Abstract

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.

Highlights

  • The Shapiro-Wilk test was used to check the normality of the data distribution; since its results showed that the data distribution was not normal, the Mann-Whitney U test was used to examine the difference between the mean total score and the scores of each Functional Movement Screen (FMS) tests

  • The results showed that there was a significant difference in total mean score of FMS tests between athletes and non-athletes (P=0.001)

  • The results of the study showed that the FMS score of athlete student was better than that of nonathlete students

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Summary

Extended Abstract

1. Introduction articipation in sports activities is increasing; it has potential benefits for all people including fight against obesity, and increased muscle endurance, muscle strength, cardiovascular fitness and other fitness factors [1]. On the other hand, participating in sports activities can lead to injury including musculoskeletal injuries [2]. The Functional Movement Screen (FMS) method has been designed to diagnose future musculoskeletal injuries and had goals such as dynamic and kinematic chain assess-. There is no definitive conclusion as to whether motor FMS can be used as a predictor of injury; the designer of this test have stated that its score can identify limitations, asymmetries and changes in normal movement patterns [12]. This study aimed to examine whether the FMS scores in athlete and non-athlete female students are different or not

Methods
Discussion
Compliance with ethical guidelines
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