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Measurement of Symptoms Following Sports-Related Concussion: Reliability and Normative Data for the Post-Concussion Scale


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It is important to carefully evaluate self-reported symptoms in athletes with known or suspected concussions. This article presents data on the psychometric and clinical properties of a commonly used concussion symptom inventory-the Post-Concussion Scale. Normative and psychometric data are presented for large samples of young men (N = 1,391) and young women (N = 355). In addition, data gathered from a concussed sample of athletes (N = 260) seen within 5 days of injury are presented. These groups represent samples of both high school and collegiate athletes. Data from a subsample of 52 concussed athletes seen 3 times post-injury are presented to illustrate symptom reporting patterns during the initial recovery period. General guidelines for the clinical use of the scale are provided.
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Measurement of Symptoms Following Sports-Related Concussion:
Reliability and Normative Data for the Post-Concussion Scale
Mark R. Lovell
University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
Grant L. Iverson
University of British Columbia & Riverview Hospital, Vancouver, British Columbia, Canada
Michael W. Collins
University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
Kenneth Podell
Henry Ford Health System, Detroit, Michigan
Karen M. Johnston
McGill University, Montreal, Quebec, Canada
Dustin Pardini
University of Pittsburgh, Pittsburgh, Pennsylvania, USA
Jamie Pardini
University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
John Norwig
Pittsburgh Steelers Football Club, Pittsburgh, Pennsylvania, USA
Joseph C. Maroon
University of Pittsburgh Medical Center, Pittsburgh, Pennsylvania, USA
It is important to carefully evaluate self-reported symptoms in athletes with known or sus
pected concussions. This article presents data on the psychometric and clinical properties of a
commonly used concussion symptom inventory—the Post-Concussion Scale. Normative and
psychometric data are presented for large samples of young men (N = 1,391) and young
women (N = 355). In addition, data gathered from a concussed sample of athletes (N = 260)
seen within 5 days of injury are presented. These groups represent samples of both high school
and collegiate athletes. Data from a subsample of 52 concussed athletes seen 3 times
post-injury are presented to illustrate symptom reporting patterns during the initial recovery
period. General guidelines for the clinical use of the scale are provided.
Key words: concussion, symptoms, traumatic brain injury, sports
Clinical strategies for the diagnosis and management
of concussion have evolved considerably over the past
decade. There has been a trend toward more sophisti
cated and individualized approaches to managing this
injury (Collins, Lovell, & McKeag, 1999; Johnston,
McCrory, Mohtadi, & Meeuwisse, 2001). More con
temporary concussion management strategies have em
phasized multiple diagnostic elements including clini
cal history, sideline evaluation, neuropsychological
testing, and neuroimaging, when appropriate.
Concussion has recently been defined as “a complex
pathophysiological process affecting the brain, induced
Applied Neuropsychology
2006, Vol. 13, No. 3, 166–174
Copyright 2006 by
Lawrence Erlbaum Associates, Inc.
Correspondence should be addressed to Mark R. Lovell, ABPN;
UPMC Center for Sports Medicine; 3200 South Water Street; Pitts
burgh, PA 15203, USA. E-mail:
by traumatic biomechanical forces” (Aubry et al.,
2002). Contemporary definitions of this injury assume
a neurophysiological rather than neuroanatomical basis
for concussion, and traditional neuroimaging proce
dures are of little value in the detection of injury and
monitoring of recovery. Although newer functional
brain imaging (fMRI) protocols show promise as a di
agnostic technology, fMRI is currently not available for
widespread clinical use (Lovell et al., 2004). Therefore,
neuropsychological assessment has played an increas
ingly prominent role in concussion management. Char
acteristic neuropsychological deficits following con
cussion in the areas of attentional processes, memory,
and neurocognitive speed following concussion have
been documented by multiple researchers (Echemendia
& Cantu, 2003; Erlanger et al., 2003; Lovell et al.,
2004a, 2004b; McCrea et al., 2003). However, in addi
tion to these common deficits that can be documented
by standardized neuropsychological assessment proto
cols, many symptoms reported by injured athletes are
of a more subjective nature.
