Athletic Training and Sports Health Care

Original Research 

No Relationship Between Concussion History and Functional Movement Screen Performance

Jordan Dorrien, MS, ATC; Jody L. Langdon, PhD; Vicky Graham, MS, ATC; Jessie R. Oldham, MS; John Dobson, PhD; Thomas Buckley, EdD, ATC

Abstract

Healthy young adults with a history of multiple concussions appear to adopt conservative postural control strategies during instrumented balance assessments. The Functional Movement Screen (FMS) is a practical assessment of balance readily available to sports medicine clinicians. The purpose of this study was to investigate the relationship between FMS performance and prior concussion history (0 to 4 concussions). Fifty-five club sports student-athletes (38 male/17 female; mean height: 1.70 ± 0.17 m; mean weight: 78.5 ± 19.9 kg; mean age: 20.0 ± 1.5 years; 60% reported prior concussion) performed the seven FMS components. A bivariate Pearson correlation was performed to compare the relationship between concussion history and composite and component FMS scores. There were no significant relationships between concussion history and either the composite (r = 0.131, P = .34) or any of the component (P > .05) scores. These results suggest that the FMS was not an effective screening tool to identify these deficits if postural control impairments were present. [Athletic Training & Sports Health Care. 2015;7(5):197–203.]

From the Department of Health and Kinesiology, Georgia Southern University, Statesboro, Georgia (JD, JLL, VG, JD); and the Department of Kinesiology and Applied Physiology, University of Delaware, Newark, Delaware (JRO, TB).

Supported in part by a Georgia Southern University College of Graduate Studies grant.

Dr. Dorrien received funding from the Georgia Southern University College of Graduate Studies to support the program. The remaining authors have no financial or proprietary interest in the materials presented herein.

Correspondence: Thomas Buckley, EdD, ATC, Department of Kinesiology and Applied Physiology, University of Delaware, 541 South College Ave., 144 Human Performance Laboratory, Newark, DE 19716. E-mail: TBuckley@UDel.edu

Received: January 20, 2015
Accepted: July 09, 2015

Abstract

Healthy young adults with a history of multiple concussions appear to adopt conservative postural control strategies during instrumented balance assessments. The Functional Movement Screen (FMS) is a practical assessment of balance readily available to sports medicine clinicians. The purpose of this study was to investigate the relationship between FMS performance and prior concussion history (0 to 4 concussions). Fifty-five club sports student-athletes (38 male/17 female; mean height: 1.70 ± 0.17 m; mean weight: 78.5 ± 19.9 kg; mean age: 20.0 ± 1.5 years; 60% reported prior concussion) performed the seven FMS components. A bivariate Pearson correlation was performed to compare the relationship between concussion history and composite and component FMS scores. There were no significant relationships between concussion history and either the composite (r = 0.131, P = .34) or any of the component (P > .05) scores. These results suggest that the FMS was not an effective screening tool to identify these deficits if postural control impairments were present. [Athletic Training & Sports Health Care. 2015;7(5):197–203.]

From the Department of Health and Kinesiology, Georgia Southern University, Statesboro, Georgia (JD, JLL, VG, JD); and the Department of Kinesiology and Applied Physiology, University of Delaware, Newark, Delaware (JRO, TB).

Supported in part by a Georgia Southern University College of Graduate Studies grant.

Dr. Dorrien received funding from the Georgia Southern University College of Graduate Studies to support the program. The remaining authors have no financial or proprietary interest in the materials presented herein.

Correspondence: Thomas Buckley, EdD, ATC, Department of Kinesiology and Applied Physiology, University of Delaware, 541 South College Ave., 144 Human Performance Laboratory, Newark, DE 19716. E-mail: TBuckley@UDel.edu

Received: January 20, 2015
Accepted: July 09, 2015

The chronic effects of concussion have received considerable attention in both the scientific community and general public.1 The 4th International Consensus Statement on Concussion in Sport indicated that a specific causative relationship between concussion history and later life neuropathologies has not been established.2 Investigations of at-risk aging populations have yielded mixed results with retired National Football League players demonstrating, either dependent or independent of concussion history, an increased risk of clinically diagnosed depression, mild cognitive impairments, and neurodegenerative related mortality rates greater than the general public.3–6 However, other findings have suggested population normative neurological disorders among former football players.7,8 Inconsistent results have also been observed in younger populations of both high school and college aged student-athletes with a history of multiple concussions, including no noted differences in neuropsychological test performance,9,10 both increased and no differences in self-reported symptoms,10,11 and potentially lower quality of life metrics.11,12 In the military population, concussion history has been associated with depression, post-traumatic stress disorder, and suicide risk; however, this may not be independent of other confounding variables.13,14 Thus, the influence of concussion history on neurological function of otherwise healthy young student-athletes has not been fully elucidated.

