- Email: [email protected]
High prevalence of dysfunctional, asymmetrical, and painful movement in elite junior Australian Football players assessed using the Functional Movement Screen
Accepted Manuscript Title: High prevalence of dysfunctional, asymmetrical, and painful movement in elite junior Australian Football players assessed using the Functional Movement Screen Author: Joel T. Fuller Samuel Chalmers Thomas A. Debenedictis Samuel Townsley Matthew Lynagh Cara Gleeson Andrew Zacharia Stuart Thomson Mary Magarey PII: DOI: Reference:
S1440-2440(16)30064-0 http://dx.doi.org/doi:10.1016/j.jsams.2016.05.003 JSAMS 1329
To appear in:
Journal of Science and Medicine in Sport
Received date: Revised date: Accepted date:
5-11-2015 18-4-2016 13-5-2016
Please cite this article as: Fuller JT, Chalmers S, Debenedictis TA, Townsley S, Lynagh M, Gleeson C, Zacharia A, Thomson S, Magarey M, High prevalence of dysfunctional, asymmetrical, and painful movement in elite junior Australian Football players assessed using the Functional Movement Screen, Journal of Science and Medicine in Sport (2016), http://dx.doi.org/10.1016/j.jsams.2016.05.003 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
*Title page (including all author details and affiliations)
1
High prevalence of dysfunctional, asymmetrical, and painful movement in elite junior
2
Australian Football players assessed using the Functional Movement Screen
3 4
Joel T. Fuller a, Samuel Chalmers a,b, Thomas A. Debenedictis a, Samuel Townsley a, Matthew
5
Lynagh a, Cara Gleeson a, Andrew Zacharia a, Stuart Thomson a & Mary Magarey a
a
Alliance for Research in Exercise, Nutrition and Activity (ARENA), Sansom Institute for Health
8 b
cr
9
Research, University of South Australia, Adelaide, SA, Australia
Sport and Exercise Science, School of Science and Health, Western Sydney University, NSW,
10
Australia
12
an
11
us
7
ip t
6
Corresponding author: Joel Fuller
14
Alliance for Research in Exercise, Nutrition and Activity
15
University of South Australia
16
GPO Box 2471, Adelaide SA 5001 Australia
17
Ac ce pt e
d
M
13
E-mail: [email protected]
18
Phone: +61 8 8302 2097
19 20
Word Count: 3,000 words (not counting phrases “Insert Table X about here” or “Insert Fig. X about
21
here”)
22
Abstract Word Count: 250 words
23
References: 30
24
Number of Tables: 2
25
Number of Figures: 1
1
Page 1 of 18
1
High prevalence of dysfunctional, asymmetrical, and painful movement in elite junior
2
Australian Football players assessed using the Functional Movement Screen
3 Abstract
5
Objectives: The purpose of this study was to describe the prevalence of dysfunctional, asymmetrical,
6
and painful movement in junior Australian Football players using the Functional Movement Screen
7
(FMS).
8
Design: Cross-sectional study.
9
Methods: Elite junior male Australian Football players (n=301) aged 15-18 years completed pre-
10
season FMS testing. The FMS consists of 7 sub-tests: deep squat, hurdle step, in-line lunge, shoulder
11
mobility, active straight leg raise, trunk stability push-up (TSPU) and rotary stability. The shoulder
12
mobility, TSPU, and rotary stability tests were combined with an accompanying clearing test to assess
13
pain. Each sub-test was scored on an ordinal scale from 0-3 and summed to give a composite score out
14
of 21. Composite scores ≤14 were operationally defined as indicating dysfunctional movement.
15
Players scoring differently on left and right sides were considered asymmetrical. Players reported
16
whether they missed any games due to injury in the preceding 22 game season.
17
Results: Sixty percent of players (n=182) had composite scores ≤14, 65% of players (n=196) had at
18
least one asymmetrical sub-test, and 38% of players (n=113) had at least one painful sub-test. Forty-
19
two percent of players (n=126) missed at least one game in the previous season due to injury. Previous
20
injury did not influence composite score (p=0.951) or asymmetry (p=0.629). Players reporting an
21
injury during the previous season were more likely to experience pain during FMS testing (odds ratio
22
1.97, 95% confidence interval 1.23 to 3.18; p=0.005).
23
Conclusions: Junior Australian Football players demonstrate a high prevalence of dysfunctional,
24
asymmetrical, and painful movement during FMS testing.
Ac ce pt e
d
M
an
us
cr
ip t
4
25 26
Keywords
27
Injury prevention; athletic injuries; risk factors; exercise test; adolescent
1
Page 2 of 18
Introduction
29
Australian Football has a high incidence of contact and non-contact injuries in both junior and senior
30
competitions.1,2 Injuries from Australian Football cause more hospital admissions and health insurance
31
claims than any other sport in Australia.3 The high number of hospital admissions resulting from
32
participation in Australian Football can be largely attributed to the contact nature of the sport. 4
33
However, non-contact injuries still account for 30-50% of Australian Football injuries presenting to
34
sports medicine clinics.5,6 To date, the majority of injury prevention research in Australian Football
35
has focused on senior players.1 Less research is available for junior players despite participation rates
36
being highest in the 15-17 year age range.6,7 Injury prevention measures are important in junior
37
Australian Football because players that sustain injuries in junior competition are more likely to
38
sustain injuries when they transition to senior level competition.8
39
Dysfunctional movement is one injury risk factor that could be important for the prevention of injuries
40
in junior Australian Football.9–11 For example, poor strength might increase the risk of muscle strain,10
41
poor mobility in one joint might cause excessive mobility at another joint,12 and poor balance might
42
result in poor landing strategies.13 The current research approach to movement testing in junior
43
Australian Football uses isolated movement tests to identify dysfunction with a specific muscle or
44
joint.11 This approach has proven useful for identifying players at high risk of certain injuries (e.g.
45
groin injury11), but does not provide an indication of the overall risk of sustaining the broad range of
46
injuries that occur in Australian Football.14 For example, reduced isometric hip adductor strength
47
indicates increased likelihood of groin pain in junior Australian Football players 11 but provides
48
minimal insight concerning the risk of injury in other body areas. Additionally, testing only one
49
movement quality (i.e. isometric hip adductor strength) ignores other movement qualities (mobility,
50
balance, etc.) that may contribute to the multifactorial nature of Australian Football injuries. 15
51
There is a growing trend for injury prevention screening to involve compound movements that test
52
multiple movement qualities (e.g. strength, mobility and balance) at the same time.13,16,17 One example
53
is the Functional Movement Screen (FMS), which consists of seven sub-tests that are suggested to
54
represent fundamental movement patterns.12 It has been hypothesised that the FMS can identify
Ac ce pt e
d
M
an
us
cr
ip t
28
2
Page 3 of 18
athletes with poor movement qualities using only these seven sub-tests.18 Poor movement quality
56
during FMS testing has been suggested as a risk factor for injury. 18 If valid, field-based tests such as
57
the FMS could be useful in team sports such as junior Australian Football, which involve large player
58
numbers and only limited access to medical personnel capable of performing numerous isolated
59
movement tests.
60
The presence of dysfunctional movement during FMS testing is a risk factor for injury (contact and
61
non-contact) in professional American Football (relative risk [RR]=1.9-4.2)18,19 and collegiate soccer,
62
volleyball and basketball (RR=1.9).20 Asymmetrical movement during FMS testing is also a risk factor
63
for injury in professional American Football (RR=1.8).19 In contrast, the presence of dysfunctional
64
movement during FMS testing is not a risk factor for injury in collegiate American Football.21
65
Additionally, Garrison et al.22 (RR=2.2), but not Warren et al.23 (RR=1.0), found that FMS movement
66
dysfunction was an injury risk factor for athletes participating in collegiate rugby, tennis, swimming,
67
diving, track and field, cross country, and golf. As a result, both the type of sport and level of
68
competition appear to be important to the validity of the FMS.
