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Interpreting Change on ImPACT Following Sport Concussion


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The purpose of this study was to examine the psychometric characteristics of Version 2.0 of ImPACT (Immediate Postconcussion Assessment and Cognitive Testing). The focus was on the stability of the test scores and the calculation of reliable change confidence intervals for the test-retest difference scores. A sample of 56 nonconcussed adolescents and young adults completed the test battery on two occasions. Test-retest coefficients, reliable change difference scores, and confidence intervals for measurement error are provided. These reliable change parameters were applied to a second sample of 41 concussed amateur athletes who were tested preseason and within 72 hr of injury. Applying these confidence intervals allows more precise determinations of deterioration, improvement, and recovery in the initial days following concussion.
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The Clinical Neuropsychologist 1385-4046/03/1704-460$16.00
2003, Vol. 17, No. 4, pp. 460–467 # Taylor & Francis Ltd.
Interpreting Change on ImPACT Following
Sport Concussion
Grant L. Iverson
, Mark R. Lovell
, and Michael W. Collins
Department of Psychiatry, University of British Columbia & Riverview Hospital, Vancouver, BC, Canada,
Department of Orthopaedic Surgery, University of Pittsburgh Medical Center,
Sports Medicine Concussion Program, Pittsburgh, PA, USA
The purpose of this study was to examine the psychometric characteristics of Version 2.0 of ImPACT
(Immediate Postconcussion Assessment and Cognitive Testing). The focus was on the stability of the test
scores and the calculation of reliable change confidence intervals for the test-retest difference scores. A
sample of 56 nonconcussed adolescents and young adults completed the test battery on two occasions. Test-
retest coefficients, reliable change difference scores, and confidence intervals for measurement error are
provided. These reliable change parameters were applied to a second sample of 41 concussed amateur
athletes who were tested preseason and within 72 hr of injury. Applying these confidence intervals allows
more precise determinations of deterioration, improvement, and recovery in the initial days following
Estimating change is the sine qua non of clinical
neuropsychology. Every neuropsychological eval-
uation includes a careful determination of change.
Typically, we try to estimate decline in functioning
that can be attributed to a brain injury, condition, or
disease. Other evaluations are undertaken to assess
interval change. Neuropsychological assessment
can be very useful for tracking recovery from a
traumatic brain injury or a stroke, or for monitoring
progression of a dementing disease such as
Alzheimer’s. For practical, clinical, and economic
reasons, follow-up evaluations typically are con-
ducted after 6–24 months (although, there are
clinical situations in which shorter retest intervals
are preferred).
Sports neuropsychology is relatively unique in
that cognitive assessments often occur over very
brief retest intervals to facilitate decisions regard-
ing returning to practice and competition. This
creates special challenges relating to estimating
change. For example, the phenomenon under
study, the effects of concussion on cognitive
functioning, is rapidly changing. The accuracy
with which we can assess this phenomenon is
related to the sensitivity of the measures, and, of
course, their reliability.
ImPACT (Immediate Postconcussion Assess-
ment and Cognitive Testing) is a computerized
neuropsychological screening battery designed
specifically for assessing sports-related concus-
sion. Version 1.0 of the battery has been used in
several studies relating to outcome from concus-
sion (Collins et al., 2003; Iverson, Gaetz, Lovell,
& Collins, 2002a; Iverson, Gaetz, Lovell, Collins,
& Maroon, 2002b; Lovell et al., 2003; Lovell,
Collins, Iverson, Johnston, & Bradley, in press).
The battery was designed to minimize practice
effects through the use of several alternate forms.
In a reliability study for Version 1.0, there were no
practice effects over a 2-week retest interval in a
Address correspondence to: Grant Iverson, Ph.D., Department of Psychiatry, 2255 Wesbrook Mall, University of
British Columbia, Vancouver, BC, Canada V6T 2A1. E-mail:
Accepted for publication: November 10, 2003.
sample of 49 amateur athletes (Iverson, Lovell,
Collins, & Norwig, 2002c). Reliable change esti-
mates for Version 1.0 were provided.
The purpose of this study is to provide de-
tailed information regarding the interpretation of
change on Version 2.0 of ImPACT. Test scores can
be inuenced by numerous factors, such as prac-
tice effects, regression to the mean, and more
random or unpredictable forms of measurement
error. Therefore, proper interpretation of the test
requires an understanding of the probable range
of measurement error that surrounds test-retest
difference scores. This allows more precise deter-
minations of deterioration, improvement, and
recovery in the initial days following concussion.
First, test-retest reliability, practice effects, and
reliable change parameters will be estimated in a
sample of healthy young people who completed
the battery over a brief retest interval (i.e.,
approximately 7 days). Second, the derived reli-
able change parameters will be applied to a
sample of amateur athletes who underwent pre-
season testing and were re-evaluated within 72 hr
of sustaining a concussion.
Participants and Procedures
The rst sample was comprised of 56 adolescents and
young adults who completed Version 2.0 of ImPACT
twice for the purpose of a test-retest study. There were
29 males and 27 females. Their average age was 17.6
years (SD ¼ 1.7, range ¼ 1522). Approximately 64%
were in high school and 36% were in university. The
average retest interval was 5.8 days (median ¼ 7,
SD ¼ 3.0, range ¼ 113). Approximately 29% were
retested within 3 days, 43% within 4 days, 82% within
7 days, and 95% within 11 days.
The second sample was comprised of 41 amateur
athletes who sustained a sports-related concussion.
All athletes completed ImPACT at the beginning of
the season. All were retested within 72 hr of their
concussions (mean ¼ 1.3, median ¼ 1, SD ¼ 0.7 days).
This sample was 90% male. Their average age was
16.8 years (median ¼ 16, SD ¼ 2.4, range ¼ 1322).
