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Objective: Youth with attention deficit hyperactivity disorder (ADHD) perform more poorly on preseason cognitive testing and report more baseline concussion-like symptoms but prior studies have not examined the influence of medication use on test performance or symptom reporting. This study investigated whether medication use is relevant when interpreting baseline ImPACT® results from student athletes with ADHD. Method: Participants were 39,247 adolescent athletes, ages 13-18 (mean age = 15.5 years, SD = 1.3), who completed baseline cognitive testing with ImPACT®. The sample included slightly more boys (54.4%) than girls. Differences in ImPACT® composite scores and concussion-like symptom reporting (between ADHD/No medication, ADHD/Medication, No ADHD/Medication, and Control groups) were examined with ANOVAs, conducted separately by gender. Results: In this large, state-wide data-set, youth with ADHD had greater rates of invalid ImPACT results compared to control subjects (ADHD/No Medication: girls = 10.9%, boys = 10%; ADHD/Medication: girls = 8.1%, boys = 9.1%; Controls: girls = 5.2%, boys = 6.7%). Groups differed across all ImPACT® composites (invalid profiles were removed), in the following order (from worse to better performance): ADHD/No Medication, ADHD/Medication, and Control participants. Pairwise effect sizes indicated that the largest differences were on the Visual Motor Speed composite, with the ADHD/No medication group performing worse than the ADHD/Medication group and the Controls. The ADHD/Medication group did not differ meaningfully from Controls on any composite, for either sex (d = 0 to .19). The ADHD groups did not differ on total symptom scores but both ADHD groups endorsed significantly more symptoms compared to Controls. Conclusions: Contrary to our hypothesis, we found medication use had only a subtle effect on cognitive performance and no significant effect on concussion-like symptom reporting. Student athletes reporting medication use for ADHD performed comparably to student athletes with no ADHD on baseline testing.
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The Clinical Neuropsychologist
ISSN: 1385-4046 (Print) 1744-4144 (Online) Journal homepage: http://www.tandfonline.com/loi/ntcn20
Baseline cognitive test performance and
concussion-like symptoms among adolescent
athletes with ADHD: examining differences based
on medication use
Nathan E. Cook, Donna S. Huang, Noah D. Silverberg, Brian L. Brooks, Bruce
Maxwell, Ross Zafonte, Paul D. Berkner & Grant L. Iverson
To cite this article: Nathan E. Cook, Donna S. Huang, Noah D. Silverberg, Brian L. Brooks,
Bruce Maxwell, Ross Zafonte, Paul D. Berkner & Grant L. Iverson (2017) Baseline cognitive test
performance and concussion-like symptoms among adolescent athletes with ADHD: examining
differences based on medication use, The Clinical Neuropsychologist, 31:8, 1341-1352, DOI:
10.1080/13854046.2017.1317031
To link to this article: http://dx.doi.org/10.1080/13854046.2017.1317031
Published online: 21 Apr 2017.
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THE CLINICAL NEUROPSYCHOLOGIST, 2017
VOL. 31, NO. 8, 13411352
https://doi.org/10.1080/13854046.2017.1317031
Baseline cognitive test performance and concussion-like
symptoms among adolescent athletes with ADHD: examining
dierences based on medication use
Nathan E. Cooka,b,c, Donna S. Huangd,e, Noah D. Silverbergc,e,f,g,h, Brian L. Brooksi,j,k,
Bruce Maxwelll, Ross Zafontee,h,m,n,o, Paul D. Berknerp and Grant L. Iversonc,d,e,h
aDepartment of Psychiatry, Harvard Medical School, Boston, MA, USA; bLearning and Emotional Assessment
Program, Department of Psychiatry, Massachusetts General Hospital, Boston, MA, USA; cMassGeneral Hospital
for Children Sport Concussion Program, Boston, MA, USA; dSpaulding Rehabilitation Hospital, Boston, MA,
USA; eDepartment of Physical Medicine and Rehabilitation, Harvard Medical School, Boston, MA, USA;
fDivision of Physical Medicine & Rehabilitation, University of British Columbia, Vancouver, Canada; gGF Strong
Rehab Centre, Vancouver, Canada; hHome Base, A Red Sox Foundation and Massachusetts General Hospital
Program, Boston, MA, USA; iNeurosciences and Vi Riddell Children’s Pain and Rehabilitation Program, Alberta
Children’s Hospital, Calgary, Canada; jDepartments of Paediatrics, Clinical Neurosciences, and Psychology,
University of Calgary, Calgary, Canada; kAlberta Children’s Hospital Research Institute, University of Calgary,
Calgary, Canada; lDepartment of Computer Science, Colby College, Waterville, ME, USA; mDepartment of
Physical Medicine and Rehabilitation, Spaulding Rehabilitation Hospital, Boston, MA, USA; nDepartment of
Physical Medicine and Rehabilitation, Massachusetts General Hospital, Boston, MA, USA; oDepartment of
Physical Medicine and Rehabilitation, Brigham and Women’s Hospital, Boston, MA, USA; pHealth Services and
the Department of Biology, Colby College, Waterville, ME, USA
ABSTRACT
Objective: Youth with attention decit hyperactivity disorder (ADHD)
perform more poorly on preseason cognitive testing and report
more baseline concussion-like symptoms but prior studies have not
examined the inuence of medication use on test performance or
symptom reporting. This study investigated whether medication
use is relevant when interpreting baseline ImPACT® results from
student athletes with ADHD. Method: Participants were 39,247
adolescent athletes, ages 13–18 (mean age= 15.5years, SD =1.3),
who completed baseline cognitive testing with ImPACT®. The sample
included slightly more boys (54.4%) than girls. Dierences in ImPACT®
composite scores and concussion-like symptom reporting (between
ADHD/No medication, ADHD/Medication, No ADHD/Medication, and
Control groups) were examined with ANOVAs, conducted separately
by gender. Results: In this large, state-wide data-set, youth with
ADHD had greater rates of invalid ImPACT results compared to
control subjects (ADHD/No Medication: girls= 10.9%, boys=10%;
ADHD/Medication: girls=8.1%, boys=9.1%; Controls: girls= 5.2%,
boys=6.7%). Groups diered across all ImPACT® composites (invalid
proles were removed), in the following order (from worse to better
performance): ADHD/No Medication, ADHD/Medication, and Control
participants. Pairwise eect sizes indicated that the largest dierences
were on the Visual Motor Speed composite, with the ADHD/No
medication group performing worse than the ADHD/Medication
group and the Controls. The ADHD/Medication group did not dier
© 2017 Informa UK Limited, trading as Taylor & Francis Group
KEYWORDS
Attention-deficit/
hyperactivity disorder
(ADHD); concussion; mild
traumatic brain injury;
adolescents
ARTICLE HISTORY
Received 16 July 2016
Accepted31 March 2017
CONTACT Nathan E. Cook necook@mgh.harvard.edu
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1342 N. E. COOK ET AL.
meaningfully from Controls on any composite, for either sex (d= 0
to .19). The ADHD groups did not dier on total symptom scores but
both ADHD groups endorsed signicantly more symptoms compared
to Controls. Conclusions: Contrary to our hypothesis, we found
medication use had only a subtle eect on cognitive performance and
no signicant eect on concussion-like symptom reporting. Student
athletes reporting medication use for ADHD performed comparably
to student athletes with no ADHD on baseline testing.
Attention Decit/Hyperactivity Disorder (ADHD) is a common neurodevelopmental disorder
occurring in approximately 8–11% of children and adolescents (Visser et al., 2014). It is
marked by inattention, distractibility, hyperactivity, and/or impulsivity, and it is associated
with multiple cognitive vulnerabilities (American Psychiatric Association, 2013). Meta-analytic
evidence suggests that ADHD is most strongly and consistently associated with weaknesses
in response inhibition, vigilance, spatial working memory, and planning (Willcutt, Doyle,
Nigg, Faraone, & Pennington, 2005). Additionally, multiple studies have established that
processing speed, including reaction time, is negatively impacted in children and adolescents
with ADHD (Goth-Owens, Martinez-Torteya, Martel, & Nigg, 2010; Shanahan et al., 2006).
