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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