Approximately 71% were in high school and 29%
were in university. The vast majority of athletes were
football players (88%), with small numbers of athletes
in other sports such as hockey, soccer, basketball, and
wrestling. Most athletes had sufcient information to
classify the severity of their concussions using the
American Academy of Neurology Concussion Grading
System (Kelly & Rosenberg, 1998; Quality Standards
Subcommittee, 1997). Approximately 54% had Grade I
Concussions, 22% had Grade II Concussions, and 7%
had Grade III Concussions. Missing data prevented the
condent classication of 17% (i.e., 7 athletes).
Version 2.0 of ImPACT is a computer administered
neuropsychological test battery that consists of six
individual test modules that measure aspects of
cognitive functioning including attention, memory,
reaction time, and processing speed. Four composite
scores were used for this study. In general, the test
battery is designed to yield multiple types of informa-
tion within a brief period of time. Each test module may
contribute scores to multiple composite scores. The
Verbal Memory composite score represents the average
percent correct for a word recognition paradigm, a
symbol number match task, and a letter memory task
with an accompanying interference task. The Visual
Memory composite score is comprised of the average
percent correct scores for two tasks; a recognition
memory task that requires the discrimination of a series
of abstract line drawings, and a memory task that
requires the identication of a series of illuminated Xs
or Os after an intervening task (mouse clicking a
number sequence from 25 to 1). The Reaction Time
composite score represents the average response time
(in milliseconds) on a choice reaction time, a go/no-go
task, and the previously mentioned symbol match task.
The Processing Speed composite represents the
weighted average of three tasks that are done as
interference tasks for the memory paradigms. The
Impulse Control composite score represents the total
number of errors of omission or commission on the go/
no-go test and the choice reaction time test. This
composite is used to identify athletes who are not
putting forth maximum effort or who are seriously
confused about test instructions. This composite was
not one of the dependent measures for this study. In
addition to the cognitive measures, ImPACT also
contains a Postconcussion Symptom Scale, utilized
throughout organized sports (Aubry et al., 2002; Lovell
& Collins, 1998), that consists of 21 commonly
reported symptoms (e.g., headache, dizziness, ‘‘foggi-
ness’’). The dependent measure is the total score
derived from this 21-item scale.
Most research to date has used version 1.0 of the
program. ImPACT 2.0 is very similar to the original
version. However, there are some signicant changes.
Version 2.0 includes an additional test module (design
memory). In addition, one of the working memory tasks
(Xs and Os) was expanded and modied, making it
more difcult than the previous version. Version 2.0
also yields two memory composite scores (Verbal
Memory and Visual Memory) while Version 1.0
contains only one memory composite score.
Design and Analysis
The rst set of analyses were based on the healthy
young people tested twice. This was a within subjects
design. Relative position across the two distributions
was examined with a Pearson correlation. Level of
performance within subjects was examined with
dependent t-tests. Reliable change estimates were
derived from a modication of the method proposed
by Jacobson and Truax (1991). This methodology has
been used extensively in clinical psychology (Hageman
& Arrindell, 1993; Hsu, 1989; Jacobson & Revenstorf,
1988; Jacobson, Roberts, Berns, & McGlinchey, 1999;
Ogles, Lambert, & Masters, 1996; Speer, 1992; Speer &
Greenbaum, 1995), clinical neuropsychology (Chelune,
Naugle, Luders, Sedlak, & Awad, 1993; Heaton et al.,
2001; Iverson, 1998, 1999, 2001; Temkin, Heaton,
Grant, & Dikmen, 1999), and sports neuropsychology
(Barr & McRea, 2001; Hinton-Bayre, Geffen, Geffen,
McFarland, & Friis, 1999; Iverson et al., 2002c). The
reliable change methodology allows the clinician to
estimate measurement error surrounding test-retest
difference scores. Specically, the standard error of
difference (S
) is used to create a condence interval
for the baseline-retest difference score. The steps for
calculating the S
are provided below:
¼ SD
1 r
ðStandard deviation from time 1 multiplied
by the square root of 1 minus the test-
retest coefficientÞ:
¼ SD
1 r
ðStandard deviation from time 2 multiplied
by the square root of 1 minus the test-
retest coefficientÞ:
ðSquare root of the sum of the squared
SEMs for each testing occasionÞ:
The reader should note that the formula used in this
study for calculating the S
uses the SEM for baseline
and retest, whereas many past studies have used an
‘‘estimated’’ S
by simply multiplying the squared
baseline SEM by two (i.e.,
). The estimated
should only be used when retest data are not
available (Hageman & Arrindell, 1993; Iverson, 1998,
2001). Several renements and modications to the
reliable change methodology have been debated in the
literature (Hageman & Arrindell, 1993, 1999a, 1999b;
Hsu, 1989, 1999; Speer, 1992; Speer & Greenbaum,
1995). The issues are far from resolved. We chose to
use the reliable change method that corrects for practice
(Chelune et al., 1993; Iverson & Green, 2001), when
practice effects are present.
Descriptive statistics for the healthy young
people tested twice are presented in Table 1. The
Pearson test-retest correlation coefcients for the
composite scores were as follows: Verbal
Memory ¼ 0.70, Visual Memory ¼ 0.67, Reaction
Time ¼ 0.79, Processing Speed ¼ 0.86, and Post-
concussion Scale ¼ 0.65. The standard errors of
measurement (SEMs), standard errors of dif-
ference (S
), and reliable change condence
intervals also are presented in Table 1. The
probable ranges of measurement error for the
ImPACT composites are as follows: Verbal
Memory Composite ¼ 6.83 points, Visual
Memory Composite ¼ 10.59 points, Reaction
Time Composite ¼ 0.05 s, Processing Speed
Table 1. Descriptive Statistics, SEMs, S
, and Reliable Change Condence Intervals for the Healthy Control
Subjects (N ¼ 56).
