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Original Research
Association of Preexisting Mental Health
Conditions With Increased Initial Symptom
Count and Severity Score on SCAT5
When Assessing Concussion
Kathryn J. Schulze,* MPhil, PhD(c), Michael Robinson,
†
CAT(C), ATC, PhD,
Heather M. MacKenzie,
‡§
SM, MD, FRCPC, and James P. Dickey,*
k
MSc, PhD
Investigation performed at Western University, London, Ontario, Canada
Background: Mental health conditions, such as depression, anxiety, and learning disabilities, are associated with symptoms that
can overlap with those seen in persons with concussion. While concussion screening tools such as the Sport Concussion
Assessment Tool–5th Edition (SCAT5) quantify the number of symptoms and symptom severity, it is not known whether these
outcomes differ among individuals with concurrent mental health conditions compared with those without them.
Purpose: To determine whether, during initial concussion assessment, individuals with a self-reported mental health condition
have a significantly different number of self-reported concussion symptoms or symptom severity compared with those without a
self-reported mental health condition (controls).
Study Design: Cohort study; Level of evidence, 3.
Methods: A retrospective chart review was performed on consecutive patients aged 13 years who underwent post-concussion
assessment at the Fowler Kennedy Sport Medicine Clinic between May 2018 and March 2020 (N ¼765). Most participants did not
self-report a mental health condition (n ¼606; 79.2%). Participants with a self-reported mental health condition (n ¼159) were
classified as having a learning disability (n ¼14; 8.8%), anxiety (n ¼62; 39.0%), depression (n ¼20; 12.6%), or multiple conditions
(2 conditions: n ¼63; 39.6%). Each participant with a mental health condition was matched with 2 control participants (overall
pool, n ¼318) based on age, sex, student status, and sport-related risk. Mann-Whitney Utests were used to determine the
statistical significance of differences between each subgroup and their matched controls for the self-reported number of con-
cussion symptoms and symptom severity as measured using the SCAT5.
Results: The anxiety and multiple-conditions subgroups had a significantly greater number of reported symptoms than their
corresponding control subgroups (median, 17 vs 15 [P¼.004] and 18 vs 14.5 [P<.001], respectively). Additionally, the SCAT5
symptom severity score was significantly greater in the anxiety and multiple-conditions subgroups than their corresponding
controls (median, 49 vs 34.5 [P¼.018] and 62 vs 32 [P<.001], respectively).
Conclusion: During initial concussion assessment, both the number of concussion-related symptoms and the symptom severity
were greater in study participants with anxiety and multiple mental health conditions than participants without these conditions.
Keywords: head injury/concussion; SCAT5; anxiety; depression
Mental health conditions, such as anxiety, depression, and
learning disabilities, are common among the general popu-
lation,
16,43,72,84,88,92
including athletes.
53
Importantly,
concussion-related symptoms overlap with symptoms of
these conditions, such as difficulty concentrating and
remembering, feeling slowed down or “in a fog,” being ner-
vous or anxious, and having low energy and sad-
ness.
17,19,21,29
The Sport Concussion Assessment Tool–5th
Edition (SCAT5) measures the occurrence of symptoms and
symptom severity cross-sectionally rather than asking
respondents to report any change in symptoms compared
with their preinjury baseline. This makes it difficult to
differentiate between concussion-related and preexisting
health condition–related symptoms. This presents a
challenge to those who interpret the SCAT5 results,
especially for individuals with preexisting mental health
conditions.
There is some evidence that youth athletes with preex-
isting mental health conditions are evaluated with an
increased number of symptoms endorsed at baseline on the
The Orthopaedic Journal of Sports Medicine, 10(9), 23259671221123581
DOI: 10.1177/23259671221123581
ªThe Author(s) 2022
1
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licenses/by-nc-nd/4.0/), which permits the noncommercial use, distribution, and reproduction of the article in any medium, provided the original author and source are
credited. You may not alter, transform, or build upon this article without the permission of the Author(s). For article reuse guidelines, please visit SAGE’s website at
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SCAT5.
17,18
For example, youth athletes with attention-
deficit/hyperactivity disorder (ADHD) have been found to
report a significantly greater number of symptoms and
higher symptom severity during baseline SCAT assess-
ments than those without ADHD.
17,19
Additionally,
collegiate and high school athletes with depression have
been found to report a significantly greater number of
symptoms during baseline Immediate Post-concussion
Assessment and Cognitive Testing (ImPACT) than those
without depression.
21
Therefore, a concussed individual
with a preexisting mental health condition may also report
greater post-injury SCAT5 scores than individuals without
preexisting mental health conditions. Accordingly, clini-
cians assessing concussed athletes may not be able to
reliably distinguish between symptoms attributable to
their preexisting medical conditions and those that have
emerged as new since the injury. Furthermore, not all
athletes will have completed baseline testing, and accord-
ingly, it may not be possible for clinicians to compare
SCAT5 scores collected for concussion assessment with a
pre-injury baseline. In fact, the most recent version of the
SCAT states that baseline testing is not required for
concussion assessment.
28
Research has yet to evaluate the
effect of adult athletes’ preexisting mental health condi-
tions on SCAT5 scores after concussion.
Evaluating different domains of concussion-related
symptoms may give insight into the effects of preexisting
mental health conditions on symptomatology.
