Comparing Functional Movement Screen Scores Between Athlete and Non-Athlete Female Students

* Corresponding Author: Maral Entezami, MSc. Address: Department of Sports Pathology and Corrective Exercise, Faculty of Physical Education, University of Guilan, Rasht, Iran. Tel: +98 (991) 6165992 E-mail: entezamidorsa2018@gmail.com 1. Department of Sports Pathology and Corrective Exercise, Faculty of Physical Education, University of Guilan, Rasht, Iran. *Maral Entezami1 , Ali Shamsi Majelan1, Hasan Daneshmandi1


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 P to injury including musculoskeletal injuries [2]. Therefore, pre-season and pre-workouts and competitions screening is performed to reduce the number of injuries and provide a safe and secure environment for athletes to identify players at risk of injury and subsequently consider the design and implementation of injury prevention programs for them.
The Functional Movement Screen (FMS) method has been designed to diagnose future musculoskeletal injuries and had goals such as dynamic and kinematic chain assess-ments, body symmetry detection, and detection of poor movement patterns [6]. There is no definitive conclusion as to whether motor FMS can be used as a predictor of injury; however, 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
This is a causal-comparative study. The study population consisted of university students aged 18-30 years. Of these, 30 physical education students and 30 non-physical education students who had no history of participating in sports activities and exercises were selected and underwent FMS. It has seven tests including deep squat, hurdle step, in-line lunge, shoulder mobility, active straight-leg raise, trunk stability push-up, and rotary stability (Table 1). Necessary explanations and instructions related to the implementation of each movement pattern were given to each subject before the test, and they performed the test for trial.
In order to evaluate the movement patterns, the examiners were placed at the same distance from the subject in all 3 directions: anterior, posterior and lateral. Subjects performed each movement 3 times. For single-sided movements, the best score was recorded in 3 repetitions, and for two-sided movements, the best score was recorded for each side; and among the best scores on each side, the lowest score was considered as the overall score. 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 FMS tests. All data were analyzed in SPSS v. 22 and the significance level was considered P<0.05.

Results
The results of Mann-Whitney U test for the two study groups are shown in Table 2. The results showed that there was a significant difference in total mean score of FMS tests between athletes and non-athletes (P=0.001).

Discussion
The purpose of this study was to examine whether the FMS scores in athlete and non-athlete female students are different or not. The results of the study showed that the FMS score of athlete student was better than that of nonathlete students. This indicate that FMS can detect different movement patterns between athletes and non-athletes, and that non-athletic students show poor movement patterns which suggest that they are more likely to be injured if they engage in sports activities, assuming the FMS test predicts sports injuries. Lack of physical activity leads to muscle weakness and decreased muscle strength, as well as decreased neuromuscular coordination, resulting in low stability and motor control and inadequate balance. It is suggested that future studies be conducted by using the FMS for both athletes and non-athletes to clarify whether the reason for the difference in FMS scores between athletes and non-athletes is physical fitness factors or other causes. Physical fitness factors between the two groups should also be measured and examined.

Compliance with ethical guidelines
All ethical principles are considered in this article. The participants were informed about the purpose of the research and its implementation stages; they were also assured about the confidentiality of their information; moreover, they were free to leave the study whenever they wished, and if desired, the research results would be available to them.

Funding
This research did not receive any grant from funding agencies in the public, commercial, or non-profit sectors.

Authors' contributions
All authors contributed in preparing this article.

Conflicts of interest
The authors declared no conflict of interest.