Composite M (SD) p SEM
Condence intervals
Time 1 Time 2 0.80 0.90
Verbal Memory 88.68 (9.50) 88.84 (8.09) .86 5.20 4.43 6.83 8.75 11.21
Visual Memory 78.70 (13.39) 77.48 (12.67) .40 7.69 7.28 10.59 13.55 17.37
Reaction Time .543 (.087) 0.536 (.063) .34 0.04 0.03 0.05 0.06 0.08
Processing Speed 40.54 (7.64) 42.24 (7.06) .002 2.86 2.64 3.89 4.98 6.38
Postconcussion Scale 5.23 (6.75) 5.79 (10.07) .59 3.99 5.96 7.17 9.18 11.76
Note. SEM: standard error of measurement; S
: standard error of difference.
Composite ¼ 3.89 points, and Postconcussion
Scale 7.17 points. The 80% condence intervals
for estimating change are as follows: Verbal
Memory 9 points, Visual Memory 14 points,
Reaction Time > 0.06 s, Processing Speed 5
points, and Postconcussion Total Scores 10
points. These are rounded values derived from
Table 1.
Level of performance was compared using
paired samples t-tests. There were no within
group differences for Verbal Memory, t(55) ¼
0.17, p < .87, Visual Memory, t(55) ¼ 0.85,
p < .40, Reaction Time, t(55) ¼ 0.97, p < .34, or
total symptoms, t(55) ¼0.54, p < .60. There
was a signicant difference between baseline
and retest on the Processing Speed Composite,
t(55) ¼3.26, p < .003, d ¼ 0.23, small effect
size. On average, there was a 1.7 point practice
effect for the Processing Speed Composite.
Approximately 68% of the sample was faster at
retest than at baseline.
The reliable change difference scores asso-
ciated with the two condence intervals were
applied to the original data. If the distributions
of difference scores were perfectly normal, then
one would expect to see 10% in each tail for the
0.80 condence interval and 5% in each tail for
the 0.90 condence interval. As seen in Table 2,
the percentages of subjects that would be classi-
ed as reliably improved or declined was reason-
ably close to what would be predicted from the
theoretical normal distribution.
The number of scores that reliably declined for
each subject was computed. A decline was
dened as reliably lower Verbal or Visual mem-
ory, slower processing speed or reaction time, or
greater symptoms at retest versus baseline (80%
condence interval). The percentages of subjects
showing declines across the ve composite scores
are as follows: no declines ¼ 63.0%, one decline ¼
39.3%, two declines ¼ 1.8%, 3 declines ¼ 0%,and
4declines¼ 1.8%.
The sensitivity of the composite scores to the
acute effects of concussion was estimated in the
sample of 41 amateur athletes who were tested
preseason and within 72 hr of injury. The athletes
demonstrated a signicant decline in Verbal
Memory (baseline M ¼ 84.9, SD ¼ 7.2; Postcon-
cussion M ¼ 76.8, SD ¼ 12.6; p < .0002, d ¼ 0.82,
large effect size) and Visual Memory (baseline
M ¼ 75.7, SD ¼ 12.3; Postconcussion M ¼ 66.4,
SD ¼ 14.7; p < .0002, d ¼ 0.69, medium-large
effect size). They also demonstrated signicantly
slower Processing Speed (baseline M ¼ 36.9,
SD ¼ 6.8; Postconcussion M ¼ 33.1, SD ¼ 8.8;
p < .006, d ¼ 0.49, medium effect size), and
Reaction Time (baseline M ¼ 0.56, SD ¼ 0.08;
Postconcussion M ¼ 0.65, SD ¼ 0.11; p < .00005,
d ¼ 0.95, large effect size). The athletes also dem-
onstrated a large increase in symptom reporting
(baseline M ¼ 8.2, SD ¼ 10.7; Postconcussion M ¼
24.3, SD ¼ 21.7; p < .00001, d ¼ 0.99, large effect
size). These ndings are illustrated in Figure 1.
The 80% condence interval for estimating
reliable change was applied to each of the con-
cussed athletes composite scores. The condence
interval for Processing Speed was adjusted by two
points for the presumed practice effect. The break-
down of reliable change for each composite
score was as follows: Verbal Memory 44% de-
clined, 7.3% improved; Visual Memory 41.5% de-
clined, 2.4% improved; Reaction Time 51.2%
Table 2. Percentages of the Healthy Sample that Would be Classied as Reliably Improved or Declined Based on
the 0.80 and 0.90 Condence Intervals.
0.80 condence interval 0.90 condence interval
Declined (%) Improved (%) Declined (%) Improved (%)
Verbal Memory 10.7 16.1 5.4 8.9
Visual Memory 10.7 8.9 5.4 3.6
Reaction Time 8.9 14.3 5.4 7.1
Processing Speed
7.1 8.9 3.6 5.4
Postconcussion Scale 12.5 7.1 10.7 3.6
The condence intervals for the Processing Speed composite were adjusted for a 2-point practice effect.
declined, 7.3% improved; Processing Speed 41.5%
declined, 4.9% improved; Postconcussion Scale
53.7% reported more symptoms, 2.4% reported
fewer symptoms.
The number of scores that reliably declined for
each subject was computed. A decline was
dened in the same manner as it was for the
healthy test-retest sample. The percentages of
athletes showing declines across the ve compo-
site score are as follows: no declines ¼ 24.4%,
one decline ¼ 12.2%, two declines ¼ 14.6%, three
declines ¼ 17.1%, four declines ¼ 19.5%, and ve
declines ¼ 12.2%. Athletes with concussions are
much more likely to have two or more declines
across the ve composites than the healthy
subjects [63.4% vs. 3.6%;
(1, 97) ¼ 41.3, p <
.00001; Odds Ratio ¼ 46.8, 95% CI ¼ 10.0220.0].
This study illustrates important aspects of the
psychometric properties of Version 2.0 of
ImPACT. The test-retest coefcients for the ve
composite scores ranged from 0.65 to 0.86.
