The Functional Movement
Screen as a predictor of injury in National Collegiate Athletic Association
Division II athletes.
B, Long T, Shaffer S, and Myer GD. J Athl Training. 2017. [Epub Ahead of Print].
Take Home Message:
The Functional Movement Screen is slightly better than flipping a coin at
predicating who will get an athletic injury.
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The Functional Movement Screen (FMS) is
a tool which helps clinicians identify body asymmetries and identify
inefficient movement patterns. While FMS may differentiate injured and
uninjured people some investigators have challenged the notion that FMS could
identify athletes at risk for injury. Therefore, Dorrel and colleagues
completed a prospective study to examine the prognostic accuracy of FMS to
predict injury among NCAA Division II athletes. The authors included 257
athletes from a single NCAA Division II institution and were uninjured at the
start of the current season. Trained members of the strength and conditioning
staff completed the FMS on all included athletes prior to the start of the
season. The institution’s athletic training staff then tracked injuries
throughout the season. An athlete was considered “injured” if the injury
affected their ability to practice. In total, 124 athletes were identified as
“injured” while 117 athletes were identified as specifically having a
musculoskeletal injury. The authors found that among the 257 athletes, an FMS
score of 15 was the best cut-off for identifying athletes who would get injured
during the season. The area under the curve score for overall injury and musculoskeletal
injury was 0.53 and 0.54. To help put this in context, an area under of the
curve of 0.50 would mean there’s a 50/50 chance of predicting who would get an
injury. The data also demonstrated that FMS was more sensitive (0.61) than
specific (0.49).
The current study is interesting
because the authors suggests that FMS is only slightly better than flipping a
coin at predicting injuries. This supports a recent systematic review by these authors, which challenged the predictive
validity of FMS. While the authors fail to support the use of FMS as an injury
prediction tool, more analyses would help clinicians further understand this.
Future studies should attempt to look to widen the scope of the study from a
single institution and more specifically track how soon an injury occurs after
completing the FMS. While the authors focused on FMS predicting injury they did
not assess the FMS with regards to its accuracy of identifying body asymmetries
or identifying inefficient movement patterns. The FMS may still be used for
these purposes; but, clinicians may be weary of using FMS to identify athletes
at high risk for injury.
Questions for Discussion: What has been your experience with FMS? Do
you feel it has been a predictor of injuries in your current position?
Written by: Kyle Harris
Reviewed by:  Jeffrey Driban
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