In recognition of the need for better concussion man-
tion (IIHF), in conjunction with the International Olym-
pic Committee (IOC) and the Federation Internationale
de Football Association (FIFA), convened in Vienna in
October of 2001 to evaluate the current status of concus-
sion management guidelines and to draft practical rec-
ommendations for making return-to-play decisions
(Aubry et al., 2002). As a prominent piece of the concus-
sion evaluation process, the Concussion in Sport (CIS)
group recommended the careful evaluation of individual
symptoms following a suspected concussion and further
suggested that any report of symptoms should lead to
more in-depth evaluation.
The measurement of symptoms is very common in
the sport concussion literature (e.g., Echemendia,
Putukian, Mackin, Julian, & Shoss, 2001; Erlanger et
al., 2003; Guskiewicz et al., 2003; Macciocchi, Barth,
Alves, Rimel, & Jane, 1996; Macciocchi, Barth,
Littlefield, & Cantu, 2001; McCrea et al., 2003). Al
though the importance of player symptoms in making
return-to-play decisions is almost universally accepted,
the availability of formal evaluation scales with known
psychometric properties is rather limited, with the nota
ble exception of the Head Injury Scale (Piland, Motl,
Ferrara, & Peterson, 2003). In addition, differences in
symptom reporting by different groups (e.g., men vs.
women, high school vs. college) have not been ade
quately explored.
This article presents data on the psychometric and
clinical properties of a single commonly used concus
sion symptom inventory—the Post-Concussion Scale
(PCS). Normative data will be presented and discussed.
In addition, data gathered from a concussed sample of
athletes will be presented to illustrate changes in symp
tom reporting following concussion. General guide
lines for the clinical use of the scale will be provided.
Normative data for the PCS were derived from 1,746
high school and university student athletes. All student
athletes completed the computerized version of the test,
as administered within ImPACT Version 1. The stu
dents represented more than 15 high schools and 10
universities. There were 707 high school students and
1,039 university students. The high school sample was
comprised of 588 (83.2%) young men and 119 (16.8%)
young women. On average, they had completed 10.3
years of school (SD = 1.0). The university sample was
comprised of 803 (77.3%) young men and 236 (22.7%)
young women. On average, they had completed 13.6
years of school (SD = 1.3).
A separate clinical sample was comprised of 260
high school and university athletes who were evaluated
within 5 days of sustaining a sports-related concussion
(M = 2.0, SD = 1.2) by either a certified athletic trainer
or team physician. A concussion was diagnosed based
on recent international criteria (Aubry et al., 2002).
Prior to the beginning of the study, all athletic trainers
were formally trained in the on-field diagnosis of con
cussion by one of the authors (Drs. Lovell or Collins).
A concussion was diagnosed if the athlete reported
symptoms such as headache, dizziness, or balance dys
function, or if he or she exhibited a decline in cognitive
functioning as demonstrated by poor performance on a
brief mental status examination, which tested aspects of
retrograde and post-traumatic amnesia (Lovell, Collins,
Iverson, Johnston, & Bradley, 2004).
The majority of the concussed athletes were seen
within 72 hours (88%). Their average age was 16.5
years (SD = 2.0), and their average education was 10.2
years (SD = 1.8). The majority of athletes were in high
school (85%). The sample was 83.5% men and 16.5%
women. From this sample, a subsample of 52
concussed athletes who were evaluated three times
within specified intervals was selected. An athlete was
selected from the larger sample, for this subsample, if
he or she was evaluated the first time within 72 hours,
the second time between 4 and 8 days, and the third
time between 7 and 30 days. The time intervals were al
lowed to overlap slightly to increase the sample size for
these analyses. The actual breakdown of mean number
of days post- injury for each assessment period was as
follows: Time 1 = 1.4 days post (Mdn =1,SD = .7,
range = 0–3), Time 2 = 5.6 days post (Mdn =5,SD =
1.3, range = 4–8), and Time 3 = 11.7 days post (Mdn =
11, SD = 4.2, range = 7–24).
