Evidence Based Application of the Functional Movement Screen: Part 2

Evidence Based Application of the Functional Movement Screen: Part 2

militaryIn Part 1 we discussed the FMS’s ability to predict injuries in the sports population.  Hopefully it turned some eyebrows and illuminated some interesting findings about the FMS.  In part 2 I wanted to speak about a few studies in the firefighting and military population.  Let’s uncover some facts and fallacies baby!  Onto the research…

Functional Movement Screening: Predicting Injuries in Officer Candidates (10)

Why worry about this population?

  • In Operation Iraqi Freedom from 2004 to 2007 the most common cause of medical evacuation was from musculoskeletal injury (24%).  Combat injuries came in at a distant second place (14%).
  • $16.5 million dollars are loss per year in the San Diego Marine Corps basic training camp alone from musculoskeletal disorders.
  • Low physical fitness levels, tobacco use, sedentary lifestyle, and a history of prior injury are cited as some of the stronger predictors for future risk of musculoskeletal injury.  (All the more reason to motivate our military patients to get active and stop smoking)
Study Basics:
  • 874 male participants aged 18-30
  • Injury was defined by a physician and was defined as sustaining physical damage to the body secondary to physical training that required the subject to seek medical care one or more times during the study period.
  • Injury type was identified and grouped into groups as either an Overuse Injury, Traumatic Injury, Any Injury and Serious Injury
  • Overuse Injuries:  Diagnosis included musculoskeletal pain, stress fractures, tendonitis, bursitis, fasciitis, muscle injury pre- sumably due to overuse (strain), joint injury presumably due to overuse (sprain), retropatellar pain syndrome, impingement, degenerative joint conditions, and shin splints
  • Traumatic injury: Diagnoses included pain, muscle injury (strain), or joint injury (sprain) due to an acute event, dislocation, fracture, blister, abrasion, laceration, contusions, and/or closed head injury/concussion.
  • Any Injury: A combination of Injuries
  • Serious Injury: An injury bad enough to remove a subject from the training program.

Results:

  • A score of <15 was indicative of a 1.5 times increased chance of getting injured.  The score was even higher in comparison to a score of <15 to a score of >17
  • FMS scores were not associated with the incidence of overuse injuries specifically.
  • Average FMS score of individuals without injury = 16.7 (+ or – 1.7)
  • Average FMS score of individuals with “any” injury 16.7 (+ or – 1.8)
  • Sensitivity (Any Injury) = 45.2 (Refer back to part 1 for definitions of sensitivity vs. specificity)
  • Specificity (Any Injury) = 78.2
  • Performance on standard PT test was as predictive as the FMS (with better specificity on the PT test)
  • FMS scores correlated with poor performance on PT testing.
  • Scores on the FMS >18 were at an increased risk of injury when compared to scores between 15 and 17

Considerations and Additional Questions:

  • Once again, the FMS is showing a low sensitivity and high specificity.  This is consistent with the previous FMS studies.
  • Interesting the FMS was not a predictor of overuse injuries.  This is important to understand given that a major goal of improving movement is to decrease the risk of overuse injury.
  • Performance on the regular good old PT military test was as good of a predictor of future injury as the FMS.  In actuality the results showed that the PT test had a better specificity then the PT test.  This brings up the question of whether we need to use the FMS for determining risk of injury.  Obviously the FMS will give us additional information as far as what we can improve in our patients/clients but the bottom line was that the FMS was not a better predictor of injury then the standard PT test.
  • Scores of 18 or great were more at risk for injury.  Scores above 14 are supposed to have decreased risk of injury, not the opposite.  This was an eyebrow raiser for sure.

Side Note: Additional research in the military population has shown a correlation between slow 3-mile run times and low FMS scores with decreased risk of injury.  This shows some reproducibility of the findings from study to study in the military population.

fire fighterModifiable Risk factors Predict Injuries in Firefighters During Training Academies (2)

Disclaimer: I did not have access to the full text of this article, I could only read the abstract

  • N = 108 firefighters enrolled into the firefighting training academy
  • Firefighters who scored a 14 or lower had an increased risk of injury
  • The pushup and deep squat tests were the best predictors of injury
  • Obviously my analysis of this study is not complete due to a lack of access to the entire study!

To wrap up: When attempting to determine risk of injury, which populations are the FMS appropriate for?

