A Review of the Current Literature on the Utility of the Functional Movement Screen as a Screening Tool to Identify Athletesʼ Risk for Injury

2019 ◽  
Vol 41 (5) ◽  
pp. 17-23
Author(s):  
Jerry-Thomas Monaco ◽  
Brad J. Schoenfeld
physioscience ◽  
2021 ◽  
Author(s):  
Simone Schweda ◽  
Daniel Leyhr ◽  
Inga Krauß

Abstract Background Several studies have evaluated the applicability of the Functional Movement Screen (FMS) as a screening tool for injury prediction. However, only few studies investigate gender differences for FMS as a screening tool for female and male college students. Objective To evaluate gender differences in FMS single items and the overall score. In addition, the applicability of FMS as a diagnostic tool for injury prevention of German exercise students will be investigated. Method N = 99 college students performed an FMS at the beginning of the semester. Injuries were recorded for the entire term. Gender differences of FMS single items were assessed using the Mann-Whitney-U-Test. Differences in injury prediction were calculated using logistic regression. If the model was statistically significant, diagnostic accuracy was calculated using receiver operating characteristic (ROC) curves and the area under the curve (AUC). The Youden index was used to identify a cut-off score. 2 × 2 contingency tables, sensitivity and specifity, positive/negative predictive values, and likelihood ratios were assessed. Results There were significant gender differences for Deep Squat, Shoulder Mobility, Trunk Stability Push Up, and Active Straight Leg Raise. The logistic regression showed that the composite score was statistically significant in clarifying the model for females (p = 0.005, RN 2 = 0.14), but not for males (p = 0.18, RN 2 = 0.04). The ROC curve indicated acceptable injury prediction in females (AUC: 0.66, p = 0.02) and poor injury prediction in males (AUC: 0.40, p = 0.19). The cut-off score of ≤ 16 for females resulted in a sensitivity of 63 % and specificity of 54 %. No cut-off score was calculated for males. Conclusion Females performed better on flexibility items, while males scored higher on strength exercises. Results of the study indicate low predictive accuracy. Therefore, no solid recommendation can be made for the use of the FMS as an injury screening tool for either female or male German exercise science students.


2019 ◽  
Vol 14 (2s) ◽  
pp. 18
Author(s):  
Jozef Simenko

<div><p>With the development of screening methods, simple screening tools could commonly be used to assess movement quality in real-world conditions.  One of those methods is the functional movement screen (FMS), that was developed to helps determine the fundamental movement patterns of an individual. FMS test was administered to 9 elite judokas aged 22 ± 4.24 years, height 176.44 ± 7.44 and weight 79.44 ± 15.92 kg. The overall FMS score was 17.56 ± 1.59. No significant asymmetries were noted in the bilateral test. The lowest score was achieved in shoulder mobility 1.89 ± 0.6 which represent and issue that needs to be addressed to prevent the occurrence of injuries. Overall the FMS testing could be a beneficial tool to strength and conditioning coaches in judo, especially in the preseason to assess the functional movement status of judo athletes and to address any issues that could be identified. It represents a fast and affordable screening tool, but it needs to be administered by a qualified assessor. The data of this study could serve as a reference score to other FMS research in judo or other combat sports or martial arts.</p></div>


2017 ◽  
Vol 26 (5) ◽  
pp. 386-395 ◽  
Author(s):  
Candice Martin ◽  
Benita Olivier ◽  
Natalie Benjamin

Context:The Functional Movement Screen (FMS) has been found to be a valid preparticipation 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 preseason 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 noninjured bowlers as well as the injured and noninjured bowlers who scored ≤ 14.Participants:27 injury-free, male, adolescent pace bowlers.Main Outcome Measures:The FMS (scoring criteria and score sheet) and standardized self-administered injury questionnaire.Results:There was no difference between the noninjured 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 noninjured 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:Preseason 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.


2017 ◽  
Vol 26 (5) ◽  
pp. 1367-1376
Author(s):  
Da-Jeong Seok ◽  
Pil-Ha Hwang ◽  
Gi-Duck Park ◽  
Dong-Hun Seong ◽  
Seong-Deok Yoon

2021 ◽  
Vol 9 (7_suppl3) ◽  
pp. 2325967121S0017
Author(s):  
Sophia M. Ulman ◽  
Laura Saleem ◽  
Kirsten Tulchin-Francis

Background: The Functional Movement Screen (FMS) is a tool designed to establish a baseline for fundamental movement capacity, highlight limitations and limb asymmetries, and identify potential injury risk. Previous research has shown that individual components of the screen are also indicative of injury risk, as well as potential predictors of athletic performance unlike the FMS composite scores. However, this literature is limited and lacks statistical power. Identifying which component scores are predictive of injury risk and athletic performance would provide a quick, powerful tool for coaches and trainers to evaluate athletes. Purpose: To determine if individual component scores of the FMS are associated with athletic performance in highly-active youth athletes. Methods: Youth athletes participated in the Specialized Athlete Functional Evaluation (SAFE) Program. Data collection was extensive, however, for the purpose of this abstract, only a selection of data was analyzed – age, BMI, years played, total number of past injuries, isokinetic knee strength, 10- and 20-meter sprint, single-leg hop (SLH) distance, and FMS scores. Seated knee flexion/extension strength was collected at 120°/second using a Biodex System 4, and peak torque was normalized by body weight. The maximum distance of three SLHs was recorded for each leg and normalized to leg length. FMS scores used for analysis included the total composite and component scores, including the deep squat, hurdle step, in-line lunge, shoulder mobility, active straight-leg raise, trunk stability push-up, and rotary stability. Wilcoxon Signed Ranks Tests were used to determine side-to-side differences, and Kruskal-Wallis tests were performed to determine differences in athletic performance based on FMS scores ( α<0.05). Results: A total of 38 highly-active, youth athletes (26F; 15.4±2.6 years; BMI 21.0±5.3) were tested. Participants reported playing organized sports for 8.7±3.4 years, having 2.0±1.2 past sports-related injuries, and 74% reported specializing in a single sport. No side-to-side differences were found. While the composite FMS score significantly differed by number of past injuries ( p=0.036), it was not associated with athletic performance. Alternatively, left knee strength, sprint speeds, and right hop distance significantly differed by the hurdle step component score (Table 1). Conclusion: While the composite FMS score was not an indicator of athletic performance, the hurdle step component score was associated with strength, speed, and jump performance. This individual task could be a beneficial tool for coaches and trainers when evaluating athletic ability and injury risk of athletes. Tables/Figures: [Table: see text]


2010 ◽  
Vol 24 (2) ◽  
pp. 479-486 ◽  
Author(s):  
Kate I Minick ◽  
Kyle B Kiesel ◽  
Lee Burton ◽  
Aaron Taylor ◽  
Phil Plisky ◽  
...  

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