69
The FMS shows promise as a method for identifying athletes at high risk of injury but has not been
70
investigated in Australian Football. Australian Football is a unique sport involving multiple player
71
positions, which collectively involve similar physical demands and technical kicking skills to soccer,
72
similar full-body tackling to American Football, and similar technical hand passing skills to basketball
73
and volleyball.24 The movement and injury profiles of Australian Football are likely to differ from
74
other sports used in FMS research. Therefore, the purpose of this study was to describe the prevalence
75
of dysfunctional, asymmetrical, and painful movement in junior Australian Football players using the
76
FMS. The effect of player position and previous injury on FMS testing was also investigated. It was
77
hypothesised that dysfunctional, asymmetrical, and painful movement would be more prevalent in
78
players that missed at least one game due to injury in the previous season.
79
Methods
80
A total of 301 male players (age: 17 ± 1 years; body mass: 74 ± 9 kg; height: 181 ± 7 cm) were
81
recruited from eight elite junior (under 18 years) clubs competing in the Under-18 South Australian
Ac ce pt e
d
M
an
us
cr
ip t
55
3
Page 4 of 18
National Football League (SANFL). Players (including parent or guardian) provided written informed
83
consent to participate in this study, which had institutional ethical approval. Players were excluded if
84
they reported a current physical impairment that prevented participation in routine club training
85
sessions. All testing was completed during the annual pre-season SANFL fitness testing combine.
86
Participants reported their current playing position, and whether they missed at least one game due to
87
injury in the preceding 22 game season. Only injuries resulting from participation in Australian
88
Football or training were considered. This injury definition is consistent with previous research in
89
junior Australian Football6 and the Australian Football League injury surveillance program.1 Player
90
positions were: midfielder, forward, defender, or ruck. Six qualified physiotherapists and one strength
91
and conditioning coach were responsible for FMS testing. To reduce errors associated with multiple
92
raters, each tester completed a level one FMS training course and was responsible for assessing a
93
separate FMS sub-test. Testing was performed using standard FMS Test Kits (Functional Movement
94
Systems Inc., Virginia, USA). The FMS has acceptable inter- and intra-rater reliability for composite
95
scores.25
96
Warm-up activities were organised by fitness staff from each SANFL club. The FMS consists of 7
97
sub-tests.12,26 These tests were the deep squat, hurdle step, in-line lunge, shoulder mobility, active
98
straight leg raise (ASLR), trunk stability push-up (TSPU) and rotary stability. The hurdle step, in-line
99
lunge, shoulder mobility, ASLR and rotary stability tests were completed for left and right sides. The
100
shoulder mobility, TSPU and rotary stability tests were combined with an accompanying clearing test
101
to assess pain. These clearing tests were the shoulder combined internal rotation and flexion test, the
102
end-range spinal extension test and the end-range spinal flexion test, respectively. Detailed
103
descriptions of FMS sub-tests have been reported previously.12,26
104
Each FMS sub-tests was scored on an ordinal scale from 0-3.12,26 A score of 3 was given when players
105
completed the sub-test without compensatory movement. A score of 2 was given when players
106
completed the sub-test, but used one or more compensatory movements. A score of 1 was given when
107
players were unable to complete the sub-test. At the completion of each sub-test players were asked if
108
they experienced pain anywhere in the body at any time during the test. A score of 0 was given when
Ac ce pt e
d
M
an
us
cr
ip t
82
4
Page 5 of 18
players reported pain of any kind during the sub-test or the accompanying clearing test. For sub-tests
110
completed on left and right sides, the overall score was the lowest score from the two sides. A sub-test
111
score of 1 indicated dysfunction with the associated movement. Scores for each sub-test were summed
112
to give a composite score out of 21, after adjusting for clearing test results. We established a-priori
113
that a FMS composite score of ≤14 (as reported in other studies) would be used to group players.18,20,22
114
All statistical analysis was performed in R 3.2.1 (R Foundation for Statistical Computing, Vienna,
115
Austria). Statistical significance was assumed for p<0.05. The proportion of players who scored 1,
116
were asymmetrical (left ≠ right), or reported pain (score = 0) were compared across the seven sub-
117
tests using Chi-squared tests and Holm-Bonferroni adjustments for multiple comparisons.
118
Multivariable logistic regression was used to investigate the relationship between dependent variables
119
(FMS composite score [two levels: ≤14 and >14]; asymmetry [two levels: at least one asymmetrical
120
sub-test and no asymmetry]; pain [two levels: at least one painful sub-test after adjusting for clearing
121
test results and no pain]) and predictor variables (player position [four levels: midfield, forward,
122
defender and ruck]; previous injury [two levels: history of injury in previous season and no history of
123
injury in previous season]). Model evaluation was undertaken by comparison to the null model using
124
Chi-squared tests. The effect of individual predictor variables was assessed using Wald tests and
125
quantified using odds ratios (OR) and RR. Precision of effect estimates was quantified using 95%
126
confidence intervals (95%CI).
127
Results
128
Median FMS composite score was 14 (interquartile range 12-15). Sixty percent of players (n=182) had
129
FMS composite scores ≤14 (Table 1). Players were most likely to score 1 during the deep squat
130
(p<0.001; Fig. 1).
Ac ce pt e
d
M
an
us
cr
ip t
109
131
**** Insert Table 1 about here ****
132
**** Insert Fig. 1 about here ****
5
Page 6 of 18
Sixty-five percent of players (n=196) had at least one asymmetrical sub-test (Table 1). Shoulder
134
mobility had the highest proportion of asymmetry (p=0.005; Fig. 1). Rotary stability had the lowest
135
proportion of asymmetry (p=0.003; Fig. 1).
136
Thirty-eight percent of players (n=113) had at least one painful sub-test (Table 1). Pain was most
137
commonly reported during TSPU (p=0.024; Fig. 1). Players were least likely to report pain during
138
hurdle step (p<0.001), in-line lunge (p=0.005) and rotary stability (p=0.009) (Fig. 1).
139
Forty-two percent of players (n=126) reported sustaining at least one injury in the previous season
140
(Table 1). Likelihood of having a FMS composite score ≤14 was not affected by previous injury (OR
141
0.99, 95%CI 0.61-1.58; p=0.951) or player position (Forward: OR 1.47, 95%CI 0.78-2.81; Defender:
142
OR 0.91, 95%CI 0.49-1.69; Ruck: OR 1.88, 95%CI 0.84-4.52; Midfield: reference condition;
143
p=0.290) (supplementary material 1).
144
Likelihood of having at least one asymmetrical sub-test was not affected by previous injury (OR 1.13,
145
95%CI 0.70-1.83; p=0.629) or player position (Forward: OR 0.93, 95%CI 0.49-1.78; Defender: OR
146
0.83, 95%CI 0.44-1.59; Ruck: OR 0.83, 95%CI 0.38-1.87; Midfield: reference condition; p=0.930)
147
(supplementary material 2). The effect of asymmetry magnitude was not investigated because no
148
players had asymmetrical scoring of 3:1 for any sub-test.
149
Likelihood of reporting pain during at least one sub-test was not affected by player position (Forward:
150
OR 1.07, 95%CI 0.56-2.02; Defender: OR 1.36, 95%CI 0.72-2.56; Ruck: 1.04, 95%CI 0.46-2.28;
151
Midfield: reference condition; p=0.820; Table 2), and therefore player position was not included in the
152
final model. Likelihood of reporting pain during one or more sub-tests was affected by previous injury
153
(OR 1.97, 95%CI 1.23-3.18; p=0.005; Table 2). Previously injured players were 1.5 times more likely
154
to report pain during at least one sub-test (RR 1.52, 95%CI 1.14-2.03; p=0.005). Including previous
155
injury as a predictor of pain improved model fit (p=0.005; Table 2).
M
d
Ac ce pt e
156 157
an
us
cr
ip t
133
**** Insert Table 2 about here **** Discussion
6
Page 7 of 18
The purpose of this study was to describe the prevalence of dysfunctional, asymmetrical, and painful
159
movement in junior Australian Football players using the FMS. The effect of previous injury and
160
player position on FMS results was also assessed. Our findings indicate a high prevalence of
161
dysfunctional, asymmetrical, and painful movement, irrespective of player position. Consistent with
162
our hypothesis, painful movement was more common for players who experienced an injury during
163
the previous season. However, sustaining an injury in the previous season did not affect the prevalence
164
of dysfunctional or asymmetrical movement.