The PCS is a 22-item scale designed to measure the
severity of symptoms in the acute phase of recovery
from concussion (Lovell, 1996, 1999; Lovell & Collins,
1998). This scale was developed in the late 1980s
within the context of the Pittsburgh Steelers concussion
management program, and variants of this scale have
been formally adopted by the National Football League
(Lovell, 1996), National Hockey League (Lovell &
Burke, 2002; Lovell, Echemendia, & Burke, 2004), by
numerous colleges and high schools, and more recently
by automobile racing leagues such as the Competitive
Automobile Racing League and the Indianapolis
Racing League (Olvey, 2002). This scale has been a de
pendent measure in several published studies (e.g., Col
lins et al., 2003; Iverson, Gaetz, Lovell, & Collins,
2004a, 2004b; Lovell et al., 2003; Lovell, Collins et al.,
2004). The scale is presented in Figure 1.
The PCS was developed to provide a formal method
of documenting post- concussion symptoms, as per
ceived and reported by the athlete. In particular, the
goal in developing this scale was to more objectively
document the often highly subjective symptoms re
ported by athletes following concussion by assigning
numeric values to each symptom. This scale was devel
oped to provide an adjunct to other tools such as
neuropsychological testing. Symptom items were
based on earlier experience gathering symptom data
Figure 1. Post-Concussion Scale.
from the Pittsburgh Steelers and later from thousands of
amateur and professional athletes. Scale items were
constructed to reflect actual player reports rather than
medical jargon. For instance, the term fogginess was
employed based on the recurrent report of this symp
tom by concussed athletes. The original scale was
based on a 7-point Likert scale with 0 and 6 reflecting
the anchor points. The written instructions that accom
pany the scale request the athletes to report symptoms
based on the severity of each symptom that day. The
scale is currently available in paper form through the
senior author at no cost and has also been incorporated
into the ImPACT computerized neuropsychological
program (Lovell et al., 2003; Lovell, Collins et al.,
2004; Maroon et al., 2000). The scale has also been
suggested as a management tool by other organizations
as well (Aubry et al., 2002).
Descriptive Statistics and
Normative Data
Descriptive statistics and psychometric analyses are
provided in Table 1. The mean, median, standard devia-
tion, range, skewness, and kurtosis of total scores for
each sample are presented. As seen from the measures
of central tendency (mean and median), skewness, and
the ranges, the distributions of total symptom scores are
clearly skewed. That is, a large percentage of athletes
score between zero and three points at baseline testing.
The distribution of scores for the concussed athletes is
not severely skewed; it is much more evenly distrib
There was no significant difference in total symptom
scores between the high school students and the univer
sity students (M = 5.31, SD = 9.21, and M = 5.28, SD =
8.36, respectively). However, there was a significant
difference between men and women in both samples.
That is, the young women reported more symptoms
than the young men in the high school (p < .03, Cohen’s
d = .33, small–medium effect size) and the university
sample (p < .001, d = .43, medium effect size). In the
concussed sample, there was no significant difference
in total symptom scores between high school athletes
and university athletes (M = 24.4, SD = 19.5, and M =
20.7, SD = 21.7, respectively). In addition, there was no
significant difference in total scores for young men ver
sus young women (M = 23.3, SD = 19.4, and M = 27.9,
SD = 22.6, respectively), although there was a trend to
wards greater symptom reporting in women.