Impairments in postural control or balance, two terms often used interchangeably, are a known acute consequence of concussion and are generally considered to recover within 3 to 5 days after injury when using static testing such as the Balance Error Scoring System (BESS).15–18 However, the BESS has multiple limitations that restrict its use in identifying recovery.19–22 Therefore, it is not surprising that more sophisticated balance assessment batteries have identified lingering deficits well beyond a week.23–28 These studies have typically identified deficits up to a month after injury, but there has been limited investigation over time of postural control in individuals with a history of concussions.29–32 Although few differences have been noted during static testing, gait assessment has suggested the presence of a conservative movement strategy likely selected to reduce the threats of instability during less stable gait phases.29–32 Although the specific mechanisms for this altered strategy have not been elucidated, a compensatory strategy has been speculated to exist in both the subacute and chronic findings; however, the clinical implications of these findings on return to participation remain undetermined.23–26,28,29

Although providing detailed scientific information, sophisticated analysis techniques such as motion capture or gait laboratories and the Sensory Organization Test are not readily available to athletic training clinicians.33 Indeed, these tests are likely cost-prohibitive to most institutions and, particularly the motion capture laboratories, may require substantial training to appropriately perform and interpret the test results. Conversely, the Functional Movement Screen (FMS) can be incorporated by clinicians with limited cost and training.34,35 The FMS is a screening system designed to evaluate an individual’s dynamic and functional capacity by assessing performance on seven fundamental movement patterns.34,35 A substantial consideration of the FMS is the identification of compensatory movement strategies whereby an individual successfully, but inefficiently, performs a task.36 Thus, the FMS has been assessed as a screening tool for future injury with moderate evidence to support this application.37–40 Both athletes and military personnel with a composite FMS score less than 14 appear to have an elevated injury risk.39–41

Persistent dynamic postural control deficits in individuals with a history of concussions may indicate compensatory movement strategies are being employed, thereby elevating future injury risk.29 Further, emerging evidence suggests an elevated risk of subsequent sports-related injury following a concussion; the mechanism for this risk is unknown but altered movements strategies have been speculated.42,43 Therefore, the purpose of this study was to investigate the relationship between FMS performance and prior concussion history (0 to 4 concussions). We hypothesized that composite FMS score would be negatively associated with concussion history.

Methods

Participants

There were 55 participants (38 male/17 female) from the collegiate club sports program of a single university enrolled in this study (Table 1). Mean height was 1.70 ± 0.12 m, mean weight was 78.5 ± 19.9 kg, and mean age was 20.0 ± 1.5 years (range: 18 to 24 years). The inclusion criteria were active participation in men’s (n = 21) or women’s (n = 5) rugby, men’s lacrosse (n = 14), cheerleading (n = 11), or ultimate frisbee (n = 4). The exclusion criteria were any concussion within the past 30 days or any self-reported injuries that would have restricted their participation in a game or practice on the testing day. These liberal inclusion/exclusion criteria were purposely selected to enroll typical student-athletes and not just those individuals without prior injuries and thus maximize the clinical meaningfulness and extrapolation of the study.20 All participants provided written informed consent as approved by the university’s Institutional Review Board.

Concussion History and Functional Movement Screening Scores

Table 1:

Concussion History and Functional Movement Screening Scores

Instrumentation

Concussion history was self-reported on a health history questionnaire and based on self-identified concussion(s), suffering typical concussion symptoms (eg, amnesia and loss of consciousness) following a blow to the head, or self-reporting “bell-ringers” or “dings.”44,45 When discrepancies were present or there was uncertainty about a response, a member of the research team interviewed the potential participation for clarification.