165
The FMS provides a simple field test for identifying athletes with dysfunctional, asymmetrical, and
166
painful movement. Simple and efficient tests are important for junior Australian Football clubs, which
167
do not have the personnel and resources for pre-season screening for injury prevention that are
168
available at elite senior clubs. The FMS could provide a method for junior Australian Football clubs to
169
identify athletes with dysfunctional movement, without relying on numerous isolated tests.18 However,
170
the validity of using the FMS to identify Australian Football players at increased risk of injury has yet
171
to be determined.
172
In the present study, there was no association between dysfunctional movement (FMS composite score
173
≤14) and injuries sustained by players in the previous season. Previous injury is a well established
174
predictor of future injury in Australian Football.8,14 Thus, our null finding might indicate that there is
175
no association between FMS composite scores and future injury in junior Australian Football.
176
Alternatively, our null finding might be explained by measurement bias associated with the
177
retrospective injury analysis. For example, players injured in the previous season might have been
178
more likely to receive treatments designed to correct dysfunctional movement. This could increase the
179
FMS composite scores of players with previous injuries and bias an association between dysfunctional
180
movement and previous injury. As a result, prospective follow-up of players after FMS testing is
181
needed to expand on our preliminary findings.
182
Prevalence of dysfunctional movement was greater in junior Australian Football players (60%) than
183
more-mature athletes (aged >18 years) from professional American Football (20%)19 and collegiate
184
sport (40%).20 Adult sporting competitions involve greater physical demands than junior
Ac ce pt e
d
M
an
us
cr
ip t
158
7
Page 8 of 18
competitions.27 This performance gap might disadvantage junior players with repeated injuries from
186
participating at higher levels.27 As a result, higher FMS composite scores in mature athletes might
187
result from junior athletes with dysfunctional movement getting injured and being less likely to
188
progress to senior competition. If correct, junior athletes may represent a population with large
189
potential to benefit from a validated movement screening protocol. To date, studies investigating if the
190
FMS can identify athletes at higher risk of injury have considered only adult athletes and have
191
reported inconsistent findings.21–23 Thus, the validity of using the FMS to determine injury risk in
192
junior athletes remains largely unclear.
193
A concerning finding from our study is the high percentage (38%) of junior players reporting pain
194
during FMS testing. In comparison, only 3% of recreational athletes (aged 18-40 years) reported pain
195
in the only other study to report the prevalence of pain using the FMS.28 The higher prevalence of pain
196
in our cohort could relate partly to the timing of testing, which occurred during the latter stages of pre-
197
season training. Training loads are often high during this stage of pre-season training and high training
198
loads can cause small increases in general muscle soreness.29 We did not quantify training load and the
199
FMS does not differentiate between pain and training-related soreness. However, we speculate that a
200
lower prevalence of pain might occur at the start of pre-season training, when training load is likely to
201
be lower. Understanding how changes in pre-season training load influence FMS results is an
202
important topic for ongoing research in this area.
203
Players reporting an injury in the previous season were 1.5 times more likely to experience pain during
204
FMS testing, despite identifying themselves as having no current injuries. We did not differentiate the
205
type of injuries sustained by players so it was not possible to determine if they were still experiencing
206
pain from injuries sustained during the previous season. However, we speculate that for some players
207
the reported pain was directly related to their previous injury and persisted due to insufficient
208
rehabilitation at the time of the injury. Conversely, for some players the reported pain might be
209
indirectly linked to previous injuries via adaptations throughout the kinetic-chain.12 If correct, the
210
FMS could provide a useful pre-season screening method to identify junior players that need
Ac ce pt e
d
M
an
us
cr
ip t
185
8
Page 9 of 18
additional clinical assessment of injuries sustained during the previous season. Further research using
212
more specific injury diagnoses is required to validate the use of the FMS in this manner.
213
The majority of junior Australian Football players (65%) demonstrated at least one asymmetrical
214
movement. Although the prevalence of asymmetrical movement has been investigated in American
215
Football,19 there are no other studies of junior Australian Football to compare. In our study, shoulder
216
mobility was the most commonly asymmetrical FMS sub-test. Shoulder joint function is important for
217
junior Australian Football players because shoulder injuries (in addition to knee injuries) cause the
218
greatest number of missed games.6 Future research should investigate how asymmetrical shoulder
219
mobility affects shoulder joint function and injury risk in junior Australian Football players.
220
The deep squat was the most commonly dysfunctional (score =1) FMS sub-test. This finding is in
221
agreement with previous research, which found the deep squat was one of the most commonly
222
dysfunctional FMS sub-tests in recreational athletes.28 The high prevalence of dysfunction with the
223
deep squat is concerning given the common use of squat movements in strength and conditioning
224
programs. Poor motor control or limited closed chain dorsiflexion of the ankles, extension of the
225
thoracic spine, and flexion of the hips can contribute to impaired (score =1) performance of the deep
226
squat.12
227
A limitation of our study was the use of only self-reported retrospective injury data, which could be
228
affected by recall bias.30 Although Australian Football players can recall whether or not they sustained
229
an injury during the previous season with 100% accuracy, they can only recall diagnostic injury
230
information with 61% accuracy.30 As a result, it was not possible to differentiate the type of injuries
231
sustained by players using our retrospective study design. Prospective studies are needed to provide
232
the diagnostic accuracy required to investigate relationships between FMS testing and different injury
233
types. A further limitation of our study was the broad comparison of midfield, forward, defender and
234
ruck groups. Greater differences between player positions may have occurred if the categories were
235
more specific (i.e. small forward/tall forward); however, these tactical roles often change at the junior
236
level in line with team strategy and the ongoing physical maturation of players.
237
Conclusion
Ac ce pt e
d
M
an
us
cr
ip t
211
9
Page 10 of 18
The high prevalence of dysfunctional, asymmetrical, and painful movement in junior Australian
239
Football players suggests that prospective studies investigating the strength of association between
240
FMS findings and injury are warranted. Additionally, the high prevalence of pain reported by players
241
suggests that identifying the cause of this pain and developing interventions to reduce its prevalence
242
should be priorities for researchers, coaches and medical professionals working in junior Australian
243
Football competitions.
244
Practical implications
246
Players reporting an injury during the previous season were more likely to experience pain during FMS testing.
250 251
us
asymmetrical, and painful movement during FMS testing.
248 249
Junior Australian Football players demonstrate a high prevalence of dysfunctional,
an
247
There was no association between FMS composite scores and injuries sustained during the previous season.
cr
M
245
ip t
238
Players were most likely to perform poorly during the deep squat sub-test. Poor motor control or limited closed chain dorsiflexion of the ankles, extension of the thoracic spine, and flexion
253
of the hips might contribute to poor performance of the deep squat.
Ac ce pt e
d
252
254
Acknowledgements
255
The authors would like to acknowledge the support of the South Australian National Football League
256
and the High Performance Manager Brenton Phillips. Furthermore, we acknowledge the valuable
257
technical assistance of Steven Milanese during the preparation of the manuscript. All authors declare
258
no conflicts of interest and have no financial or other interests in the Functional Movement Screen or
259
Functional Movement Systems Inc. No financial assistance was obtained for the study.
10
Page 11 of 18
260
References
261
1.
262
of data in the Australian Football League. Am J Sports Med 2013; 41(4):734–41. 2.
264
forward? Phys Ther Sport 2013; 14(3):175–182. 3.
266 267
Gabbe BJ, Finch CF, Cameron PA. Priorities for reducing the burden of injuries in sport: the example of Australian football. J Sci Med Sport 2007; 10(5):273–276.
4.
ip t
265
Chalmers S, Magarey ME, Scase E. Junior Australian football injury research: are we moving
cr
263
Orchard JW, Seward H, Orchard JJ. Results of 2 decades of injury surveillance and public release
Ekegren CL, Gabbe BJ, Finch CF. Medical-attention injuries in community Australian football: a review of 30 years of surveillance data from treatment sources. Clin J Sport Med 2015;
269
25(2):162–172.
271
J Sci Med Sport 2001; 4(4):386–395. 6.
273 274
Scase E, Magarey ME, Chalmers S, et al. The epidemiology of injury for an elite junior
M
272
Gabbe B, Finch C. A profile of Australian football injuries presenting to sports medicine clinics.
an
5.