Consensus groups in sport-related concussion (McCrory et al., 2013) as well as pediatrics
(Halstead, Walter, & Council on Sports Medicine & Fitness, 2010) have identied youth with
ADHD as a unique and important population to study in regards to risk for MTBI and outcome
from this injury. Moreover, the assessment and management of pediatric sport-related con-
cussion and MTBI is an important societal concern, with legislators around the United States
mandating that student athletes be evaluated by a health care professional before resuming
participation in sports. To address this growing concern, many student athletes undergo
preseason cognitive testing. In the event a student sustains a concussion, they can be
re-tested and results can be compared to their baseline performance. These test results can
assist in the management of student injuries and help determine a youth’s readiness to
resume sport participation.
One widely used cognitive testing platform for assessing the eects of sport-related con-
cussion is the Immediate Post-Concussion Assessment and Cognitive Testing battery, or
ImPACT® (ImPACT Applications Inc, 2011). Several prior studies have examined baseline
cognitive functioning and symptom reporting with ImPACT® among youth with ADHD. The
results have been mixed. Some studies have reported that adolescent athletes with ADHD
score lower on all composite scores during baseline ImPACT® testing compared to youth
without ADHD (Elbin et al., 2013; Sussman & Mautner, 2014; Zuckerman, Lee, Odom, Solomon,
& Sills, 2013). However, the largest available study, with a sample of over 27,000 athletes
(mostly high-school students, mean age of 15) reported negligible eect sizes (Cohen’s d < .2)
between ADHD and control groups (Elbin et al., 2013). In contrast, one study reported that
youth with ADHD only scored lower than matched controls on the Verbal Memory composite
(Mautner, Sussman, Axtman, Al-Farsi, & Al-Adawi, 2015) and another study reported gen-
der-specic dierences between youth with ADHD and matched controls across various
composites (Brooks, Iverson, Atkins, Zafonte, & Berkner, 2016). Generally, these studies
reported small eect sizes between ADHD and control groups, although Brooks et al. (2016)
reported a medium eect size for girls on Visual Motor Speed. Youth with ADHD also report
more concussion-like symptoms on baseline testing, with eect sizes ranging from small to
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THE CLINICAL NEUROPSYCHOLOGIST 1343
medium (Brooks et al., 2016; Elbin et al., 2013; Iverson et al., 2015). Lastly, ADHD appears to
be associated with increased rates of performing below the cutos on the validity indicators
during baseline testing (Nelson, Pfaller, Rein, & McCrea, 2015).
Researchers to date have not examined the intersection of ADHD, baseline cognitive
testing, and medication use among younger adolescents. This is an important area of inquiry
given meta-analytic ndings that stimulant medication can reduce the behavioral symptoms
of ADHD, and the improvement appears to be roughly comparable in inattentive symptoms
and hyperactivity/impulsivity (Faraone & Buitelaar, 2010). Moreover, recent meta-analytic
evidence has suggested that stimulant medication can also improve cognitive functioning
in children and adolescents with ADHD, including memory, reaction time, reaction time
variability, and response inhibition (Coghill et al., 2014). A recent study compared neurocog-
nitive test performance (CNS Vital Signs) of 22 young adults with ADHD (mean age 21 years)
when they were on vs. o stimulant medication. These authors found comparable verbal
and visual memory test performances, and improved performance on tests of psychomotor
speed (d = 1.06) and reaction time (d = .58) when athletes were on medication (Littleton
et al., 2015). Further, when these young adults with ADHD where medicated, their test per-
formances did not dier from controls. However, other evidence suggests that youth with
ADHD, even those on stimulant medication, may still not perform similarly to healthy controls
on neurocognitive testing. For example, a study of older adolescents (mean age 17) com-
pared 29 psychostimulant users to matched controls who did not report medication use
and, although groups performed comparably on ImPACT Visual Memory and Verbal Memory
composites, signicant dierences were reported such that psychostimulant users per-
formed worse on the Visual Motor Speed and Reaction Time composites, with medium eect
sizes (Yengo-Kahn & Solomon, 2015).
The purpose of this study was to examine whether there are dierences in baseline cog-
nitive test results and concussion-like symptom reporting in adolescent athletes with ADHD
based on self-reported medication use. Given evidence of neurocognitive vulnerabilities
among adolescents with ADHD and the improvement in cognition attributable to pharma-
cotherapy, it was hypothesized that youth with ADHD who did not report taking medication
would perform more poorly on cognitive testing than controls without ADHD and youth
with ADHD who do report taking medication. This hypothesis includes a greater rate of
invalid ImPACT® test results as well as poorer performance across the cognitive composite
scores in those with ADHD who were not on medications. It was hypothesized that both
groups with ADHD would report more concussion-like symptoms than controls and that
girls would report more symptoms than boys.
Method
Participants
Participants for this study were derived from a cohort of 41,430 adolescent student athletes
from Maine, between the ages of 13 and 18, who completed baseline cognitive testing with
ImPACT® between 2009 and 2014. Students were included if they took the test in English
(n = 633 excluded), did not report suering a concussion within the past 6 months (n = 1,047
excluded), and did not report a lifetime history of epilepsy, brain surgery, or meningitis
(n = 548 excluded). The nal sample included 39,247 adolescents, with a mean age of
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1344 N. E. COOK ET AL.
15.5 years (SD = 1.3). The sample included slightly more boys (54.4%) than girls. Data regard-
ing race and ethnicity were not available. A total of 2,543 participants (6.5%) self-reported
having ADHD. Of those, 838 (32.9%) reported taking medication to treat ADHD. Boys and
girls with ADHD did not dier meaningfully in terms of the percentages reporting ADHD
medication use (girls: 31.8%; boys: 33.4%).
Procedure
All health history information in this study is retrospective and based on adolescent self-re-
port. Student athletes in our sample completed baseline testing with ImPACT® prior to par-
ticipating in sports for a given season. These data were systematically collected and merged
into a data-set that includes preseason ImPACT® data for student athletes from across the
state of Maine. Institutional Review Board approval for use of this de-identied database
was obtained from Colby College and an exemption was obtained from Spaulding
Rehabilitation Hospital. ImPACT® is a brief computer-administered test battery measuring
self-reported symptoms (i.e. the Post-Concussion Scale) and neurocognitive functioning (i.e.
Verbal Memory, Visual Memory, Visual Motor Speed, and Reaction Time). It also includes a
demographics and history questionnaire. Of interest to the current study are questionnaire
items asking students if they have ADHD as well as to record medication(s) they are taking
in a free-text eld. Of note, they are not explicitly asked whether they took their medication
on the day of testing, about the specic medication formulations (i.e. short vs. long-acting
medications), or dosing. A physician (DSH) individually examined each open-ended student
response to the medication question and coded medications based on class (e.g. amphet-
amines, selective serotonin reuptake inhibitors, etc.) and likely indication (e.g. ADHD, depres-
sion, etc.). The current study focused on self-reported medications used to treat ADHD, both
stimulants (amphetamine, atomoxetine, dexmethylphenidate, dextroamphetamine, and
lisdexamfetamine) and non-stimulants (clonidine and guanfacine). Three main study groups
were formed: (a) students who did not report ADHD or ADHD medication use (Controls); (b)
students who reported ADHD but did not report taking ADHD medication (ADHD/No
Medication); and (c) students who reported ADHD and ADHD medication use (ADHD/
Medication). A fourth group was formed consisting of youth who did not endorse having
ADHD but who did indicate ADHD medication use (No ADHD/Medication). This type of
reporting could suggest that our self-report history data are unreliable, however, very few
participants responded this way. In fact, this group included only 265 participants, or .006%
of the full sample. We did not have hypotheses in regards to how this group would perform
because the composition of this group is unclear. Groups did not dier appreciably by age
(range 15.5–15.7 years). Groups did dier in terms of percentages of boys and girls.