Although, seemingly relatively modest, these
stability coefcients are comparable or higher
than many other neuropsychological tests, such as
the Wechsler Memory Scale Third Edition
Index scores (Psychological Corporation, 1997),
DelisKaplan Executive Function System Trail-
Making Test or Color-Word Test (Delis, Kaplan,
& Kramer, 2001), or the California Verbal
Learning TestSecond Edition (Delis, Kramer,
Kaplan, & Ober, 2000).
When evaluating changes in cognitive per-
formance following concussion, it is critically
important to understand the probable range of mea-
surement error surrounding test-retest difference
scores to more accurately document deterioration
from preseason testing and recovery during the
initial days postinjury. In the present study, we
made adjustments to the ImPACT Processing
Speed composite score reliable change indices be-
cause practice effects were present. It was not nec-
essary to adjust the other composite scores because
practice effects were not identied. ImPACT was
designed to reduce practice effects through ran-
domization of stimuli presentation. This was an
essential design feature because the battery is
intended to be used repeatedly, over short intervals.
A quick reference guide for estimating change on
the composite scores is presented in Table 3.
In the second part of this study, preseason and
postconcussion scores were examined for 41
concussed amateur athletes. As a group, these
athletes demonstrated a large change in Verbal
Memory, reaction time, and self-reported symp-
toms. They experienced a medium-to-large
change in Visual Memory and processing speed.
The effect sizes from preseason to postconcus-
sion were medium to large, ranging from 0.49 to
Fig. 1. Comparison of preseason and postinjury scores
on the ve composites transformed into uni-
form T-scores (N ¼ 41).
Note. These T-scores are not normative T-
scores. They are standardized scores.
The distributions of baseline and
postconcussion scores for each compo-
site were standardized with a mean of 50
and a standard deviation of 10. The
direction of the symptom score and the
reaction time score was reversed, so that
lower T-scores represent worse scores.
Thus, all ve composites can be com-
pared graphically on a common metric.
Table 3. Quick Reference Reliable Change Estimates:
80% Condence Interval.
Composite Declined Improved
Verbal Memory 9 points 9 points
Visual Memory 14 points 14 points
Reaction Time 0.06 s 0.06 s
Processing Speed 3 points 7 points
Postconcussion Scale 10 points 10 points
0.99 across the ve composite scores. These effect
sizes are comparable to the magnitude of
‘‘impairments’’ on other tests in other popula-
tions. For example, the effect sizes comparing
orthopedically injured trauma control subjects to
patients with moderate-severe traumatic brain
injuries were 0.46 for the Category Test and
0.37 for Trails B (calculated from Dikmen,
Ross, Machamer, & Temkin, 1995; patients with
TBIs took 713 days postinjury to reliably follow
commands, and they were tested 1-year postin-
jury). Patients with Alzheimers disease showed a
0.79 effect size for the WAIS-III Working Mem-
ory Index and a 1.39 effect size for the Processing
Speed Index (Psychological Corporation, 1997).
When the reliable change methodology was
applied to the concussed athletes, 44%54%
showed statistically reliable declines across the
ve individual composite scores. Athletes with
concussions were 47 times more likely to have 2
or more declines across the ve composites than
nonconcussed subjects tested twice. Clearly, the
computerized screening battery is sensitive to the
acute effects of concussion and a large percentage
of athletes show substantial changes in functioning
in the rst few days postinjury. This sensitivity to
the acute effects of concussion is consistent with
research with version 1.0 of ImPACT (Collins
et al., 2003; Iverson et al., 2002a; Lovell et al.,
2003; Lovell et al., in press). It is important to
emphasize that concussion is a highly individua-
lized injury. Some athletes experience immediate,
pronounced problems whereas others experience
very mild problems that resolve quickly. All ath-
letes are not expected to show cognitive problems
on neuropsychological testing, even in the rst
couple days postinjury.
This was a preliminary study designed to
investigate reliable change on Version 2.0 of
ImPACT. It is limited by the relatively small
sample size, a common limitation with most
(e.g., Barr, 2003; Hinton-Bayre et al., 1999;
Moritz, Iverson, & Woodward, in press; Sawrie,
Chelune, Naugle, & Luders, 1996), but not all
(e.g., Erlanger et al., 2003; Temkin et al., 1999)
reliable change studies. The effect of the hetero-
geneity of the sample (i.e., high school and
college students) on the test-retest coefcients is
unknown. Future research with larger, more
homogeneous samples might further rene the
interpretation of change on this battery.
Another limitation in this study is the retest
interval. This interval was very short. Thus, it is
relevant for postconcussion testing over at least one
short interval. However, it is possible that the
reliable change estimates would change over a
longer interval, such as from preseason to postcon-
cussion. This limits the external validity of these
results because the brief retest interval in healthy
subjects was used to estimate reliable change in
healthy then concussed athletes tested at a longer
interval. It is also possible that the practice effect
seen on the Processing Speed composite might
diminish or disappear over a longer retest interval.
Three practical methodological issues relating
to estimating reliable change will be presented.
First, there is the statistical issue of regression to
the mean and the practical issue of an unusually
good or unusually poor performance. As a general
rule, extreme scores are likely to be less extreme
at retest. The reliable change methodology essen-
tially averages this phenomenon into the measure-
ment error estimate. The end result is that the
reliable change estimate is optimized for the
entire sample but is not as accurate for subsam-
ples, such as the top 20%, middle 60%, and
bottom 20% of scores. In other words, one of
the most important predictors of a retest score is
the level of the baseline score (Sawrie et al., 1996;
Temkin et al., 1999). Optimally, reliable change
estimates would be based on large samples of
more homogeneous baseline scores.
Second, it is most common to present 90% or
95% condence intervals for reliable change. This
is a sensitivity and specicity issue. Do we really
want to be 95% sure that the change observed is not
due to possible measurement error, leaving only
2.5% in each tail? Under many clinical circum-
stances we want to adopt a more liberal statistical
criterion so that we are more likely to identify real
change when it occurs. That is why the 80%
condence interval was emphasized in this study
and in previous work (Iverson, 1999, 2001; Iverson
& Green, 2001). Barr (2003) recently included the
70% condence interval.