Australian Football cohort. J Sci Med Sport 2012; 15(3):207–212. 7.
Australian
Bureau
of
Statistics.
Football:
d
270
us
268
four
games,
one
name.
Available
at:
http://www.abs.gov.au/AUSSTATS/[email protected]/Lookup/4156.0.55.001Feature+Article1May%202
276
009. Accesed 29 August 2015.
277
8.
Ac ce pt e
275
Gabbe BJ, Bailey M, Cook JL, et al. The association between hip and groin injuries in the elite
278
junior football years and injuries sustained during elite senior competition. Br J Sports Med 2010;
279
44(11):799–802.
280 281 282 283
9.
Scase E, Cook J, Makdissi M, et al. Teaching landing skills in elite junior Australian football: evaluation of an injury prevention strategy. Br J Sports Med 2006; 40(10):834–838.
10. Cameron M, Adams R, Maher C. Motor control and strength as predictors of hamstring injury in elite players of Australian football. Phys Ther Sport 2003; 4(4):159–166.
284
11. Crow JF, Pearce AJ, Veale JP, et al. Hip adductor muscle strength is reduced preceding and
285
during the onset of groin pain in elite junior Australian football players. J Sci Med Sport 2010;
286
13(2):202–204.
11
Page 12 of 18
287
12. Cook G, Burton L, Hoogenboom B, Voight M. Functional movement screening: the use of
288
fundamental movements as an assessment of function – part 1. Int J Sports Phys Ther 2014;
289
9(3):396–409. 13. Plisky PJ, Rauh MJ, Kaminski TW, et al. Star excursion balance test as a predictor of lower
291
extremity injury in high school basketball players. J Orthop Sports Phys Ther 2006; 36(12):911–
292
919.
298 299 300 301 302 303 304 305
cr
us
297
J Sports Med 2001; 35(6):418–23.
16. Brumitt J, Heiderscheit BC, Manske RC, et al. Lower extremity functional tests and risk of injury
an
296
15. Norton K, Schwerdt S, Lange K. Evidence for the aetiology of injuries in Australian football. Br
in division III collegiate athletes. Int J Sports Phys Ther 2013; 8(3):216–227. 17. Frohm A, Heijne A, Kowalski J, et al. A nine-test screening battery for athletes: a reliability
M
295
community level of Australian football. Clin J Sport Med 2004; 14(2):56–63.
study. Scand J Med Sci Sports 2012; 22(3):306–315.
18. Kiesel K, Plisky PJ, Voight ML. Can serious injury in professional football be predicted by a
d
294
14. Gabbe BJ, Finch CF, Wajswelner H, et al. Predictors of lower extremity injuries at the
preseason functional movement screen? N Am J Sports Phys Ther 2007; 2(3):147–158.
Ac ce pt e
293
ip t
290
19. 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(2):88–94. 20. Chorba RS, Chorba DJ, Bouillon LE, et al. Use of a functional movement screening tool to
306
determine injury risk in female collegiate athletes. N Am J Sports Phys Ther 2010; 5(2):47–54.
307
21. Wiese BW, Boone JK, Gino MC, et al. Determination of the functional movement screen to
308
predict musculoskeletal injury in intercollegiate athletics. Athl Train Sport Health Care 2014;
309
6(4):161–169.
310
22. Garrison M, Westrick R, Johnson MR, et al. Association between the functional movement
311
screen and injury development in college athletes. Int J Sports Phys Ther 2015; 10(1):21–28.
312
23. Warren M, Smith CA, Chimera NJ. Association of the functional movement screen with injuries
313
in division I athletes. J Sport Rehabil 2015; 24(2):163–170.
12
Page 13 of 18
314 315
24. Colby MJ, Dawson B, Heasman J, et al. Accelerometer and GPS-derived running loads and injury risk in elite Australian footballers. J Strength Cond Res 2014; 28(8):2244–2252.
316
25. Moran RW, Schneiders AG, Major KM, et al. How reliable are functional movement screening
317
scores? A systematic review of rater reliability. Br J Sports Med 2015; doi:10.1136/bjsports-
318
2015-094913. 26. Cook G, Burton L, Hoogenboom B, Voight M. Functional movement screening: the use of
320
fundamental movements as an assessment of function – part 2. Int J Sports Phys Ther 2014;
321
9(4):549–563.
324 325
cr
us
323
27. Burgess D, Naughton G, Norton K. Quantifying the gap between under 18 and senior AFL football: 2003 and 2009. Int J Sports Physiol Perform 2012; 7(1):53–58.
28. Schneiders AG, Davidsson A, Hörman E, et al. Functional movement screen normative values in
an
322
ip t
319
a young, active population. Int J Sports Phys Ther 2011; 6(2):75–82. 29. Montgomery PG, Hopkins WG. The effects of game and training loads on perceptual responses
327
of muscle soreness in Australian Football. Int J Sports Physiol Perform 2013; 8(3):312-318.
328
30. Gabbe BJ, Finch CF, Bennell KL, et al. How valid is a self reported 12 month sports injury
d
history? Br J Sports Med 2003; 37(6):545–547.
Ac ce pt e
329
M
326
13
Page 14 of 18
330
Figure legend
331
Fig. 1. Proportion of players that scored 1, were asymmetrical, or reported pain for each of the
332
Functional Movement Screen sub-tests. Error bars represent 95% confidence intervals. * Deep squat
333
and trunk stability push-up sub-tests are not unilateral tests and do not provide information about
334
asymmetry.
335
squat, hurdle step, in-line lunge, active straight leg raise and rotary stability. c Greater proportion than
336
in-line lunge, shoulder mobility, trunk stability push-up and rotary stability (p<0.05).
337
proportion than all other sub-tests (p<0.05). e Greater proportion than in-line lunge (p<0.05). f Lower
338
proportion than deep squat, shoulder mobility, active straight leg raise and trunk stability push-up
339
(p<0.05).
Greater proportion than all other sub-tests (p<0.05).
b
Greater proportion than deep
ip t
a
Lower
Ac ce pt e
d
M
an
us
cr
d
14
Page 15 of 18
cr
ip t
Table 1
Ac c
ep te
d
M
an
us
Table 1. The effect of player position and injury on Functional Movement Screen composite score, asymmetry, and pain. Total FMS score ≤14 ≥1 Asymmetry ≥1 Painful test Previous Injury (n) (% Total) (% Total) (% Total) (% Total) All players 301 182(60%) 196(65%) 113(38%) 126(42%) Midfield 156 90(58%) 104(67%) 56(36%) 66(42%) Forward 57 38(67%) 37(65%) 21(37%) 22(39%) Defender 56 31(55%) 35(63%) 24(43%) 23(41%) Ruck 32 23(72%) 20(63%) 12(38%) 15(47%) Previous injury Yes 126 56(44%) 84(67%) 59(47%) a – No 175 73(42%) 112(64%) 54(31%) – a Increased likelihood of having at least one painful sub-test when compared to players with no previous injury (Relative Risk: 1.52; 95% confidence interval: 1.14-2.03; p=0.005).
Page 16 of 18
cr
ip t
Table 2
Ac c
ep te
d
M
an
us
Table 2. Multivariable logistic regression analysis of pain reported during the Functional Movement Screen. Predictor Coefficient (β) SE (β) Wald’s χ 2 df p OR (95%CI) Model 1 Intercept -0.885 0.204 4.344 1 <0.01 NA Player position Midfield Ref. Ref. Ref. Ref. Ref. Ref. Forward 0.068 0.326 0.209 1 0.83 1.07 (0.56-2.02) Defender 0.309 0.322 0.960 1 0.34 1.36 (0.72-2.56) Ruck 0.039 0.407 0.095 1 0.92 1.04 (0.46-2.28) Previous injury No Ref. Ref. Ref. Ref. Ref. Ref. Yes 0.685 0.243 2.818 1 <0.01 1.98 (1.23-3.20) Model evaluation vs. Null model 8.869 4 0.06 Model 2 Intercept -0.807 0.164 4.930 1 <0.01 NA Previous injury No Ref. Ref. Ref. Ref. Ref. Ref. Yes 0.680 0.242 2.806 1 <0.01 1.97 (1.23-3.18) Model evaluation vs. Null model 7.940 1 <0.01 95%CI, 95% confidence interval; df, degrees of freedom; NA, not applicable; OR, odds ratio; SE, standard error; Ref., reference condition; vs., versus.