Specically, the control group included 46.6% girls and 53.2% boys, compared to the three
other groups which included roughly 29% girls (range 28.8–30.6%) and 70% boys (range
69.4–71.8%).
Measure
ImPACT® is a brief computer-administered neuropsychological test battery that assesses
multiple aspects of cognitive functioning. The battery includes composite scores called
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THE CLINICAL NEUROPSYCHOLOGIST 1345
Verbal Memory, Visual Memory, Visual Motor Speed, Reaction Time, and Impulse Control.
The program uses an algorithm to evaluate test results and identify those that are suspected
of being invalid. It also includes the Post-Concussion Symptom scale, a self-report question-
naire comprised of 22 commonly reported symptoms such as headache, dizziness, diculty
concentrating, and ‘fogginess.’ Students rate the severity of each symptom from 0 to 6. A
‘Total Symptom Score was computed as the sum from these 22 item severity ratings. Readers
are referred to the test manual for a more complete description of ImPACT® (ImPACT
Applications Inc, 2011).
Statistical analyses
Chi-square tests were conducted to examine for diering rates of invalid ImPACT® results.
Odds Ratios (ORs) were computed to characterize the magnitude of dierences. The ORs
can be interpreted as eect sizes (ES) based on a conversion method reported by Chinn
(2000) and interpreted according to criteria suggested by Cohen (1992). A small ES is
indicated by ORs between 1.2 and 1.71, a medium ES is indicated by ORs between 1.72 and
2.4, and a large ES is indicated by ORs greater than 2.4. Five separate one-way between-group
ANOVAs, with post hoc comparisons using the Tukey test, were conducted to examine for
mean dierences across the ImPACT® composite scores, excluding participants with invalid
test results. Given the number of analyses conducted, to maintain an acceptable familywise
Type I error rate we corrected alpha and considered results statistically signicant at p < .01
(.05/5 = .01 for ANOVAs with boys and girls conducted separately). The Post-Concussion
Scale was also analyzed with ANOVAs (conducted separately by sex) and post hoc Tukey
tests. Participants with invalid ImPACT® results were included in analyses of the Post-
Concussion Scale because one or more invalid scores on the cognition composites might
not be relevant to symptom reporting. The percentage of participants in each group who
engaged in ‘high symptom reporting’ was computed. A total symptom score of 13 or greater
(boys) or 21 or greater (girls) indicated high symptom reporting (Lovell et al., 2006). Lastly,
given our large sample size and associated statistical power we also computed eect sizes
(Cohen’s d) to assist in interpreting the results. Eect sizes were evaluated according to
available criteria, i.e. d of .2, .5, and .8 representing small, medium, and large eects,
respectively (Cohen, 1992). Parametric analyses were used despite skewed distributions on
some variables given inherent safeguards against Type I (i.e. large sample) and Type II (i.e.
calculating eect sizes and comparing rates of high symptom reporters) errors. Further,
non-parametric tests produced the same pattern of results as those reported below.
Prior studies with this metadata-set revealed that girls and boys dier in terms of con-
cussion history (Iverson, Atkins, Zafonte, & Berkner, 2014) and also symptom reporting, with
ADHD appearing dierentially associated with symptom reporting between sexes (Brooks
et al., 2016; Iverson et al., 2015). Further, the percentages of boys and girls diered between
the Control group and the other three study groups. Thus, analyses were conducted sepa-
rately by sex. All analyses were performed on IBM SPSS Statistics version 22, except for ORs
and their 95% condence intervals (CI), which were calculated using formulas from MedCalc
version 13.3.3 (retrieved from http://www.medcalc.org/calc/odds_ratio.php) and Cohen’s d
values, which were calculated using an online eect size calculator (Ellis, 2009).
Downloaded by [Colby College] at 04:35 10 October 2017
1346 N. E. COOK ET AL.
Results
Rates of invalid ImPACT® results
For both sexes, groups diered in the rates of invalid ImPACT® results [girls: χ2 (3) = 46.99,
p < .001; boys: χ2 (3) = 31.43, p < .001]. Girls with ADHD and not taking medication had
modestly greater rates of invalid scores (10.9%) than Control subjects (5.2%; OR = 2.21, 95%
CI = 1.92–2.50, medium eect), and girls with ADHD who were on medication, although this
dierence was not statistically signicant [8.1%; Odds Ratio (OR) = 1.40, 95% CI = .85–1.94,
small eect]. Similarly, boys with ADHD and not taking medication had a modestly greater
rate of invalid scores (10.0%) than Control subjects (6.7%; OR = 1.56, 95% CI = 1.36–1.76,
small eect), and slightly higher rate compared to boys with ADHD who were on medication
(9.1%; OR = 1.11, 95% CI = .77–1.44, minimal eect), although this dierence was not statis-
tically signicant. The No ADHD/Medication group had the highest rates of invalid test results
(girls: 14.8%; boys: 12%).
Group dierences on ImPACT® composite scores
Descriptive statistics and ANOVA results for composite scores are presented in Tables 1 and
2. For both sexes, groups diered signicantly across all ImPACT® neurocognitive composites.
Post-hoc comparisons are also presented in Tables 1 and 2. Pair wise eect sizes suggest most
of the dierences were small eects and thus of questionable clinical relevance. The ADHD/
Medication group did not dier meaningfully from Controls on any composite, for either
sex (d ranging from 0 to .19). However, a few small to medium eects were noted (i.e. Cohen’s
d.29) for other group comparisons. For boys, on the Visual Memory and Visual Motor Speed
composites, those in the No ADHD/Medication group scored lower than both the ADHD/
Medication group (d = .31 and .37, respectively) and the Control group (d = .41 and .36,
respectively). For girls, the ADHD/No Medication and the No ADHD/Medication group both
performed worse compared to the ADHD/Medication group and the Controls (d ranging
from .32 to .42) on the Visual Motor Speed composite. Additionally, girls in the Control group
Table 1.Summary of group differences on ImPACT® composite scores and total symptom scores for girls.
Notes: Means sharing a common subscript (i.e. a,b,c’) are statistically different at p<.01. The cell sizes differ between ImPACT
Composite results and Total Symptom Score due to participants with invalid ImPACT results being excluded when ana-
lyzing ImPACT data but included when analyzing symptom reporting. ADHD=Attention-Deficit/Hyperactivity Disorder.
For ImPACT composites, ANOVA degrees of freedom are 3 and 16,904. Participants with invalid baseline test results were
excluded from these analyses. For Total Symptom Score, ANOVA degrees of freedom are 3 and 17,885. Participants with
invalid baseline test results were included in this analysis.
^Lower scores reflect better performance or fewer symptoms.
ImPACT ®
composite
ADHD/no
medication
ADHD/
medication
No ADHD/
medication Controls
ANOVAn=450 n=217 n=69 n=16,172
M SD M SD M SD M SD F p
Verbal memory 81.95a10.47 82.97 10.59 81.23 10.91 84.53a9.83 14.01 <.001
Visual memory 67.34ab 13.97 70.86a13.02 67.20 13.05 71.84b13.10 20.18 <.001
Visual motor speed 32.59ab 6.14 34.57a6.38 32.32c6.00 35.03bc 6.69 23.39 <.001
Reaction time^.65a.09 .63 .10 .66 .18 .62a.12 7.54 <.001
Impulse control^7.94a5.23 7.79 5.40 8.52 5.77 6.99a4.73 9.93 <.001
n=505 n=236 n=81 n=17,067
Total symptom
score^
13.1a15.7 13.9b15.2c12.0 14.3 6.1abc 9.5 139.16 <.001
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THE CLINICAL NEUROPSYCHOLOGIST 1347
performed better than the ADHD/No Medication (d = .33) and No ADHD/Medication (d = .35)
groups on Visual Memory. Lastly, girls in the ADHD/No Medication group diered from
Controls on Reaction Time (d = .29), whereas the No ADHD/Medication group diered from
Controls on Verbal Memory (d = −.32).
