugby league players was monitored at pre-, mid- and late-season periods. There was no bias (P > 0.05) found between trials for the FMS, with the majority of components reaching 100% 'perfect agreement', reflecting the good reliability of the FMS tool. There were no effects (P > 0.05) of season stage on any of the FMS components; however, an improvement (P < 0.05) between the pre- and both mid- and late-season periods was apparent in every component of fitness, such as 1 RM bench-press (112.92 +/- 24.54 kg; 125.83 +/- 21.41 kg; 125.98 +/- 24.48 kg) and 40 m sprint time (5.69 +/- 0.35 s; 5.62 +/- 0.31 s; 5.64 +/- 0.27 s). Our findings demonstrate that the FMS can be reliably administered to elite rugby league players but will not change in accordance with physical performance across a competitive season. Our findings should not necessarily deter practitioners from using the FMS but begin to question the specific qualities that are being assessed through its administration. Copyright (C) 2015 by the National Strength & Conditioning Association.
Objectives
(1) Describe performance on the Functional Movement Screen™ (FMS™) by reporting the proportion of adolescents with a score of ≤14 and the frequency of asymmetries in cross-sectional sample; (2) explore associations between FMS™ to age and body mass, and explore the construct validity of the FMS™ against common postural stability measures; (3) examine the inter-rater and test-retest reliability of the FMS™ in adolescents.
Design
Cross-sectional.
Setting
Field-setting.
Participants
94 male high-school athletes.
Main Outcome Measure
The FMS™, YBT, BESS.
Results
The median FMS™ composite score was 16 (9–21), 33% of participants scored below the suggested injury risk cutoff composite score of ≤14, and 62.8% had at least one asymmetry. No relationship was observed between the FMS™ to common static/dynamic balance tests. The inter-rater reliability of the FMS™ composite score suggested good reliability (ICC = 0.88, CI 95%:0.77, 0.94) and test-retest reliability for FMS™ composite scores was good with ICC = 0.83 (CI 95%:0.56, 0.95).
Conclusions
FMS™ results should be interpreted cautiously with attention to the asymmetries identified during the screen, regardless of composite score. The lack of relationship between the FMS™ and other balance measures supports the notion that multiple screening tests should be used in order to provide a comprehensive picture of the adolescent athlete.
Purpose: despite being commonly used, the interaction between Functional Movement Screen (FMS™) score and injury in any elite football population has not been studied. The aim of the present study was to investigate the relationship between FMS™ score and non-contact injury among elite youth players from a Premier League football academy.
Materials and methods: eighty-four players were screened during the pre-season period and non-contact injuries recorded prospectively for the entirety of the 2013/14 football season. Logistic regression analysis was utilized to explore the relationships between the individual sub-tests of the FMS™ and injury. Receiver operating characteristic (ROC) curves were used to assess the predictive value of the FMS™ composite score.
Results: logistic regression revealed no relationships between score achieved on the individual sub-tests and injury. ROC curves indicated poor predictive ability of the composite score. Players scoring below the identified cut-off values (≤14 or ≤15 depending on injury type considered) were 0.66 (95%CI: 0.40-1.10), 0.70 (95%CI: 0.32-1.57) and 1.52 (95%CI: 0.50-4.61) times as likely to suffer ‘any’, ‘overuse’ and ‘severe’ injuries respectively than those who scored above the identified cut-off values.
Conclusions: there was no relationship between FMS™ score and injury. It was unable to predict any non-contact injury among English Premier League youth academy players.
Practical implications: The present findings suggest that the FMS™ should not be used for risk stratification among young elite soccer players since the composite score was unrelated to injury likelihood. However, the FMS™ may be useful in other ways. For example, it may provide useful information to applied practitioners when designing strength-training programs for groups of players they are unfamiliar with, as is often the case at the start of a new season.
Aim:
This paper aims to systematically review studies investigating the strength of association between FMS composite scores and subsequent risk of injury, taking into account both methodological quality and clinical and methodological diversity.
Design:
Systematic review with meta-analysis.
Data sources:
A systematic search of electronic databases was conducted for the period between their inception and 3 March 2016 using PubMed, Medline, Google Scholar, Scopus, Academic Search Complete, AMED (Allied and Complementary Medicine Database), CINAHL (Cumulative Index to Nursing and Allied Health Literature), Health Source and SPORTDiscus.
Eligibility criteria for selecting studies:
Inclusion criteria: (1) English language, (2) observational prospective cohort design, (3) original and peer-reviewed data, (4) composite FMS score, used to define exposure and non-exposure groups and (5) musculoskeletal injury, reported as the outcome.