Page 17 of 18
Ac
ce
pt
ed
M
an
us
cr
i
Figure(s)
Page 18 of 18
S1440-2440(16)30064-0 http://dx.doi.org/doi:10.1016/j.jsams.2016.05.003 JSAMS 1329
To appear in:
Journal of Science and Medicine in Sport
Received date: Revised date: Accepted date:
5-11-2015 18-4-2016 13-5-2016
Please cite this article as: Fuller JT, Chalmers S, Debenedictis TA, Townsley S, Lynagh M, Gleeson C, Zacharia A, Thomson S, Magarey M, High prevalence of dysfunctional, asymmetrical, and painful movement in elite junior Australian Football players assessed using the Functional Movement Screen, Journal of Science and Medicine in Sport (2016), http://dx.doi.org/10.1016/j.jsams.2016.05.003 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting proof before it is published in its final form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
*Title page (including all author details and affiliations)
1
High prevalence of dysfunctional, asymmetrical, and painful movement in elite junior
2
Australian Football players assessed using the Functional Movement Screen
3 4
Joel T. Fuller a, Samuel Chalmers a,b, Thomas A. Debenedictis a, Samuel Townsley a, Matthew
5
Lynagh a, Cara Gleeson a, Andrew Zacharia a, Stuart Thomson a & Mary Magarey a
a
Alliance for Research in Exercise, Nutrition and Activity (ARENA), Sansom Institute for Health
8 b
cr
9
Research, University of South Australia, Adelaide, SA, Australia
Sport and Exercise Science, School of Science and Health, Western Sydney University, NSW,
10
Australia
12
an
11
us
7
ip t
6
Corresponding author: Joel Fuller
14
Alliance for Research in Exercise, Nutrition and Activity
15
University of South Australia
16
GPO Box 2471, Adelaide SA 5001 Australia
17
Ac ce pt e
d
M
13
E-mail: [email protected]
18
Phone: +61 8 8302 2097
19 20
Word Count: 3,000 words (not counting phrases “Insert Table X about here” or “Insert Fig. X about
21
here”)
22
Abstract Word Count: 250 words
23
References: 30
24
Number of Tables: 2
25
Number of Figures: 1
1
Page 1 of 18
1
High prevalence of dysfunctional, asymmetrical, and painful movement in elite junior
2
Australian Football players assessed using the Functional Movement Screen
3 Abstract
5
Objectives: The purpose of this study was to describe the prevalence of dysfunctional, asymmetrical,
6
and painful movement in junior Australian Football players using the Functional Movement Screen
7
(FMS).
8
Design: Cross-sectional study.
9
Methods: Elite junior male Australian Football players (n=301) aged 15-18 years completed pre-
10
season FMS testing. The FMS consists of 7 sub-tests: deep squat, hurdle step, in-line lunge, shoulder
11
mobility, active straight leg raise, trunk stability push-up (TSPU) and rotary stability. The shoulder
12
mobility, TSPU, and rotary stability tests were combined with an accompanying clearing test to assess
13
pain. Each sub-test was scored on an ordinal scale from 0-3 and summed to give a composite score out
14
of 21. Composite scores ≤14 were operationally defined as indicating dysfunctional movement.
15
Players scoring differently on left and right sides were considered asymmetrical. Players reported
16
whether they missed any games due to injury in the preceding 22 game season.
17
Results: Sixty percent of players (n=182) had composite scores ≤14, 65% of players (n=196) had at
18
least one asymmetrical sub-test, and 38% of players (n=113) had at least one painful sub-test. Forty-
19
two percent of players (n=126) missed at least one game in the previous season due to injury. Previous
20
injury did not influence composite score (p=0.951) or asymmetry (p=0.629). Players reporting an
21
injury during the previous season were more likely to experience pain during FMS testing (odds ratio
22
1.97, 95% confidence interval 1.23 to 3.18; p=0.005).
23
Conclusions: Junior Australian Football players demonstrate a high prevalence of dysfunctional,
24
asymmetrical, and painful movement during FMS testing.
Ac ce pt e
d
M
an
us
cr
ip t
4
25 26
Keywords
27
Injury prevention; athletic injuries; risk factors; exercise test; adolescent
1
Page 2 of 18
Introduction
29
Australian Football has a high incidence of contact and non-contact injuries in both junior and senior
30
competitions.1,2 Injuries from Australian Football cause more hospital admissions and health insurance
31
claims than any other sport in Australia.3 The high number of hospital admissions resulting from
32
participation in Australian Football can be largely attributed to the contact nature of the sport. 4
33
However, non-contact injuries still account for 30-50% of Australian Football injuries presenting to
34
sports medicine clinics.5,6 To date, the majority of injury prevention research in Australian Football
35
has focused on senior players.1 Less research is available for junior players despite participation rates
36
being highest in the 15-17 year age range.6,7 Injury prevention measures are important in junior
37
Australian Football because players that sustain injuries in junior competition are more likely to
38
sustain injuries when they transition to senior level competition.8
39
Dysfunctional movement is one injury risk factor that could be important for the prevention of injuries
40
in junior Australian Football.9–11 For example, poor strength might increase the risk of muscle strain,10
41
poor mobility in one joint might cause excessive mobility at another joint,12 and poor balance might
42
result in poor landing strategies.13 The current research approach to movement testing in junior
43
Australian Football uses isolated movement tests to identify dysfunction with a specific muscle or
44
joint.11 This approach has proven useful for identifying players at high risk of certain injuries (e.g.
45
groin injury11), but does not provide an indication of the overall risk of sustaining the broad range of
46
injuries that occur in Australian Football.14 For example, reduced isometric hip adductor strength
47
indicates increased likelihood of groin pain in junior Australian Football players 11 but provides
48
minimal insight concerning the risk of injury in other body areas. Additionally, testing only one
49
movement quality (i.e. isometric hip adductor strength) ignores other movement qualities (mobility,
50
balance, etc.) that may contribute to the multifactorial nature of Australian Football injuries. 15
51
There is a growing trend for injury prevention screening to involve compound movements that test
52
multiple movement qualities (e.g. strength, mobility and balance) at the same time.13,16,17 One example
53
is the Functional Movement Screen (FMS), which consists of seven sub-tests that are suggested to
54
represent fundamental movement patterns.12 It has been hypothesised that the FMS can identify
Ac ce pt e
d
M
an
us
cr
ip t
28
2
Page 3 of 18
athletes with poor movement qualities using only these seven sub-tests.18 Poor movement quality
56
during FMS testing has been suggested as a risk factor for injury. 18 If valid, field-based tests such as
57
the FMS could be useful in team sports such as junior Australian Football, which involve large player
58
numbers and only limited access to medical personnel capable of performing numerous isolated
59
movement tests.
60
The presence of dysfunctional movement during FMS testing is a risk factor for injury (contact and
61
non-contact) in professional American Football (relative risk [RR]=1.9-4.2)18,19 and collegiate soccer,
62
volleyball and basketball (RR=1.9).20 Asymmetrical movement during FMS testing is also a risk factor
63
for injury in professional American Football (RR=1.8).19 In contrast, the presence of dysfunctional
64
movement during FMS testing is not a risk factor for injury in collegiate American Football.21
65
Additionally, Garrison et al.22 (RR=2.2), but not Warren et al.23 (RR=1.0), found that FMS movement
66
dysfunction was an injury risk factor for athletes participating in collegiate rugby, tennis, swimming,
67
diving, track and field, cross country, and golf. As a result, both the type of sport and level of
68
competition appear to be important to the validity of the FMS.
69
The FMS shows promise as a method for identifying athletes at high risk of injury but has not been
70
investigated in Australian Football. Australian Football is a unique sport involving multiple player
71
positions, which collectively involve similar physical demands and technical kicking skills to soccer,
72
similar full-body tackling to American Football, and similar technical hand passing skills to basketball
73
and volleyball.24 The movement and injury profiles of Australian Football are likely to differ from
74
other sports used in FMS research. Therefore, the purpose of this study was to describe the prevalence
75
of dysfunctional, asymmetrical, and painful movement in junior Australian Football players using the
76
FMS. The effect of player position and previous injury on FMS testing was also investigated. It was
77
hypothesised that dysfunctional, asymmetrical, and painful movement would be more prevalent in
78
players that missed at least one game due to injury in the previous season.