Group dierences on the Post-Concussion Scale
Groups diered signicantly on the Post-Concussion Scale [girls: F (3, 17,885) = 139.16,
p < .001; boys: F (3, 21,354) = 106.76, p < .001]. Follow-up pairwise comparisons revealed
similar results for both sexes. The ADHD/Medication group, ADHD/No Medication group,
and No ADHD/Medication group did not dier from one another (see Tables 1 and 2).
However, the ADHD/No Medication group (girls: d = .56; boys: d = .33), ADHD/Medication
group (girls: d = .63; boys: d = .42), and the No ADHD/Medication group (girls: d = .50; boys:
d = .32) all diered signicantly and reported more severe symptoms compared to Control
subjects, representing small to medium eects. A sex dierence was notable such that girls
with ADHD, regardless of medication status, had greater total symptom scores compared
to boys with ADHD. The frequencies of endorsing specic symptoms (i.e. item score ≥ 1) and
the percentage of participants endorsing an elevated number of symptoms, stratied by
group and gender, are presented in Table 3. For both sexes, the ADHD groups were more
likely to endorse an elevated number of symptoms.
Discussion
This study investigated whether medication use is relevant when interpreting baseline cog-
nitive test results from student athletes with ADHD. This study does not purport to evaluate
the ecacy of ADHD medications but, rather, examine dierences in obtained baseline
assessment results and symptom reporting based on self-report of medication use. Youth
with ADHD who reported taking medication had modestly lower rates of invalid ImPAC
results compared to youth with ADHD who did not report taking medication on a preseason
Table 2.Summary of group differences on ImPACT® composite scores and total symptom scores for boys.
Notes: Means sharing a common subscript (i.e. a,b,c’) are statistically different at p<.01. The cell sizes differ between ImPACT
Composite results and Total Symptom Score due to participants with invalid ImPACT results being excluded when ana-
lyzing ImPACT data but included when analyzing symptom reporting. ADHD=Attention-Deficit/Hyperactivity Disorder.
For ImPACT composites, ANOVA degrees of freedom are 3 and 19,868. Participants with invalid baseline test results were
excluded from these analyses. For Total Symptom Score, ANOVA degrees of freedom are 3 and 21,354. Participants with
invalid baseline test results were included in this analysis.
^Lower scores reflect better performance or fewer symptoms.
ImPACT ® composite
ADHD/no
medication ADHD/medication
No ADHD/
medication Controls
ANOVAn=1080 n=547 n=162 n=18,083
M SD M SD M SD M SD F p
Verbal memory 81.16a10.38 81.85 10.11 81.23 9.19 82.82a9.87 12.16 <.001
Visual memory 70.05a13.89 71.32b13.91 67.14bc 13.41 72.65ac 13.23 23.11 <.001
Visual motor speed 32.23ab 6.96 34.09ac 6.79 31.60cd 6.60 34.03bd 7.06 28.04 <.001
Reaction time^.64ab .11 .63a.09 .64 .10 .63b.10 11.96 <.001
Impulse control^8.81a5.91 8.49b5.38 8.25 5.01 7.50ab 5.03 29.37 <.001
n=1200 n=602 n=184 n=19,372
Total symptom
score^
7.1a 10.4 8.0b11.0 7.3c12.8 4.1abc 7.4 106.76 <.001
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1348 N. E. COOK ET AL.
baseline assessment. ‘Invalid’ results on ImPACT® may be caused by careless responding,
misunderstanding the test instructions, deliberate under-performance, or other test-taking
factors. After excluding those with invalid scores, statistically signicant group dierences
were noted across ImPACT® composite scores. However, eect sizes for these dierences
were generally small, and thus of questionable clinical relevance and practical signicance.
Across all ImPACT® composite scales, for both girls and boys, youth with ADHD who reported
taking medication performed similarly to controls. There were only a few small to medium
eects between the ADHD/No medication as well as the No ADHD/Medication groups and
both the ADHD/Medication and Control groups. Dierences were most consistent in the
Visual Motor Speed domain. Additionally, there were some dierences in Visual Memory as
well. Youth with ADHD who reported taking medication did not dier meaningfully from
controls. In general, eect sizes tended to be greater among girls compared to boys. In
contrast to cognitive test results, self-reported medication use did not appear to inuence
concussion-like symptom reporting. That is, the ADHD groups did not dier from one another
on total symptom scores but both ADHD groups endorsed signicantly more symptoms
compared to controls. Of note, girls with ADHD endorsed higher levels of symptoms com-
pared to boys with ADHD.
Taken together, these ndings partially supported our hypotheses. Youth with ADHD had
greater rates of invalid ImPACT results compared to control subjects. However, this appeared
to be the case for comparisons between ADHD youth and control youth. Medication use
among youth self-reporting ADHD appeared to slightly attenuate the likelihood of an invalid
test result but, in general, the two ADHD groups demonstrated roughly equivalent rates of
invalid results. Next, consistent with our hypothesis, youth with ADHD who did not report
taking medication performed worse on ImPACT® composites compared to controls. However,
dierences were generally small and of limited practical signicance when comparing the
ADHD groups (i.e. medication vs. no medication). The primary cognitive domain inuenced
by ADHD medication use was visual motor speed; this is the only domain on which the
ADHD/Medication group performed appreciably better compared to the ADHD/No
Medication group. Our ndings are consistent with recent evidence that medication use
among college athletes with ADHD is associated with better test performances in certain
neurocognitive domains (Littleton et al., 2015), and extend these ndings to high school
students. Our ndings are inconsistent, however, with another recent study reporting that
youth with ADHD who are on stimulant medication perform more poorly than control sub-
jects (with medium eect sizes) (Yengo-Kahn & Solomon, 2015). In our study, youth with
ADHD who reported taking medication performed comparably to controls. Finally, our
hypothesis that youth with ADHD would endorse greater levels of concussion-like symptoms
during preseason assessments was supported. Medication use did not appear to inuence
symptom reporting, because the two ADHD groups endorsed similar levels of symptoms
but both were notably elevated when compared to controls without ADHD.
Our ndings suggest that clinicians should consider whether or not a youth has ADHD
when interpreting symptom reporting and neurocognitive test results in the context of
concussion management. Regarding symptom reporting, youth with ADHD report more
concussion-like symptoms on baseline assessment, in the absence of recent injury. Further,
on ImPACT composites, youth with ADHD who reported taking medication performed com-
parably to controls whereas youth with ADHD who did not endorse medication performed
worse, though only modestly, particularly on Visual Memory and Visual Motor Speed.
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THE CLINICAL NEUROPSYCHOLOGIST 1349
Table 3.Symptom reporting by groups and sex.
Notes: ADHD=Attention-Deficit/Hyperactivity Disorder. Values represent the percentage of students who endorsed the symptom as present (i.e. score of 1 or greater).
aHigh symptom reporting for boys: Total symptom score of 13 or greater. High symptom reporting for girls: Total symptom score of 21 or greater (Lovell et al., 2006).