Exclusion criteria:
(1) data reported in conference abstracts or non-peer-reviewed literature, including theses, and (2) studies employing cross-sectional or retrospective study designs.
Results:
24 studies were appraised using the Quality of Cohort Studies assessment tool. In male military personnel, there was 'strong' evidence that the strength of association between FMS composite score (cut-point ?14/21) and subsequent injury was 'small' (pooled risk ratio=1.47, 95% CI 1.22 to 1.77, p<0.0001, I(2)=57%). There was 'moderate' evidence to recommend against the use of FMS composite score as an injury prediction test in football (soccer). For other populations (including American football, college athletes, basketball, ice hockey, running, police and firefighters), the evidence was 'limited' or 'conflicting'.
Conclusion:
The strength of association between FMS composite scores and subsequent injury does not support its use as an injury prediction tool.
Trial registration number:
PROSPERO registration number CRD42015025575.
The purpose of this study was to determine the relationship between Functional Movement Screen™ (FMS) score and the risk of time-loss injury in experienced male rugby union athletes. A secondary purpose was to determine the relationship between FMS-determined asymmetries and the risk of time-loss injury in these athletes.FMS scores were collected from male rugby union athletes (n=73) during preseason and half-way through one eight-month season. Time-loss injury data were collected throughout the full season. A receiver-operator characteristic curve was created for each half of the season to identify FMS composite and asymmetry cut-off scores associated with increased likelihood of injury and determined odds ratios, sensitivity and specificity in evaluating FMS as a predictor of injury risk.Odds ratio analyses revealed that when compared to those scoring >14, athletes with FMS ≤14 were 10.42 times more likely (95%CI: 1.28-84.75, p=0.007) to have sustained injury the first half of the season and 4.97 times (95%CI: 1.02-24.19, p=0.029) more likely in the second half of the season. The presence of asymmetries was not associated with increased likelihood of injury.Experienced male rugby union athletes with FMS composite scores ≤14 are significantly more likely to sustain time-loss injury in a competitive season compared to those scoring >14. The quality of fundamental movement, as assessed by the FMS, is predictive of time-loss injury risk in experienced rugby union athletes and should be considered an important preseason assessment tool used by strength and conditioning and medical professionals in this sport with inherently high injury rates.
This study assessed if the Functional Movement Screen (FMS™) can accurately predict non-contact injury in adult soccer players when normalizing non-contact injury occurrence against match exposure levels. Senior male players (n=89) from five League of Ireland semi-professional clubs participated in the study (mean age=23.2 ± 4.4 years; mean height=179.5 ± 6.6 cm; mean body mass=77.5 ± 7.8 kg). Participants performed the FMS™ during preseason and their injury occurrence rates and match minutes were tracked throughout one season. In total, 66 non-contact injuries were recorded. No significant difference was found in FMS™ composite scores between players receiving non-contact injuries and players not suffering a non-contact injury (p=0.96). There was no significant difference in exposure-normalized non-contact injury incidence between those scoring 14 or below and those scoring above 14 on the FMS™ (0.36 vs. 0.29 non-contact injuries per player per 1000 match minutes). Players scoring 14 or below on the FMS™ had an odds ratio of 0.63 (p=0.45; CI 95%=0.19- 2.07) of receiving a non contact injury. Despite previous research showing links between low FMS™ composite scores and subsequent injury, these results suggest the FMS™ cannot accurately predict a male soccer player's likelihood of receiving a non-contact injury and that a lower FMS™ composite score does not significantly increase their non-contact injury incidence rate per 1000 match minutes. Caution should therefore be used when employing the FMS™ as a predictor of non-contact injury, and pain prevalence during the FMS™, previous injuries, and training/match exposure levels should also be taken into account.
Background
Identification of risk factors for lower extremity (LE) injury in sport and military/first-responder occupations is required to inform injury prevention strategies.
Objective
To determine if poor movement quality is associated with LE injury in sport and military/first-responder occupations.
Materials and methods
5 electronic databases were systematically searched. Studies selected included original data; analytic design; movement quality outcome (qualitative rating of functional compensation, asymmetry, impairment or efficiency of movement control); LE injury sustained with sport or military/first-responder occupation. The Preferred Reporting Items for Systematic reviews and Meta-Analyses (PRISMA) guidelines were followed. 2 independent authors assessed the quality (Downs and Black (DB) criteria) and level of evidence (Oxford Centre of Evidence-Based Medicine model).