Given that there were no significant differences be-
tween high school students and university students,
normative data for the PCS are presented by gender. As
previously noted, the distributions of total scores are
skewed because healthy young people tend to report
few symptoms on this scale. With this degree of skew,
forced-normalization of the distributions will (a) distort
the true nature of the construct being measured, that is,
healthy young people’s total symptoms are not nor-
mally distributed in the population; and (b) result in in
Table 1.
Descriptive and Psychometric Analyses for Concussion Symptom Reporting at Baseline and Postconcussion for High School and
College Men and Women Athletes
N M Mdn SD Range Skew Kurtosis Alpha
High school
Young men 588 4.8 2 7.9 0–54 2.8 9.7 .89 2.62 3.35
Young women 119 7.7 3 13.7 0–78 3.1 10.8 .94 3.36 4.30
Young men 803 4.5 2 7.5 0–56 2.9 10.6 .88 2.60 3.33
Young women 236 8.0 5 10.3 0–55 2.1 5.2 .88 3.57 4.57
Combined sample
Young men 1,391 4.6 2 7.7 0–56 2.9 10.2 .88 2.66 3.40
Young women 355 7.9 4 11.5 0–78 2.7 9.2 .91 3.46 4.43
Athletes with concussions
Young men 217 23.3 19 19.4 0–94 1.1 .8 .93 5.13 6.57
Young women 43 27.9 23 22.4 0–82 .8 –.3 .92 6.34 8.12
Combined sample 260 24.0 19 20.0 0–94 1.0 .5 .93 5.29 6.77
Note. The statistics presented in this table are stratified by concussion status, level of competition, and gender.
Cronbach’s Unstandardized Alpha; this represents the lower bound of reliability.
Standard error of measurement.
.80 and confidence interval.
creased interpretation error. Therefore, the natural dis
tribution of scores was examined, and classification
ranges were created that reflect proportions of norma
tive subjects. Classification descriptors were created
that reflect raw score ranges and percentile rank ranges
in the natural distribution of scores. For example, in Ta
ble 2, 42% of young men obtained a total score of zero
on the scale. Thus, a score of zero would be considered
“Low–Normal”. In contrast, 89% scored 12 or less, so
only 11% scored 13 or higher. Thus, scores between 13
and 26 are considered “Very High. The percentile rank
values represent the percentage of students who scored
at the lower and upper bound of that raw score range.
For the “Very High” range, 91% of young men scored
13 or less and 97% scored 26 or less; therefore, scores
above 26 are considered “Extremely High.
As seen in Table 3, young women report more symp
toms than young men. Approximately 28% obtained a
score of zero. The “Broadly Normal” range is from 1 to
9 points, and the “Borderline” range is from 10 to 20
points. Ninety percent of young women scored 20 or
less on the scale.
As seen in Table 1, the concussed athletes have high
total scores for the PCS. The breakdown of concussed
athletes into the total score normative classification
ranges is provided in Table 4. The percentages of the
normative sample that fall in each classification range
are presented for comparison. Combining the two low-
est classification ranges provides a “Broadly Normal”
range of total scores. For the normative sample, 74% of
young men and 73% of young women fell in this range.
In contrast, 21% of concussed young men and approxi
mately 26% of concussed young women fell in this
range. If the “Very High” and “Extremely High” classi
fication ranges are combined, 10% of healthy young
men and 9% of healthy young women fell in this com
bined category. In contrast, 67% of concussed young
men and 51% of concussed young women fell in this
combined category.
Scale Reliability
Reliability can be viewed as the ability of an instru-
ment to reflect an individual score that is minimally in-
fluenced by error. Reliability should not be considered
a dichotomous concept, rather it falls on a continuum.
One cannot say an instrument is reliable or unreliable,
but more accurately should say it possesses a high or
low degree of reliability for a specific purpose, with a
specific population (Franzen, 2000).
An important aspect of reliability is internal consis
tency. Internal consistency can be estimated using
Cronbach’s alpha (Cronbach, 1951). Alpha is believed
to represent the lower bound for the true reliability of
the scale and is influenced by the number of items on
the scale, the average inter-item covariance, and the av
erage item variance (SPSS, 1998).