3,5,8,61
One
study found that the symptom domain of mental health
contributes to the variance of concussion-related symptom-
atology.
3
Another study determined that ADHD is associ-
ated with reporting 1 or more cognitive symptoms, whereas
anxiety and depression are associated with reporting 1 or
more emotional symptoms.
8
Additional research is required
to investigate these symptom domains in concussed indivi-
duals with mental health conditions.
The purpose of this study was to determine whether, at
the time of initial presentation for medical assessment of a
concussion, individuals with a self-reported preexisting men-
tal health condition—anxiety, depression, or learning dis-
ability—had a significantly different number of concussion
symptoms or symptom severity compared with individuals
without a preexisting mental health condition. It was
hypothesized that individuals with a preexisting mental
health condition who subsequently experienced a concussion
would be evaluated with a significantly greater number of
symptoms and an increased symptom severity compared
with individuals without the same past medical history.
METHODS
The protocol for this study was approved by our ethics com-
mittee. A retrospective chart review was performed for con-
secutive patients diagnosed with a concussion at the Fowler
Kennedy Sport Medicine Clinic, London, Ontario, between
May 2018 and March 2020. The concussion diagnosis was
performed by a sport and exercise physician who is a mem-
ber of the Canadian Academy of Sport and Exercise
Medicine,islicensedasafamilyphysician,andhas
received additional training on concussion management.
The diagnosis was based on the mechanism of injury, clin-
ical examination, and reporting of symptoms. Because of
the differences between the Child– and Adult–SCAT5
assessments, participants aged <13 years were excluded
from the study. Of 765 patients reviewed, 477 were
included in the study (Figure 1).
During the initial evaluation for concussion assessment,
participants self-reported mental health conditions on a
questionnaire. Participants who self-reported specific
preexisting mental health conditions (condition group;
n¼159) were organized into subgroups based on the nature
of their mental health condition; the remainder of the par-
ticipants (n ¼412) were placed in the control pool (Figure 1).
Separate condition subgroups were defined for those with
a learning disability (n ¼14; 8.8%), anxiety (n ¼62;
39.0%), depression (n ¼20; 12.6%), and multiple conditions
(2 conditions: n ¼63; 39.6%). Each participant in these
subgroups was matched with 2 control participants based
on sex, age, student status, and sport-related risk (1:2
matching without replacement). This 1:2 matching was
performed to improve test power and estimator precision
compared with 1:1 matching.
74
Sport-related concussion
risk was assessed by categorizing their self-reported sport
participation as either high risk (such as rugby), medium
risk (such as football and ice hockey), or low risk (such as
running and volleyball).
96
Individuals participating in
sports were clustered as either medium or high risk, or low
risk, and were matched to control individuals within the
same risk cluster.
All participants also completed the Adult–SCAT5 at
their initial clinic visit for concussion assessment. This tool
measures the presence and severity of 22 symptoms, each
rated from 0 (none) to 6 (severe), and the scores are
summed to generate a symptom severity score. The total
number of symptoms present and the overall symptom
severity score were compared between each condition sub-
group and its respective control subgroup.
k
Address correspondence to James P. Dickey, MSc, PhD, School of Kinesiology TH4125, Western University, 1151 Richmond Street, London, Ontario
N6A3K7, Canada (email: jdickey@uwo.ca).
*School of Kinesiology, Western University, London, Ontario, Canada.
†
Faculty of Health Science, Lawson Health Research Institute, Fowler Kennedy Sport Medicine Clinic, London, Ontario, Canada.
‡
Schulich School of Medicine & Dentistry, Western University, London, Ontario, Canada.
§
Parkwood Institute, St. Joseph’s Health Care London, London, Ontario, Canada.
Final revision submitted May 25, 2022; accepted June 9, 2022.
The authors declared that they have no conflicts of interest in the authorship and publication of this contribution. AOSSM checks author disclosures
against the Open Payments Database (OPD). AOSSM has not conducted an independent investigation on the OPD and disclaims any liability or responsibility
relating thereto.
2Schulze et al The Orthopaedic Journal of Sports Medicine
Statistical Analysis
Using SPSS 27.0 (IBM Corp) and ttests, we evaluated the
differences in age between the mental health condition
subgroups and their respective control subgroups. Addi-
tionally, Mann-Whitney Utests were used to assess
between-group differences in number of symptoms, symp-
tom severity scores, and time (in days) from injury to initial
clinical assessment. Nonparametric statistics were used, as
the Shapiro-Wilk test for normality indicated that the data
were not normally distributed. Furthermore, a Mann-
Whitney Utest was used to calculate the corresponding Z
scores for each Pvalue. The differences were considered
statistically significant if P<.05.
Nonparametric effect sizes with 95%CIs were calculated
using the probability of superiority approach,
79,80
using an
open-source spreadsheet, GENERALISEDMW.xls, avail-
able online.
81
This measure of effect size, also called the
common language effect size,
35,66
indicates the proportion
of instances that a random member of the distribution with
the higher mean (eg, mental health condition group) will
have a higher score than a random member of the other (eg,
control group) distribution. Probability of superiority
values of 0.56, 0.64, and 0.71 correspond to small, medium,
and large effect sizes, respectively.