Results
Of 4361 potential studies, 17 were included. The majority were low-quality cohort studies (level 4 evidence). Median DB score was 11/33 (range 3–15). Heterogeneity in methodology and injury definition precluded meta-analyses. The Functional Movement Screen was the most common outcome investigated (15/17 studies). 4 studies considered inter-relationships between risk factors, 7 reported diagnostic accuracy and none tested an intervention programme targeting individuals identified as high risk. There is inconsistent evidence that poor movement quality is associated with increased risk of LE injury in sport and military/first-responder occupations.
Conclusions
Future research should focus on high-quality cohort studies to identify the most relevant movement quality outcomes for predicting injury risk followed by developing and evaluating preparticipation screening and LE injury prevention programmes through high-quality randomised controlled trials targeting individuals at greater risk of injury based on screening tests with validated test properties.
Aim. Functional motor training is intended to lower the risk of sustaining an injury. The aim of the study was to conduct a functional analysis and assessment of track and ield male athletes. Methods. The sample group consisted of 90 participants divided into three groups: sprinters (sprint, N.=32), middledistance runners (middle, N.=28), and athletes who did not practice running (control, N.=30). The study was conducted in high-intensity training periods, during which the athletes displayed a high level of sports performance. For the purposes of the functional assessment, the functional movement screen (FMS) was used. Results. A mean test score equaled 16.53 in the sprint group and 16.96 in the middle group. These groups scored signiicantly higher (P<0.001) than non-athletes, which suggests that the risk of sustaining an injury due to functional movement deicits amounts to approximately 25%. Athletes scored signiicantly higher than non-athletes (13.32; P<0.001). In none of the groups it resulted the existence of statistically signiicant relationships (P>0.05) between a score achieved in the FMS test and the variables age, height, body mass, and athletic experience demonstrated. Both groups scored the lowest in the rotary stability test. Conclusion. The results corroborate the beneicial impact of athletic training on functional itness, which warrants the elements of such training to be introduced to general physical itness training as part of injury prevention. FMS may be an effective tool for screen testing in sport.
Abnormal fundamental movement patterns and upper quarter dynamic balance are proposed mechanisms affecting athletic performance and injury risk. There are few studies investigating functional movement and closed chain upper extremity dynamic stability in swimmers. The purpose of this study was to determine differences in fundamental movement competency and closed chain upper extremity dynamic balance, utilizing the Functional Movement Screen (FMS) and Upper Quarter Y-Balance Test (YBT-UQ), of high school (HS; n=70) and collegiate (COL; n=70) swimmers. Variables included the individual movement tests on the FMS, and the average normalized reach (%LL) for each direction, with the YBT-UQ. Statistical analysis was completed utilizing a chi-square for the independent test scores on the FMS while independent samples t-test to examine performance on the YBT-UQ (p<0.05). HS swimmers exhibited a statistically significant greater percentage of below average performance (score of 0 or 1) on the following FMS tests: lunge (HS:22.9%, COL:4.3%), hurdle step (HS:31.4%, COL:7.1%) and push up (HS:61.4 %, COL:31.4%). Furthermore, COL males performed worse in the lunge (Male 9%, Female 0%), while COL females had poorer efficiency in the pushup (Male: 17.6%, Female 44%). Significant effects of competition level and sex were observed in YBT-UQ medial reach (HS: Female 92.06, Male 101.63, COL: Female 101.3, Male 101.5 %LL). Individual fundamental movement patterns that involved lumbopelvic neuromuscular control differed between HS and COL swimmers. General upper extremity dynamic balance differed between competition levels. These data may be helpful in understanding injury and performance based normative data for participation and return to swimming.
Context:
The Functional Movement Screen (FMS) has been found to be a valid pre-participation screening tool in the prediction of injury among various athletes in different sports. The validity thereof in the prediction of injury among adolescent cricketers is yet to be established.
Objective:
To determine if a pre-season FMS total score is a valid predictor of in-season injury among adolescent pace bowlers.
Design:
Prospective observational quantitative study.
Setting:
Bowlers performed the FMS before the start of the season. Injury incidence was monitored monthly throughout the season. The student t-test and Fisher's exact test were used to compare the FMS scores of the injured and non-injured bowlers as well as the injured and non-injured bowlers who scored ≤ 14.
Participants:
27 injury free, male adolescent pace bowlers.
Main outcome measures:
The FMS (scoring criteria and score sheet) and standardised self-administered injury questionnaire.
Results:
There was no difference between the non-injured group (16.55±2.57) and the injured (16.1±2.07) group in terms of FMS scores. There was no significant difference between injured and non-injured bowlers who scored ≤14. A total FMS score of 14 does not provide the sensitivity needed to assess injury risk among adolescent pace bowlers and no other accurate cut-off score could be calculated.