The FMS consists of seven component tests (Deep Squat, Hurdle Step, Inline Lunge, Shoulder Mobility Test, Active Straight Leg Raise, Trunk Stability Test, and Rotary Stability Test), which have been thoroughly described in the literature.34–36,46 The FMS reliability assessments have ranged from low (0.38) to high (0.97) and most achieve reliability values of at least 0.80.47–50 The sensitivity and specificity of the FMS in predicting injury using scores with less than 14 points as a cut-off score are 0.58 and 0.74, respectively.51,52 The total composite FMS score appears to be consistent at least over the duration of an athletic season.53

Procedures

Participants were actively recruited from the university’s club sports program during the Spring and Fall 2014 semesters. There were no financial incentives or inducements for participation; however, participants were provided their FMS scores on request. On arrival at the testing site, potential participants were informed of the study requirements and completed the health history questionnaire to ensure inclusion and exclusion criteria were met. Participants were instructed to refrain from physical activity for at least 90 minutes prior to testing and were dressed in gym shorts and shirt to allow for adequate visualization of all test maneuvers.

The testing herein was performed consistent with published FMS guidelines.34,35 Prior to performing each individual test and to ensure consistency of instruction, the participants watched an instructional video with verbal and visual directions for each maneuver. After observing the video, participants had the opportunity to ask follow-up questions prior to performing the test maneuver and were instructed to recreate the movement as closely as possible. Participants were provided a maximum of three trials per test and on tests with bilaterally independent scoring they were allotted three trials per side.34,35 A research team member corrected participants on their starting position, but provided no feedback once the attempt began and instructed the individual to stop if the tests caused pain. All FMS testing was conducted by a member of the research team who was Level 1 certified by FMS at the time of testing. The entire testing battery took approximately 25 to 30 minutes to complete.

Data and Statistical Analysis

This was a cross-sectional study; the independent variable was self-reported concussion history (0 to 4) and the dependent variable was the composite FMS score (0 to 21). Each of the seven FMS components are scored from 0 to 3 with specific criteria for each maneuver and consistent with FMS protocols.35 Generally, a “3” was awarded if the participant met all movement criteria, a “2” was awarded if the movement did not meet all criteria, a “1” was given if the participant could not complete the movement, and a “0” was awarded if a participant reported pain beyond soreness regardless of movement performance; however, the specifics of the scoring program have been thoroughly presented in the literature.35,46

Descriptive statistics were calculated to determine normality of the data and provide measures of central tendency and variability. Only mass appeared to have a high kurtosis, but no adjustments were made. Intraclass correlations determined inter-rater (0.60) and intra-rater (0.63) reliability of the FMS and inter-rater was compared to another FMS Level 1 certified individual who was also a certified athletic trainer. To identify the relationship between concussion history and composite FMS score, a bivariate Pearson correlation was performed. A bivariate Pearson correlation was also performed between number of previous concussions and each of the seven individual component FMS scores (SPSS software version 22; IBM Corporation, Armonk, NY). An alpha level of .05 was set for all analyses.

Results

All participants completed all trials without any reported pain. Participants reported between 0 and 4 concussions (60% with positive history; 1.0 ± 1.1 prior concussions) and mean FMS score was 15.8 ± 2.4 (Table 1). There was no significant correlation for FMS composite score and concussion history (r = 0.131, P = .34). There was no significant correlation between any of the FMS component scores and concussion history (Table 2).

Pearson Correlation Between Concussion History and Functional Movement Screen Component Scores

Table 2:

Pearson Correlation Between Concussion History and Functional Movement Screen Component Scores

Discussion

Both compensatory movement strategies and elevated risk of injury appear to be consequences of sports-related concussion.29,42 The FMS was designed to identify compensatory movement strategies that may elevate the risk of the injury.34,35 However, the primary finding of this study was the lack of association between concussion history and FMS composite score or any of the FMS component scores. This finding suggests that sports medicine practitioners may not be able to use the clinically applicable FMS to evaluate the effects of chronic or multiple concussions on gross motor performance.

The FMS was designed to identify compensatory movement strategies that would be grossly visible to a trained clinician and does not require expensive laboratory equipment.34,35 The lack of relationship identified herein likely has one of two explanations: there were no impairments during the motor tasks performed during the FMS or the FMS lacked the sensitivity to identify the changes, either subtle or gross, associated with concussion history. Sophisticated assessment techniques have identified subtle postural control impairments in individuals with prior history of concussions; however, herein the clinically applicable FMS failed to identify any relationships.29,30,32 Indeed, individuals with a history of prior concussion have demonstrated a more conservative gait strategy (eg, slower velocity, shorter steps, and longer duration in double support), which was exacerbated with the addition of a cognitive challenge and increased number of prior concussions.29,32 During quiet stance, subtle changes in center of pressure displacement and regularity have been noted among individuals with prior concussion history, which has been suggested to be a compensatory mechanism to maintain stability.30,31 These identified changes have generally been subtle (eg, 0.08 m/s change in gait velocity) and thus may not be identifiable by visual observation during FMS motor tasks, which was designed to identify gross movement abnormalities.29