Third, the issue of practice effects is important
(Chelune et al., 1993), yet complicated. Is it
appropriate to correct all scores for an ‘‘average’’
practice effect? What if 55% of subjects score
higher at retest and 15% score substantially
higher? Correcting for the average practice effect
might not be optimal for a large percentage of
these subjects. Iverson and Green (2001) recom-
mended correcting for the average practice effect
if 75% or more of the sample had a higher score,
of any magnitude, at retest. This approach, of
course, has limitations too, and more research,
especially with regression modeling of large
representative samples over relevant retest inter-
vals, is needed.
With regard to the use of neuropsychological
assessment procedures in sports medicine, it is
important to stress that the reliable change differ-
ence scores are meant to supplement, not replace,
clinical judgment. The determination of decline
and then subsequent improvement in functioning
following concussion is a complex clinical process
that involves multiple sources of data. This reliable
change methodology simply allows clinicians to
estimate the probable range of measurement error
it is possible for athletes to experience real decline
or improvement even if their scores do not exceed
the 0.80 condence interval for measurement error.
The practitioner simply should have less con-
dence in clinical inferences based on changes that
fall within the probable range of measurement
error, and seek more ancillary evidence to support
his or her opinion.
The authors thank Jennifer Bernardo for assistance with
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... This study employed the PCSS to define patients who recovered well (PCSS <7) or poorly (PCSS 7) from concussion. Iverson et al 14 reported that the mean PCSS in 56 healthy adolescents with a mean age of 17.6 years was 5.23 to 5.79, tested at 2 time points. On the basis of these data, Lau et al 17 utilized a PCSS cutoff <7 in their research, therefore accounting for up to 76% of PCSS scores in uninjured adolescents. ...
... Last recorded PCSS score, defined as that at the last office visit, was used to define the recovered group (PCSS <7) and the poorly recovered group (PCSS 7) based on previous studies. 14,17 A total of 162 individuals with concussion visited the SM concussion clinic between January 2015 and December 2019. After the exclusion of 52 patients, 110 were retained for statistical analysis: 79 in the recovered group and 31 in the poorly recovered group. ...
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Background Concussion is a common injury among children and adolescents, with a growing body of literature supporting a variety of diagnostic and treatment modalities. Recovery is variable and depends on multiple factors that can be evaluated through a clinic visit: a thorough history, physical examination, and use of the Post-concussion Symptom Scale (PCSS). Purpose/Hypothesis The purpose of this study was to evaluate factors associated with overall recovery from concussion in children and adolescents in the clinical setting. It was hypothesized that the presence of 1 of a number of pre- or postinjury characteristics will be associated with poor concussion recovery. Study Design Case-control study; Level of evidence, 3. Methods We conducted a retrospective chart review of adolescents and children aged 6 to 17 years with a diagnosis of concussion who were evaluated at a single sports medicine center between January 2015 and December 2019. Cases were categorized into recovered (PCSS <7) and poorly recovered (PCSS ≥7) cohorts based on the last PCSS scores during clinical follow-ups for concussion management. Results Of the 162 charts reviewed, 110 cases met inclusion criteria. Significant statistical differences were found between the recovered and poorly recovered cohorts regarding mean days from injury to last clinic visit, previous migraine diagnosis, and emergency room (ER) visit before the first clinic visit ( P < .01 for all). Binary logistic regression analysis revealed that the most predictive factors associated with poorer recovery were having an ER visit before the first clinic evaluation ( P = .01) and previous migraine diagnosis ( P = .04). Conclusion While many factors may contribute to overall recovery from concussion in pediatric populations, our study suggested that a history of migraine and an ER visit before clinic evaluation may be associated with poor recovery of concussive symptoms.
... We computed the proportion of youth with and without ADHD who showed a reliable change on the neurocognitive and PCSS composites. The following criteria were used to determine whether a youth showed a reliable decline on post-injury testing as compared to baseline testing: decline of 9 or more points on Verbal Memory; decline of 14 or more points on Visual Memory; increase of 0.06 or more on Reaction Time; decline of 3 or more points on Visual Motor Speed; and an increase of 10 or more points of the PCSS total score (Iverson et al., 2003). ...
... It is interesting to note that the group without ADHD did not, on average, experience worsening on the Visual Motor Speed composite. The reason for this is unknown, but that composite appears to have greater practice effects than other composites (Brett et al., 2016;Gaudet et al., 2020;Iverson et al., 2003;Womble et al., 2016). Moreover, there might be general effects of both context and motivation that could have influenced the cognitive test results, such as group testing, which is done at baseline, being associated with modestly lower scores than when testing is done in small groups or individually (Moser et al., 2011) and students being much more concerned and motivated during their individual post-injury testing than they were during their preseason baseline testing. ...
Adolescents with ADHD have a greater lifetime history of concussion and experience concussion-like symptoms in the absence of a concussion, complicating concussion assessment and management. It is well established that individuals who experience greater acute symptoms following concussion are at risk for slower recovery and persistent symptoms. We examined whether youth with ADHD experience worse acute effects, within the first 72 h following concussion, compared to youth without ADHD. We hypothesized that youth with ADHD would perform worse on neurocognitive testing and endorse more severe symptoms acutely following injury, but the magnitude of change from pre injury to post injury would be similar for both groups, and thus comparable to baseline group differences. The sample included 852 adolescents with pre-injury and post-injury ImPACT results (within 72 h); we also conducted supplementary case-control analyses on a subset of youth with and without ADHD matched on demographics and pre-injury health history. For both samples, there were significant interaction effects for the Verbal Memory and Visual Motor Speed composites (p < 0.01, η2=.01-.07, small-medium effect), such that youth with ADHD showed a greater magnitude of diminished cognitive functioning from pre-injury to post-injury testing. There were no significant differences in the magnitudes of changes from pre injury to post injury with regard to overall symptom reporting (i.e., total symptom severity scores, total number of symptoms endorsed); however, there were group differences in endorsement rates for several individual symptoms. Further research is needed to determine whether such differential acute effects are associated with recovery time in youth with ADHD.
