How movement screening may lead to decreased injury incidence / greater efficiency of movement.

Numerous movement screening methods have been identified, where there is a common trend in the literature demonstrating that movement screening is of importance in the potential prediction of injury and has the capability in some instances to identify performers in sport with enhanced movement scores leading to improved sports play (11, 18, 25, 34, 35, 38, 39).

Giles (29) discussed the implementation of a physical competence screening where a 20-test battery outlined both the functional and athletic competence variables of athletes. He stated that running / jumping / kicking activities may be severely impeded if physical limitations seen in the hip and lower limb chain are allowed to influence learning. He also noted that a lack of physical competence in these screening areas would limit sports skill development.

Kritz (38) conducted a study to attempt to identify whether descriptive movement competency screening(MCS) scores could predict physical performance or injury over one year. Screening / testing data was taken from 91 New Zealand national level athletes. Physical performance measures of sprinting, counter movement jumps, standing static jumps, and clap push ups on a force platform were taken four times throughout the year. Injury status was recorded over the year via an online data collection system. Evidence indicated in the study that a lower body MCS score may moderately predict lower body power for females, and a trunk MCS score may predict with trunk injury in all participants with moderate to high accuracy.

The larger body of recent evidence has a strong focus on the functional movement screen (FMS). Cook et al. (18) discussed research findings of the functional movement screen (FMS). They stated that research using this method determined that athletes who scored below the benchmark cut-off score of 14 or less possessed dysfunctional movement patterns that may correlate with a greater risk of injury. They also reported findings of a study examining female collegiate athletes and found that those who scored less than 14 had an approximate four-fold increased risk of lower extremity injury throughout the course of a season. Garrison et al. (25) completed a study of the FMS with 160 collegiate athletes. They identified that athletes with a composite score of 14 or less with a self-reported history of previous injury are at a 15 times increased risk of injury compared to athletes scoring higher on the FMS. This test involved a large number of athletes, both male and female, in a variety of contact and non-contact sports. This added to the value of the study as it demonstrated a broad base for data collection, where error may have increased potential, if there was a similar data pool (i.e. all male athletes / same sport / etc.). It should also be noted that there was potential for limitation in this study. As the criteria established by the authors stated each athlete must complete a minimum of three hours training time each week, there was no upper limit in the amount of training time for each athlete. This may have been a potential cause for injury in some athletes due to the monotony or strain from potentially excessive training over time. Keisel et al. (34) performed a study on 238 American professional football players. They established FMS scores at the start of the training camp prior to the season. A score of 14 or less with a combination of the presence of any asymmetries were examined. They found that when this combination was used, there was a high correlation with injury. They concluded that fundamental movement patterns and movement asymmetry are risk factors for time-loss injury in professional football players. Chapman et al. (11) used FMS scores longitudinally to attempt to predict performance outcomes in elite track and field athletes. They segregated the athletes into cohorts for comparison. Performance change between 2010 and 2011 was noted and the athletes were compared via a) high FMS score (greater than 14) to low FMS score (14 or less), b) athletes with at least one asymmetry vs. athletes with no asymmetry, c) athletes scoring 1 on the deep squat pattern vs. athletes scoring 2 or 3. The results demonstrated that on category “a” athletes with a score of greater than 14 had a greater improvement in performance. On category “b” athletes with no asymmetries had a greater improvement in performance as opposed to athletes with one or more asymmetries. On category “c” athletes who scored 1 on the squat pattern had a significantly different change in performance. They concluded by stating that functional movement ability is related to the ability to improve longitudinal competitive performance outcomes.

As there have been positive indications for the FMS being able to potentially predict injury and improvements in performance, there have also been strong limitations in the research, and studies where minimal indication was seen. Lockie et al. (40) studied the relationship between functional movement screen scores and female athletic performance. They suggested that the FMS was limited in its ability to detect movement compensations that could impact athletic performance in female athletes. Their results showed that greater flexibility as measured by numerous FMS scores related to slower change of direction speed and poorer unilateral jump performance. They also made comment that the positioning and speed of particular individual screens is atypical to team sports. They also suggested limitations of their own study however, where they only had data collection from nine athletes. Dossa et al. (20) performed research on ice hockey players and injury prediction with the FMS. There results did not support their hypothesis that low scores (14 or less) could predict injuries over the course of an ice hockey season. They stated limitations where research with contact sports where stick and puck injuries are high may have lower capability in predicting risk, also due to the altered definition of the classification of an “injury”. They stated further limitations where they did not factor the volume of training, the playing position, or the physical maturity of the athletes being studied, which all have the potential for disproportionate results with individual athlete injury.

This review explains a range of results and opinions on movement screening and how it may lead to improved performance. Due to the differing nature of the multiple studies, there is no strong conclusive evidence to date that movement screening is capable of accurately predicting injury and that athletes with high movement screen scores will have greater performance improvement. It is apparent however on numerous occasions that movement screening models, particularly that of the FMS with the most repetition in the literature, that there is reason for implementing a movement screening model, as it may ascertain a bench mark for functional capability with which a strength and conditioning coach can then provide further exercise prescription over time and improve the likelihood of minimizing athletic injury and enhancing performance status longitudinally. More ‘specific’ examples are required in the research in the future to form a stronger argument for higher success of implementation of movement screening.


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