AJSM PreView, published on July 18, 2011 as doi:10.1177/0363546511413375
The Influence of Musculoskeletal
Injury on Cognition
Implications for Concussion Research
Michael Hutchison,*y MSc, Paul Comper,yz§ PhD, CPsych, Lynda Mainwaring,z PhD, CPsych,
and Doug Richards,z MD, Dip Sport Med
Investigation performed at the University of Toronto, Toronto, Ontario, Canada
Background: Safe return-to-play decisions after concussion can be challenging for sports medicine specialists. Neuropsychological testing is recommended to objectively measure concussion-related cognitive impairments.
Purpose: The objective of this study was to measure cognitive functioning among 3 specific athletic groups: (1) athletes with no
injuries (n = 36), (2) athletes with musculoskeletal injuries (n = 18), and (3) athletes with concussion (n = 18).
Study Design: Case-control study; Level of evidence, 3.
Methods: Seventy-two intercollegiate athletes completed preseason baseline cognitive testing and follow-up assessment using
the Automated Neuropsychological Assessment Metrics (ANAM) test battery. Injured athletes were tested within 72 hours of
injury. A 1-way analysis of covariance adjusted for baseline scores was performed to determine if differences existed in cognitive
test scores among the 3 groups.
Results: A group of athletes with concussion performed significantly worse than a group of athletes with no injuries on the following subtests of the ANAM at follow-up: Code Substitution Learning, Match to Sample, and Simple Reaction. Athletes with
musculoskeletal injuries performed significantly worse than those with no injury on the Match to Sample subtest. No significant
differences between athletes with concussion and athletes with musculoskeletal injuries were found on all ANAM subtests.
Conclusion: Concussion produces cognitive impairment in the acute recovery period. Interestingly, athletes with musculoskeletal
injuries also display a degree of cognitive impairment as measured by computerized tests.
Clinical Relevance: Although these findings support previous research that neuropsychological tests can effectively measure
concussion-related cognitive impairment, this study provides evidence that athletic injury, in general, also may produce a degree
of cognitive disruption. Therefore, a narrow interpretation of scores of neuropsychological tests in a sports concussion context
should be avoided.
Keywords: concussion; musculoskeletal injury; sport; neuropsychological testing
induced by traumatic biomechanical forces,29 occurs frequently. There is now consensus among medical and sports
communities that concussion is a serious health issue
affecting a large number of male and female athletes, spanning all age groups, across all levels of competition.
Establishing a positive diagnosis of concussion can be
challenging for sports medicine specialists. For example,
many concussions occur in the chaos of competition, and
a cause-effect mechanism may not be directly apparent
from the sidelines, or an athlete may not initially present
with concussion symptoms until hours or even days after
injury. Even when a positive diagnosis is made, such as
when a player is obviously rendered unconscious, most athletes who sustain concussions rarely have objective neuropathological signs or positive neuroradiological findings16;
furthermore, the effects on mental status are often subtle
and transient, making concussion difficult to quantify or
observe on clinical examination or formal neuropsychological
Sports-related concussion (‘‘concussion’’), which is defined
by the Consensus Panel of the 2008 Zurich Conference as
a complex pathophysiological process affecting the brain,
*Address correspondence to Michael Hutchison, MSc, Graduate
Department of Rehabilitation Science, Faculty of Medicine, University of
Toronto, 500 University Avenue, Toronto, ON M5G 1V7, Canada
(e-mail: michael.hutchison@utoronto.ca).
y
Graduate Department of Rehabilitation Science, Faculty of Medicine,
University of Toronto, Toronto, Ontario, Canada.
z
Faculty of Physical Education and Health, University of Toronto, Toronto, Ontario, Canada.
§
Toronto Rehabilitation Institute, Toronto, Ontario, Canada.
One or more of the authors has declared the following potential conflict of interest or source of funding: Physicians Incorporated Services
(PSI) provided financial support during the study period.