35,66
Box-and-whisker
plots were used to identify the median, interquartile range,
and outliers of the number of symptoms, symptom severity,
and time from injury to initial clinical assessment. The
whiskers were extended 1.5 times the length of the inter-
quartile range beyond the box boundaries, defining the
inner fence for identifying outliers.
47
Outliers were not
removed from statistical analysis. Individuals who did not
report an initial clinical assessment date were removed
from the Mann-Whitney Uanalysis.
Using SPSS 27.0 and chi-square analyses, we deter-
mined if the distributions of male and female participants,
and students and nonstudents, within the condition sub-
groups were related to the condition itself (ie, learning dis-
ability, anxiety, depression, multiple conditions).
90
Cramer’s Vtest was used to determine the effect size, inter-
preted using values of 0.06, 0.17, and 0.29 to correspond to
small, medium and large effect sizes (df ¼3), respectively.
54
Adjusted residuals were used to determine which cells were
making the greatest contribution to the chi-square test,
related to the presence of significant differences between
observed and expected frequencies. Adjusted residuals
>2.0 corresponded to a significantly greater difference in
distribution than would be expected. Additionally, chi-
square analyses were used to determine if there were sig-
nificant differences in the proportion of individuals who
reported a history of concussion in each condition subgroup.
Cramer’s Vtest was used to determine the effect sizes as
described above (df ¼1).
Factor weightings were extracted from studies that per-
formed exploratory factor analysis on SCAT symptom
scores
3,5
or reported symptom domain groupings.
8,61
These
factor weightings were used to calculate factor scores for all
participants,
44
following the 3-factor (Migraine Fatigue,
Affective, Cognitive-Ocular),
5
4-factor (Physical/Somatic,
Insomnia/Sleep, Emotional, Cognitive),
8,61
and 5-factor
(Energy, Mental Health, Migrainous, Cognitive, Vesti-
bulo-ocular)
3
schemes. Using SPSS 27.0, we ran 2-way
Paents Assessed for Concussion
at Fowler Kennedy Sport Medicine Clinic
(n = 765)
Control Group
(n = 412)
Matched Control Group
(n = 28)
Matched Control Group
(n = 124)
Matched Control Group
(n = 40)
Matched Control Group
(n = 126)
Unmatched Controls
(n = 94)
Condion Group
(n = 159)
Learning Disability Group
(n = 14)
Anxiety Group
(n = 62)
Depression Group
(n = 20)
Mulple Condions Group
(n = 63)
Excluded (n = 194)
- Not Meeng Inclusion Criteria
(n = 194)
- Declined to Parcipate (n = 0)
- Other Reasons (n = 0)
Depression & Learning Disability (n = 1; 1.6%)
Anxiety & Learni ng Disability (n = 7; 11.1%)
Depression & Anxiety (n = 46; 73.0%)
Depression, Anxiety, & Learning Disability (n = 9; 14.3%)
Figure 1. CONSORT (Consolidated Standards of Reporting Trials) flow diagram illustrating the grouping of participants.
The Orthopaedic Journal of Sports Medicine Association of Preexisting Mental Health Conditions 3
analyses of variance for each factor, investigating whether
the factor scores were significantly different between men-
tal health conditions, and between the control and condi-
tion subgroups. Levene tests of equality of error variances
were not performed, as they are not recommended for large
sample sizes.
51,104
RESULTS
All individuals reporting a mental health condition identified
as having a learning disability, anxiety, depression, or mul-
tiple conditions. Three of the 4 subgroups had a greater pro-
portion of female participants (anxiety, 58.1%;depression,
65.0%; multiple conditions, 68.3%); the learning disability
subgroup had a smaller proportion of female participants
(28.6%) (Table 1). This sex distribution varied significantly
within the mental health condition groups (w
2
¼7.87; df ¼3;
P¼.049), with a large effect size (Cramer’s V¼0.35). Based
on the adjusted residuals, the learning disability subgroup
(adjusted residual magnitude, 2.55) was the only mental
health condition subgroup with a significantly different sex
distribution when compared with the other condition sub-
groups. There were no significant differences in age between
the condition groups and their respective control groups.
Between 80%and 100%of the participants in each con-
dition and corresponding control group reported a sport-
related cause for their concussion (Table 1). Additionally,
approximately 40%to 65%of individuals in each condition
and corresponding control group reported a history of con-
cussion and had experienced 1 previous concussion (Table
1). The proportion of individuals reporting a history of con-
cussion was significantly greater in the anxiety and
multiple-conditions subgroups than their respective control
subgroups (w
2
¼4.75, df ¼1, P¼.043, Cramer’s V¼0.16;
and w
2
¼8.30, df ¼1, P¼.005, Cramer’s V¼0.21, respec-
tively). However, history of concussion did not vary signif-
icantly between the depression and learning disability
subgroups and their respective control subgroups (w
2
¼
0.84, df ¼1, P¼.418, Cramer’s V¼0.12; and w
2
¼0.44,
df ¼1, P¼.530, Cramer’s V¼0.10, respectively). Most
individuals in the learning disability subgroup fell within
the age range of 13 to 16 years, whereas more individuals in
the depression, anxiety, and multiple-conditions subgroups
fell in the 17- to 20-year age category (Table 2).