79
Methods
80
A total of 301 male players (age: 17 ± 1 years; body mass: 74 ± 9 kg; height: 181 ± 7 cm) were
81
recruited from eight elite junior (under 18 years) clubs competing in the Under-18 South Australian
Ac ce pt e
d
M
an
us
cr
ip t
55
3
Page 4 of 18
National Football League (SANFL). Players (including parent or guardian) provided written informed
83
consent to participate in this study, which had institutional ethical approval. Players were excluded if
84
they reported a current physical impairment that prevented participation in routine club training
85
sessions. All testing was completed during the annual pre-season SANFL fitness testing combine.
86
Participants reported their current playing position, and whether they missed at least one game due to
87
injury in the preceding 22 game season. Only injuries resulting from participation in Australian
88
Football or training were considered. This injury definition is consistent with previous research in
89
junior Australian Football6 and the Australian Football League injury surveillance program.1 Player
90
positions were: midfielder, forward, defender, or ruck. Six qualified physiotherapists and one strength
91
and conditioning coach were responsible for FMS testing. To reduce errors associated with multiple
92
raters, each tester completed a level one FMS training course and was responsible for assessing a
93
separate FMS sub-test. Testing was performed using standard FMS Test Kits (Functional Movement
94
Systems Inc., Virginia, USA). The FMS has acceptable inter- and intra-rater reliability for composite
95
scores.25
96
Warm-up activities were organised by fitness staff from each SANFL club. The FMS consists of 7
97
sub-tests.12,26 These tests were the deep squat, hurdle step, in-line lunge, shoulder mobility, active
98
straight leg raise (ASLR), trunk stability push-up (TSPU) and rotary stability. The hurdle step, in-line
99
lunge, shoulder mobility, ASLR and rotary stability tests were completed for left and right sides. The
100
shoulder mobility, TSPU and rotary stability tests were combined with an accompanying clearing test
101
to assess pain. These clearing tests were the shoulder combined internal rotation and flexion test, the
102
end-range spinal extension test and the end-range spinal flexion test, respectively. Detailed
103
descriptions of FMS sub-tests have been reported previously.12,26
104
Each FMS sub-tests was scored on an ordinal scale from 0-3.12,26 A score of 3 was given when players
105
completed the sub-test without compensatory movement. A score of 2 was given when players
106
completed the sub-test, but used one or more compensatory movements. A score of 1 was given when
107
players were unable to complete the sub-test. At the completion of each sub-test players were asked if
108
they experienced pain anywhere in the body at any time during the test. A score of 0 was given when
Ac ce pt e
d
M
an
us
cr
ip t
82
4
Page 5 of 18
players reported pain of any kind during the sub-test or the accompanying clearing test. For sub-tests
110
completed on left and right sides, the overall score was the lowest score from the two sides. A sub-test
111
score of 1 indicated dysfunction with the associated movement. Scores for each sub-test were summed
112
to give a composite score out of 21, after adjusting for clearing test results. We established a-priori
113
that a FMS composite score of ≤14 (as reported in other studies) would be used to group players.18,20,22
114
All statistical analysis was performed in R 3.2.1 (R Foundation for Statistical Computing, Vienna,
115
Austria). Statistical significance was assumed for p<0.05. The proportion of players who scored 1,
116
were asymmetrical (left ≠ right), or reported pain (score = 0) were compared across the seven sub-
117
tests using Chi-squared tests and Holm-Bonferroni adjustments for multiple comparisons.
118
Multivariable logistic regression was used to investigate the relationship between dependent variables
119
(FMS composite score [two levels: ≤14 and >14]; asymmetry [two levels: at least one asymmetrical
120
sub-test and no asymmetry]; pain [two levels: at least one painful sub-test after adjusting for clearing
121
test results and no pain]) and predictor variables (player position [four levels: midfield, forward,
122
defender and ruck]; previous injury [two levels: history of injury in previous season and no history of
123
injury in previous season]). Model evaluation was undertaken by comparison to the null model using
124
Chi-squared tests. The effect of individual predictor variables was assessed using Wald tests and
125
quantified using odds ratios (OR) and RR. Precision of effect estimates was quantified using 95%
126
confidence intervals (95%CI).
127
Results
128
Median FMS composite score was 14 (interquartile range 12-15). Sixty percent of players (n=182) had
129
FMS composite scores ≤14 (Table 1). Players were most likely to score 1 during the deep squat
130
(p<0.001; Fig. 1).
Ac ce pt e
d
M
an
us
cr
ip t
109
131
**** Insert Table 1 about here ****
132
**** Insert Fig. 1 about here ****
5
Page 6 of 18
Sixty-five percent of players (n=196) had at least one asymmetrical sub-test (Table 1). Shoulder
134
mobility had the highest proportion of asymmetry (p=0.005; Fig. 1). Rotary stability had the lowest
135
proportion of asymmetry (p=0.003; Fig. 1).
136
Thirty-eight percent of players (n=113) had at least one painful sub-test (Table 1). Pain was most
137
commonly reported during TSPU (p=0.024; Fig. 1). Players were least likely to report pain during
138
hurdle step (p<0.001), in-line lunge (p=0.005) and rotary stability (p=0.009) (Fig. 1).
139
Forty-two percent of players (n=126) reported sustaining at least one injury in the previous season
140
(Table 1). Likelihood of having a FMS composite score ≤14 was not affected by previous injury (OR
141
0.99, 95%CI 0.61-1.58; p=0.951) or player position (Forward: OR 1.47, 95%CI 0.78-2.81; Defender:
142
OR 0.91, 95%CI 0.49-1.69; Ruck: OR 1.88, 95%CI 0.84-4.52; Midfield: reference condition;
143
p=0.290) (supplementary material 1).
144
Likelihood of having at least one asymmetrical sub-test was not affected by previous injury (OR 1.13,
145
95%CI 0.70-1.83; p=0.629) or player position (Forward: OR 0.93, 95%CI 0.49-1.78; Defender: OR
146
0.83, 95%CI 0.44-1.59; Ruck: OR 0.83, 95%CI 0.38-1.87; Midfield: reference condition; p=0.930)
147
(supplementary material 2). The effect of asymmetry magnitude was not investigated because no
148
players had asymmetrical scoring of 3:1 for any sub-test.
149
Likelihood of reporting pain during at least one sub-test was not affected by player position (Forward:
150
OR 1.07, 95%CI 0.56-2.02; Defender: OR 1.36, 95%CI 0.72-2.56; Ruck: 1.04, 95%CI 0.46-2.28;
151
Midfield: reference condition; p=0.820; Table 2), and therefore player position was not included in the
152
final model. Likelihood of reporting pain during one or more sub-tests was affected by previous injury
153
(OR 1.97, 95%CI 1.23-3.18; p=0.005; Table 2). Previously injured players were 1.5 times more likely
154
to report pain during at least one sub-test (RR 1.52, 95%CI 1.14-2.03; p=0.005). Including previous
155
injury as a predictor of pain improved model fit (p=0.005; Table 2).
M
d
Ac ce pt e
156 157
an
us
cr
ip t
133
**** Insert Table 2 about here **** Discussion
6
Page 7 of 18
The purpose of this study was to describe the prevalence of dysfunctional, asymmetrical, and painful
159
movement in junior Australian Football players using the FMS. The effect of previous injury and
160
player position on FMS results was also assessed. Our findings indicate a high prevalence of
161
dysfunctional, asymmetrical, and painful movement, irrespective of player position. Consistent with
162
our hypothesis, painful movement was more common for players who experienced an injury during
163
the previous season. However, sustaining an injury in the previous season did not affect the prevalence
164
of dysfunctional or asymmetrical movement.
165
The FMS provides a simple field test for identifying athletes with dysfunctional, asymmetrical, and
166
painful movement. Simple and efficient tests are important for junior Australian Football clubs, which
167
do not have the personnel and resources for pre-season screening for injury prevention that are
168
available at elite senior clubs. The FMS could provide a method for junior Australian Football clubs to
169
identify athletes with dysfunctional movement, without relying on numerous isolated tests.18 However,
170
the validity of using the FMS to identify Australian Football players at increased risk of injury has yet
171
to be determined.