The underlying neurophysiological mechanisms associated with concussion-related altered postural control are not well elucidated. Acutely after concussion, altered postural control is frequently suggested to be the result of sensory interaction deficits between the visual, vestibular, and somatosensory systems during quiet stance assessments.54 However, in addition to the sensory system, postural control is also regulated by both motor and cognitive processes.55 Chronic neurophysiological adaptations to multiple concussions have not been well established; however, transcranial magnetic stimulation studies have identified primary motor cortex inhibitions.31,56 Further, there is an apparent dose response relationship whereby increasing concussion history is associated with greater motor cortex inhibitions.31 The primary motor cortex plays a key role in encoding and executing complex movements and, via the corticospinal tract, stimulates both alpha and gamma motor neurons.55 Thus, motor cortex synaptic inhibitions would likely adversely affect complex movement patterns such as required by the FMS; however, the results of this study failed to identify associations between concussion history and FMS scores. During cognitive challenges, imaging studies suggest the compensatory mechanisms occur at a supraspinal level and it is possible the motor system experiences similar supraspinal adaptations.57 Thus, if the motor system compensatory strategies are central in nature, they may not identified by a peripheral outcome measure such as FMS.

The 4th International Consensus Statement on Concussion in Sport specifically states that a causative relationship between concussion history and later life neuropathologies has not been established.2 Thus, the participants herein may have fully intact and normally functioning neurological systems despite their concussion history and therefore no relationship between concussion history and FMS performance would be expected. Conversely, the otherwise healthy young adult may exhibit sufficient compensatory strategies, thereby masking which become more pronounced with age-related reductions in postural control.58 The mean FMS score in this study (15.8 ± 2.4) was generally similar to the composite score of college aged student-athletes (14.1 to 16.7 years) and generally consistent across concussion histories and sports37,59 (Table 1). Recently, emerging evidence is suggesting a potential association between concussion and elevated risk of subsequent sports-related injury.42,43 The FMS, specifically composite scores of 14 or less, has moderate to good predictive ability to identify risk of future injury; however, the results of this study do not support a relationship between concussion history and FMS score as potential predictors of future injury.37,39,51,60 Herein, 17 of 55 participants scored 14 or less and 58.8% (10 of 17) of these individuals had no history of prior concussion. Further, only two participants with three or more concussions had an FMS composite score of 14 or less. Future investigations could further evaluate this relationship by measuring changes in FMS performance following a concussion during the acute and subacute post-injury phases in an attempt to identify a window of vulnerability.

This study used the original 21-point grading scale of the FMS; however, a 100-point scale has recently been proposed that may allow for a more sensitive and discriminatory assessment of the motor task.59 Perhaps most importantly, although the study enrolled 55 total participants, only 60% (n = 22) of participants had a prior concussion history, with only eight participants reporting more than three concussions, and future studies could target individuals in this potentially elevated risk category. Further, the participant’s history of concussion was self-reported, which has shown moderate to high levels of reliability.61,62 The research team did follow up with participants in an attempt to maximize reporting accuracy and identify all potential concussions (eg, bell ringers); however, no perfect method for concussion reporting exists because even medical records reviews are unreliable.45,63 Time from the last concussion was not recorded. None of the participants had a concussion within the previous month and all participants were cleared for full unrestricted participating in their current sport at the time of testing, but a prior unresolved injury could have influenced the results. An additional limitation to consider was the moderate reliability of the FMS scoring within this study (inter-rater = 0.60; intra-rater = 0.63), but this was within the range of previous studies of FMS testing reliability (0.38 to 0.97) and there has been a recent call to further the development and the criterion validation of the grading scales.48–50,64 Finally, a comparison to a gold-standard postural control assessment (eg, kinematics or kinetics) could have helped determine whether impairments were actually present and not identified by the FMS, and this could be addressed in future studies.