The proportion of individuals who self-reported a mental
health condition did not differ by student status (w
2
¼2.55;
df ¼3; P¼.466) (Table 1). All mental health condition
groups tended to have greater average symptom severity
scores, number of symptoms, and number of days between
TABLE 1
Demographics and Concussion-Related Characteristics for Participants in Each of the Mental Health Condition Subgroups
and Their Respective Control Groups
Age, y, mean ±SD
%Sport-Related
Concussion
%History of
Concussion %Student Status
Condition Subgroup n
a
%Female
b
Condition Control PCondition Control Condition Control Condition Control
Learning disability 14 28.6 20.7 ±9.3 20.4 ±8.6 .922 100 100 50.0 39.3 78.6 78.6
Anxiety 62 58.1 20.2 ±6.6 20.4 ±7.1 .917 95.2 96.0 60.0
c
42.7
c
80.6 77.4
Depression 20 65.0 24.6 ±11.5 25.3 ±13.0 .822 80.0 87.5 45.0 57.5 65.0 65.0
Multiple conditions 63 68.3 22.5 ±9.1 23.9 ±13.0 .470 88.9 97.0 65.1
c
42.9
c
66.7 72.0
a
The number of participants (n) was doubled in the respective control subgroups based on the 1:2 matching.
b
The percentage of female participants was identical between the mental health condition subgroups and their respective control sub-
groups based on the matching.
c
Statistically significant difference between condition and control subgroups (P<.01; w
2
test).
TABLE 2
Percentage of Individuals in the Mental Health Condition Subgroups and Respective Control Subgroups Across 5 Age
Categories
a
Learning Disability Anxiety Depression Multiple Conditions
Age Group,
y
Condition (n ¼
14)
Control (n ¼
28)
Condition (n ¼
62)
Control (n ¼
124)
Condition (n ¼
20)
Control
(n ¼
40)
Condition (n ¼
63)
Control (n ¼
126)
13-16 43.0 43.0 32.3 32.3 15.0 20.0 20.6 31.7
17-20 28.6 28.6 37.1 35.5 40.0 37.5 34.9 28.6
21-25 14.3 14.3 11.3 17.7 20.0 15.0 19.0 13.5
26-30 0 0 11.3 4.8 0 0 11.1 7.1
31 14.3 14.3 8.1 9.7 25.0 27.5 14.3 19.0
a
Data are reported as the percentage of the overall number of participants within each subgroup.
4Schulze et al The Orthopaedic Journal of Sports Medicine
injury and initial clinical visit compared with their respec-
tive control groups (Tables 3 and 4). The anxiety and the
multiple-conditions subgroups showed the largest differ-
ences in symptom severity score and number of symptoms
compared with their corresponding control subgroups
(Figure 2).
Individuals with self-reported anxiety had significantly
higher average symptom severity scores and a significantly
greater average number of symptoms (P¼.018 and .004,
respectively) compared with their control subgroup (Table
3 and Figure 2). Similarly, individuals who self-reported
multiple mental health conditions had significantly higher
average symptom severity scores and a significantly
greater average number of symptoms compared with their
control subgroup (P<.001 for both) (Table 3 and Figure 2).
There were no significant differences in average symptom
severity scores or the average number of symptoms for
either the depression or the learning disability subgroups,
although the effect sizes for these comparisons ranged from
small to medium (Table 3 and Figure 2).
All condition groups had a greater number of average
days between injury and initial clinical assessment than
their respective control group (Table 4). There were signif-
icant differences in the number of days from injury to initial
assessment between the control subgroup and the anxiety
(P¼.016), depression (P¼.013), and multiple-conditions
(P¼.002) subgroups (Table 4); however, there was no sig-
nificant difference in this outcome between the learning
disability subgroup (P¼.215) and its control subgroup.
Effect sizes for number of days from injury to initial assess-
ment ranged from small to large (Table 4). All condition and
control groups contained outliers.
Considering the symptom scores in each of the factor
domains, the interaction between mental health conditions
and control/conditions was not statistically significant, and
there were no statistically significant differences between
TABLE 3
Comparison of SCAT5 Symptom Severity Score and Number of Symptoms at Initial Concussion Assessment Between the
Condition Subgroups and Respective Control Subgroups
a
Symptom Severity Score, Median [IQR]
Condition Subgroup Condition Control PZScore Effect Size (95%CI)
Learning disability 43.5 [28, 66] 29.5 [8.25, 44.75] .085 –1.722 0.665
b
(0.477-0.807)
Anxiety 49 [26.75, 63] 34.5 [16, 56] .018 –2.359 0.606
b
(0.518-0.687)
Depression 47.5 [17.75, 78] 35 [20, 62.5] .348 –0.949 0.576
c
(0.422-0.714)
Multiple conditions 62 [29, 75] 32 [12, 56.25] <.001 –4.305 0.692
b
(0.607-0.764)
No. of Symptoms, Median [IQR]
Condition Subgroup Condition Control PZScore Effect Size (95%CI)
Learning disability 16 [12.5, 21.25] 14 [5, 17.75] .089 –1.699 0.662
b
(0.475-0.805)
Anxiety 17 [13.75, 21] 15 [9, 19] .004 –2.846 0.628
c
(0.540-0.707)
Depression 16.5 [11, 19] 11 [9.25, 19] .753 –0.314 0.525
c
(0.375-0.670)
Multiple conditions 18 [14, 21] 14.5 [7, 18] <.001 –4.454 0.698
b
(0.614-0.770)
a
Boldface Pvalues indicate a statistically significant difference between the condition subgroup and control subgroup (P<.05; Mann-
Whitney Utest). IQR, interquartile range; SCAT5, Sport Concussion Assessment Tool, 5th Edition.
b
Medium effect size.
c
Small effect size.