172
In the present study, there was no association between dysfunctional movement (FMS composite score
173
≤14) and injuries sustained by players in the previous season. Previous injury is a well established
174
predictor of future injury in Australian Football.8,14 Thus, our null finding might indicate that there is
175
no association between FMS composite scores and future injury in junior Australian Football.
176
Alternatively, our null finding might be explained by measurement bias associated with the
177
retrospective injury analysis. For example, players injured in the previous season might have been
178
more likely to receive treatments designed to correct dysfunctional movement. This could increase the
179
FMS composite scores of players with previous injuries and bias an association between dysfunctional
180
movement and previous injury. As a result, prospective follow-up of players after FMS testing is
181
needed to expand on our preliminary findings.
182
Prevalence of dysfunctional movement was greater in junior Australian Football players (60%) than
183
more-mature athletes (aged >18 years) from professional American Football (20%)19 and collegiate
184
sport (40%).20 Adult sporting competitions involve greater physical demands than junior
Ac ce pt e
d
M
an
us
cr
ip t
158
7
Page 8 of 18
competitions.27 This performance gap might disadvantage junior players with repeated injuries from
186
participating at higher levels.27 As a result, higher FMS composite scores in mature athletes might
187
result from junior athletes with dysfunctional movement getting injured and being less likely to
188
progress to senior competition. If correct, junior athletes may represent a population with large
189
potential to benefit from a validated movement screening protocol. To date, studies investigating if the
190
FMS can identify athletes at higher risk of injury have considered only adult athletes and have
191
reported inconsistent findings.21–23 Thus, the validity of using the FMS to determine injury risk in
192
junior athletes remains largely unclear.
193
A concerning finding from our study is the high percentage (38%) of junior players reporting pain
194
during FMS testing. In comparison, only 3% of recreational athletes (aged 18-40 years) reported pain
195
in the only other study to report the prevalence of pain using the FMS.28 The higher prevalence of pain
196
in our cohort could relate partly to the timing of testing, which occurred during the latter stages of pre-
197
season training. Training loads are often high during this stage of pre-season training and high training
198
loads can cause small increases in general muscle soreness.29 We did not quantify training load and the
199
FMS does not differentiate between pain and training-related soreness. However, we speculate that a
200
lower prevalence of pain might occur at the start of pre-season training, when training load is likely to
201
be lower. Understanding how changes in pre-season training load influence FMS results is an
202
important topic for ongoing research in this area.
203
Players reporting an injury in the previous season were 1.5 times more likely to experience pain during
204
FMS testing, despite identifying themselves as having no current injuries. We did not differentiate the
205
type of injuries sustained by players so it was not possible to determine if they were still experiencing
206
pain from injuries sustained during the previous season. However, we speculate that for some players
207
the reported pain was directly related to their previous injury and persisted due to insufficient
208
rehabilitation at the time of the injury. Conversely, for some players the reported pain might be
209
indirectly linked to previous injuries via adaptations throughout the kinetic-chain.12 If correct, the
210
FMS could provide a useful pre-season screening method to identify junior players that need
Ac ce pt e
d
M
an
us
cr
ip t
185
8
Page 9 of 18
additional clinical assessment of injuries sustained during the previous season. Further research using
212
more specific injury diagnoses is required to validate the use of the FMS in this manner.
213
The majority of junior Australian Football players (65%) demonstrated at least one asymmetrical
214
movement. Although the prevalence of asymmetrical movement has been investigated in American
215
Football,19 there are no other studies of junior Australian Football to compare. In our study, shoulder
216
mobility was the most commonly asymmetrical FMS sub-test. Shoulder joint function is important for
217
junior Australian Football players because shoulder injuries (in addition to knee injuries) cause the
218
greatest number of missed games.6 Future research should investigate how asymmetrical shoulder
219
mobility affects shoulder joint function and injury risk in junior Australian Football players.
220
The deep squat was the most commonly dysfunctional (score =1) FMS sub-test. This finding is in
221
agreement with previous research, which found the deep squat was one of the most commonly
222
dysfunctional FMS sub-tests in recreational athletes.28 The high prevalence of dysfunction with the
223
deep squat is concerning given the common use of squat movements in strength and conditioning
224
programs. Poor motor control or limited closed chain dorsiflexion of the ankles, extension of the
225
thoracic spine, and flexion of the hips can contribute to impaired (score =1) performance of the deep
226
squat.12
227
A limitation of our study was the use of only self-reported retrospective injury data, which could be
228
affected by recall bias.30 Although Australian Football players can recall whether or not they sustained
229
an injury during the previous season with 100% accuracy, they can only recall diagnostic injury
230
information with 61% accuracy.30 As a result, it was not possible to differentiate the type of injuries
231
sustained by players using our retrospective study design. Prospective studies are needed to provide
232
the diagnostic accuracy required to investigate relationships between FMS testing and different injury
233
types. A further limitation of our study was the broad comparison of midfield, forward, defender and
234
ruck groups. Greater differences between player positions may have occurred if the categories were
235
more specific (i.e. small forward/tall forward); however, these tactical roles often change at the junior
236
level in line with team strategy and the ongoing physical maturation of players.
237
Conclusion
Ac ce pt e
d
M
an
us
cr
ip t
211
9
Page 10 of 18
The high prevalence of dysfunctional, asymmetrical, and painful movement in junior Australian
239
Football players suggests that prospective studies investigating the strength of association between
240
FMS findings and injury are warranted. Additionally, the high prevalence of pain reported by players
241
suggests that identifying the cause of this pain and developing interventions to reduce its prevalence
242
should be priorities for researchers, coaches and medical professionals working in junior Australian
243
Football competitions.
244
Practical implications
246
Players reporting an injury during the previous season were more likely to experience pain during FMS testing.
250 251
us
asymmetrical, and painful movement during FMS testing.
248 249
Junior Australian Football players demonstrate a high prevalence of dysfunctional,
an
247
There was no association between FMS composite scores and injuries sustained during the previous season.
cr
M
245
ip t
238
Players were most likely to perform poorly during the deep squat sub-test. Poor motor control or limited closed chain dorsiflexion of the ankles, extension of the thoracic spine, and flexion
253
of the hips might contribute to poor performance of the deep squat.
Ac ce pt e
d
252
254
Acknowledgements
255
The authors would like to acknowledge the support of the South Australian National Football League
256
and the High Performance Manager Brenton Phillips. Furthermore, we acknowledge the valuable
257
technical assistance of Steven Milanese during the preparation of the manuscript. All authors declare
258
no conflicts of interest and have no financial or other interests in the Functional Movement Screen or
259
Functional Movement Systems Inc. No financial assistance was obtained for the study.
10
Page 11 of 18
260
References
261
1.
262
of data in the Australian Football League. Am J Sports Med 2013; 41(4):734–41. 2.
264
forward? Phys Ther Sport 2013; 14(3):175–182. 3.
266 267
Gabbe BJ, Finch CF, Cameron PA. Priorities for reducing the burden of injuries in sport: the example of Australian football. J Sci Med Sport 2007; 10(5):273–276.
4.
ip t
265
Chalmers S, Magarey ME, Scase E. Junior Australian football injury research: are we moving
cr
263
Orchard JW, Seward H, Orchard JJ. Results of 2 decades of injury surveillance and public release
Ekegren CL, Gabbe BJ, Finch CF. Medical-attention injuries in community Australian football: a review of 30 years of surveillance data from treatment sources. Clin J Sport Med 2015;
269
25(2):162–172.
271
J Sci Med Sport 2001; 4(4):386–395. 6.
273 274
Scase E, Magarey ME, Chalmers S, et al. The epidemiology of injury for an elite junior
M
272
Gabbe B, Finch C. A profile of Australian football injuries presenting to sports medicine clinics.
an
5.
Australian Football cohort. J Sci Med Sport 2012; 15(3):207–212. 7.
Australian
Bureau
of
Statistics.
Football:
d
270
us
268
four
games,
one
name.
Available
at:
http://www.abs.gov.au/AUSSTATS/[email protected]/Lookup/4156.0.55.001Feature+Article1May%202
276
009. Accesed 29 August 2015.
277
8.
