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As my frequent readers know, I’ve written several posts in the past where I’ve investigated some of the research done on the Functional Movement Screen.  You can check out the four articles below to get up to speed.

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Interrater Reliability of the Functional Movement Screen

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Core strength: A New Model for Injury Prediction and Prevention

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Research Review: Can Serious Injury in Professional Football be Predicted by a Preseason Functional Movement Screen?

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Research Review: Can Serious Injury in Professional Football be Predicted by a Preseason Functional Movement Screen?

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In the near future I will provide my review of Gray’s book Movement and my final review on the FMS as a whole (I’ve honestly been meaning to get to this for some time).  However, today I wanted to share with you an interview I did recently with Dr. Robert Butler who is currently one of the principal investigators of the FMS.  My goal here is to provide some balance to the discussion and to share the current state of FMS research.

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Without further ado, let’s get at it!

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Mark:  Thanks for taking the time to do this interview today.  Could you please tell my readers a little bit about yourself and your background?

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Rob – Mark, it is a pleasure and honor to be able to participate in this interview. As far as my background, I am currently an Assistant Professor in the Doctor of Physical Therapy Division at Duke University as well as a Clinical Researcher for Duke Health Systems Sports Medicine Division.

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I completed my undergraduate degree at Marietta College with a degree in Biology. I then followed up with MS in Movement Science with a concentration in Biomechanics from Springfield College and received my PhD in Biomechanics and Movement Science from the University of Delaware. After completing my PhD, I completed a post-doc at UNC-Chapel Hill before completing my DPT at the University of Evansville.

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It was at the University of Evansville where I began working with the Functional Movement Screen through collaborative work with Kyle Kiesel. My research has focused on the role of functional movement outcomes in identifying and addressing movement dysfunction with regards to reducing injury risk, improving therapeutic outcomes, and reducing the rate of joint degeneration.

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I currently have 14 publications in peer-reviewed manuscripts and have had over 50 abstracts accepted for presentation at national and international meetings.

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Mark:  That’s excellent Rob!  You’ve recently been involved with some of the research on the Functional Movement Screen.  Can you talk a little bit about how this opportunity came about and your affiliation with the system?

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Rob – I was a student and a fellow faculty member with Kyle Kiesel at the University of Evansville and I originally rebuffed the idea of the screen as I went to tinker in the high tech motion analysis lab I directed. However, as I learned more about the system I began to appreciate the use of the screen in clearing the fundamental motor programs that we often attempt to retrain at a higher level in athletes who are having pain and seek out biomechanical based movement retraining. It quickly became the screen that all of the runners at our clinic would have to pass prior to higher level gait retraining, it was our blood pressure test for movement.

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We found that as the fundamental pattern issues resolved there tended to be less of a need for higher level retraining. This continues to be the notion with which I encourage the use of the screen. I never have had a formal affiliation with Functional Movement Systems until recently when I began to instruct some of their courses. In addition, Functional Movement Systems has never financially supported any of the research projects that we have published.

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Mark: Looking at all of the research that has been done to date on the Functional Movement Screen, what things do you think we can currently say we know about the system?

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Rob – I think we can say the screen is reliable between raters trained in the system. We found very high reliability in a recently developed 100 pt screen we use in a research setting which simply forces the rater to score each individual component of the test. I think this step-by-step grocery list approach addresses some of the questions you raised in regards to the reliability study.

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I think we can say that performance on the screen can identify individuals at a higher risk for sustaining an injury in the NFL, military and firefighters. We have two larger scale studies, one in the NFL (N =232) and one in firefighters (N=109), that are currently in review that address these gaps in the currently available literature. The study in the NFL will also be the first study to formally support the role of an asymmetry on the FMS and elevated injury risk in the scientific literature.

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I think we also can say that performance on the FMS is modifiable when using a movement based intervention program.

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I do want to touch a bit on the generic “elevated risk for injury” comment that tends to draw so much ire. Sometimes this comment is taken out of context and I hope this commentary will clarify. The elevated risk of injury in subjects =< 14 on the composite score is 2.2x based on our current study in review. It is not an end all be all number but it was statistically derived and not randomly fabricated by the research group.