TABLE 4
Comparison of Time Between Injury and Initial Clinical Assessment for Concussion Between the Condition Subgroups and
Respective Control Subgroups
a
Days From Injury to Initial Clinical Assessment, Median [IQR]
Condition Subgroup Condition Control PZScore Effect Size (95%CI)
Learning disability 11.5 [6.25, 22.25] 7 [5, 12] .215 –1.241 0.619
b
(0.433-0.772)
Anxiety 12 [8, 27.75] 8.5 [5, 16] .016 –2.407 0.606
c
(0.513-0.683)
Depression 26.5 [10.75, 67.25] 9 [5.75, 17.75] .013 –2.472 0.715
c
(0.559-0.828)
Multiple conditions 18 [7, 37] 9 [5, 20] .002 –3.065 0.638
b
(0.550-0.716)
a
Boldface Pvalues indicate a statistically significant difference between the condition subgroup and control subgroup (P<.05;
Mann-Whitney Utest). IQR, interquartile range.
b
Small effect size.
c
Large effect size.
The Orthopaedic Journal of Sports Medicine Association of Preexisting Mental Health Conditions 5
the mental health condition subgroups for all symptom fac-
tor domains (all P>.05). However, the symptom factor
scores were significantly higher in the mental health con-
dition groups than the corresponding control groups for all
symptom factor domains (all P<.05) (Table 5).
DISCUSSION
It was hypothesized that participants with a preexisting
mental health condition—anxiety, depression, a learning
disability, or multiple conditions—would report a greater
number of symptoms and an increased symptom severity as
assessed by the SCAT5 at the time of initial concussion
assessment compared with control participants. This study
determined that during initial concussion assessment, indi-
viduals who self-report preexisting anxiety or multiple
mental health conditions had a significantly greater num-
ber of symptoms and higher symptom severity compared
with individuals without a preexisting mental health con-
dition. However, participants with a history of depression
or a learning disability in isolation did not differ
TABLE 5
Comparison of Overall SCAT5 Symptom Scores Between the Condition and Control Groups Using 4-Factor Loading Sources
and Their Respective Symptom Factor Categories
a
Study Symptom Factor Category
Anderson et al (2020)
5
Migraine-Fatigue Cognitive-Ocular Affective
Condition 9.28 ±5.13 4.37 ±3.68 7.10 ±5.19
Control 7.89 ±7.80 2.72 ±2.83 4.02 ±4.89
P.004 <.001 <.001
Langer et al (2021)
61
Somatic Cognitive Emotional Sleep
Condition 19.67 ±11.18 9.58 ±6.82 9.33 ±6.78 4.82 ±3.33
Control 16.34 ±10.58 6.49 ±5.69 5.32 ±5.74 3.28 ±3.04
P.002 <.001 <.001 <.001
Asken et al (2017)
8
Physical Cognitive Emotional Insomnia
Condition 19.67 ±11.18 9.58 ±6.82 9.33 ±6.78 4.82 ±3.33
Control 16.34 ±10.58 6.49 ±5.69 5.32 ±5.74 3.28 ±3.04
P.002 <.001 <.001 <.001
Alsalaheen et al (2022)
3
Mental Health Vestibulo-ocular Cognitive Migrainous Energy
Condition 8.10 ±5.83 3.63 ±3.24 5.04 ±4.04 9.39 ±5.15 11.91 ±6.94
Control 4.68 ±4.94 2.68 ±2.73 3.15 ±3.10 8.14 ±4.91 8.85 ±6.95
P<.001 <.001 <.001 .010 <.001
a
Data are reported as mean ±SD. Boldface Pvalues indicate a statistically significant difference between the condition group and control group
(P<.05; 2-way analysis of variance). The interactions between mental health conditions and control conditions were not statistically significant.
There were no statistically significant differences between mental health conditions. SCAT5, Sport Concussion Assessment Tool–5th Edition.
Figure 2. Box-and-whisker plots illustrating (A) Sport Concussion Assessment Tool–5th Edition (SCAT5) symptom severity scores
and (B) number of SCAT5 symptoms for the mental health condition subgroups and their corresponding control subgroups. The
bars illustrate the medians, the boxes illustrate the interquartile range (IQR), the whiskers extend 1.5 times the length of the IQR,
and the triangles illustrate outliers.
6Schulze et al The Orthopaedic Journal of Sports Medicine
significantly from control participants without a preexist-
ing mental health condition. Factor scores for each of the
different factor schemes were not significantly different
between the mental health conditions.
Concussion Assessment Tools
Concussion assessment tools are used for diagnosis and
monitoring of recovery.
24,49,71
This study examined the
symptom evaluation component of the SCAT5 tool in indi-
viduals undergoing a concussion assessment.
28
SCAT5
evaluates for common immediate and delayed symptoms
related to concussion.
8,28,61
Interpretation of the SCAT5
scores does not require baseline data.
28
Although clinicians
can diagnose concussions using normative data,
28
baseline
measures are necessary for intraindividual comparisons
with a nonconcussed state.