The American Journal of Sports Medicine, Vol. XX, No. X
DOI: 10.1177/0363546511413375
Ó 2011 The Author(s)
1
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Hutchison et al
assessment.25 Compounding this issue, athletes have the tendency to underreport or mask symptoms, possibly in anticipation of a more rapid return to play.28
In an effort to objectively measure concussion-related
cognitive impairment, neuropsychological (NP) testing
was introduced into the athletic setting in the late 1980s.
Pioneered by Barth and colleagues, the Sports as a Laboratory Model (SLAM) approach used traditional ‘‘paper-andpencil’’ NP tests in a preinjury (ie, ‘‘baseline’’)–postinjury
paradigm. The use of NP tests in athletic settings was
based on the premise that such tests have proven to be
valid and reliable in the detection and quantification of
acute and residual cognitive deficits after mild traumatic
brain injury in other settings; so, the application of NP
testing within the sports arena was both intuitive and logical. However, there were practical difficulties (eg, one-onone test administration, time requirement, scoring) using
traditional paper-and-pencil measures in sports settings.
These difficulties, in conjunction with advances in technology, contributed to the emergence of relatively brief, computerized NP ‘‘screening’’ batteries. The development of
such batteries offered significant advantages over penciland-paper testing, such as standardization of administration, easier scoring, storage and access to data, minimization of learning effects (by having multiple versions of
the test available), and ability to accurately measure reaction time and impulse control.4
Currently, several computerized NP batteries are available for concussion assessment. Without exception, all of
these batteries attempt to evaluate various domains of cognitive functioning quickly and efficiently, using a variety of
timed tasks.2,5,9,17 Domains of testing include working
memory, attention, concentration, information processing,
reaction time, and short-term verbal and nonverbal memory
abilities. Central to the use of computerized NP assessment
is the tenet that cognitive functions measured by these tests
are susceptible to changes after concussion.6,8,11,12,20,27
Research generally supports the notion that concussion
temporarily disrupts cognitive functioning, which often
resolves on average within 7 to 10 days.1,6,10,20,26,27 Within
this context, a NP ‘‘impairment’’ is characterized by a significant decline between an athlete’s baseline and postinjury
scores or on NP test scores deemed to be significantly different from a healthy comparison group. In either case, the
underlying assumption is that any decline in NP scores
observed after concussion is attributable to an impairment
of cortical functioning. This assumption, however, has yet
to be empirically investigated; that is, it is currently
unknown whether cognitive impairment after concussion is
exclusively because of the effects of traumatic brain injury
or is related to other factors associated with athletic injury
in general. Although it is assumed that cognitive impairment
is a direct, expected consequence of concussion affecting cortical (or possibly white matter tract) processing, it is possible,
but not yet investigated, that the mechanism is indirect, that
is, that other factors associated with athletic injury (eg, pain)
might somehow mediate thinking and reasoning.
Therefore, the purpose of this study was to explore this
issue. Using computerized NP tests, we sought to measure
cognitive functioning among 3 specific athletic groups: (1)
The American Journal of Sports Medicine
athletes with no injuries, (2) athletes with musculoskeletal
injuries, and (3) athletes with concussion. We hypothesized
that athletes with concussion would perform significantly
worse than athletes with no injuries and athletes with
musculoskeletal injuries. In addition, we did not expect
the cognitive functioning of athletes with musculoskeletal
injuries to be significantly different than that of athletes
with no injuries.
MATERIALS AND METHODS
Participants and Procedure
Since 2000, every student athlete engaged in an intercollegiate sport at the University of Toronto, deemed at risk for
concussion, has been required to complete a mandatory,
brief NP assessment before the start of his or her athletic
participation. Although a baseline NP assessment is mandatory, athletes who sustain concussions can also choose to
participate in a research component of the program.