Conclusion:
Pre-season observed total FMS score is a poor predictor of in-season injury among adolescent pace bowlers. Further research should be conducted to determine if a specific FMS test will be a more valid predictor of injury.
Background Hurling and Gaelic Football are amateur team field sports which are native to Ireland. Due to the speed, player to player contact and multidirectional nature of the sports, injury to players is inevitable.
Objective Determine normative values for the Functional Movement Screen™ (FMS) in Elite and Sub-Elite male Gaelic Football and Hurling players.
Design A cross sectional study of functional movement in Gaelic games. Players were video recorded completing the FMS™ and scored post-test.
Setting Testing of Elite and Sub-Elite Gaelic players in a gym and university biomechanics laboratory.
Participants A total of 62 players (injury-free) were included. This consisted of 41 Hurling, and 21 Gaelic Football players. 30 of these participants were deemed Elite and 32 were deemed Sub-Elite. The mean age of the sample was 22.15±3.02 years.
Risk factor assessment The FMS™ is a screening method which is proposed to identify potential injury causing deficits in the human body. There are 7 specific components to the test (Deep Squat, Hurdle Step, In-line Lunge, Shoulder Mobility, Active Straight Leg Raise, Trunk Stability Push Up, Rotary Stability), accompanied by 3 clearing tests (Spinal flexion, Spinal extension, Shoulder internal rotation with flexion). Each is scored out of 3 for a maximum of 21. The clearing tests are not scored.
Main outcome measurement Functional Movement Screen™ (FMS).
Results The FMS mean score for the sample was 15.56±1.456. The Elite group (15.8±1.58) scored higher than the Sub-Elite group (15.34±1.31), but there was no significant difference between groups.
Conclusions This study provides normative reference values for Gaelic Players. Elite Gaelic Players perform no better than a young, active population in the FMS indicating a potential problem with the FMS as a measure. The ability of the FMS to detect injury risk is not well supported and clinicians should be cautious using it as such.
Background Little is known about the impact of functional muscle restrictions on the level of functional performance among female soccer players.
Objective The aim of this study was to analyze: a) abnormalities in the length of lower limb muscles, b) the correctness of movement patterns, and c) the impact of functional limitations of muscles on the correctness of fundamental movement patterns in a group of female soccer players, in relation to their skill level.
Design Cross Sectional Study.
Setting Elite and sub-elite division.
Participants 21 female soccer players from Polish Ekstraklasa (PE) and 22 players from the 1st Division (1D).
Interventions All participants were tested for lower limb muscle length restrictions and level of fundamental movement skills (with the Fundamental Movement ScreenTM test). Chi-square test was used for categorical unrelated variables. Differences between groups in absolute point values were analyzed using the non-parametric Mann-Whitney U test. Statistical significance was set at P<.05.
Main outcome measurements Lower leg muscle length, FMSTM score.
Results Significantly higher number of abnormal rectus femoris length in the 1D (P=.0433) and abnormal hamstring results (P=.0006) in the PE was observed. PE scored higher in the trunk rotational stability test (P=.0008), the 1D players scored higher in the deep squat (P=.0220), in-line lunge (P=.0042) and active straight leg raise (P=.0125) tests. The results suggest that there are different functional reasons affecting point values obtained in the FMSTM tests in both groups.
Conclusions The differences in the rectus femoris and hamstring muscle flexibility observed between female soccer players with different levels of training may result from a long-term impact of soccer training on the muscle-tendon system and articular structures. Different causes of abnormalities in fundamental movement patterns in both groups suggest the need for tailoring prevention programs to the level of sport skills represented by the players.
Background:
The Functional Movement Screen (FMS) is utilized by professional and collegiate sports teams and the military for the prevention of musculoskeletal injuries.
Hypothesis:
The FMS demonstrates good interrater and intrarater reliability and validity and has predictive value for musculoskeletal injuries.
Study design:
Systematic review and meta-analysis.
Methods:
A systematic review and meta-analysis were conducted using a computerized search of the electronic databases MEDLINE and ScienceDirect in adherence with the Preferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines. Extracted relevant data from each included study were recorded on a standardized form. The Cochran Q statistic was utilized to evaluate study heterogeneity. Pooled quantitative synthesis was performed to measure the intraclass correlation coefficient (ICC) for interrater and intrarater reliability, along with 95% CIs, and odds ratios with 95% CIs for the injury predictive value for a score of ≤14.