... All items were summed to give a total symptom score, with higher scores indicating a higher symptom burden. Although the psychometric properties of this questionnaire were not reported [79], the test-retest reliability for the questionnaire within the ImPACT test battery was 0.65 [80,81]. ...
Background: An estimated 99 in 100,000 people experience a traumatic brain injury (TBI), with 85% being mild (mTBI) in nature. The Post-Concussion Symptom Scale (PCSS), is a reliable and valid measure of post-mTBI symptoms; however, diagnostic specificity is challenging due to high symptom rates in the general population. Understanding the neurobiological characteristics that distinguish high and low PCSS raters may provide further clarification on this phenomenon. Aim: To explore the neurobiological characteristics of post-concussion symptoms through the association between PCSS scores, brain network connectivity (using quantitative electroencephalography; qEEG) and cognition in undergraduates. Hypotheses: high PCSS scorers will have (1) more network dysregulation and (2) more cognitive dysfunction compared to the low PCSS scorers. Methods: A sample of 40 undergraduates were divided into high and low PCSS scorers. Brain connectivity was measured using qEEG, and cognition was measured via neuropsychological measures of sustained attention, inhibition, immediate attention, working memory, processing speed and inhibition/switching. Results: Contrary to expectations, greater frontoparietal network dysregulation was seen in the low PCSS score group (p = 0.003). No significant difference in cognitive dysfunction was detected between high and low PCSS scorers. Post-hoc analysis in participants who had experienced mTBI revealed greater network dysregulation in those reporting a more recent mTBI. Conclusions: Measuring post-concussion symptoms alone is not necessarily informative about changes in underlying neural mechanisms. In an exploratory subset analysis, brain network dysregulation appears to be greater in the early post-injury phase compared to later. Further analysis of underlying PCSS constructs and how to measure these in a non-athlete population and clinical samples is warranted.
... As previously described [21][22][23][24], deviations from baseline to PI and then FU in composite Symptom score and the four ImPACT composite scores were used to track the severity and recovery of symptoms and neurocognitive dysfunction post-concussion. Deviations were standardized as the deviation between two subsequent baseline tests of healthy control participants at the 80% confidence interval (S diff ) [25]. For the Symptom Score composite the historic S diff is 9.18, for Verbal Memory 8.75, for Visual Memory 13.55, for Processing Speed 4.98, and for Reaction Time 0.06. ...
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Abstract Objective/ background Chronic headaches and sports-related concussions are among the most common neurological morbidities in adolescents and young adults. Given that the two can overlap in presentation, studying the effects of one on another has proven difficult. In this longitudinal study, we sought to assess the relationship between chronic headaches and concussions, analyzing the role of historic concussions on chronic headaches, as well as that of premorbid headaches on future concussion incidence, severity, and recovery. Methods This multi-center, longitudinal cohort study followed 7,453 youth athletes who were administered demographic and clinical surveys as well as a total of 25,815 Immediate Post-concussion Assessment and Cognitive Testing (ImPACT) assessments between 2009 and 2019. ImPACT was administered at baseline. Throughout the season concussions were examined by physicians and athletic trainers, followed by re-administration of ImPACT post-injury (PI), and at follow-up (FU), a median of 7 days post-concussion. Concussion incidence was calculated as the total number of concussions per patient years. Concussion severity and recovery were calculated as standardized deviations from baseline to PI and then FU in Symptom Score and the four neurocognitive composite ImPACT scores: Verbal Memory, Visual Memory, Processing Speed, and Reaction Time. Data were collected prospectively in a well-organized electronic format supervised by a national research-oriented organization with rigorous quality assurance. Analysis was preformed retrospectively. Results Of the eligible athletes, 1,147 reported chronic headaches (CH) at the start of the season and 6,306 reported no such history (NH). Median age of the cohort was 15.4 ± 1.6 years, and students were followed for an average of 1.3 ± 0.6 years. A history of concussions (OR 2.31, P
Objective: Following sport-related concussion (SRC), early studies have demonstrated racial differences in time-to-clinical-recovery; however, these differences have not been fully explained. We sought to further explore these associations by considering possible mediating/moderating factors. Methods: Data from patients aged 12-18 years diagnosed with SRC from 11/2017-10/2020 were analyzed. Those missing key data, lost to follow-up, or missing race were excluded. The exposure of interest was race, dichotomized as Black/White. The primary outcome was time to clinical recovery (days from injury until the patient was either deemed recovered by an SRC provider or symptom score returned to baseline or zero.) RESULTS: A total of 389 (82%) White and 87 (18%) Black athletes with SRC were included. Black athletes more frequently reported no SRC history (83% vs. 67%, p=0.006) and lower symptom burden at presentation [median total Post-Concussion Symptom Scale (PCSS) 11 vs. 23, p<0.001] than White athletes. Black athletes achieved earlier clinical recovery (HR=1.35, 95%CI 1.03-1.77, p=0.030), which remained significant (HR=1.32, 95%CI 1.002-1.73, p=0.048) after adjusting for confounders associated with recovery but not race. A third model adding initial PCSS nullified the association between race/recovery (HR=1.12, 95%CI 0.85-1.48, p=0.410). Adding prior concussion history further reduced the association between race/recovery (HR=1.01, 95%CI 0.77-1.34, p=0.925). Conclusions: Overall, Black athletes initially presented with fewer concussion symptoms than White athletes, despite no difference in time-to-clinic. Black athletes achieved earlier clinical recovery following SRC, a difference explained by differences in initial symptom burden and self-reported concussion history. These crucial differences may stem from cultural/psychological/organic factors.