As seen in Table 1, internal consistency reliability of
the PCS ranged from .88 to .94 across the various sam
ples of healthy high school and college students in this
study. The standard error of measurement (SEM) is
considered an estimate of measurement error in a per
son’s observed test score. SEMs for the different groups
also are presented in Table 1. These SEMs were used to
create confidence intervals. A confidence interval rep
resents a range or band of scores, surrounding an ob
served score, in which the individual’s true score is be
Table 2.
Classifications, Raw Scores, and Percentile Ranks
Based on a Sample of 1,391 Healthy Young Men
Raw Scores Percentile Ranks
Low–normal 0 42
Broadly normal 1–5 49–74
Borderline 6–12 77–89
Very high 13–26 91–97
Extremely high 27+ 98
Table 3. Classifications, Raw Scores, and Percentile Ranks
Based on a Sample of 355 Healthy Young Women
Raw Scores Percentile Ranks
Low–normal 0 28
Broadly normal 1–9 35–73
Borderline 10–20 76–90
Very high 21–43 91–97
Extremely high 44+ 98
Table 4. Percentage of Normative Participants and Concussed
Athletes Falling in Each Classification Range
Normative Sample Concussed Sample
Low–normal 42 28 6.5 2.3
Broadly normal 32 45 14.7 23.3
Borderline 15 17 11.5 23.2
Very high 8 7 32.7 25.6
Extremely high 2 2 34.6 25.6
lieved to fall. For young men, the 80% confidence
interval for the total score was ±3.4 points. For young
women, the 80% confidence interval was ±4.4 points
(i.e., the SEM multiplied by a z-score of 1.28).
For the concussed athletes, the internal consistency
of the PCS was very high (r = .93). The standard error
of measurement is 5.3 points, and the 80% confidence
interval is 6.8 points.
Individual Symptom Reporting
The frequencies of individual symptom endorse
ment by level of severity for the concussed athletes are
presented in Table 5. The most frequently endorsed
symptoms, at a severity of mild or greater, were as fol
lows: headaches, fatigue, feeling slowed down, drowsi
ness, difficulty concentrating, feeling mentally foggy,
and dizziness. These individual symptoms were en
dorsed by 60–79% of the sample. The least frequently
endorsed symptoms were nervousness, feeling more
emotional, sadness, numbness or tingling, and vomit-
ing. These individual symptoms were endorsed by less
than 25% of the sample.
A sample of 52 concussed athletes was evaluated
three times, within 72 hours (M = 1.4 days), between 4
and 8 days (M = 5.6 days), and between 7 and 30 days
(M = 11.7 days). Forty-seven of these athletes were men
and only 5 were women. Therefore specific data by
gender are not presented in this current study. As seen
in Figure 2 and Table 6, there was a linear decrease in
total symptoms reported across the three intervals. Dur
ing the first time period, subjects reported numerous
symptoms. By the third time period, their symptom re
porting was essentially normal. However, as seen by the
error bars, there is considerable variability in symptom
reporting within each time period. A small percentage
of athletes were still quite symptomatic at the third time
interval. At 11 days, 15% scored greater than 10 points
and 10% scored greater than 17 points. Notably, the sig
nificant minority of athletes reporting high levels of
symptoms at 11 days probably reflects a selection bias,
given that symptomatic athletes are more likely to be
seen in follow-up on a third occasion.
The distributions of difference scores were exam
ined to determine if there was a consistent trend toward
improvement across all participants. From Time 1 to
Time 2, 90.4% of the participants reported fewer symp-
toms. From Time 1 to Time 3, 92.3% reported fewer
symptoms. From Time 2 to Time 3, 84.6% reported the
same or fewer symptoms. Therefore, for the vast major-
Table 5.