Implications for Clinical Practice

The results of this study failed to identify a relationship between concussion history and performance on the FMS. The need for clinically applicable postural control metrics, as opposed to cost-prohibitive sophisticated techniques, remains an important and ongoing challenge for sports medicine clinicians. Although the FMS is a potential screening tool for identifying compensatory movement strategies and may be useful in prediction of injury risk, it was not effective in identifying potential chronic balance deficits in young individuals with a history of prior concussion.

References

  1. McCrory P, Meeuwisse WH, Kutcher JS, Jordan BD, Gardner A. What is the evidence for chronic concussion-related changes in retired athletes: behavioural, pathological and clinical outcomes?Br J Sports Med. 2013;47:327–330. doi:10.1136/bjsports-2013-092248 [CrossRef]
  2. McCrory P, Meeuwisse WH, Aubry M, et al. Consensus statement on concussion in sport: the 4th International Conference on Concussion in Sport, Zurich, November 2012. J Athl Train. 2013;48:554–575. doi:10.4085/1062-6050-48.4.05 [CrossRef]
  3. Guskiewicz KM, Marshall SW, Bailes J, et al. Association between recurrent concussion and late-life cognitive impairment in retired professional football players. Neurosurgery. 2005;57:719–726. doi:10.1227/01.NEU.0000175725.75780.DD [CrossRef]
  4. Guskiewicz KM, Marshall SW, Bailes J, et al. Recurrent concussion and risk of depression in retired professional football players. Med Sci Sports Exerc. 2007;39:903–909. doi:10.1249/mss.0b013e3180383da5 [CrossRef]
  5. Randolph C, Karantzoulis S, Guskiewicz K. Prevalence and characterization of mild cognitive impairment in retired National Football League players. J Int Neuropsychol Soc. 2013;19:873–880. doi:10.1017/S1355617713000805 [CrossRef]
  6. Lehman EJ, Hein MJ, Baron SL, Gersic CM. Neurodegenerative causes of death among retired National Football League players. Neurology. 2012;79:1970–1974. doi:10.1212/WNL.0b013e31826daf50 [CrossRef]
  7. Casson I, Viano D, Haacke E, Kou Z, LeStrange D. Is there chronic brain damage in retired NFL players? Neuroradiology, neuropsychology, and neurology examinations of 45 retired players. Sports Health. 2014;6:384–395. doi:10.1177/1941738114540270 [CrossRef]
  8. Savica R, Parisi JE, Wold LE, Josephs KA, Ahlskog JE. High school football and risk of neurodegeneration: a community-based study. Mayo Clinic Proc. 2012;87:335–340. doi:10.1016/j.mayocp.2011.12.016 [CrossRef]
  9. Broglio SP, Ferrara MS, Piland SG, Anderson RB, Collie A. Concussion history is not a predictor of computerised neurocognitive performance. Br J Sports Med. 2006;40:802–805. doi:10.1136/bjsm.2006.028019 [CrossRef]
  10. Iverson GL, Brooks BL, Lovell MR, Collins MW. No cumulative effects for one or two previous concussions. Br J Sports Med. 2006;40:72–75. doi:10.1136/bjsm.2005.020651 [CrossRef]
  11. Brooks BL, McKay CD, Mrazik M, Barlow KM, Meeuwisse WH, Emery CA. Subjective, but not objective, lingering effects of multiple past concussions in adolescents. J Neurotrauma. 2013;30:1469–1475. doi:10.1089/neu.2012.2720 [CrossRef]
  12. Kuehl MD, Snyder AR, Erickson SE, McLeod TC. Impact of prior concussions on health-related quality of life in collegiate athletes. Clin J Sport Med. 2010;20:86–91. doi:10.1097/JSM.0b013e3181cf4534 [CrossRef]
  13. Bryan CJ, Clemans TA. Repetitive traumatic brain injury: psychological symptoms, and suicide risk in a clinical sample of deployed military personnel. JAMA Psychiatry. 2013;70:686–691. doi:10.1001/jamapsychiatry.2013.1093 [CrossRef]