Within our research program, the NP batteries used to
assess baseline and postinjury functioning have varied
over the years and have included a variety of traditional
paper-and-pencil as well as computerized NP tests. In
2002, the Automated Neuropsychological Assessment Metrics (ANAM) was added to the assessment/research protocol.31 The ANAM system is designed to assess cognitive
performance for various clinical and research applications.
For the current study, participants completed a demographic questionnaire that assessed background information
including age, sex, height, weight, and previous concussion
history (up to 5 previous concussions). The study sample
was drawn from our large prospective research program
that includes 3 cohorts of athletes with concussion, athletes
with musculoskeletal injury, and uninjured athletes. Concussion diagnosis was based on the following criteria: (1)
observed or reported acceleration/deceleration of the head;
(2) any observable alteration in mental status; (3) observable
signs such as confusion, vacant stare, poor coordination, difficulty concentrating, and poor balance; and/or (4) any selfreported symptoms such as headache, loss of consciousness,
nausea, balance problems, or difficulty reading or concentrating. Musculoskeletal injury was operationally defined as any
soft tissue injury that did not include the head and resulted
in an initial removal from participation (game or practice) for
a minimum of 48 hours but no longer than 3 weeks. Injured
athletes were tested within 72 hours of injury. At the postinjury assessment, in addition to the computerized NP test battery, injured athletes completed a self-report Symptom
Rating Scale (SRS).21 The SRS consists of 36 items and measures symptom intensity from 0 (none at all) to 4 (extreme) of
common symptoms frequently reported in brain-injured populations. The items of the SRS are grouped into 5 core categories: (1) functional, (2) cognitive, (3) physical, (4) sensory/
perceptual, and (5) mood.
From the convenience sample, all injured athletes were
matched for history of concussion and sex. In addition, we
matched healthy student athletes with each injured athlete for history of concussion and sex. In total, the study
Vol. XX, No. X, XXXX
Influence of Musculoskeletal Injury on Cognition
TABLE 1
Study Sample Demographicsa
Age, y
Men
Women
Height, cm
Men
Women
Mass, kg
Men
Women
Mean
Standard Deviation
Minimum
Maximum
19.9
19.4
2.1
1.5
17.8
18
25.5
23
183.8
169.1
7.4
8.4
155
155
200
188
88.9
63.2
16.2
9.4
59
50
136
84
a
Men, n = 48; women, n = 24.
sample included 72 athletes in the following 3 groups: athletes with concussion (CONC; n = 18), athletes with musculoskeletal injury (MSK; n = 18), and uninjured athletes
(CTL; n = 36).
Of the 72 athletes, 67% were men (n = 48), and 33% were
women (n = 24), with an average age of 19.78 years (standard deviation [SD], 1.89 years; range, 17.83-25.50 years).
Sixty-four percent (n = 46) of the athletes reported no history of concussion at the baseline assessment (see Table 1
for additional demographics). The breakdown by sport was
as follows: basketball (n = 1), football (n = 28), hockey (n =
14), lacrosse (n = 10), rugby (n = 6), soccer (n = 5), and volleyball (n = 8). At baseline assessment, no student athlete in
this sample reported a prior learning disability, a prior psychiatric disorder, or a recent concussion from which they
were recovering.
All participants read an information letter and completed
an informed consent form prior to participation. The study
was approved by the Ethics Review Board of the Office of
Research Services at the University of Toronto.
Measure
The ANAM is a self-directed, computerized NP test battery
that takes approximately 20 to 25 minutes to administer.
The most recent version of the ANAM designed to assess
sports-related concussion, referred to as the Automated
Sports Medicine Battery (ASMB),4 includes the following
subtests: Simple Reaction Time (SRT), Code Substitution:
Learning (CDS), Code Substitution: Delayed (CDD), Procedural Processing (PRO), Match to Sample (MSP), Spatial
Processing (SPD), and Sternberg Memory Search. Each of
these tests is a putative measure of cognitive functioning.