Ac ce pt e
275
Gabbe BJ, Bailey M, Cook JL, et al. The association between hip and groin injuries in the elite
278
junior football years and injuries sustained during elite senior competition. Br J Sports Med 2010;
279
44(11):799–802.
280 281 282 283
9.
Scase E, Cook J, Makdissi M, et al. Teaching landing skills in elite junior Australian football: evaluation of an injury prevention strategy. Br J Sports Med 2006; 40(10):834–838.
10. Cameron M, Adams R, Maher C. Motor control and strength as predictors of hamstring injury in elite players of Australian football. Phys Ther Sport 2003; 4(4):159–166.
284
11. Crow JF, Pearce AJ, Veale JP, et al. Hip adductor muscle strength is reduced preceding and
285
during the onset of groin pain in elite junior Australian football players. J Sci Med Sport 2010;
286
13(2):202–204.
11
Page 12 of 18
287
12. Cook G, Burton L, Hoogenboom B, Voight M. Functional movement screening: the use of
288
fundamental movements as an assessment of function – part 1. Int J Sports Phys Ther 2014;
289
9(3):396–409. 13. Plisky PJ, Rauh MJ, Kaminski TW, et al. Star excursion balance test as a predictor of lower
291
extremity injury in high school basketball players. J Orthop Sports Phys Ther 2006; 36(12):911–
292
919.
298 299 300 301 302 303 304 305
cr
us
297
J Sports Med 2001; 35(6):418–23.
16. Brumitt J, Heiderscheit BC, Manske RC, et al. Lower extremity functional tests and risk of injury
an
296
15. Norton K, Schwerdt S, Lange K. Evidence for the aetiology of injuries in Australian football. Br
in division III collegiate athletes. Int J Sports Phys Ther 2013; 8(3):216–227. 17. Frohm A, Heijne A, Kowalski J, et al. A nine-test screening battery for athletes: a reliability
M
295
community level of Australian football. Clin J Sport Med 2004; 14(2):56–63.
study. Scand J Med Sci Sports 2012; 22(3):306–315.
18. Kiesel K, Plisky PJ, Voight ML. Can serious injury in professional football be predicted by a
d
294
14. Gabbe BJ, Finch CF, Wajswelner H, et al. Predictors of lower extremity injuries at the
preseason functional movement screen? N Am J Sports Phys Ther 2007; 2(3):147–158.
Ac ce pt e
293
ip t
290
19. 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(2):88–94. 20. Chorba RS, Chorba DJ, Bouillon LE, et al. Use of a functional movement screening tool to
306
determine injury risk in female collegiate athletes. N Am J Sports Phys Ther 2010; 5(2):47–54.
307
21. Wiese BW, Boone JK, Gino MC, et al. Determination of the functional movement screen to
308
predict musculoskeletal injury in intercollegiate athletics. Athl Train Sport Health Care 2014;
309
6(4):161–169.
310
22. Garrison M, Westrick R, Johnson MR, et al. Association between the functional movement
311
screen and injury development in college athletes. Int J Sports Phys Ther 2015; 10(1):21–28.
312
23. Warren M, Smith CA, Chimera NJ. Association of the functional movement screen with injuries
313
in division I athletes. J Sport Rehabil 2015; 24(2):163–170.
12
Page 13 of 18
314 315
24. Colby MJ, Dawson B, Heasman J, et al. Accelerometer and GPS-derived running loads and injury risk in elite Australian footballers. J Strength Cond Res 2014; 28(8):2244–2252.
316
25. Moran RW, Schneiders AG, Major KM, et al. How reliable are functional movement screening
317
scores? A systematic review of rater reliability. Br J Sports Med 2015; doi:10.1136/bjsports-
318
2015-094913. 26. Cook G, Burton L, Hoogenboom B, Voight M. Functional movement screening: the use of
320
fundamental movements as an assessment of function – part 2. Int J Sports Phys Ther 2014;
321
9(4):549–563.
324 325
cr
us
323
27. Burgess D, Naughton G, Norton K. Quantifying the gap between under 18 and senior AFL football: 2003 and 2009. Int J Sports Physiol Perform 2012; 7(1):53–58.
28. Schneiders AG, Davidsson A, Hörman E, et al. Functional movement screen normative values in
an
322
ip t
319
a young, active population. Int J Sports Phys Ther 2011; 6(2):75–82. 29. Montgomery PG, Hopkins WG. The effects of game and training loads on perceptual responses
327
of muscle soreness in Australian Football. Int J Sports Physiol Perform 2013; 8(3):312-318.
328
30. Gabbe BJ, Finch CF, Bennell KL, et al. How valid is a self reported 12 month sports injury
d
history? Br J Sports Med 2003; 37(6):545–547.
Ac ce pt e
329
M
326
13
Page 14 of 18
330
Figure legend
331
Fig. 1. Proportion of players that scored 1, were asymmetrical, or reported pain for each of the
332
Functional Movement Screen sub-tests. Error bars represent 95% confidence intervals. * Deep squat
333
and trunk stability push-up sub-tests are not unilateral tests and do not provide information about
334
asymmetry.
335
squat, hurdle step, in-line lunge, active straight leg raise and rotary stability. c Greater proportion than
336
in-line lunge, shoulder mobility, trunk stability push-up and rotary stability (p<0.05).
337
proportion than all other sub-tests (p<0.05). e Greater proportion than in-line lunge (p<0.05). f Lower
338
proportion than deep squat, shoulder mobility, active straight leg raise and trunk stability push-up
339
(p<0.05).
Greater proportion than all other sub-tests (p<0.05).
b
Greater proportion than deep
ip t
a
Lower
Ac ce pt e
d
M
an
us
cr
d
14
Page 15 of 18
cr
ip t
Table 1
Ac c
ep te
d
M
an
us
Table 1. The effect of player position and injury on Functional Movement Screen composite score, asymmetry, and pain. Total FMS score ≤14 ≥1 Asymmetry ≥1 Painful test Previous Injury (n) (% Total) (% Total) (% Total) (% Total) All players 301 182(60%) 196(65%) 113(38%) 126(42%) Midfield 156 90(58%) 104(67%) 56(36%) 66(42%) Forward 57 38(67%) 37(65%) 21(37%) 22(39%) Defender 56 31(55%) 35(63%) 24(43%) 23(41%) Ruck 32 23(72%) 20(63%) 12(38%) 15(47%) Previous injury Yes 126 56(44%) 84(67%) 59(47%) a – No 175 73(42%) 112(64%) 54(31%) – a Increased likelihood of having at least one painful sub-test when compared to players with no previous injury (Relative Risk: 1.52; 95% confidence interval: 1.14-2.03; p=0.005).
Page 16 of 18
cr
ip t
Table 2
Ac c
ep te
d
M
an
us
Table 2. Multivariable logistic regression analysis of pain reported during the Functional Movement Screen. Predictor Coefficient (β) SE (β) Wald’s χ 2 df p OR (95%CI) Model 1 Intercept -0.885 0.204 4.344 1 <0.01 NA Player position Midfield Ref. Ref. Ref. Ref. Ref. Ref. Forward 0.068 0.326 0.209 1 0.83 1.07 (0.56-2.02) Defender 0.309 0.322 0.960 1 0.34 1.36 (0.72-2.56) Ruck 0.039 0.407 0.095 1 0.92 1.04 (0.46-2.28) Previous injury No Ref. Ref. Ref. Ref. Ref. Ref. Yes 0.685 0.243 2.818 1 <0.01 1.98 (1.23-3.20) Model evaluation vs. Null model 8.869 4 0.06 Model 2 Intercept -0.807 0.164 4.930 1 <0.01 NA Previous injury No Ref. Ref. Ref. Ref. Ref. Ref. Yes 0.680 0.242 2.806 1 <0.01 1.97 (1.23-3.18) Model evaluation vs. Null model 7.940 1 <0.01 95%CI, 95% confidence interval; df, degrees of freedom; NA, not applicable; OR, odds ratio; SE, standard error; Ref., reference condition; vs., versus.
Page 17 of 18
Ac
ce
pt
ed
M
an
us
cr
i
Figure(s)
Page 18 of 18