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The factor that tends to be the strongest consistent predictor of injury is a previous injury; however, this factor is not modifiable. Teasing out this factor is often difficult from a research design standpoint; however, we recently were able to accomplish this in a prospective epidemiology study in collegiate athletes. The results of the study observed that poor movement was a much stronger predictor of non-contact lower extremity injuries in comparison with previous injury alone. We are working on the publication of these findings.

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That being said, no one that I work with is suggesting we have solved all of the non-contact lower extremity injury worries with this model, rather we have simply outlined some patterns that should probably be cleared to minimize injury risk. Our clients do not sit on the couch and as a result they have a risk of injury. The FMS gives us a consistent feedback loop to clear through and maintain motor programs in order to minimize our client’s injury risk when exercising.

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 Mark: What things do you think that we don’t yet know, but might in the future?  Can you tell us what research is on the horizon for the FMS or is awaiting publication?

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Rob – The one thing that continues to arise in the literature is that a prior injury is one of the strongest predictors of subsequent injuries. This suggests that something inherently changes in the motor program following an injury and at this point in time we have yet to establish rehabilitation protocols that normalize the effect of the injury that is being rehabilitated. We think that the FMS may be an integral component of normalizing movement patterns during rehabilitation from an injury. The addition of this model may allow for the factor of prior injury to be removed from the injury equation.  This large scale study can only occur following a series of other studies;  however, it continues to take up valuable space on the office white board.

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We also are not sure how changing the FMS scores effect injury risk and this is another component that we are currently researching. This is often one of the fundamental and appropriate critiques of the system, however to the best of our knowledge there are not many other systems that have shown this either, particularly in an efficient and individualized manner. The goal of the FMS model is to provide an efficient screening process that provides a systematic intervention scheme based on the results of the testing. The goal of the screen is to identify the weakest link in the chain which is a different paradigm in retraining compared to the majority of the group programs that are currently promoted.

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In addition, the goal is to utilize the system in 100s of people a day not 100s of people a year. To borrow from the cardiovascular literature again, it took researchers approximately 30 years from the time hypertension was established as being a risk factor for cardiovascular disease to the research showing that reducing hypertension actually reduced the risk for a cardiovascular event. However, physicians did not wait 30 years to develop models to monitor and reduce hypertension. They proactively addressed the modifiable risk factors to optimize the health of their patients. I feel as if this is a nice and appropriate corollary to the Functional Movement Screen and corrective exercise strategy except that the FMS assessment and treatment is cheaper, easier, and more accessible with less potential side effects.

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Another area that continues to be examined is the composite score cutpoints of the screen in different populations. I think the =< 14 serves as a good starting point but not an end all be all and I think this view point is shared by the majority of the Functional Movement Systems group. The evidence currently supports the specific =< 14 cut off in the certain populations it has been established in, however, we expect that the relevant cutpoints for elevated injury risk may differ across populations.  We are looking to establish relevant injury prediction cut points across recreational, amateur and professional athletes of different age groups and across sports. Other research will also expand to look at the loading of certain variables on the injury algorithm.

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It may be that in certain populations performance on certain components of the FMS may have stronger relevance to injury prediction than other components of the test.  That does not disregard the seven FMS tests and the FMS model rather it would serve to establish a set of specific thresholds for performance on the FMS in a given population along in the presence of general movement competency.

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Finally, we are looking at linking the FMS with other tests that have been related to an elevated risk of injury to provide a more robust model for injury risk identification. It is likely that multiple tests that have independent movement constructs from the FMS will provide a more complete assessment to provide the optimal feedback to individuals who work in the realm of injury prevention.

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Mark: Now I know you were a little miffed about some of the comments about on my most recent review of the FMS research.  Please feel free to take a second to address some of these comments.

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Rob – I cannot recall my initial thoughts on this, however, I think the overlying concept that people have a difficult time with until they use the screen is that the FMS is a filter to catch large scale movement dysfunction not 2 degree differences in movement patterns.  The goal is to establish basic movement competency, to get your movement BP to 120/80. Why is it okay for a 14 year old to lose the ability to deep squat when in a 2 year old it would be a medical emergency?