The utility of the ANAM as a sensitive and specific NP
measure has been examined in a number of research and
clinical populations1,19,30,34; its use in sports-related concussion research and clinical management has grown considerably over the past 15 years. The ANAM subtests included in
concussion assessment batteries have varied over time, but
overall, the subtests assess a number of cognitive constructs
that appear to be vulnerable to concussion (eg, reaction
time, cognitive processing speed, working memory, and
visuospatial memory). Various studies have reported
3
moderate correlations with the ANAM subtests compared
with traditional NP measures.3,18,35 The ANAM has also
been demonstrated to be sensitive to concussion in athletic
samples.1,32 The ANAM reliabilities have been assessed in
military and adolescent samples, with reliabilities ranging
from .38 to .87.4,33 The subtests of the ANAM described in
Table 2 were used in our analyses, as these tests have
remained constant throughout various iterations of the
test batteries used at the University of Toronto.
Data Analysis
Outcome measures commonly reported with the ANAM
include percentage correct (accuracy), average time to
respond to stimuli or tasks, and throughput (a derivative
score based on speed and accuracy). For the present study,
average time to respond to stimuli and tasks and throughput scores were included in the analyses. A 1-way analysis
of covariance (ANCOVA) adjusted for baseline scores was
performed to determine if differences existed in cognitive
test scores among the 3 groups. We used a Tukey-Kramer
post hoc test to identify specific between-group differences.
RESULTS
With respect to participants’ demographic characteristics,
there were no differences among groups for history of concussion, weight, height, age, and elapsed time to follow-up from
baseline assessment. The CONC group reported significantly
more physical symptoms (ie, headache, nausea, dizziness,
fatigue) on the SRS than the MSK-injured group (P = .03).
No significant differences were observed for items related
to function, cognition, sensation/perception, and mood.
Throughput
Table 3 shows throughput results for each of the groups. A
visual inspection of throughput scores at the follow-up
assessment identified a consistent pattern of performance
across all ANAM subtests among the 3 groups (Figures 1
and 2). The stepwise pattern of performance demonstrated
that the CTL group obtained the highest mean scores, the
CONC group obtained the lowest mean values, and the
MSK group fell in the middle.
Significant differences were found in 3 subtests at followup: CDS, MSP, and SRT. An ANCOVA revealed a significant
difference among the 3 groups for the CDS subtest (F2,66 =
6.26, P = .003). Subsequent Tukey-Kramer post hoc analyses showed that the CONC group performed significantly
worse than the CTL group (P = .003) (Figure 1). No significant differences were found between the MSK group and
the CTL or CONC groups. There was also a significant difference among the 3 groups for the MSP subtest (F2,67 =
8.15, P \ .001). Post hoc analyses revealed that the CONC
group was significantly worse than the CTL group (P =
.002). The MSK group also performed significantly worse
than the CTL group (P = .014), but the MSK group’s performance was not significantly different from the CONC group
(Figure 1). Lastly, SRT performance was statistically
4
Hutchison et al
The American Journal of Sports Medicine
TABLE 2
Description of Automated Neuropsychological Assessment Metrics (ANAM) Subtests
Subtest
Description
Simple Reaction
Time (SRT)
Code Substitution:
Learning (CDS)
Cognitive Domain(s) Targeted
The user is presented a series of stimuli and
instructed to respond as quickly as possible.
The user must compare a displayed digit-symbol
pair with a set of defined digit-symbol pairs, that is,
the key or legend. The defined pairs are presented
along with the digit-symbol in question, and the user
must indicate whether the pair in question is correct
or incorrect relative to the key.
The user must indicate whether the pair in question
represents a correct or incorrect mapping relative
to the key, without the presence of the key in CDS.
The user views a 4 3 4 grid and determines the
pattern produced by 8 shaded cells. The sample is removed,
and then 2 comparison 4 3 4 grids are displayed, and the
user must identify which grid matches the sample.