28
As we observed that indivi-
duals with anxiety or multiple mental health conditions
have a significantly greater number of symptoms and
severity of symptoms compared with matched control par-
ticipants, data for individuals with these mental health
conditions should not be compared with normative baseline
values. Rather, baseline data should be collected for indivi-
duals with a mental health condition, as this enables the
monitoring of intraindividual changes in symptomatology.
In addition to the symptom evaluation, the SCAT5
includes cognitive and neurological screening sections to
evaluate memory, concentration, coordination, and
balance.
28
Medical professionals rely on an individual’s
self-reported symptoms as one criterion for diagnosing con-
cussions; therefore, our study was limited to the symptom
evaluation.
9,76
Although concussion assessment tools are
available, medical professionals are not mandated to use
them to diagnose concussion.
9,75
The Brief Symptom Inven-
tory–18 (BSI-18) is similar to the SCAT5 as it also aims to
assess and quantify individuals’ symptoms related to psy-
chological distress and psychiatric disorders.
24
The
ImPACT is another common tool composed of neurocogni-
tive tests, vestibulo-ocular motor screening, and the Bal-
ance Error Scoring System.
71
As further evidence of the
importance of symptom evaluations, research using concus-
sion assessment tools often evaluates symptoms even when
the tools themselves do not.
49,99
Concussion assessments can be used to monitor the
recovery of signs and symptoms; however, they do not mon-
itor the physiological recovery of the brain.
26,36,37,40,85
Neu-
roimaging has been employed to quantify the change in
brain physiology due to concussion, expanding beyond the
use of concussion assessment tools.
26,36,37,40,85
Brain phys-
iology can be measured through modalities such as diffu-
sion tensor imaging (DTI),
37
magnetic resonance
spectroscopy (MRS),
36
and functional magnetic resonance
imaging (fMRI).
40,65,85
Unlike computed tomography and
MRI, DTI, MRS and fMRI can be used to detect physiolog-
ical disturbance associated with concussion.
85
While pro-
viding insights, they require costly off-field equipment,
85
which limits their widespread adoption. In contrast, con-
cussion assessment tools such as SCAT5, BSI-18, and
ImPACT are more feasible.
Assessment of Concussion Symptoms in Patients
With Mental Health Conditions
Research has shown that individuals with mental health
conditions reported a significantly higher number of symp-
toms and symptom severity during preconcussion baseline
testing using assessment tools such as the Child–SCAT,
ImPACT, and BSI-18.
17,19,99
Literature investigating base-
line Child–SCAT scores also found that preexisting ADHD
was associated with a greater number and severity of symp-
toms.
17,19
Additionally, literature investigating the Adult–
SCAT as a baseline test has found that individuals with
anxiety, depression, and multiple mental health conditions
reported a significantly greater number and severity of
symptoms compared with an extremely large independent
control group (>29 times larger than any of the mental
condition groups), which may have resulted in an overpow-
ered study.
99
This is a concern since overpowered studies
can produce outcomes that are statistically significant yet
have little practical meaning.
101
To the best of our knowledge, this is the first study to
show that individuals with preexisting anxiety or multiple
mental health conditions have a significantly greater num-
ber of symptoms and symptom severity when undergoing
initial screening with the SCAT5 after suspected concus-
sion. This differs from the current baseline testing litera-
ture and might be explained by the inflated power in the
study by Weber et al,
99
as they noted their results were
likely affected by oversampling. Additionally, both Weber
et al and Collings et al,
17
in their studies of baseline testing,
did not case-match for each participant but rather com-
pared condition groups with the entire pool of controls. In
contrast, while Cook et al
19
did case-match participants,
they did not evaluate any preexisting mental health condi-
tions other than ADHD. Our experiment had a greater
number of participants with learning disabilities in the
multiple-conditions group than in the isolated learning dis-
abilities group. Accordingly, a significant proportion of the
participants in the Cook et al study may have had multiple
conditions rather than an isolated learning disability. Addi-
tionally, Cook et al used the Child–SCAT,
23
requiring both
the child and the parent to report the child’s symptoms. The
parent’s perception of the child’s symptoms may differ from
the child’s true experience; furthermore, children may pos-
sibly struggle to fully understand the extent of their symp-
toms or how to properly report them.
23,69
Factor Scores and Mental Health Conditions
We did not observe any statistically significant differences
in factor scores between the mental health conditions for
any of the factor schemes.
3,5,8,61
In contrast, Asken et al
8
found that individuals with psychiatric disorders (depres-
sion and anxiety) had higher scores in the Emotional
domain. These differences may be because of the different
study populations since Asken et al
8
studied nonconcussed
individuals while the current study evaluated individuals
who were being assessed for concussion. Additionally, we
observed that the mental health condition groups had
higher scores on all domains compared with their
The Orthopaedic Journal of Sports Medicine Association of Preexisting Mental Health Conditions 7
corresponding control groups. This is consistent with our
findings of an increased total number of symptoms in men-
tal health condition groups compared with their respective
control groups. Therefore, the division of symptoms into
factor domains did not reflect any information beyond the
total symptom score measure.
Time From Injury to Assessment
In our study, condition group individuals attended their
initial clinical assessment on average more days post-
injury than individuals in the respective control group.