  14. Spira JL, Lathan CE, Bleiberg J, Tsao JW. The impact of multiple concussions on emotional distress, postconcussive symptoms, and neurocognitive functioning, in active duty U.S. marines independent of combat exposure or emotional distress. J Neurotrauma. 2014;31:1823–1834. doi:10.1089/neu.2014.3363 [CrossRef]
  15. Gao J, Hu J, Buckley T, White K, Hass C. Shannon and Renyi entropies to classify effects of mild traumatic brain injury on postural sway. PLoS One. 2011;6:e24446. doi:10.1371/journal.pone.0024446 [CrossRef]
  16. Howell DR, Osternig LR, Koester MC, Chou L-S. The effect of cognitive task complexity on gait stability in adolescents following concussion. Exp Brain Res. 2014;232:1773–1782. doi:10.1007/s00221-014-3869-1 [CrossRef]
  17. McCrea M, Guskiewicz KM, Marshall SW, et al. Acute effects and recovery time following concussion in collegiate football players: the NCAA Concussion Study. JAMA. 2003;290:2556–2563. doi:10.1001/jama.290.19.2556 [CrossRef]
  18. McCrea M, Barr WB, Guskiewicz K, et al. Standard regression-based methods for measuring recovery after sport-related concussion. J Int Neuropsychol Soc. 2005;11:58–69. doi:10.1017/S1355617705050083 [CrossRef]
  19. Rahn C, Munkasy BA, Barry Joyner A, Buckley TA. Sideline performance of the balance error scoring system during a live sporting event. Clin J Sport Med. 2015;25:248–253. doi:10.1097/JSM.0000000000000141 [CrossRef]
  20. Burk JM, Munkasy BA, Joyner AB, Buckley TA. Balance error scoring system performance changes after a competitive athletic season. Clin J Sport Med. 2013;23:312–317. doi:10.1097/JSM.0b013e318285633f [CrossRef]
  21. Fox ZG, Mihalik JP, Blackburn JT, Battaglini CL, Guskiewicz KM. Return of postural control to baseline after anaerobic and aerobic exercise protocols. J Athl Train. 2008;43:456–463. doi:10.4085/1062-6050-43.5.456 [CrossRef]
  22. McLeod TCV, Perrin DH, Guskiewicz KM, Shultz SJ, Diamond R, Gansneder BM. Serial administration of clinical concussion assessments and learning effects in healthy young athletes. Clin J Sport Med. 2004;14:287–295. doi:10.1097/00042752-200409000-00007 [CrossRef]
  23. Howell DR, Osternig LR, Chou LS. Return to activity after concussion affects dual-task gait balance control recovery. Med Sci Sports Exerc. 2015;47:673–680. doi:10.1249/MSS.0000000000000462 [CrossRef]
  24. Parker TM, Osternig LR, Van Donkelaar P, Chou LS. Gait stability following concussion. Med Sci Sports Exerc. 2006;38:1032–1040. doi:10.1249/01.mss.0000222828.56982.a4 [CrossRef]
  25. Parker TM, Osternig LR, van Donkelaar P, Chou L-S. Recovery of cognitive and dynamic motor function following concussion. Br J Sports Med. 2007;41:868–873. doi:10.1136/bjsm.2006.033761 [CrossRef]
  26. Catena RD, van Donkelaar P, Halterman CI, Chou L-S. Spatial orientation of attention and obstacle avoidance following concussion. Exp Brain Res. 2009;194:67–77. doi:10.1007/s00221-008-1669-1 [CrossRef]
  27. Slobounov S, Sebastianelli W, Hallett M. Residual brain dysfunction observed one year post-mild traumatic brain injury: combined EEG and balance study. Clin Neurophysiol. 2012;123:1755–1761. doi:10.1016/j.clinph.2011.12.022 [CrossRef]
  28. Buckley TA, Munkasy BA, Tapia-Lovler TG, Wikstrom EA. Altered gait termination strategies following a concussion. Gait Posture. 2013;38:549–551. doi:10.1016/j.gaitpost.2013.02.008 [CrossRef]
  29. Martini DN, Sabin MJ, DePesa SA, et al. The chronic effects of concussion on gait. Arch Phys Med Rehabil. 2011;92:585–589. doi:10.1016/j.apmr.2010.11.029 [CrossRef]
  30. Sosnoff JJ, Broglio SP, Shin S, Ferrara MS. Previous mild traumatic brain injury and postural-control dynamics. J Athl Train. 2011;46:85–91. doi:10.4085/1062-6050-46.1.85 [CrossRef]
  31. De Beaumont L, Mongeon D, Tremblay S, et al. Persistent motor system abnormalities in formerly concussed athletes. J Athl Train. 2011;46:234–240.