Results:
Eleven studies for reliability, 5 studies for validity, and 9 studies for the injury predictive value were identified that met inclusion and exclusion criteria; of these, 6 studies for reliability and 9 studies for the injury predictive value were pooled for quantitative synthesis. The ICC for intrarater reliability was 0.81 (95% CI, 0.69-0.92) and for interrater reliability was 0.81 (95% CI, 0.70-0.92). The odds of sustaining an injury were 2.74 times with an FMS score of ≤14 (95% CI, 1.70-4.43). Studies for validity demonstrated flaws in both internal and external validity of the FMS.
Conclusion:
The FMS has excellent interrater and intrarater reliability. Participants with composite scores of ≤14 had a significantly higher likelihood of an injury compared with those with higher scores, demonstrating the injury predictive value of the test. Significant concerns remain regarding the validity of the FMS.
The Functional Movement Screen(TM) (FMS) is a screening tool used to evaluate functional movement quality and subsequent musculoskeletal injury risk. Despite recent research on the factorial validity of the FMS, no confirmatory factor analysis (CFA) has been conducted to examine measurement invariance across sex among student-athletes. The primary purpose of the current study was to confirm the factor structure of the FMS measurement model in a collegiate student-athlete population. It was hypothesized that the one-factor model would demonstrate better model fit than the recently proposed two-factor model. The secondary purpose of the study was to examine FMS measurement invariance across sex using the previously identified measurement model. It was hypothesized that FMS measurement invariance would hold across sex. Male (n = 88) and female (n = 88) collegiate student-athletes completed FMS screening during the off-season. Factorial validity was examined using CFA procedures and model parameters were estimated using maximum likelihood (ML) estimation. Measurement invariance was examined via comparisons of fit indices between hierarchically constrained models. Results revealed support for both the one- and two-factor models; however, the two-factor model failed to fit the data significantly better than the one-factor model. Results also indicated that measurement invariance did not hold across sex, indicating that the FMS sum score construct is not measured equivalently in males and females. Collectively, results provide evidence for the use of the unidimensional FMS sum score among collegiate student-athletes, yet prompt caution as it relates to the evaluation of sex differences in sum or movement pattern scores. Copyright (C) 2016 by the National Strength & Conditioning Association.
Objective:
To define the relationship between Functional Movement Screen (FMS) scores and hop performance, hip strength, and knee strength in collegiate football players.
Design:
Cross-sectional cohort.
Participants:
Freshmen of a Division I collegiate American football team (n = 59).
Main outcome measures:
The athletes performed the FMS, and also a variety of hop tests, isokinetic knee strength, and isometric hip strength tasks. We recorded total FMS score, peak strength, and hop performance, and we calculated asymmetries between legs on the different tasks. Spearman correlation coefficients quantified the relationships between these measures, and χ analyses compared the number of athletes with asymmetries on the different tasks.
Results:
We observed significant correlations (r = 0.38-0.56, P ≤ 0.02) between FMS scores and hop distance but not between FMS scores and hip or knee strength (all P ≥ 0.21). The amount of asymmetry on the FMS test was significantly correlated to the amount of asymmetry on the timed 6-m hop (r = 0.44, P < 0.01) but not to hip or knee strength asymmetries between limbs (all P ≥ 0.34).
Conclusions:
Functional Movement Screen score was positively correlated to hop distance, and limb asymmetry in FMS tasks was correlated to limb asymmetry in 6-m hop time in football players. No significant correlations were observed between FMS score and hip and knee strength or between FMS asymmetry and asymmetries in hip and knee strength between limbs. These results indicate that a simple hop for distance test may be a time-efficient and cost-efficient alternative to FMS testing in athletes and that functional asymmetries between limbs do not coincide with strength asymmetries.
Context:
Functional Movement Screen (FMS) scores of ≤14 have been used to predict injury in athletic populations. Movement asymmetries and poor-quality movement patterns in other functional tests have been shown to predict musculoskeletal injury (MSI). Therefore, movement asymmetry or poor-quality movement patterns on the FMS may have more utility in predicting MSI than the composite score.
Objective:
To determine if an asymmetry or score of 1 on an individual FMS test would predict MSI in collegiate athletes.
Design:
Cohort study.
Setting:
National Collegiate Athletic Association Division II university athletic program.
Patients or other participants:
A total of 84 Division II rowers, volleyball players, and soccer players (men: n = 20, age = 20.4 ± 1.3 years, height = 1.77 ± 0.04 m, mass = 73.5 ± 4.8 kg; women: n = 64, age = 19.1 ± 1.2 years, height = 1.69 ± 0.09 m, mass = 64.8 ± 9.4 kg).