Code Substitution:
Delayed (CDD)
Matching to
Sample (MSP)
Visuomotor response timing
Visual search, sustained
attention, encoding
Verbal working memory,
sustained attention
Spatial and visuospatial
working memory
TABLE 3
Automated Neuropsychological Assessment Metrics (ANAM) Subtest Throughput Scores (Correct Responses per Minute)a
CDS
CDD
MSP
SRT
Group
Baseline
Postinjury
Baseline
Postinjury
Baseline
Postinjury
Baseline
Postinjury
CTL
MSK
CONC
62.29 (12.57)
60.73 (11.70)
57.23 (7.42)
68.32 (11.38)
62.00 (10.07)
56.13 (10.48)b
62.92 (13.93)
58.63 (16.69)
57.09 (13.89)
61.56 (15.20)
57.14 (16.87)
54.09 (13.89)
39.58 (14.22)
41.32 (14.13)
36.70 (13.55)
45.23 (13.80)
37.98 (8.30)b
33.71 (6.74)b
238.12 (29.40)
221.03 (41.27)
234.57 (23.07)
252.87 (29.22)
236.60 (31.18)
230.56 (52.63)b
a
Values presented as mean (standard deviation). CDS, Code Substitution: Learning; CDD, Code Substitution: Delayed; MSP, Matching to
Sample; SRT, Simple Reaction Time; CTL, uninjured; MSK, musculoskeletal injury; CONC, concussion.
b
Significance from the CTL group (P \ .05).
significant based on ANCOVA analysis (F2,66 = 4.02, P =
.023). Tukey-Kramer post hoc results revealed the CONC
mean values to be significantly lower than the CTL group
values (P = .02) (Figure 2). No statistically significant differences between the MSK group and CTL or CONC groups
were observed. ANCOVA analysis was not significant for
the CDD subtest (F2,67 = 2.69, P = .08) (Figure 1).
To summarize, results from Tukey post hoc analyses
found significant differences between the CONC group
and the CTL group for CDS, MSP, and SRT subtests.
Also, significant differences were observed between the
MSK and the CTL group for the MSP subtest. However,
no significant differences were found between the CONC
and the MSK groups on any of the subtests.
Reaction Time
A similar pattern of group performances was apparent for
the average time to respond to stimuli and tasks variable:
The CONC group mean scores were the slowest, while the
CTL group had the fastest reaction times; the MSK group
values lay between the CONC and CTL groups (see Table 4
for group means).
ANCOVA analyses for reaction times were significant for
all subtests: CDS (F2,66 = 5.93, P = .0043), MSP (F2,67 = 9.71,
P \ .001), CDD (F2,67 = 4.83, P \ .001), and SRT (F2,66 =
3.89, P = .025). Specific to the CDS subtest, post hoc analysis
indicated that the CONC group was significantly slower
than the CTL group (P = .003). For the MSP subtest, post
hoc analyses identified the CTL group to be significantly different from both of the comparison groups (CTL vs CONC
[P \ .001] and CTL vs MSK [P = .011]). Post hoc analysis
for the SRT subtest revealed a significant difference between
the CTL group and the CONC group (P = .02). Similarly, post
hoc analysis for the CDD subtest identified that the CONC
group was significantly slower than the CTL group (P =
.014). All other post hoc analyses for the CDS, MSP, CDD,
and SRT subtests found no significant differences.
Therefore, significant differences for average time to
respond to stimuli were found between the CONC group
and the CTL groups for CDS, MSP, SRT, and CDD
subtests. Similar to throughput scores, significant differences were observed for reaction time values on the MSP subtest between the MSK and the CTL group. Finally, there
were no significant differences between the CONC and
the MSK groups.
Vol. XX, No. X, XXXX
Influence of Musculoskeletal Injury on Cognition
300
80
*
280
*
260
60
50
240
*
40
Throughput Score
Throughput Score
70
*
30
20
220
200
180
160
140
10
0
5
120
MSP
CDD
CTL
MSK
CDS
CONC
Figure 1. Matching to Sample (MSP), Code Substitution:
Delayed (CDD), and Code Substitution: Learning (CDS)
throughput means at follow-up assessment for each group.