  • Sports population: In DII female collegiate athletes and in 1 american professional football team the FMS has shown to be a predictor of injury
  • Military and firefighting population:  Several research studies support the FMS as a predictive test for injuries.
  • Fitness Population? Injury prediction ability of the FMS in the general fitness community is currently not supported by the literature.  Keep in mind that a lack of evidence does not mean a lack of effectiveness.  This research has not yet been undertaken.  I personally believe that the FMS is promising and will yield similar results in an active fitness population.  I would definitely like to see some research in this population given that the FMS is marketing itself to the fitness community.  Until then we really have no high quality evidence in this area.

To Recap:

  • The FMS has been shown to be predictive of injury in 1 professional football team, DII female winter sports teams and the military and fire fighting populations.
  • What constitutes an injury varies from study to study.
  • An FMS score of 14 or lower appears to be the cut-off point for risk of injury.
  • Specificity = High – The FMS has shown promising results for ruling in risk of injury
  • Sensitivity = Low – On the flip side of the coin the FMS has not been shown to be an effective means of ruling out injury.  This goes against the objective of a good “screen.”
  • A low FMS score did not correlate with a previous ACL injury or previous incidence of injury in general in the female collegiate winter sports population.   *Previous injury is the greatest predictor of future injury.  In theory low FMS scores should correlate with previous injury since this is an at risk population.
  • Low FMS scores did not correlate with increased overuse injuries in the military population.
  • Scores greater then 18 correlated with increased incidence of injury in the military population (marine officers).  Strange finding…
  • FMS was not shown to be a better predictor of injury compared to the standard military PT test.

Ultimately, understanding what this evidence is showing us is absolutely pivotal in how we apply the FMS to our patients and clients.  It gives us guidance about where it fits into our practice and maybe more importantly where it doesn’t fit or where there is possibly a better test.

In part 3 we’ll go over some additional aspects of the FMS including whether or not functional movement screen correlates with athletic performance, what is the best way to improve FMS scores and whether or not improving someone’s FMS score actually decreases their risk of injury.

Find Part 3 HERE:

Gray Cook for President,

Dan Pope

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REFERENCES:

  1. Bhk FP, Koehle MS. Normative Data for the Functional Movement Screen in middle-aged adults. J Strength Cond Res. 2012 May 3.

  2. Butler RJ, Contreras M, Burton LC, Plisky PJ, Kiesel KB. Modifiable Risk Factors Predict injuries in Firefighters during Training Academies. Work. in press.

  3. Chorba RS, Chorba DJ, Bouillon LE, Overmyer CA, Landis JA. Use of a functional movement screening tool to determine injury risk in female collegiate athletes. N Am J Sports Phys Ther. 2010 Jun;5(2):47- 54.

  4. Cowen VS. Functional fitness improvements after a worksite-based yoga initiative. J Bodyw Mov Ther. 2010;14:50-4.

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  6. Gribble P, Brigle J, Pietrosimone B, Pfile K, Webster K. Intrarater Reliability of the Functional Movement Screen. J Strength Cond Res. 2012 May 15.

  7. Kiesel KB, Plisky PJ, Butler RJ. Functional movement test scores improve following a standardized off-season intervention program in professional football players. Scand J Sci Med Sports. 2011; 287- 292.

  8. Kiesel K, Plisky PJ, Voight M. Can serious injury in professional football be predicted by a preseason Functional Movement Screen? N Am J Sports Phys Ther. 2007; 2(3):76-81.

  9. Kiesel KB, Plisky PJ, Butler RJ. Fundamental movement limitations and asymmetries relate to injury risk in professional football players. in review.

  10. O’Connor FG, Deuster PA, Davis J, Pappas CG, Knapik JJ. Functional movement screening: predicting injuries in officer candidates. Med Sci Sports Exerc. 2011 Dec;43(12):2224-30.

  11. Onate JA, Dewey T, Kollock RO, Thomas KS, Van Lunen BL, DeMaio M, Ringleb SI. Real-time intersession and interrater reliability of the functional movement screen. J Strength Cond Res. 2012 Feb;26(2):408-15.

  12. Parchmann CJ, McBride JM. Relationship between functional movement screen and athletic performance. J Strength Cond Res. 2011 Dec;25(12):3378-8.

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  14. Smith CA, Chimera NJ, Wright N, Warren M. Interrater and Intrarater Reliability of the Functional Movement Screen. J Strength Cond Res. 2012 Jun 11.

  15. Teyhen DS, Shaffer SW, Lorenson CL, Halfpap JP, Donofry DF, Walker MJ, Dugan JL, Childs JD. The Functional Movement Screen: a reliability study. J Orthop Sports Phys Ther. 2012 Jun;42(6):530-40.

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