  32. Buckley TA, Vallabhajosula S, Oldham JD, et al. Evidence of a conservative gait strategy in athletes with a history of concussions. J Sport Health Sci. In press.
  33. Kelly KC, Jordan EM, Burdette GT, Buckley TA. NCAA Division I athletic trainers concussion management practice patterns. J Athl Train. 2014;49:665–673. doi:10.4085/1062-6050-49.3.25 [CrossRef]
  34. Cook G, Burton L, Hoogenboom B. Pre-participation screening: the use of fundamental movements as an assessment of function—part 1. N Am J Sports Phys Ther. 2006;1:62–72.
  35. Cook G, Burton L, Hoogenboom B. Pre-participation screening: the use of fundamental movements as an assessment of function—part 2. N Am J Sports Phys Ther. 2006;1:132–139.
  36. Cook G, Burton L, Hoogenboom BJ, Voight M. Functional movement screening: the use of fundamental movements as an assessment of function—part 1. Int J Sports Physical Ther. 2014;9:396–409.
  37. Shojaedin SS, Letafatkar A, Hadadnezhad M, Dehkhoda MR. Relationship between functional movement screening score and history of injury and identifying the predictive value of the FMS for injury. Int J Injury Control Saf Promot. 2014;21:355–360. doi:10.1080/17457300.2013.833942 [CrossRef]
  38. Krumrei K, Flanagan M, Bruner J, Durall C. The accuracy of the functional movement screen to identify individuals with an elevated risk of musculoskeletal injury. J Sport Rehabil. 2014;23:360–364. doi:10.1123/jsr.2013-0027 [CrossRef]
  39. Kiesel K, Plisky PJ, Voight ML. Can serious injury in professional football be predicted by a preseason functional movement screen?N Am J Sports Phys Ther. 2007;2:147–158.
  40. 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;5:47–54.
  41. O’Connor FG, Deuster PA, Davis J, Pappas CG, Knapik JJ. Functional movement screening: predicting injuries in officer candidates. Med Sci Sports Exerc. 2011;43:2224–2230. doi:10.1249/MSS.0b013e318223522d [CrossRef]
  42. Nordstrom A, Nordstrom P, Ekstrand J. Sports-related concussion increases the risk of subsequent injury by about 50% in elite male football players. Br J Sports Med. 2014;48:1447–1450. doi:10.1136/bjsports-2013-093406 [CrossRef]
  43. Pietrosimone B, Golightly YM, Mihalik JP, Guskiewicz KM. Concussion frequency associates with musculoskeletal injury in retired NFL players [online advanced publication April 11, 2015]. Med Sci Sports Exerc.
  44. Llewellyn TA, Burdette GT, Joyner AB, Buckley TA. Concussion reporting rates at the conclusion of an intercollegiate athletic career. Clin J Sport Med. 2014;24:76–79. doi:10.1097/01.jsm.0000432853.77520.3d [CrossRef]
  45. McLeod TCV, Bay RC, Heil J, McVeigh SD. Identification of sport and recreational activity concussion history through the preparticipation screening and a symptom survey in young athletes. Clin J Sport Med. 2008;18:235–240. doi:10.1097/JSM.0b013e3181705756 [CrossRef]
  46. Cook G, Burton L, Hoogenboom BJ, Voight M. Functional movement screening: the use of fundamental movements as an assessment of function–part 2. Int J Sports Phys Ther. 2014;9:549–563.
  47. Kraus K, Schutz E, Taylor WR, Doyscher R. Efficacy of the functional movement screen: a review. J Strength Conditioning Res. 2014;28:3571–3584. doi:10.1519/JSC.0000000000000556 [CrossRef]
  48. Shultz R, Anderson SC, Matheson GO, Marcello B, Besier T. Test-retest and interrater reliability of the Functional Movement Screen. J Athl Train. 2013;48:331–336. doi:10.4085/1062-6050-48.2.11 [CrossRef]
  49. Onate JA, Dewey T, Kollock RO, et al. Real-time intersession and interrater reliability of the Functional Movement Screen. J Strength Conditioning Res. 2012;26:408–415. doi:10.1519/JSC.0b013e318220e6fa [CrossRef]