The Frequencies of Symptom Endorsements for the Post-Concussion Scale in Concussed Athletes
Mild Moderate Severe
None 1 2 3 4 5 6
Headache 21.5 14.6 16.5 18.5 15.0 11.2 2.7
Fatigue 30.8 21.5 12.3 11.9 13.1 6.9 3.5
Feeling slowed down 33.1 19.6 20.0 14.6 6.9 3.8 1.9
Drowsiness 33.8 18.8 15.0 10.8 11.2 6.5 3.8
Difficulty concentrating 34.2 16.9 15.0 18.1 8.1 6.2 1.5
Feeling mentally “foggy” 37.7 18.1 16.2 15.8 5.4 4.6 2.3
Dizziness 38.8 20.4 20.8 10.0 6.2 3.1 0.8
Difficulty remembering 45.0 20.0 18.1 5.4 5.8 4.6 1.2
Sensitivity to light 46.2 16.2 13.1 9.2 4.2 8.1 3.1
Balance problems 50.8 21.2 14.2 9.6 2.7 1.5
Nausea 53.8 21.9 12.3 8.1 2.7 1.2
Sensitivity to noise 54.2 15.0 8.5 8.1 7.3 6.5 0.4
Irritability 61.2 11.2 14.6 6.5 2.7 1.9 1.9
Trouble falling asleep 65.4 8.1 8.5 6.2 6.9 2.7 2.3
Sleeping more than usual 66.2 8.5 6.2 6.2 7.3 3.5 2.3
Visual problems 70.4 11.5 6.9 6.9 1.9 2.3
Sleeping less than usual 75.0 6.2 6.2 4.2 2.7 4.6 1.2
Nervousness 78.8 9.6 6.5 1.9 1.9 1.2
Feeling more emotional 82.3 7.7 2.7 5.8 0.8 0.8
Sadness 85.0 6.2 4.2 2.3 1.5 0.8
Numbness or tingling 85.4 7.7 2.7 3.5 0.8
Vomiting 91.2 6.2 2.3 0.4
Note. N = 260.
ity of athletes, there was steady improvement across the
test intervals. Worsening in symptoms was very un
common across these time intervals. From Time 1 to
Time 2, only one participant (2%) reported a worsening
by 5 or more points. From Time 1 to Time 3, 3 partici-
pants (5.8%) reported a worsening by 5 or more points.
From Time 2 to Time 3, 4 participants (i.e., 7.7%) re-
ported a worsening by 5 or more points.
Preliminary psychometric data and information re-
garding the clinical interpretation of the PCS has been
previously reported (Iverson & Gaetz, 2004; Iverson,
Lovell, & Collins, 2003). This article provides com-
prehensive normative data and additional psycho-
metric data for the inventory. This scale was originally
developed to provide information to athletes, physi-
cians, and athletic trainers regarding post-concussive
symptoms and their resolution over time. Although
the normative and psychometric work that has been
completed thus far has been limited to the English
language version, this inventory is currently available
in Spanish, French, Russian, and Czech, and research
studies are underway to study its utility in other cul
tural groups.
The measurement of subjective symptoms repre
sents an important component in the evaluation of the
concussed athlete. Resolution of post-concussion
symptoms, in combination with normal neuro
psychological test results, is generally regarded as a re
quirement for return to play (Aubry et al., 2002;
Echemendia & Cantu, 2003). Although all self-report
scales are subjective in nature, it is hoped that the inves
tigation of psychometric properties of this scale will
provide clinicians and researchers with additional in
formation regarding the significance of symptom re
porting following sports-related concussion.
The internal consistency reliability of the PCS is
very high in healthy and concussed adolescents and
young adults. There is no baseline or post-concussion
difference in total symptom scores between high school
students and university students. There is a difference,
Figure 2. Total symptoms reported at approximately 1, 5, and 11 days post injury (N = 52). The bars represent the mean and the error
bars represent one standard deviation. Median scores were 26, 8, and 1 for the three time periods, respectively.