Main outcome measure(s):
The FMS was administered during preseason preparticipation examinations. Injury-incidence data were tracked for an academic year by each team's certified athletic trainer via computer software. An MSI was defined as physical damage to the body secondary to athletic activity or an event for which the athlete sought medical care. Composite FMS scores were categorized as low (≤14) or high (>14). Pearson χ(2) analyses were used to determine if MSI could be predicted by the composite FMS score or an asymmetry or score of 1 on an individual FMS test (P < .05).
Results:
Athletes with FMS scores of ≤14 were not more likely to sustain an injury than those with higher scores (relative risk = 0.68, 95% confidence interval = 0.39, 1.19; P = .15). However, athletes with an asymmetry or individual score of 1 were 2.73 times more likely to sustain an injury than those without (relative risk = 2.73, 95% confidence interval = 1.36, 5.4; P = .001).
Conclusions:
Asymmetry or a low FMS individual test score was a better predictor of MSI than the composite FMS score.
Objective:
To synthesize the literature and perform a meta-analysis for both the interrater and intrarater reliability of the FMS™.
Methods:
Academic Search Complete, CINAHL, Medline and SportsDiscus databases were systematically searched from inception to March 2015. Studies were included if the primary purpose was to determine the interrater or intrarater reliability of the FMS™, assessed and scored all 7-items using the standard scoring criteria, provided a composite score and employed intraclass correlation coefficients (ICCs). Studies were excluded if reliability was not the primary aim, participants were injured at data collection, or a modified FMS™ or scoring system was utilized.
Results:
Seven papers were included; 6 assessing interrater and 6 assessing intrarater reliability. There was moderate evidence in good interrater reliability with a summary ICC of 0.843 (95% CI = 0.640, 0.936; Q7 = 84.915, p < 0.0001). There was moderate evidence in good intrarater reliability with a summary ICC of 0.869 (95% CI = 0.785, 0.921; Q12 = 60.763, p < 0.0001).
Conclusion:
There was moderate evidence for both forms of reliability. The sensitivity assessments revealed this interpretation is stable and not influenced by any one study. Overall, the FMS™ is a reliable tool for clinical practice.
The functional movement screen (FMS) is a pre-participation screening tool comprising 7 individual tests for which both individual scores and an overall score are given. The FMS displays both interrater and intrarater reliability but has been challenged on the basis of a lack of validity in several respects. The FMS seems to have some degree of predictive ability for identifying athletes who are at an increased risk of injury. However, a poor score on the FMS does not preclude athletes from competing at the highest level nor does it differentiate between athletes of differing abilities. Copyright © National Strength and Conditioning Association.
Objectives:
The effect of maturity on Functional Movement Screen (FMS) scores in elite, adolescent soccer players was examined.
Design:
A cross-sectional observational study was completed.
Methods:
Participants were 1163 male English Football League soccer players (age 8-18 years). Players were mid-foundation phase (MF) (U9); late foundation phase (LF) (U10 and U11); early youth development phase (EYD) (U12 and U13); mid-youth development (MYD) phase (U14-U15); Late Youth Development Phase (LYD) (U16) and early professional development phase (EPD) (U18). Age from peak height velocity was estimated and players were categorized as pre- or post-peak height velocity (PHV). To analyse where differences in FMStotal score existed we separated the screen into FMSmove (3 movement tests); FMSflex (2 mobility tests) and FMSstab (2 stability tests).
Results:
FMStotal median score ranged from 11 at MF to 14 for EPD. There was a substantial increase (10%) in those able to achieve a score of ≥14 on FMStotal in those who were post-PHV compared to pre-PHV. This was explained by a substantial increase in those achieving a score of ≥4 on FMSstab (21%). There was a substantial increase in the proportion of players who achieved the FMStotal threshold of ≥14 with an increase of 47.5 (41.4-53.6)% from the MF phase to the EPD phase due to improvements in FMSmove and FMSstab.
Conclusions:
PHV and maturity have substantial effects on FMS performance. FMS assessment appears to be invalid for very young players. Findings are relevant to those analyzing movement in soccer players.
Background: The Functional Movement Screen (FMS) is designed to detect deficits and asymmetries in the movement patterns of athletes that predispose them to injury. This tool has been found to be predictive of injury in select populations but has not been studied in professional basketball players. Our hypothesis was that injured players have lower FMS scores than noninjured players, and an FMS score of 14 is predictive of injury in this population. Methods: Preseason FMS testing was performed on all members of a single team in the National Basketball Association (NBA) over the course of four seasons. Injury was defined as a musculoskeletal condition that prevented an athlete from participating in practices or games for at least 1 wk. The data were retrospectively analyzed to determine the ability of the FMS to accurately predict future injury over the course of a season. Results: A total of 34 players met inclusion criteria, of whom 17 went on to sustain injuries and 17 did not. The mean FMS score for all subjects was 13.2 (minimum-maximum: 7-19; standard deviation=2.6). Injured players did not have a significantly lower mean FMS score than noninjured players (P=0.16). A positive correlation existed between the hurdle test and injury (P=0.004); however, no other subscore of the FMS correlated with injury. Conclusions: While the FMS is a valuable tool for identifying deficits and asymmetries of movement in some athletic activities, it is not predictive of injury in male professional basketball players.