Individuals in the depression, anxiety, and multiple-
conditions subgroups took significantly more days to attend
a clinic than individuals in the control subgroups. This dif-
ference in duration suggests a delay in seeking treatment.
This is consistent with literature stating that people with
mental health conditions are more likely to engage in poor
personal health behaviors, such as delaying evaluation
when medical care is needed.
64,67,103
This is further seen
through the factor analysis of SCAT5 symptoms, in which
individuals with higher symptom scores related to the Men-
tal Health domain are associated with a longer time
between injury and assessment.
3
While 1 in 3 individuals
will eventually seek treatment for their mental health con-
dition,
95,98
the initial evaluation is often delayed from the
initial onset of symptoms. On average, individuals with a
mood disorder will delay treatment for 8 years, while those
with an anxiety disorder will delay for 9 years.
95,97
This
may be related to the internalized stigma of mental health
conditions, which has been associated with longer delays in
seeking treatment
25
and decreased treatment adherence.
70
Furthermore, the Lauver’s theory of care-seeking behavior
states that a series of psychosocial variables, including anx-
iety, play a significant role in determining when an individ-
ual will seek health care.
87
Individuals with mental health
conditions are more likely to avoid seeking health care,
even when they suspect they should.
103
Health care avoid-
ance is a significant barrier to and has a negative effect on
the well-being of individuals with mental health condi-
tions.
103
Similarly, when immediate diagnosis and treat-
ment for a concussion are not sought, the individual
increases their risk of experiencing a delay in healing; an
increase in symptom severity; an increase in time
away from work, school, and/or sport; or second-hit
syndrome.
6,7,10,12,30,45,48,100
However, the observed delay in seeking treatment is the
opposite of what is expected, according to the diasthesis-
stress model.
102
In this model, a concussion would be con-
sidered a significant stressor and therefore would likely
result in the presentation of previously dormant psycholog-
ical difficulties.
8
For individuals with mental health condi-
tions, the sudden onset of new symptoms can lead to
catastrophic thinking.
31,83
According to Ellis,
31
cata-
strophic thinking is the tendency to magnify a perceived
threat and overestimate the seriousness of its potential con-
sequences. Catastrophizing leads to avoidance and safety-
seeking behaviors.
38
Individuals avoid situations that lead
to perceived negative outcomes and react to these outcomes
by partaking in safety-seeking behaviors.
38
Safety-seeking
behaviors would likely urge individuals to seek treatment
sooner than their noncatastrophizing counterparts. How-
ever, individuals with mental health conditions that lead
to catastrophizing avoid seeking treatment, as it can lead to
a diagnosis, solidifying their catastrophic thoughts.
38
Cat-
astrophic thinking ultimately leads to a delay in seeking
and attending treatment.
68,91
Self-Reporting Symptoms and Mental Health
Conditions
Individuals with mental health conditions are known to
ruminate, overanalyze, and catastrophize
31,33,94
; however,
research has yet to investigate how this may affect self-
reported concussion symptoms. Self-reporting symptoms
has been associated with the inaccurate portrayal of pre–
and post–mild traumatic brain injury symptoms in children
and adults.
56,62,63
Similarly, in individuals without mental
health conditions, this can be due to poor effort during test-
ing or the exaggeration of one’s symptoms.
59
These inac-
curacies can lead to personal gain, such as financial gain
for adults,
62,63
or getting out of tasks for children.
55
Exag-
geration may be purposeful, such as “sandbagging,”
32
or
unknowing. The phenomenon of unknowingly exaggerat-
ing one’s symptoms is referred to as the “good old days”
bias.
42
This bias is the outcome of an individual’s viewing
one’s past state of symptoms as “better” than one’s current
state.
42,50,60
This can lead to the inaccurate portrayal of
past symptoms and the misinterpretation of current post-
injury symptoms as new.
42,50,60
Research has yet to inves-
tigate if there is a link between the good old days bias and
increased symptom exaggeration in individuals with men-
tal health conditions.
Studies have shown that concussed individuals without
mental health conditions exhibit higher pain catastrophiz-
ing associated with having more post-concussion symp-
toms.
14,41
Multidimension symptom exaggeration has also
been observed in individuals with depression.
78
This may
correspond to these individuals’ exaggerating their concus-
sion symptoms, resulting in increased self-reported symp-
tom severity and perhaps an increased number of
symptoms. Additionally, individuals with depression and
anxiety show a similar symptomatology to post-concussion
syndrome.
13,42
Accordingly, the increased number and
severity of concussion symptoms observed in the current
experiment may be related to a combination of exaggerated
symptoms and genuine dysfunction.
78
Ratio of Male to Female Participants
In our study, a greater proportion of male participants self-
reported learning disabilities than female participants,
whereas a greater proportion of female participants self-
reported anxiety, depression, and multiple mental health
conditions. The latter difference is expected in part due to
the larger number of female participants recruited to the
study sample. Our study population is also in keeping with
the existing literature, which has demonstrated that a
greater proportion of female participants self-report
8Schulze et al The Orthopaedic Journal of Sports Medicine
anxiety and depression than male participants.
1,57,89
The
larger proportion of male participants seen in the learning
disability subgroup is consistent with the existing scientific
literature reporting on the demographic data from athletes
and adults with mental health conditions.