Objective: To examine the frequency and association of neck pain symptoms in patients with a concussion. Study setting and participants: Three-hundred and thirty-one consecutively enrolled patients aged 9 to 68 years with a diagnosed concussion 1 to 384 days post-injury were enrolled at a concussion clinic from a single integrated healthcare system in Western Pennsylvania between 2019 and 2021. Design: Retrospective cohort analysis of prospectively collected concussion screening tool intake survey responses and clinical outcomes data. The primary outcome was self-reported neck pain or difficulty with neck movement on the Concussion Clinical Profiles Screening (CP Screen) tool, recovery time, and incidence of treatment referral. Immediate Post-concussion Assessment and Cognitive Testing (ImPACT) composite scores, Vestibular/Ocular Motor Screening (VOMS) item scores, type and severity of neck symptoms, mechanism of injury, time from injury to clinic presentation, medical history, and concussion symptom profile were secondary outcomes. Results: Of the 306 consecutively enrolled eligible patients in the registry, 145 (47%) reported neck pain, 68 (22.2%) reported difficulty moving their neck, and 146 (47.7%) reported either symptom. A total of 47 (15.4%) participants reported more severe neck symptoms, and this group took longer to recover (40 ± 27 days) than those not reporting neck symptoms (30 ± 28 days; U = 8316, P < .001). Stepwise logistic regression predicting more severe neck symptoms was significant (Nagelkerke R2 = 0.174, χ2 = 9.315, P = .316) with older age (P = .019) and mechanism of injury including motor vehicle collisions (MVCs) (P = .047) and falls (P = .044) as risk factors. MVCs and falls were associated with over 4 times and 2 times greater risk, respectively, for reporting more severe neck symptoms. Conclusion: Neck pain and stiffness symptoms are common in patients with a concussion following high-energy mechanisms of injury including MVCs or falls from height. These symptoms are associated with prolonged recovery. Providers should evaluate neck symptoms and consider targeted treatment strategies to limit their effects in patients with a concussion.
Objective: Neurocognitive testing and oculomotor assessment have been an integral component to provide objective measures for sport-related concussion (SRC) detection and management. Hormonal contraceptive (HC) use is common among collegiate female athletes and may modify baseline SRC performance. The purpose was to examine the effects of HC use on baseline computerized neurocognitive testing (CNT) and oculomotor testing in college-aged individuals. Method: A total of 63 participants (22 HC using females, 22 non-HC using females, 19 males) completed a baseline SRC battery consisting of CNT, near point of convergence (NPC), and the King-Devick (KD) test. CNT measures were composite scores of verbal and visual memory, visual motor processing speed and reaction time, impulse control, and cognitive efficiency index (CEI). NPC was measured as the average convergence distance across three trials. KD time was recorded as total time for each of the two trials and best trial marked as baseline. Results: There were no group differences between HC, non-HC, and male control groups on all baseline CNT composite scores (p = .13-.98), impulse control (p = .47), and CEI (p = .49). NPC distance was similar between groups (p = .41), as well as KD time by trial (Trial 1 p = .65; 2 p = .48) and best time (p = .49). Conclusions: HC use does not appear to influence baseline SRC measures of neurocognition and oculomotor assessment. Clinicians should continue to consider the effects of modifying factors at baseline and post-concussion. Additional research is needed to better understand sex hormone levels and SRC performance measures.
Purpose: Numerous studies have reported electrophysiological differences between concussed and non-concussed groups, but few studies have systematically explored recovery trajectories from acute concussion to symptom recovery and the transition from acute concussion to prolonged phases. Questions remain about recovery prognosis and the extent to which symptom resolution coincides with injury resolution. This study therefore investigated the electrophysiological differences in recoveries between simple and complex concussion. Methods: Student athletes with acute concussion from a previous study (19(2) years old) were tracked from pre-injury baseline, 24-48 hours after concussion, and through in-season recovery. The electroencephalography (EEG) with P300 evoked response trajectories from this acute study were compared to an age-matched population of 71 patients (18(2) years old) with prolonged post-concussive symptoms (PPCS), 61 (SD 31) days after concussion. Results: Acute, return-to-play, and PPCS groups all experienced a significant deficit in P300 amplitude compared to the pre-injury baseline group. The PPCS group, however, had significantly different EEG spectral and coherence patterns from every other group. Conclusion: These data suggest that while the evoked response potentials deficits of simple concussion may persist in more prolonged stages, there are certain EEG measures unique to PPCS. These metrics are readily accessible to clinicians and may provide useful parameters to help predict trajectories, characterize injury (phenotype), and track the course of injury.
Objective: (1) To determine test-retest reliability of individual Sport Concussion Assessment Tool-Third Edition (SCAT-3) symptom scores and symptom severity scores, (2) to examine the specificity/sensitivity of individual SCAT-3 symptom severity scores acutely (24-48 hours) postconcussion, and (3) to develop a model of symptoms best able to differentiate concussed from nonconcussed student athletes and cadets. Design: Prospective, longitudinal, and cross-sectional. Setting: Twenty-six civilian schools and 3 US service academies. Participants: Collegiate student athletes (n = 5519) and cadets (n = 5359) from the National Collegiate Athletic Association-Department of Defense Grand Alliance: Concussion Assessment, Research and Education Consortium, including 290 student athletes and 205 cadets, assessed 24 to 48 hours postconcussion. Independent variables: Concussed and nonconcussed student athlete and cadet groups. Main outcome measures: Sport Concussion Assessment Tool-Third Edition individual symptom severity scores, total symptom scores, and symptom severity scores. Results: Results indicated poor test-retest reliability across all symptom scores (intraclass correlation coefficient = 0.029-0.331), but several individual symptoms had excellent predictive capability in discriminating concussed from nonconcussed participants (eg, headache, pressure in the head, and don't feel right had area under the curve >0.8, sensitivity >70%, and specificity >85%) regardless of baseline testing. These symptoms were consistent with Chi-square Automatic Interaction Detector classification trees with the highest mean probability. Conclusions: Findings support the excellent diagnostic accuracy of honest symptom reporting, notwithstanding the known limitations in symptom underreporting, and suggest that there may be added value in examining individual symptoms rather than total symptom scores and symptom severity scores alone. Finally, findings suggest that baseline testing is not necessary for interpreting postconcussion symptom scores.