Context:
The Functional Movement Screen (FMS) is an assessment tool for quality of human movement. Research reports a significant difference between FMS scores of subjects who later experienced injury and those who remain uninjured.
Objective:
To systematically review literature related to predictive validity of the FMS. From the aggregated data, a meta-analysis was conducted to determine the prognostic accuracy of the FMS.
Data sources:
PubMed, Ebscohost, Google Scholar, and the Cochrane Review databases were searched between 1998 and February 20, 2014.
Study selection:
Identified studies were reviewed in full detail to validate inclusion criteria. Seven of the 11 identified studies were included. Articles were reviewed for inclusion criteria, then bias assessment and critical analysis were conducted.
Study design:
Systematic review and meta-analysis.
Level of evidence:
Level 3.
Data extraction:
Extracted data included the following: study type, methodology, study subjects, number of subjects, injury classification definition, FMS cut score, sensitivity, specificity, odds ratios, likelihood ratios (LR), predictive values, receiver operator characteristic (ROC) analysis, and area under the curve (AUC).
Results:
Overall bias for the included 7 studies was low with respect to patient selection. Quality assessment scored 1 study 5 of a possible 7, 2 studies were scored 3 of 7, and 4 studies were scored 2 of 7. The meta-analysis indicated the FMS was more specific (85.7%) than sensitive (24.7%), with a positive predictive value of 42.8% and a negative predictive value of 72.5%. The area under the curve was 0.587 (LR+, 1.7; LR-, 0.87; 95% CI, 0.6-6.1) and the effect size was 0.68.
Conclusion:
Based on analysis of the current literature, findings do not support the predictive validity of the FMS. Methodological and statistical limitations identified threaten the ability of the research to determine the predictive validity of FMS.
Several physical assessment protocols to identify intrinsic risk factors for injury aetiology related to movement quality have been described. The Functional Movement Screen (FMS) is a standardised, field-expedient test battery intended to assess movement quality and has been used clinically in preparticipation screening and in sports injury research.
To critically appraise and summarise research investigating the reliability of scores obtained using the FMS battery.
Systematic literature review.
Systematic search of Google Scholar, Scopus (including ScienceDirect and PubMed), EBSCO (including Academic Search Complete, AMED, CINAHL, Health Source: Nursing/Academic Edition), MEDLINE and SPORTDiscus. Studies meeting eligibility criteria were assessed by 2 reviewers for risk of bias using the Quality Appraisal of Reliability Studies checklist. Overall quality of evidence was determined using van Tulder's levels of evidence approach.
12 studies were appraised. Overall, there was a 'moderate' level of evidence in favour of 'acceptable' (intraclass correlation coefficient ≥0.6) inter-rater and intra-rater reliability for composite scores derived from live scoring. For inter-rater reliability of composite scores derived from video recordings there was 'conflicting' evidence, and 'limited' evidence for intra-rater reliability. For inter-rater reliability based on live scoring of individual subtests there was 'moderate' evidence of 'acceptable' reliability (κ≥0.4) for 4 subtests (Deep Squat, Shoulder Mobility, Active Straight-leg Raise, Trunk Stability Push-up) and 'conflicting' evidence for the remaining 3 (Hurdle Step, In-line Lunge, Rotary Stability).
This review found 'moderate' evidence that raters can achieve acceptable levels of inter-rater and intra-rater reliability of composite FMS scores when using live ratings. Overall, there were few high-quality studies, and the quality of several studies was impacted by poor study reporting particularly in relation to rater blinding.
Published by the BMJ Publishing Group Limited. For permission to use (where not already granted under a licence) please go to http://group.bmj.com/group/rights-licensing/permissions.
Context:
Research is limited regarding the effects of injury or surgery history and sex on the Functional Movement Screen (FMS) and Y Balance Test (YBT).
Objective:
To determine if injury or surgery history or sex affected results on the FMS and YBT.
Design:
Cross-sectional study.
Setting:
Athletic training facilities.