{
Additionally,
our study population is consistent with previous literature
reporting that males are diagnosed with learning disabil-
ities at a higher rate than females.
39,86,93
Interestingly,
these subgroup proportions are likely related to sex-based
differences in mental disorder diagnoses.
1,39,46,52,77
This is
directly linked to referral bias and gender stereotypes in
the Fifth edition of the Diagnostic and Statistical Manual
of Mental Disorders.
4
Clinical Relevance
In the anxiety and multiple-conditions subgroups, the num-
ber of symptoms and symptom severity were significantly
greater than in their respective control subgroups; however,
they had a small and medium effect size, respectively. In
contrast, although not statistically significant, there were
medium effect sizes associated with greater number of symp-
toms and symptom severity for the learning disability sub-
group compared with its respective control subgroup and
small effect sizes associated with greater number of symp-
toms and symptom severity for the depression subgroup
compared with its respective control subgroup. Accordingly,
these differences are practically important.
73
Clinicians will
often need to interpret the SCAT5 results with no baseline
assessment data available for comparison. Not only does the
latest version of the SCAT5 not require the completion of a
baseline assessment,
22
but also baseline assessments are not
practical outside of athletes participating in certain orga-
nized sports. Normative data are readily available for
athletes with a valid baseline and acute SCAT5 evalua-
tions,
11,15,27,58
excluding individuals with neurological and
balance disorders,
27
concomitant illness or injury,
58
and
multiple evaluations for suspected concussion or multiple
prospective diagnosed concussions.
11
However, these norma-
tive values may not be applicable to all individuals post-con-
cussion given that the current study has provided evidence
to suggest that some preexisting mental health conditions—
such as anxiety, depression, and learning disabilities in
adults and athletes
16,43,53,72,84,88,92
—may be associated with
differences in symptom number and severity post-injury.
Additionally, the normative values for symptom number and
severity developed using the entire population may be inap-
propriately inflated for individuals without concurrent men-
tal health conditions. In order for clinicians to properly
interpret SCAT5 scores and develop appropriate manage-
ment plans, they must understand the effects of preexisting
mental health conditions on symptom number and severity
and must have access to a complete past medical history for
each athlete undergoing assessment. This study indicates
that clinicians should consider the effects of preexisting anx-
iety or multiple mental health conditions on an individual’s
concussion-related symptomatology at the time of initial
evaluation. Future research should assess the effect of addi-
tional mental health conditions—such as posttraumatic
stress disorder (PTSD), substance abuse, and psychosis—
and investigate whether individuals with mental health con-
ditions have altered concussion recovery compared with
individuals without mental health conditions.
Limitations
A primary limitation of this study was the sample used. All
participants were concussed, and accordingly, we were
unable to make comparisons between concussed and non-
concussed individuals with mental health conditions. Addi-
tionally, the sample only contains individuals who actively
sought health care for their concussion at a single clinic.
Furthermore, the clinical questionnaires in use in this
clinic did not prompt patients to report an exhaustive list
of mental health conditions; specifically, patients were not
prompted to report a history of PTSD, psychosis, or sub-
stance abuse. This limits the generalizability of our find-
ings to a specific context and population, in addition to the
single-site sample population. Furthermore, most indivi-
duals in this sample sustained a sport-related concussion,
which also limits the generalizability of the findings. An
additional limitation is that we were unaware of what
prompted participants to attend the clinic (eg, a change in
daily symptoms or advice from a peer). Therefore, it is not
known if those with mental health conditions attended the
clinic because of a noticeable difference in their usual daily
symptoms as an outcome of a concussion. Furthermore, it is
possible that some individuals did not attend the clinic, as
mild concussion-related symptoms may not have been suf-
ficiently different from their daily symptoms thus not
prompting the need to seek health care. Future studies
would benefit from recruiting participants with sport- and
non–sport related concussion origins as well as collecting
data on a wider range of preexisting mental health condi-
tions. Additionally, studying individuals with physician-
diagnosed mental health conditions rather than basing
analysis on participant self-report would be advantageous.
Individuals may self-report a mental health condition yet
have limited or subtle symptoms, whereas physician-
diagnosed conditions are derived from a clinically informed
decision and evidence-based diagnostic criteria. Further-
more, individuals may choose to not self-report a mental
health condition because of the social pressure or related
stigma, regardless of a formal diagnosis.
20,34,57,82,89
CONCLUSION
Understanding how preexisting mental health conditions
can affect the number and severity of concussion symptoms
is important and can aid clinicians in the interpretation of
SCAT5 symptom evaluation scores at the time of initial
presentation for concussion assessment. Given that indivi-
duals with preexisting anxiety or multiple mental health
conditions report an increased number of symptoms and
symptom severity on the SCAT5 after concussion, clini-
cians should choose to take a complete past medical history
{
References 1, 2, 43, 53, 72, 84, 88, 92,99.
The Orthopaedic Journal of Sports Medicine Association of Preexisting Mental Health Conditions 9
before interpreting their patients’ scores. Furthermore,
normative data should be used with caution for individuals
with mental health conditions. More research is needed to
determine how other mental health conditions may affect
SCAT5 symptom and severity scores.
ACKNOWLEDGMENT
The authors thank the patients and staff at the Fowler
Kennedy Sport Medicine Clinic for participating in and
assisting with this study.
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