  50. Smith CA, Chimera NJ, Wright NJ, Warren M. Interrater and intra-rater reliability of the Functional Movement Screen. J Strength Conditioning Res. 2013;27:982–987. doi:10.1519/JSC.0b013e3182606df2 [CrossRef]
  51. Kiesel KB, Butler RJ, Plisky PJ. Prediction of injury by limited and asymmetrical fundamental movement patterns in American football players. J Sport Rehabil. 2014;23:88–94. doi:10.1123/JSR.2012-0130 [CrossRef]
  52. Schneiders AG, Davidsson A, Horman E, Sullivan SJ. Functional movement screen normative values in a young, active population. Int J Sports Phys Ther. 2011;6:75–82.
  53. Sprague PA, Mokha GM, Gatens DR. Changes in functional movement screen scores over a season in collegiate soccer and volleyball athletes. J Strength Conditioning Res. 2014;28:3155–3163. doi:10.1519/JSC.0000000000000506 [CrossRef]
  54. Guskiewicz KM. Postural stability assessment following concussion: one piece of the puzzle. Clin J Sport Med. 2001;11:182–189. doi:10.1097/00042752-200107000-00009 [CrossRef]
  55. Shumway-Cook A, Woollacott MH. Motor Control: Translating Research into Clinical Practice, 4th ed. Philadelphia: Lippincott, Williams & Wilkins; 2012.
  56. De Beaumont L, Tremblay S, Henry LC, Poirier J, Lassonde M, Theoret H. Motor system alterations in retired former athletes: the role of aging and concussion history [online advanced publication August 26, 2013]. BMC Neurol.
  57. Chen JK, Johnston KM, Frey S, Petrides M, Worsley K, Ptito A. Functional abnormalities in symptomatic concussed athletes: an fMRI study. Neuroimage. 2004;22:68–82. doi:10.1016/j.neuroimage.2003.12.032 [CrossRef]
  58. Buckley TA, Pitsikoulis C, Barthelemy E, Hass CJ. Age impairs sit-to-walk motor performance. J Biomech. 2009;42:2318–2322. doi:10.1016/j.jbiomech.2009.06.023 [CrossRef]
  59. Frost DM, Beach TAC, Callaghan JP, McGill SM. Using the Functional Movement Screen to evaluate the effectiveness of training. J Strength Conditioning Res. 2012;26:1620–1630.
  60. Letafatkar A, Hadadnezhad M, Shojaedin S, Mohamadi E. Relationship between functional movement screening score and history of injury. Int J Sports Phys Ther. 2014;9:21–27.
  61. Kerr ZY, Marshall SW, Guskiewicz KM. Reliability of concussion history in former professional football players. Med Sci Sports Exerc. 2012;44:377–382. doi:10.1249/MSS.0b013e31823240f2 [CrossRef]
  62. McCrea M, Hammeke T, Olsen G, Leo P, Guskiewicz K. Unreported concussion in high school football players: implications for prevention. Clin J Sport Med. 2004;14:13–17. doi:10.1097/00042752-200401000-00003 [CrossRef]
  63. Kerr ZY, Mihalik JP, Guskiewicz KM, Rosamond WD, Evenson KR, Marshall SW. Agreement between athlete-recalled and clinically documented concussion histories in former collegiate athletes. Am J Sports Med. 2015;43:606–613. doi:10.1177/0363546514562180 [CrossRef]
  64. Whiteside D, Deneweth JM, Pohorence MA, et al. Grading the Functional Movement Screen: a comparison of manual (real-time) and objective methods [online advanced publication August 26, 2014]. J Strength Cond Res.

Concussion History and Functional Movement Screening Scores

GROUPNO.MEAN ± SDRANGE
0 concussions2215.3 ± 2.79 to 19
1 concussion1815.8 ± 2.310 to 19
2 concussions716.9 ± 2.014 to 20
3 concussions716.4 ± 1.414 to 18
4 concussions113.0 ± 0.0NA
Overall5515.8 ± 2.49 to 20

Pearson Correlation Between Concussion History and Functional Movement Screen Component Scores

TESTCOMPONENT SCORE (MEAN ± SD)CORRELATION (R)Pa
Deep squat2.00 ± 0.720.047.736
Hurdle step2.25 ± 0.480.227.096
Inline lunge2.49 ± 0.60−0.027.844
Shoulder mobility test2.40 ± 0.760.071.609
Active straight leg raise2.36 ± 0.650.007.959
Trunk stability test2.44 ± 0.740.252.063
Rotary stability test1.78 ± 0.53−0.049.722

10.3928/19425864-20150831-05

Sign up to receive

Journal E-contents