Individual
Symptoms
Boys Girls
ADHD/no
medication
ADHD/
medication
No ADHD/
medication Controls
ADHD/no
medication
ADHD/
medication
No ADHD/
medication Controls
n=1200 n=602 n=184 n=19,372 n=505 n=236 n=81 n=17,067
% % % % % % % %
Headache 19.4 17.1 15.2 15.3 30.5 33.1 25.9 23.8
Nausea 4.9 2.8 3.8 2.8 5.0 5.1 6.2 3.0
Vomiting 4.3 4.7 6.0 3.1 10.9 9.3 11.1 4.5
Balance problems 6.8 5.1 7.1 3.8 14.5 14.4 11.1 6.0
Dizziness 8.6 9.5 8.7 6.4 17.0 21.6 27.2 9.9
Fatigue 26.8 29.7 21.2 19.7 37.8 43.2 34.6 25.9
Trouble falling asleep 20.3 28.2 22.3 17.5 31.7 39.0 21.0 21.7
Sleeping more than
usual
11.4 9.3 11.4 6.5 11.3 11.4 11.1 7.1
Sleeping less than
usual
24.1 30.2 23.4 19.5 35.0 38.6 29.6 24.5
Drowsiness 13.8 13.0 14.1 10.6 20.8 22.9 21.0 13.3
Sensitivity to light 17.7 21.6 15.2 12.5 26.3 28.8 19.8 15.1
Sensitivity to noise 7.2 8.6 10.3 4.5 16.2 16.9 17.3 6.3
Irritability 15.8 21.8 22.3 9.9 30.1 33.9 25.9 16.7
Sadness 17.9 19.4 22.3 14.0 39.0 35.2 42.0 23.1
Nervousness 15.7 16.6 15.2 9.6 30.5 37.7 33.3 17.1
Feeling more
emotional
13.1 14.5 14.7 7.8 35.0 34.3 34.6 21.4
Numbness or tingling 5.6 4.0 7.1 3.4 7.7 5.1 8.6 3.6
Feeling slowed down 10.7 12.3 10.3 6.6 16.4 17.8 18.5 7.2
Feeling mentally
‘Foggy’
10.9 13.5 9.8 6.8 17.2 18.2 13.6 8.1
Difficulty
concentrating
35.5 44.7 34.2 15.2 49.5 56.4 39.5 19.1
Difficulty
remembering
16.8 16.8 16.8 9.2 21.6 22.9 14.8 9.4
Visual problems 9.3 8.1 7.1 5.6 16.6 12.7 13.6 7.7
‘High’ symptom
reportinga
17.6 22.9 19.0 9.5 24.6 24.2 22.2 7.4
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1350 N. E. COOK ET AL.
This study has several methodological limitations to consider when interpreting results.
This is a cross-sectional, retrospective study that relied on student athlete self-report to
determine both ADHD and medication status. Thus, we were not able to conrm that stu-
dents had a formal ADHD diagnosis. Indeed, we were limited to the self-report elds included
in the health history section of ImPACT. Therefore, we were also unable to determine which
subtype of ADHD students were diagnosed with (i.e. either predominantly inattentive, pre-
dominantly hyperactive/impulsive, or combined presentation). Moreover, we did not have
access to details about their medication dosing and adherence, which could have contrib-
uted to the negligible eects of medication on cognitive performance. Our sample also
included a mixture of stimulant and non-stimulant medications, which we did not dieren-
tiate in our analyses. Unexpectedly, a small number of participants (n = 265; .006% of the
full sample) reported taking ADHD medication but did not report having ADHD. This group
resembled the ADHD/No Medication group with respect to concussion-like symptom report-
ing and cognition, but produced slightly higher rates of invalid testing. The composition of
this group is unclear. It may include students with ADHD who simply failed to report it due
to carelessness, who believe their ADHD was ‘cured’ by medication, who were prescribed
ADHD medication for an alternate indication (e.g. narcolepsy), or who obtained ADHD med
-
ication illegally. Further, as noted above, our data do not allow us to know whether youth
took their medication on the day of testing.
In summary, our ndings are consistent with prior research, further demonstrating that
youth with ADHD produce higher rates of invalid ImPACT® results, score lower overall on
ImPACT® composite scores compared to youth without ADHD, and also endorse more
post-concussion like symptoms on preseason testing. Our study extends the available liter-
ature by examining the potential inuence of medication use in youth with ADHD. Contrary
to our hypothesis, we found only a subtle eect of medication use on cognitive performance
and no signicant eect on concussion-like symptom reporting. Student athletes with
treated ADHD performed comparably to student athletes with no ADHD on cognitive testing.
Student athletes with ADHD reported more symptoms regardless of the medication use.
These ndings can help clinicians to appreciate that baseline, pre-injury scores and symptom
reporting may be inuenced by existing conditions and vulnerabilities, such as ADHD, which
may assist in tracking recovery from sport-related concussion.
Acknowledgements
The data were gathered as part of the Maine Concussion Management Initiative (MCMI) under the
direction of Dr. Paul Berkner. The authors thank the Maine Athletic Trainers Association for their col-
laboration with the MCMI.
General disclosure
GLI has been reimbursed by the government, professional scientic bodies, and commercial organ-
izations for discussing or presenting research relating to mild TBI and sport-related concussion at
meetings, scientic conferences, and symposiums. He has a clinical and consulting practice in foren-
sic neuropsychology involving individuals who have sustained mild TBIs (including athletes). He has
received research funding from several test publishing companies, including ImPACT Applications, Inc.,
CNS Vital Signs, and Psychological Assessment Resources (PAR, Inc.). He acknowledges unrestricted
philanthropic support from the Mooney-Reed Charitable Foundation and ImPACT Applications, Inc. BB
is a principal investigator, co-investigator, or collaborator on several grants relating to the study of mild
Downloaded by [Colby College] at 04:35 10 October 2017
THE CLINICAL NEUROPSYCHOLOGIST 1351
TBI/concussion in youth. He receives royalties for the sales of the Pediatric Forensic Neuropsychology
textbook (2012, Oxford University Press) and pediatric neuropsychological tests [Child and Adolescent
Memory Prole (ChAMP, Sherman and Brooks, 2015, PAR Inc.), Memory Validity Prole (MVP, Sherman
and Brooks, 2015, PAR Inc.), and Multidimensional Everyday Memory Ratings for Youth (MEMRY,
Sherman and Brooks, 2017, PAR Inc.)]. He has previously received support (in-kind test credits) from a
dierent computerized cognitive test publisher (CNS Vital Signs).
Funding
This work was supported in part by the Goldfarb Center for Public Policy and Civic Engagement at
Colby College, and the Bill and Joan Alfond Foundation.
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... Patient-reported symptom inventories, such as the Sport Concussion Assessment Tool (SCAT), remain a staple of clinical assessments due to their ease of administration and the strong predictive relationship between greater acute/subacute symptom severity and prolonged concussion recovery across a number of clinical settings (Eagle et al., 2020;Eisenberg et al., 2013;Fehr et al., 2019;Putukian et al., 2021;Rabinowitz et al., 2015). However, despite an emerging body of evidence indicating that individuals with ADHD report greater concussion-related symptom severity compared with their non-ADHD counterparts (Biederman et al., 2015;Collings et al., 2017;Cook et al., 2017;Elbin et al., 2013;Houck et al., 2019;Iaccarino et al., 2018), such associations are not always observed, and a recent systematic review found no clear association for the presence of ADHD being related to differences in clinical outcomes (Cook et al., 2020). ...
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Introduction Pre-injury and post-injury anxiety are prevalent and important to consider in the medical management of concussions in youth. We examined the association between anxiety and other physical, cognitive, and emotional symptoms in injured adolescents and young adults undergoing an initial evaluation in a specialty concussion clinic. Methods Participants were 158 adolescents and young adults presenting to a multidisciplinary concussion clinic for evaluation and treatment (54.4% girls and women; mean age = 17.3 years; SD = 2.9). Their median days post injury was 29 (interquartile range = 14–49; range = 7–349). They were divided into binary groups based on whether they had a pre-injury history of anxiety diagnosis or treatment and whether they were experiencing current anxiety in the week prior to the evaluation, and then compared on the Post-Concussion Symptom Scale. Results Youth with a pre-injury history of anxiety reported greater post-concussion symptoms (Md total score = 36.0, IQR = 21.5–53.0) compared to youth with no pre-injury history of anxiety (Md total score = 20.5, IQR = 6.0–36.0; MW U = 1,520.00 p = 0.001, r = 0.26, small-medium effect size). They reported significantly worse headaches, nausea, balance difficulty, dizziness, vision problems, fatigue, concentration difficulty, irritability, nervousness, sadness, feeling more emotional, trouble falling asleep, and sleeping more than usual. Youth with high post-injury anxiety reported greater post-concussion symptoms (Md total score = 55.0, IQR = 33.0–62.5) compared to youth with low post-injury anxiety (Md total score = 19.0, IQR = 6.0–35.0; MW U = 681.00, p < 0.001, r = 0.49, large effect size). They reported significantly worse headaches, nausea, vomiting, dizziness, vision problems, fatigue, sensitivity to light, feeling mentally foggy, feeling slowed down, concentration difficulty, memory difficulty, irritability, sadness, feeling more emotional, drowsiness, trouble falling asleep, sleeping less than usual, and sleeping more than usual. Logistic regressions revealed that both pre-injury and post-injury anxiety were strong predictors of persistent post-concussion symptoms, with high post-injury anxiety presenting the strongest independent predictor, while attention-deficit hyperactivity disorder and pre-injury migraines were not significant predictors. Essentially all adolescents with high post-injury anxiety (97.1%) and nearly 9 of 10 adolescents with pre-injury treatment for anxiety (87.8%) met criteria for persistent post-concussion symptoms. Discussion Pre-injury and post-injury anxiety are important risk factors for greater post-concussion symptoms among adolescents and young adults. Elevated post-injury anxiety was the strongest predictor of persistent post-concussion symptoms. Assessment of anxiety is important among adolescents presenting for concussion care and delivery of evidence-supported treatments for anxiety are important considerations for treatment planning for these youth.