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Part of it boils down to a lack of standards for basic movement competency. There are a number of research studies that have associated mal-alignment and poor movement with injury and pathology using much more precise and sophisticated equipment. This is one of the reasons why I feel the screen is often dismissed at first site…. It has to be more expensive to be meaningful… the course has to cost more to be worthy of my time …. my patients/clients could pass that test easy. These are often the comments reflected back to the screen.  My response to these lines of comments is fairly standard… “Perfect, then if you are interested just start collecting the FMS data and just see what happens.”

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The screening process is outlined in the reliability study (Minick et al., 2010, J Strength Cond Res) and Gray discusses how to build your own kit in “Athletic Body and Balance” for less than $20. All the information is out there for someone who wants to learn and incorporate the screen. The uber-transparency of the model is one of the reasons I am drawn to it. In a world of rehabilitation where there are often closed door assessments and jargon laden evaluations it is nice to have a model for all to understand and talk about at a common level of understanding across disciplines.

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If all the screen is used for is a standardized way to assess basic patterns of movement that were imperative in the neurodevelopmental process then I think the screen has accomplished a great deal. The importance of these fundamental patterns become more clear everyday as my two girls learn to defy gravity from the ground up and balance their own dual pendulum setups as they explore their everyday lives.

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Mark:  And finally, where do you think the FMS is most useful for the average trainer who is about to start training a new person?

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Rob – I think the screen gives everyone (you, the client, the client’s family, the client’s MD, a client’s MD in another country) an idea of where the client’s program is headed and why it is headed in that way with regards to the client’s plan of care.  I love the fact that health care providers do not have to speak the same language to talk movement.

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The screen also gives the patient some specific goals that they can often self-assess.  My patients often want to know we they aren’t running, jumping, doing kettlebells for Turkish getups, etc. during therapy.  I often will have a rationale in my mind as to why we are not doing these activities and when I explain the rationale for this it often falls on deaf ears. However, the second I give them the criteria of a wall squat with hands overhead and hips below parallel prior to starting plyometrics it tends to stick with the individual to a greater degree and the patient tends to become more engaged in the pursuit of the goal.

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I love empowering my patients to move better and to screen themselves in whether or not they are making gains.

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Mark:  Awesome!  Thanks for the interview Rob.

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Rob – Mark, thanks for your time and patience as I put this together. I hope this interview can provide some open dialogue with regards to the screen and what it can and cannot do. I look forward to speaking with you more in the future as we all aim to provide the best care and information to the clients and patients we serve.

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Like this interview?  Please share!

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What do you think?

Recently I’ve undertaken the task of reviewing some of the research on the very popular Functional Movement Screen.  Previously I’ve reviewed the Interrater Reliability of the Functional Movement Screen and Core strength: A New Model for Injury Prediction and Prevention.

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Today I’ll be taking on the 3rd of 4 studies I hope to review.  After the final review I’ll talk a little bit more about my overall impression of the FMS and how I believe it should be used.

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Can Serious Injury in Professional Football be Predicted by a Preseason Functional Movement Screen?

Kiesel K, et al.  North American Journal of Sports Physical Therapy Aug 27, 2:3

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Background

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Risk factors for injuries in high school and collegiate football include previous injury, body mass index, body fat percentage, playing experience, femoral intercondylar notch width, cleat design, playing surface, muscle flexibility, ligamentous laxity, and foot biomechanics.  However, injury risk is likely a combination of many of the above.

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Further, evaluation of isolated risk factors does not take into consideration how the athlete performs functional movement patterns required for sport.  The goal of this study was to examine functional movement scores (assessed by the FMS) and to determine the relationship between professional football players’ score on the FMS and the likelihood of serious injury.

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Methods

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FMS scores were obtained prior to the start of the season for 46 professional football players.  A receiveroperator characteristic curve the FMS score was used to predict injury during one complete football season.  For the sake of this study, injury was defined as membership on the injured reserve for at least 3 weeks.

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A dependent t-test was used to determine if a difference existed between of the FMS scores of those who were injured versus those who were not.

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Sidebar – Definitions

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To have a clear understanding of the methods and the results of this study a brief discussion is needed to definte sensitivity, specificity, and how these are used to create a ROC curve (receiveroperator characteristic curve).