*Significance from the CTL group (uninjured athletes) (P \ .05).
100
CTL
MSK
CONC
Figure 2. Simple Reaction Time (SRT) throughput means at
follow-up assessment for each group. *Significance from the
CTL group (uninjured athletes) (P \ .05).
DISCUSSION
The main objective of this study was to assess and compare
the cognitive functioning of concussed athletes to athletes
with musculoskeletal injuries and also to a group of
healthy controls, using a computerized NP test battery
(ANAM). To our knowledge, this is the first study of NP
sequelae of sports-related concussion to include a musculoskeletal-injured control group. The advantage of including
a musculoskeletal-injured comparison group is to account
for the possible effects of nonneurological factors not
related to traumatic brain injury.
Consistent with the previous sports neuropsychology
literature,1,6,10,13,20,26,27 we have provided further evidence
that concussion results in cognitive impairment among
concussed athletes in the acute recovery period. Specifically, using the ANAM, we detected impairment on tests
that are targeted to assess sustained attention (CDS),
visuomotor response (SRT), and spatial working memory
(MSP). These findings add considerable support to the
widely held view that cognitive deficits occur after sportsrelated concussion.
In the current study, we also included an uninjured control group to allow us to evaluate cognitive functioning in
a healthy population. Evaluation of the data revealed a consistent stepwise pattern of performance; that is, uninjured
athletes were relatively better at some cognitive tasks than
athletes with musculoskeletal injuries, who in turn were
better than athletes with concussion. The finding that athletes with musculoskeletal injuries also showed indication
of cognitive decline immediately after injury raises the
issue that NP impairment after concussion might be
related to factors other than, or in combination with, the
effects of traumatic brain injury. Although we observed
that the group of athletes with musculoskeletal injuries
performed worse than the healthy controls on one ANAM
subtest, there were no significant differences observed
between athletes with musculoskeletal injuries and those
with concussions. The finding that musculoskeletalinjured athletes performed worse than healthy controls
on cognitive tests suggests that factors other than concussion may influence an athlete’s thinking abilities over the
short term.
Consistent with previous literature, the results of this
study indicate that athletes with concussion exhibit a significant decline in cognitive functioning during the acute
postconcussion period. Compared with athletes with musculoskeletal injuries and those with no injury, athletes
with concussion performed worse across all domains of cognitive functioning. Although these findings support previous research that NP tests can effectively measure
concussion-related cognitive impairment, the current
data also challenge the assumption that cognitive deficits
as measured by NP tests administered after concussion
are solely attributed to traumatic brain injury. As such,
we caution researchers and clinicians alike that a narrow
interpretation of scores of NP tests in a sports concussion
context should be avoided.
With the increasing use of NP test batteries in the
sports context to evaluate and manage athletes with concussions, researchers should continue to identify variables
that potentially affect performance on NP tests. In a recent
article, Echemendia et al7 reviewed the numerous variables that should be considered in the valid interpretation
of NP test data, including psychological factors (anxiety,
depression, fear), physiological factors (sleep, fatigue,
nutrition, medication), cultural factors (language, education), and premorbid characteristics (learning or personality disorders). Based on our present findings, it also seems
reasonable to consider that musculoskeletal injuries may
negatively influence performance on these tests.