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Background: The Post-Concussion Symptom Scale (PCSS) is a self-report questionnaire measuring symptoms that commonly occur after a concussion; however, these symptoms are nonspecific and can be related to co-occurring orthopaedic injuries (eg, cervical strain) or patient characteristics and preexisting conditions, even in the absence of a recent injury. As such, clinicians may have difficulty determining whether symptom elevations are attributable to a recent concussion as opposed to a confounding injury or a preexisting condition, which may be especially difficult when preinjury baseline symptom data are unavailable. Purpose: This study aimed to further validate the 4-factor model of the PCSS (ie, cognitive, sleep-arousal, physical, and affective symptoms) with adolescent student-athletes and provide normative reference data for each factor and the total score, stratified by gender and preexisting health conditions. Study design: Cross-sectional study; Level of evidence, 3. Methods: Participants were 9358 adolescent student-athletes who completed the PCSS during a preseason baseline evaluation (mean age, 14.9 years; SD, 1.3 years [range, 13-18 years]; 49.3% boys). The 4-factor model of the PCSS was tested for the full sample and separately for boys and girls using confirmatory factor analysis. Symptom severity percentiles were created for the PCSS total score and each factor, stratified by gender and preexisting conditions (ie, attention-deficit/hyperactivity disorder, mental health history, headache/migraine history, learning disability/dyslexia, academic problems, and concussion history). Results: The 4-factor model of the PCSS replicated in the full sample (comparative fit index [CFI] = 0.959) and in both gender groups (boys: CFI = 0.961; girls: CFI = 0.960). The total PCSS score at the 84th percentile varied by preexisting conditions as follows: healthy participants = 8, attention-deficit/hyperactivity disorder = 18, mental health history = 26, headache/migraine history = 18, learning disability = 19, and academic problems = 17. On all PCSS subscales, participants with a mental health history had the highest scores, and high scores were associated with having >1 preexisting condition. Girls had higher scores than boys for each stratification. Conclusion: The 4-factor model of the PCSS replicates for adolescent student-athletes. Gender, number of preexisting conditions, and mental health history are important factors to account for when interpreting PCSS symptom severity. The normative data provided herein could assist clinicians in determining whether an adolescent student-athlete is presenting with persistent postconcussion symptoms or a typical symptom experience based on their gender and personal health history.
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Athletic programs are more frequently turning to computerized cognitive tools in order to increase efficiencies in concussion assessment. However, assessment using a traditional neuropsychological test battery may provide a more comprehensive and individualized evaluation. Our goal was to inform sport clinicians of the best practices for concussion assessment through a systematic literature review describing the psychometric properties of standard neuropsychological tests and computerized tools. We conducted our search in relevant databases including Ovid Medline, Web of Science, PsycINFO, and Scopus. Journal articles were included if they evaluated psychometric properties (e.g., reliability, sensitivity) of a cognitive assessment within pure athlete samples (up to 30 days post-injury). Searches yielded 4,758 unique results. Ultimately, 103 articles met inclusion criteria, all of which focused on adolescent or young adult participants. Test–retest reliability estimates ranged from .14 to .93 for computerized tools and .02 to .95 for standard neuropsychological tests, with strongest correlations on processing speed tasks for both modalities, although processing speed tasks were most susceptible to practice effects. Reliability was improved with a 2-factor model (processing speed and memory) and by aggregating multiple baseline exams, yet remained below acceptable limits for some studies. Sensitivity to decreased cognitive performance within 72 h of injury ranged from 45%–93% for computerized tools and 18%–80% for standard neuropsychological test batteries. The method for classifying cognitive decline (normative comparison, reliable change indices, regression-based methods) affected sensitivity estimates. Combining computerized tools and standard neuropsychological tests with the strongest psychometric performance provides the greatest value in clinical assessment. To this end, future studies should evaluate the efficacy of hybrid test batteries comprised of top-performing measures from both modalities.
In 2021, over 100,000 people died prematurely from opioid overdoses. Neuropsychiatric and cognitive impairments are underreported comorbidities of reward dysregulation due to genetic antecedents and epigenetic insults. Recent genome-wide association studies involving millions of subjects revealed frequent comorbidity with substance use disorder (SUD) in a sizeable meta-analysis of depression. It found significant associations with the expression of NEGR1 in the hypothalamus and DRD2 in the nucleus accumbens, among others. However, despite the rise in SUD and neuropsychiatric illness, there are currently no standard objective brain assessments being performed on a routine basis. The rationale for encouraging a standard objective Brain Health Check (BHC) is to have extensive data available to treat clinical syndromes in psychiatric patients. The BHC would consist of a group of reliable, accurate, cost-effective, objective assessments involving the following domains: Memory, Attention, Neuropsychiatry, and Neurological Imaging. Utilizing primarily PUBMED, over 36 years of virtually all the computerized and written-based assessments of Memory, Attention, Psychiatric, and Neurological imaging were reviewed, and the following assessments are recommended for use in the BHC: Central Nervous System Vital Signs (Memory), Test of Variables of Attention (Attention), Millon Clinical Multiaxial Inventory III (Neuropsychiatric), and Quantitative Electroencephalogram/P300/Evoked Potential (Neurological Imaging). Finally, we suggest continuing research into incorporating a new standard BHC coupled with qEEG/P300/Evoked Potentials and genetically guided precision induction of “dopamine homeostasis” to diagnose and treat reward dysregulation to prevent the consequences of dopamine dysregulation from being epigenetically passed on to generations of our children.
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Aims: The objective of this study was to compare recovery time and duration of active rehabilitation following concussion between adolescents with and without attention-deficit/hyperactivity disorder (ADHD). Methods: A retrospective cohort study was conducted among adolescents presenting to a specialty concussion clinic. One-quarter of the eligible episodes of care were selected. The final sample included 540 adolescents (ages 13-17 years, median age 15 years; 49.8% girls), of which 65 (12.0%) had a pre-injury diagnosis of ADHD. Days to recovery and days of active rehabilitation were examined. Results: ADHD was not associated with recovery time (ADHD: median = 49 days, IQR = 25-77; No ADHD: median = 47 days, IQR = 29-85) in univariate (Z = -0.45; p = 0.65) or multivariable analyses (Hazard Ratio: 1.17 (0.85-1.61); χ2(1) = 0.95; p = 0.33). The duration of active rehabilitation services received did not differ between youth with ADHD (median = 38.5 days, IQR = 27.5-54.5) and without ADHD (median = 37.5 days, IQR = 18.5-66) in univariate (Z = -0.19; p = 0.85) or multivariable analyses (Hazard Ratio: 1.04 (0.67-1.63); χ2(1) = 0.03; p = 0.85). Conclusions: Our findings support accumulating evidence that ADHD, in and of itself, is not a risk factor for longer recovery or worse outcomes following pediatric concussion.