Objective The objective of this study was to document the prevalence of post-computerized neurocognitive test (post-CNT) increases in symptoms in athletes with sport-related concussion, and to examine the effect of post-CNT symptom increases on concussion neurocognitive and vestibular/ocular motor clinical outcomes. Methods This was a retrospective analysis of medical records from a concussion specialty clinic. Two hundred and three athletes (M = 16.48 ± 1.97 years; 44% [90/203] female) completed a clinical visit for concussion within 30 days of injury (M = 7.73 ± 5.54 days). Computerized neurocognitive testing (the Immediate Post-concussion Assessment and Cognitive Testing: ImPACT), the Post-Concussion Symptom Scale (PCSS), and the Vestibular Ocular Motor Screening (VOMS) were the main outcome measures for the current study. Results Sixty-nine percent (141/203) of the sample did not report significant increases in PCSS scores following post-concussion CNT and were classified into a No Provocation (NO PROV) group. Thirty-one percent (62/203) of participants did report a significant increase in symptoms following post-concussion CNT and were classified into a Provocation (PROV) group. Neurocognitive performance was similar between groups. However, the PROV group reported significantly higher scores on the VOMS symptom items than the NO PROV group. Conclusions The majority of adolescent athletes can complete a post-concussion CNT without experiencing significant increases in concussion symptoms. Individuals that report symptom increases from completing a post-concussion CNT are more likely to exhibit increased vestibular/ocular motor symptoms. These findings underscore the relationship between the clinical findings from both CNT and vestibular/ocular motor measures following concussion.
The Concussion Resolution Index (CRI) is an online assessment tool designed to track resolution of symptoms following sports-related concussion. The CRI is composed of six subtests measuring reaction time, visual recognition, and speed of information processing. Three factors are derived from the subtests: Simple Reaction Time (SRT), Complex Reaction Time (CRT), and Processing Speed (PS). Multiple alternate forms within subtests afford simple, reliable, assessment of change, relative to a baseline test completed by an athlete. The test also assesses self-reported neurophysiological symptoms at the time of injury and tracks resolution of these symptoms. The data demonstrate the CRI is a valid and reliable measure of cognitive performance in a relatively heterogeneous group of athletes aged 13–35. Two methods of statistical analysis for assessing change from baseline were compared to establish a psychometric basis for return-to-play decision-making: the Reliable Change Index (RCI) and multiple regression. Multiple regression was more accurate than the RCI in determining a decline in performance relative to the baseline.
This study provides preliminary norms and test–retest indices on a brief battery of neuropsychological tests administered to a sample of 60 male and 40 female high school athletes. Forty-eight subjects completed retesting 8 weeks later. Analyses of baseline scores indicate that girls outperform boys on selected measures of processing speed and executive functions [Wechsler Adult Intelligence Scale—III (WAIS-III) Digit Symbol, Trails B, and Controlled Oral Word Association Test (COWAT)]. Test–retest reliability was low and varied widely among the tests. There were no gender differences in test–retest reliability. Reliable Change Indices (RCIs) were computed on the test–retest data for use in clinical interpretation. These preliminary results indicate that caution should be used in interpreting neuropsychological test data from high school athletes. The current findings indicate that separate norms for boys and girls are warranted. Caution should be used in interpreting discrepancies from baseline scores as a result of what may turn out to be poor test–retest reliability in this population.
Reports an error in the original article by D. C. Speer (Journal of Consulting & Clinical Psychology, 1992[Jun], Vol 60[3], 402–408). On page 402, column 2, line 3, the symbol for standard deviation was omitted. The correct formula is SE = SD[1 – rxx]1/2. (The following abstract of this article originally appeared in record 1992-29860-001.) The relationship between statistically and clinically significant change has been enigmatic. N. S. Jacobson and P. Truax (1991) have proposed an important step toward rapprochement. However, their suggested index of clinically significant change neglects possible confounding of improvement rate estimates by regression to the mean. An alternative method is described that incorporates an adjustment that minimizes this confounding when statistical regression has been shown to be present. If regression is not present, the Jacobson and Truax method is more appropriate; if regression is present, the Edwards-Nunnally method (D. W. Edwards et al, 1978) is more appropriate. The 2 methods are compared, and the effects of instrument reliability and sample deviance on estimated improvement rates are demonstrated using general well-being test–retest data from a sample of older adult mental health outpatients. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Reviews recently proposed definitions of "reliable" raw change scores in psychotherapy that do not take into account regression toward the mean effects attributable to measurement error and explores some implications of these effects. An alternative definition that focuses on the difference between a posttreatment score and the value of this score, which would be expected because of regression toward the mean, can result in conclusions that are different from those of the raw change score definitions, and can also result in counterintuitive conclusions about treatment efficacy. Comparisons of the 2 types of definitions are made by re-expressing critical change scores of both types of definitions on a common scale. Practical problems in the use of these definitions are discussed. (PsycINFO Database Record (c) 2012 APA, all rights reserved)
Addresses problems, issues, and dilemmas identified in attempting to apply statistics developed by N. S. Jacobson et al (see record 1985-00073-001) to delineate the clinical significance of treatment effects in psychotherapy research. After describing the statistics, various considerations are outlined, including optimal, less than optimal, and inappropriate uses of these statistics. Three major dilemmas are discussed: how to deal with the use of multiple outcome measures within a single study; how to minimize the problem of measurement error in S classification; and how to deal with measures that are not normally distributed. (PsycINFO Database Record (c) 2012 APA, all rights reserved)