The question as to why athletes with musculoskeletal
injuries would exhibit cognitive changes when there is no
evidence they have suffered concussions is a matter for
future research. However, one potential explanation is
6
Hutchison et al
The American Journal of Sports Medicine
TABLE 4
Automated Neuropsychological Assessment Metrics (ANAM) Subtest Mean Reaction Time Responses (Milliseconds)a
CDS
CDD
MSP
SRT
Group
Baseline
Postinjury
Baseline
Postinjury
Baseline
Postinjury
Baseline
Postinjury
CTL
MSK
CONC
951.67 (171.37)
992.52 (211.42)
1026.48 (132.17)
863.49 (158.13)
963.44 (179.92)
1078.8 (277.87)b
929.75 (207.07)
971.97 (245.34)
974.09 (142.16)
941.07 (214.11)
1062.66 (298.88)b
1066.97 (313.75)
1594.79 (557.94)
1449 (481.93)
1656.22 (571.02)
1337.56 (377.68)
1553.56 (382.34)b
1737.83 (335.92)b
248.34 (194.22)
282.74 (67.02)
256.46 (24.74)
240.44 (28.62)
258.68 (41.72)
282.63 (108.70)b
a
Values presented as mean (standard deviation). CDS, Code Substitution: Learning; CDD, Code Substitution: Delayed; MSP, Matching to Sample; SRT, Simple Reaction Time; CTL, uninjured; MSK, musculoskeletal injury; CONC, concussion.
b
Significance from the CTL group (P \ .05).
that negative emotional and psychological factors, or preexisting vulnerabilities, may surface when an athlete is
injured.15,22,23 Initially, this could be because of the frustration of being both highly trained, with great expectations of performance, only to be ‘‘sidelined’’ and in effect
rendered helpless and noncontributory in a situation for
which the athlete has no previous experience. Over the longer term, the psychological and emotional consequences of
chronic injury can lead to adjustment issues such as
depression and anxiety, and these factors have been shown
to be associated with cognitive dysfunction in experimental
settings.14,24 Although factors such as anxiety and depression may mediate normal cognitive functioning, any such
changes would be unique to an individual and would not
be expected to manifest as uniform attributes within
a group. Most importantly, the effects of psychological
and emotional functioning would not be as severe or as
selective as might be seen in individuals with concussion.
Another possibility is that orthopaedic pain and discomfort
actually influence cognitive deficits.
In recent years, there has been tremendous emphasis on
the application of NP testing in concussion evaluation, and
it has been shown to be of clinical value and continues to
contribute significant information.29 With that in mind,
the present study was a preliminary analysis to examine
computerized NP test results among 3 specific athletic
groups: (1) athletes with no injuries, (2) athletes with musculoskeletal injuries, and (3) athletes with concussion. The
reason we assessed cognitive functioning in athletes with
musculoskeletal injuries was to address factors other
than traumatic brain injury that are perhaps associated
with NP performance after injury. Although this study
did not have sufficient power to detect some of the intermediate differences between the MSK and CONC groups and
the MSK and CTL groups, the findings raise an interesting
possibility that athletes with musculoskeletal injuries are
truly more similar to the CONC group than we had
hypothesized. For exploratory purposes, we found larger
effect sizes between the MSK group and the CONC group
than the MSK group and the CTL group in 2 of the 4
ANAM subtests, which suggests that this may indeed be
the case. This would suggest that future studies should
be constructed to examine the differences between these
2 groups. Also, future studies should assess these groups
of athletes throughout the clinical course as repeated
assessment may also help to distinguish between the athletes with musculoskeletal injuries and athletes with concussion. Larger sample sizes and multiple assessments
may detect significant differences and identify NP profiles
and patterns specific to athletes with concussion and those
with musculoskeletal injuries and/or healthy controls.
Such findings will further clarify whether injury in general
(regardless of its type) results in cognitive disruption and
the extent to which it contributes. Furthermore, additional
studies of sports-related concussion that include a comparison group of athletes with musculoskeletal injuries could
help elucidate important factors associated with cognitive
impairment postconcussion.
ACKNOWLEDGMENT
The authors thank the Faculty of Physical Education and
Health, University of Toronto, and the coaches and athletes of the Varsity Blues athletic teams for their support
and contribution. They also thank the research assistants
of the University of Toronto Concussion Program, particularly Sam Esfandiari and Sandra Sokoloff, for their assistance in the preparation and review of the article.
Finally, the research team is grateful to Physicians Incorporated Services (PSI) for financial support during the
study period.
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