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The diagnosis, management, and ultimate decision for medical clearance following sport-related concussion are complex and multifactorial. In recent years, for example, we have observed a transition from the conservative prescription of rest following sport-related concussion to the recommendation of early introduction of activities. The chapter begins with a historical contextualization of concussion/mild traumatic brain injury, followed by describing the formalization and evolution of concussion assessment tools. Next, the chapter provides a chronological narrative of the development and advancements of graded return-to-sport guidelines. This section of the chapter will also review the challenges and research opportunities in determining when to initiate activity, at what intensity, duration, and type. The chapter also highlights that activity is not limited to sport participation (i.e., return-to-sport protocols) and that management guidelines have been developed for both school and work settings. The chapter concludes by highlighting that sport-related concussion is a heterogeneous clinical condition and necessitates an interdisciplinary team with concussion expertise in certain situations, irrespective of return-to-activity goals.KeywordsSport-related concussionReturn to activityReturn to playReturn to schoolReturn to workExercisePhysical activity
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This study examined the association between past concussions and current preseason symptom reporting and cognitive performance in 9,257 youth ages 11–13. Participants completed neurocognitive testing prior to participating in a school sports between 2009 and 2019. We stratified the sample by gender and number of prior concussions and assessed group differences on the Post-Concussion Symptom Scale total score and the ImPACT cognitive composite scores. Those with≥2 prior concussions reported more symptoms than those with 0 concussions (d=0.43–0.46). Multiple regressions examining the contribution of concussion history and developmental/health history to symptom reporting showed the most significant predictors of symptoms scores were (in descending order): treatment for a psychiatric condition, treatment for headaches, history of learning disability (in boys only), history of attention-deficit/hyperactivity disorder, and age. Concussion history was the weakest statistically significant predictor in boys and not significant in girls. Cognitively, boys with 1 prior concussion had worse speed those with 0 concussions (d=0.11), and girls with≥2 prior concussions had worse verbal/visual memory than girls with 0 concussions (ds=0.38–0.39). In summary, youth with≥2 prior concussions reported more symptoms than those with no concussions. Boys with multiple concussions performed similarly on cognitive testing, while girls had worse memory scores.
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Importance Every state in the United States has passed legislation for sport-related concussion, making this health issue important for physicians and other health care professionals. Safely returning athletes to sport after concussion relies on accurately determining when their symptoms resolve.Objective To evaluate baseline concussion-like symptom reporting in uninjured adolescent student athletes. Design, Setting, and Participants In this cross-sectional, observational study, we studied 31 958 high school athletes from Maine with no concussion in the past 6 months who completed a preseason baseline testing program between 2009 and 2013.Results Symptom reporting was more common in girls than boys. Most students with preexisting conditions reported one or more symptoms (60%-82% of boys and 73%-97% of girls). Nineteen percent of boys and 28% of girls reported having a symptom burden resembling an International Classification of Diseases, 10th Revision (ICD-10) diagnosis of postconcussional syndrome (PCS). Students with preexisting conditions were even more likely to endorse a symptom burden that resembled PCS (21%-47% for boys and 33%-72% for girls). Prior treatment of a psychiatric condition was the strongest independent predictor for symptom reporting in boys, followed by a history of migraines. For girls, the strongest independent predictors were prior treatment of a psychiatric condition or substance abuse and attention-deficit/hyperactivity disorder. The weakest independent predictor of symptoms for both sexes was history of prior concussions.Conclusions and Relevance In the absence of a recent concussion, symptom reporting is related to sex and preexisting conditions. Consideration of sex and preexisting health conditions can help prevent misinterpretation of symptoms in student athletes who sustain a concussion.
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Background: Preseason baseline testing using computerized neurocognitive tests (CNTs) is increasingly performed on athletes. Adequate effort is critical to establish valid estimates of ability, but many users do not evaluate performance validity, and the conditions that affect validity are not well understood across the available CNTs. Purpose: To examine the rates and predictors of invalid baseline performance for 3 popular CNTs: Automated Neuropsychological Assessment Metrics (ANAM), Axon Sports, and Immediate Post-Concussion and Cognitive Testing (ImPACT). Study Design: Controlled laboratory study. Methods: High school and collegiate athletes (N = 2063) completed 2 of 3 CNTs each during preseason evaluations. All possible pairings were present across the sample, and the order of administration was randomized. Examiners provided 1-on-1, scripted pretest instructions, emphasizing the importance of good effort. Profile validity was determined by the manufacturers’ standard criteria. Results: The overall percentage of tests flagged as of questionable validity was lowest for ImPACT (2.7%) and higher for ANAM and Axon (10.7% and 11.3%, respectively). The majority of invalid baseline profiles were flagged as such because of failure on only 1 validity criterion. Several athlete and testing factors (eg, attention deficit hyperactivity disorder [ADHD], estimated general intellectual ability, administration order) predicted validity status for 1 or more CNTs. Considering only first CNT administrations and participants without ADHD and/or a learning disability (n = 1835) brought the rates of invalid baseline performances to 2.1%, 8.8%, and 7.0% for ImPACT, ANAM, and Axon, respectively. Invalid profiles on the Medical Symptom Validity Test (MSVT) were rare (1.8% of participants) and demonstrated poor correspondence to CNT validity outcomes. Conclusion: The validity criteria for these CNTs may not identify the same causes of invalidity or be equally sensitive to effort. The validity indicators may not be equally appropriate for some athletes (eg, those with neurodevelopmental disorders). Clinical Relevance: The data suggest that athletes do not put forth widespread low effort or that some validity criteria are more sensitive to invalid performance than others. It is important for examiners to be aware of the conditions that maximize the quality of baseline assessments and to understand what sources of invalid performance are captured by the validity criteria that they obtain.
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Amateur athletic programs often use computerized cognitive testing as part of their concussion management programs. There is evidence that athletes with preexisting attention problems will have worse cognitive performance and more symptoms at baseline testing. The purpose of this study was to examine whether attention problems affect assessments differently for male and female athletes. Participants were drawn from a database that included 6,840 adolescents from Maine who completed Immediate Postconcussion Assessment and Cognitive Testing (ImPACT) at baseline (primary outcome measure). The final sample included 249 boys and 100 girls with self-reported attention problems. Each participant was individually matched for sex, age, number of past concussions, and sport to a control participant (249 boys, 100 girls). Boys with attention problems had worse reaction time than boys without attention problems. Girls with attention problems had worse visual-motor speed than girls without attention problems. Boys with attention problems reported more total symptoms, including more cognitive-sensory and sleep-arousal symptoms, compared with boys without attention problems. Girls with attention problems reported more cognitive-sensory, sleep-arousal, and affective symptoms than girls without attention problems. When considering the assessment, management, and outcome from concussions in adolescent athletes, it is important to consider both sex and preinjury attention problems regarding cognitive test results and symptom reporting.
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Little is known about the rate of concussions in adolescents with attention-deficit hyperactivity disorder (ADHD). We hypothesized that high school athletes with ADHD would report a greater history of concussion than students without ADHD. 6,529 adolescent and young adult student athletes, between the ages of 13 and 19 (M=15.9, SD=1.3 years), completed a preseason health survey in 2010. Of those with ADHD, 26.1% reported a history of one or more concussions compared to 17.1% of those without ADHD (p<.00001; OR=1.71). Stratified by gender, 27.0% of boys with ADHD reported a history of one or more concussions compared to 20.0% of boys without ADHD (p<.004; OR=1.48), and 23.6% of girls with ADHD reported a history of one or more concussions compared to 13.6% of girls without ADHD (p<.003; OR=1.97). Of those with ADHD, 9.8% reported a history of two or more concussions compared to 5.5% of those without ADHD (p<.0003; OR=1.87). Stratified by gender, 10.0% of boys with ADHD reported a history of two or more concussions compared to 6.7% of boys without ADHD (p<.033; OR=1.54), and 9.1% of girls with ADHD reported a history of two or more concussions compared to 3.8% of girls without ADHD (p<.006; OR=2.51). In this large-scale, retrospective survey study, boys and girls with ADHD were significantly more likely to report a history of concussion. Additional research is needed to determine if students with ADHD are more susceptible to injury (i.e., have a lower threshold) or have different recovery trajectories.
