Functional Movement Screen Score Change and Injury Occurrence in Collegiate Female Athletes Across Two Seasons

2015 ◽  
Vol 47 ◽  
pp. 854
Author(s):  
Christine O. Samson ◽  
Michael Dew ◽  
Ronald W. Courson ◽  
Brian G. Ragan ◽  
Kathy J. Simpson ◽  
...  
2019 ◽  
Vol 5 (1) ◽  
pp. e000501 ◽  
Author(s):  
Manuel Trinidad-Fernandez ◽  
Manuel Gonzalez-Sanchez ◽  
Antonio I Cuesta-Vargas

ObjectiveTo assess whether Functional Movement Screen (FMS) score is associated with subsequent injuries in healthy sportspeople.DesignSystematic review and meta-analysis.Data sourcesThe following electronic databases were searched to December 2017: Medline, PubMed, PsycINFO, SPORTDiscus, Cumulative Index of Nursing and Allied Health Literature, Scopus, Embase, and Physiotherapy Evidence Database.Eligibility criteria for selecting studiesEligibility criteria included (1) prospective cohort studies that examined the association between FMS score (≤14/21) and subsequent injuries, (2) a sample of healthy and active participants without restrictions in gender or age, and (3) the OR was the effect size and the main outcome.ResultsThirteen studies met the criteria for the systematic review and 12 were included in the meta-analysis. In 5 of the 12 studies, and among female athletes in 1 study, FMS score ≤14 out of 21 points was associated with subsequent injuries. The overall OR of the selected studies in the meta-analysis was 1.86 (95% CI 1.32 to 2.61) and showed substantial heterogeneity (I2=70%).Summary/ConclusionWhether or not a low FMS score ≤14 out of 21 points is associated with increased risk of injury is unclear. The heterogeneity of the study populations (type of athletes, age and sport exposure) and the definition of injury used in the studies make it difficult to synthesise the evidence and draw definitive conclusions.Trial registration numberCRD42015015579.


Author(s):  
Parvaneh Hesami ◽  
Ramin Balouchy ◽  
Mohammadreza Ghasemian

Background: Researchers have always sought to investigate the factors affecting sports injuries in order to identify ways of preventing and controlling such factors. These studies have more emphasis on physical aspects, while the cognitive and psychological components may also be effective. Objectives: The present study was conducted to answer the question whether or not injury can be predicted in volleyball athletes through physical and cognitive components. Methods: For this purpose, 50 volleyball players with the age range of 18 to 25 years old participated in the study. The subjects were evaluated using Barratt impulsiveness scale, Functional movement screen and continuous performance test (for sustained attention). Then, the injuries occurrence were recorded. Furthermore, logistic regression test was run to predict injury in athletes and the bi-serial correlation coefficient was used to investigate the relationship between the factors. Results: The findings showed that there was a significant negative correlation between functional movement screen scores and injuries occurrence. There was also a significant positive correlation between omission and commission errors and injury occurrence, meaning that alongside the increase in the omission and commission errors, the injury occurrence increased; however, there was no significant relationship between the scores of Barratt impulsiveness scale and the injury occurrence. Conclusions: The findings of this study showed that mental and cognitive components, along with the physical factor, play a significant role in injury occurrence in volleyball players, so it is better to consider it in prevention and rehabilitation programs.


2020 ◽  
Vol 2020 ◽  
pp. 1-8
Author(s):  
Wen-Dien Chang ◽  
Chi-Cheng Lu

Objectives. Sport-specific functional tests were used to assess the power, speed, and agility of the lower extremity for a specific sport, but comparison of the differences and association with sport injury was rare. The aim of this study was to investigate the differences in sport-specific functional tests between junior basketball and soccer athletes and analyze the sport injury risk and occurrences. Methods. All participants were evaluated using the sprint test, vertical jump (VJ) test, agility T test, and functional movement screen (FMS). There were significant intergroup differences in the sprint test, VJ test, agility T test, and FMS. Specific functional tests were compared against FMS score, either FMS ≤ 14 or FMS > 14 . The FMS subtests, namely, in-line lunge, trunk stability push-up (TSPU), and quadruped rotary stability, were also performed. In one-year follow-up, the sport injury incidence was also recorded. Results. Significant differences in sprint, agility, and FMS performance were found between the junior basketball and soccer athletes. Individual FMS scores of the in-line lunge, TSPU, and quadruped rotary stability were evaluated. No significant differences in sprint, VJ, and agility scores were found between FMS ≤ 14 and FMS > 14 . FMS total score ≤ 14 was significantly associated with high sport injury occurrence. Conclusions. The scores of sprint, agility, and FMS performance were differed between basketball and soccer athletes. The scores of sprint, VJ, and agility tests did not have differences with sport injury risks and occurrences, but the FMS score was associated with sport injury occurrence.


2020 ◽  
Vol 5 (4) ◽  
pp. 240-249
Author(s):  
Maral Entezami ◽  
◽  
Ali Shamsi Majelan ◽  
Hasan Daneshmandi ◽  
◽  
...  

Objective: The present study aimed to compare the Functional Movement Screen (FMS) scores between athlete and non-athlete female students. Methods: Participants were 30 athlete female students (Mean±SD age, 23.36±3.10 years; Mean±SD height, 163.45±5.06 cm; Mean±SD weight, 57.40±6.43 kg) and 30 non-athlete female students (Mean±SD age, 25.00±2.36 years; Mean±SD height, 162.6±3.72; Mean±SD weight, 58.76±9.29 kg). They underwent FMS to assess their movement patterns. Mann–Whitney U test was used to compare the mean FMS scores between athletes and non-athletes. Data analysis was performed in SPSS v. 22 software at a significance level of P≥0.05. Results: The Mann–Whitney U test results showed a significant difference between the total mean FMS scores of female athletes and non-athletes (P=0.001). Considering a cut-off point of 14, Results revealed that 66% of athletes 40% of non-athletes had a FMS score <14, while 93.34% of athletes and 60% of non-athletes had a FMS score >14. Conclusion: FMS can help identify the difference in movement patterns between female athletes and non-athletes. Higher FMS scores of female athletes indicate that non-athletes have poor movement patterns which suggest that they are more likely to be injured if they engage in sports activities.


2021 ◽  
Vol 9 (2) ◽  
pp. 76-81
Author(s):  
Dimitrije Kovac ◽  
Zarko Krkeljas ◽  
Dusko Spasovski ◽  
Vladimir Grbic ◽  
Lazar Miceta

Assessments and testing of young athletes often exclude the fundamental and functional movement capacity, which are critical for healthy motor development of adolescents. The aim of this study was to evaluate functional capacity of young female volleyball players and determine if participation in volleyball leads to development of movement dysfunctions. Two-hundred fifty-eight (258) adolescent female volleyball players (14.3 ± 1.7 yrs) underwent the functional movement screen. Person correlation showed no significant relationship between functional tests and playing experience, while age showed significant, but weak relationship with total functional score (r = 0.189; p < 0.005). Overall, 44% of participants scored less than 14. Paired sample t-tests show significant bilateral asymmetries in hurdle step, in-line lunge, and shoulder mobility tests. Functional movement screen was useful in identifying functional limitations and asymmetries in young female athletes. However, as neither age nor playing experience were strongly associated with functional score, more attention should be given to the qualitative movement assessment of individual tests, rather than the composite score.


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

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