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Sensitivity is basically the power to detect a true positive.  For example, if you were to go through a scanner at the airport to detect for metal it would be very sensitive to decrease the likelihood that someone were able to slip onto an airplane with a weapon.  On the other hand, the scanner doesn’t have very high specificity in that it will sound for almost any piece of metal not just weapons.  In this case, a high sensitivity is most important because it is important that weapons do not sneak aboard the aircraft.

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A dog trained to sniff for narcotics would have a high specificity since only those carrying drugs would need to be stopped.  If the dog didn’t have a high specificity for a specific substance, but was highly sensitive it would possibly alert people needlessly to any scent and make the purpose of having the dog useless (since every bag would have to be checked anyway).

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In a perfect world every test would have 100% sensitivity and 100% specificity (i.e., identifying every weapon at the airport without going off for every other piece of metal), but this is rarely the case.  There is usually a tradeoff between one and the other and the ROC curve plots sensitivity against specificity to determine the ideal cutoff number to use to maximize both.

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With the FMS the the cutoff was chosen using the ROC curve such that the test correctly identifies the greatest number of athletes at risk of injury (true positives) while minimizing incorrectly identifying athletes not at risk of injury (false positives).

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Results

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A score of 14 or less on the FMS was able to predict injury with specificity of 0.91 and sensitivity of 0.54. 

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The test had a very high specificity indicating that the majority of people with a score below 14 had a greater chance of injury.

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Those with a score under 14 that got an injury = 7

Those with a score under 14 that didn’t get an injury = 3

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Unfortunately, the test had a only a moderate sensitivity so it did not detect those with a score over 14 who did experience an injury.

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Those with a score over 14 that got an injury = 6

Those with a score over 14 that didn’t get an injury = 30

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In other words, the bulk of the people with an FMS score over 14 did not get an injury and the bulk of those with a score under 14 did.  Using something called an odds ratio the authors determined that the likelihood of injury was 11 times more likely if the player had a score below 14 on the FMS.

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However, 6 people that did have a score higher than 14 did end up getting injured.  These ones were missed by the screen.  In fact, it failed to identify almost as many people as it did identify as being at risk.

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Funding

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None declared, but I believe at least two of the authors have affiliation with the FMS.  (Not that there is anything wrong with that, but I would declare this as a possible conflict of interest.)

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My Thoughts

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All in all I think that the FMS did a great job of determining that those with a score less than 14 were at risk for injury.  In terms of practical application, these players could have been flagged for specific work with a fitness/rehab professional.  On the other hand, the test wasn’t sensitive enough to detect risk of injury such that 6 athletes slipped through the cracks and ended up being injured without this being detected by the screen.

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Unfortunately, there was no differentiation between the types of injuries that landed people on the reserve list so it is possible that some of the injured athletes suffered from contact injuries that could not have been predicted by any test or screen.  Perhaps if contact injuries were ruled out (since you can’t really test for these) the FMS would have proven to be more sensitive.  Then again, maybe some of those with a score below 14 suffered contact injuries as well.  It would have been interesting to see if the results were different if these types of injuries were excluded.

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It is also possible that one reason the FMS predicted injuries so well below the score cutoff of 14 with this group is because it is the same group whose results were used to create the cutoff in the first place.  Only future research will tell if this pass/fail cutoff is equally as effective for other groups.

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Summing Up

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The FMS indicated correctly that those with a score less than 14 were more prone to injury.  However, the results of the present study indicate that the FMS may also miss equally as many people as it detected (which may be the reason why the pass/fail score for the FMS when it is typically used is actually lower than this).

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It would also have been interesting to see which of the individual scores within the FMS were most related in injury.  Since the FMS typically suggests that side to side imbalances are most important to address, it would have been nice to see this data to see if this hypothesis holds true.

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In the end though, the FMS does appear to effectively predict injury in this below a value of 14 in the group studied.  It does not catch all injuries and as such is not a perfect screen, but effective at picking out some who are at risk.  And since the results are those of professional football players, we should be careful when generalizing them to other populations.

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What do you think?

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