Article
Effects of attention deficit hyperactivity disorder (ADHD) and stimulant medications on concussion measures are unclear. The objectives of this study were to (i) examine consistency of performance in an unmedicated ADHD group and a control group on concussion measures, (ii) assess performance differences between the two groups, and (iii) assess the effect of stimulant medication on performance in the ADHD group. College-aged participants (22 ADHD and 22 matched controls) were administered a symptom checklist and a computerized neurocognitive test (CNS Vital Signs, CNSVS) 3 times (1 week apart): Sessions 1 and 2 were unmedicated for all participants; Session 3 was medicated for the ADHD group. The reliability of the measures (intraclass correlation coefficients, ICC2,1) was consistent for both groups. When unmedicated, the ADHD group performed worse than controls on psychomotor speed [F(1,40) = 15.19, p < 0.001], and worse than when medicated on reaction time [F(1,39) = 6.34, p = 0.02]. The ADHD group performed better and comparable with controls when medicated. Clinicians should take medication status into account when interpreting scores. © The Author 2015. Published by Oxford University Press. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.
Article
Objectives: Baseline and post-concussive neurocognitive testing is useful in managing concussed athletes. The Concussion in Sport Group has postulated that the use of psychotropic medications is a modifying factor in the management of sport-related concussion. About 7% of US adolescents are prescribed psychotropics in a given year. Our aim was to investigate whether psychotropic medication use or psychiatric illness is associated with differences in baseline neurocognitive test scores. Methods: From 2007 to 2012, over 7000 athletes underwent pre-participation baseline neurocognitive testing using the Immediate Post-Concussion Assessment and Cognitive Testing (ImPACT) battery. Following application of inclusion and exclusion criteria, athletes' self-reported medication lists were reviewed and: 1) classified as psychotropic or not and 2) subclassified. Group subclassification yielded: 1) use of any psychotropic medication, 2) psychostimulant use, 3) antidepressant use and 4) self-reported history of depression and/or anxiety without psychotropic use. Each group was matched, by sex, age, body mass index, education level and concussion history with athletes who were not reportedly prescribed psychotropic medications or did not report a depression/anxiety history, respectively. Each group's baseline ImPACT scores were compared to matched controls. Results: The use of prescribed psychotropic medications without regard to subclass had no effect on baseline ImPACT composite scores among athletes ages 13-25. However, athletes reportedly prescribed psychostimulants displayed significantly lower visual motor speed scores (32.8 vs 37.1, p = 0.030) and slower reaction times (0.65 vs 0.60, p = 0.044) than non-users. In contrast, antidepressant users displayed significantly faster reaction times (0.58 vs 0.61, p = 0.029). Those reporting a history of depression/anxiety, not treated with psychotropics, displayed significantly lower visual memory (70.4 vs 75.2, p = 0.010) and higher symptom scores (8.83 vs 4.72, p = 0.005). Conclusions: This pilot study suggests that self-reported psychotropic medications are associated with differences in baseline ImPACT test scores, which appear dependent on medication subclass. Our preliminary results support the inclusion of psychotropic medications, specifically psychostimulants and antidepressants, as well as history of depression/anxiety as potential concussion modifiers.
Article
Objective: To investigate whether attention deficit hyperactivity disorder (ADHD) influences postconcussion recovery, as measured by computerized neurocognitive testing. Design: This is a retrospective case control study. Setting: Computer laboratories across 10 high schools in the greater Atlanta, Georgia area. Participants: Immediate postconcussion assessment and cognitive testing (ImPACT) scores of 70 athletes with a self-reported diagnosis of ADHD and who sustained a sport-related concussion were compared with a randomly selected age-matched control group. Immediate postconcussion assessment and cognitive testing scores over a 5-year interval were reviewed for inclusion. Main outcome measures: Postconcussion recovery was defined as a return to equivalent baseline neurocognitive score on the ImPACT battery, and a concussion symptom score of ≤7. Results: Athletes with ADHD had on average a longer time to recovery when compared with the control group (16.5 days compared with 13.5 days), although not statistically significant. The number of previous concussions did not have any effect on the rate of recovery in the ADHD or the control group. In addition, baseline neurocognitive testing did not statistically differ between the 2 groups, except in verbal memory. Conclusions: Although not statistically significant, youth athletes with ADHD took on average 3 days longer to return to baseline neurocognitive testing compared with a control group without ADHD. Clinical relevance: Youth athletes with ADHD may have a marginally prolonged recovery as indexed by neurocognitive testing and should be considered when prognosticating time to recovery in this subset of student athletes.
Article
Data from the 2003 and 2007 National Survey of Children's Health (NSCH) reflect the increasing prevalence of parent-reported attention-deficit/hyperactivity disorder (ADHD) diagnosis and treatment by health care providers. This report updates these prevalence estimates for 2011 and describes temporal trends. Weighted analyses were conducted with 2011 NSCH data to estimate prevalence of parent-reported ADHD diagnosis, current ADHD, current medication treatment, ADHD severity, and mean age of diagnosis for U.S. children/adolescents aged 4 to 17 years and among demographic subgroups. A history of ADHD diagnosis (2003-2011), as well as current ADHD and medication treatment prevalence (2007-2011), were compared using prevalence ratios and 95% confidence intervals. In 2011, 11% of children/adolescents aged 4 to 17 years had ever received an ADHD diagnosis (6.4 million children). Among those with a history of ADHD diagnosis, 83% were reported as currently having ADHD (8.8%); 69% of children with current ADHD were taking medication for ADHD (6.1%, 3.5 million children). A parent-reported history of ADHD increased by 42% from 2003 to 2011. Prevalence of a history of ADHD, current ADHD, medicated ADHD, and moderate/severe ADHD increased significantly from 2007 estimates. Prevalence of medicated ADHD increased by 28% from 2007 to 2011. Approximately 2 million more U.S. children/adolescents aged 4 to 17 years had been diagnosed with ADHD in 2011, compared to 2003. More than two-thirds of those with current ADHD were taking medication for treatment in 2011. This suggests an increasing burden of ADHD on the U.S. health care system. Efforts to further understand ADHD diagnostic and treatment patterns are warranted.
Article
Attention-deficit/hyperactivity disorder (ADHD) is associated with a broad range of neuropsychological impairments. The relationship between these neuropsychological deficits and the defining symptoms of ADHD seems more complex than originally thought. Methylphenidate (MPH) is an effective treatment for ADHD symptoms, but its impact on cognition is less clearly understood. With a common systematic search strategy and a rigorous coding and data extraction strategy across domains, we searched electronic databases to identify published placebo controlled trials that compared MPH and placebo on executive and nonexecutive memory, reaction time, reaction time variability and response inhibition in children and adolescents (5-18 years) with a formal diagnosis of ADHD. Sixty studies were included in the review, of which 36 contained sufficient data for meta-analysis. Methylphenidate was superior to placebo in all five meta-analyses: executive memory, standardized mean difference (SMD) .26, 95% confidence interval (CI): -.39 to -.13; non-executive memory, SMD .60, 95% CI: -.79 to -.41; reaction time, SMD .24, 95% CI: -.33 to -.15; reaction time variability, SMD .62, 95% CI: -.90 to -.34; response inhibition, SMD .41, 95% CI: -.55 to -.27. These data support the potentially important effects of MPH on various aspects of cognition known to be associated with ADHD. Consideration should be given to adding cognitive outcomes to the assessment of treatment outcome in ADHD, considering the complexity of the relationship between ADHD symptoms and cognition.