Patients or other participants:
A total of 200 National Collegiate Athletic Association Division I female (n = 92; age = 20.0 ± 1.4 years, body mass index = 22.8 ± 3.1 kg/m(2)) and male (n = 108; age = 20.0 ± 1.5 years, body mass index = 27.0 ± 4.6 kg/m(2)) athletes were screened; 170 completed the FMS, and 190 completed the YBT.
Intervention(s):
A self-reported questionnaire identified injury or surgery history and sex. The FMS assessed movement during the patterns of deep squat, hurdle step, in-line lunge, shoulder mobility, impingement-clearing test, straight-leg raise, trunk stability push-up, press-up clearing test, rotary stability, and posterior-rocking clearing test. The YBT assessed balance while participants reached in anterior, posteromedial, and posterolateral directions.
Main outcome measure(s):
The FMS composite score (CS; range, 0-21) and movement pattern score (range, 0-3), the YBT CS (% lower extremity length), and YBT anterior, posteromedial, and posterolateral asymmetry (difference between limbs in centimeters). Independent-samples t tests established differences in mean FMS CS, YBT CS, and YBT asymmetry. The Mann-Whitney U test identified differences in FMS movement patterns.
Results:
We found lower overall FMS CSs for the following injuries or surgeries: hip (injured = 12.7 ± 3.1, uninjured = 14.4 ± 2.3; P = .005), elbow (injured = 12.1 ± 2.8, uninjured = 14.3 ± 2.4; P = .02), and hand (injured = 12.3 ± 2.9, uninjured = 14.3 ± 2.3; P = .006) injuries and shoulder surgery (surgery = 12.0 ± 1.0, no surgery = 14.3 ± 2.4; P < .001). We observed worse FMS movement pattern performance for knee surgery (rotary stability: P = .03), hip injury (deep squat and hurdle: P < .042 for both), hip surgery (hurdle and lunge: P < .01 for both), shoulder injury (shoulder and hand injury: P < .02 for both), and shoulder surgery (shoulder: P < .02). We found better FMS movement pattern performance for trunk/back injury (deep squat: P = .02) and ankle injury (lunge: P = .01). Female athletes performed worse in FMS movement patterns for trunk (P < .001) and rotary (P = .01) stability but better in the lunge (P = .008), shoulder mobility (P < .001), and straight-leg raise (P < .001). Anterior asymmetry was greater for male athletes (P = .02).
Conclusions:
Injury history and sex affected FMS and YBT performance. Researchers should consider adjusting for confounders.
The sport of ice hockey requires coordination of complex skills involving musculoskeletal and physiological abilities while simultaneously exposing players to a high risk for injury. The Functional Movement Screen (FMS) was developed to assess fundamental movement patterns that underlie both sport performance and injury risk. The top one hundred and one elite, junior hockey players from around the world took part in the 2013 NHL Entry Draft Combine (NHL Combine). The FMS was integrated into the comprehensive medical and physiological fitness evaluations at the request of strength and conditioning coaches with affiliations to National Hockey League (NHL) teams. The inclusion of the FMS aimed to help develop strategies that could maximize its utility among elite hockey players and to encourage or inform further research in this field. This study evaluated the outcomes of integrating the FMS into the NHL Combine and identified any links to other medical plus physical and physiological fitness assessment outcomes. These potential associations may provide valuable information to identify elements of future training programs that are individualized to athletes' specific needs. The results of the FMS (total score and number of asymmetries identified) were significantly correlated to; various body composition measures, aerobic and anaerobic fitness, leg power, timing of recent workouts and the presence of lingering injury at the time of the NHL Combine. Although statistically significant correlations were observed, the implications of the FMS assessment outcomes remain difficult to quantify until ongoing assessment of FMS patterns, tracking of injuries and hockey performance are available.
THE FUNCTIONAL MOVEMENT SCREEN (FMS) IS A PRE-PARTICIPATION SCREENING TOOL COMPRISING 7 INDIVIDUAL TESTS FOR WHICH BOTH INDIVIDUAL SCORES AND AN OVERALL SCORE ARE GIVEN. THE FMS DISPLAYS BOTH INTERRATER AND INTRARATER RELIABILITY BUT HAS BEEN CHALLENGED ON THE BASIS OF A LACK OF VALIDITY IN SEVERAL RESPECTS. THE FMS SEEMS TO HAVE SOME DEGREE OF PREDICTIVE ABILITY FOR IDENTIFYING ATHLETES WHO ARE AT AN INCREASED RISK OF INJURY. HOWEVER, A POOR SCORE ON THE FMS DOES NOT PRECLUDE ATHLETES FROM COMPETING AT THE HIGHEST LEVEL NOR DOES IT DIFFERENTIATE BETWEEN ATHLETES OF DIFFERING ABILITIES.