Table 6.
The Frequencies of Serial Symptom Endorsements for
the Post-Concussion Scale in Concussed Athletes
Time 1 Time 2 Time 3
Headache 88.5 61.5 32.7
Difficulty concentrating 82.7 51.9 23.1
Feeling slowed down 78.8 40.4 19.2
Dizziness 78.8 30.8 17.3
Nausea 77.3 21.2 15.4
Fatigue 76.9 50.0 21.2
Feeling mentally “foggy” 75.0 46.2 19.2
Drowsiness 73.1 48.1 17.3
Difficulty remembering 69.2 50.0 23.1
Sensitivity to light 57.7 40.4 17.3
Balance problems 55.8 26.9 11.5
Sensitivity to noise 50.0 40.4 15.4
Trouble falling asleep 45.0 25.0 15.4
Irritability 38.5 36.5 11.5
Sleeping more than usual 34.6 28.8 9.6
Visual problems 32.7 19.2 7.7
Sleeping less than usual 30.8 15.4 7.7
Nervousness 30.8 15.4 7.7
Feeling more emotional 19.2 11.5 7.7
Sadness 19.2 7.7 5.8
Numbness or tingling 15.4 7.7 1.9
Vomiting 11.5 7.7 1.9
Note. N = 52.
however, in baseline symptom reporting between
young men and young women; healthy young women
tend to report more symptoms. Therefore, normative
data for the PCS were provided by gender (see Tables 2
and 3). It is interesting to note that although the samples
of men and women differed with regard to report of
symptoms at baseline, these differences were not sig
nificant following injury. However, there was a trend to
wards greater symptom reporting in the group of
women. In another recent study, Broshek, Kaushik,
Freeman, Erlanger, Webbe, and Barth (2005) did find
significantly higher post-injury symptom reporting in a
group of high school and collegiate women athletes,
compared to a group of men. Therefore, this issue con
tinues to warrant further exploration.
An advantage of the PCS is that it is a “state” mea
sure of perceived symptoms. It is designed to provide
an estimate of symptoms experienced on that day. As
such, it can be used over short retest intervals (in con
trast to other scales which require the respondent to rate
symptoms over the past week, 2 weeks, month, or in
general). As a state measure, however, the scale can re-
flect an unusually good or unusually bad day for the
athlete, which might mislead the clinician. This can
occur during the preseason evaluation or during
post-injury evaluations. Moreover, people with depres-
sion, anxiety, life stress, or pain report very similar
symptoms. Potential comorbid factors or frank differ-
ential diagnoses influencing symptom reporting are es-
sential to consider in athletes with protracted recovery
periods. The authors have seen athletes with presumed
slow recoveries from concussions whose primary prob
lem several months post-injury was a pre-existing anxi
ety disorder that appeared to be mimicking a post
concussion syndrome. The PCS is simply a tool that
can be used to quantify symptoms; it should not be used
in isolation. Rather it should be used within the context
of a thorough clinical evaluation.
One limitation of this study is that we did not con
duct a direct comparison of the concussed group who
were tested three times post-injury with a non-injured
control group who also underwent multiple assess
ments. The addition of this component to future studies
would help to determine variability in symptom report
ing in non-injured (“normal”) athletes. In addition,
through future studies we intend to examine the factor
structure of the scale and determine whether reliable
subscales can be identified. If so, these subscales will
be normed. In addition, we will evaluate the reliability
of the subscales and provide information regarding how
to interpret statistically reliable and clinically meaning
ful change.
A portion of this study was presented at the Interna
tional Neuropsychological Society, Honolulu, Hawaii
in February of 2003.
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... A widely used self-report measure of symptoms following mTBI is the Post-Concussion Symptom Scale (PCSS) [31]. Although it is a reliable and valid measure of PPCS [32,33], the vast and heterogeneous nature of PPCS makes diagnostic specificity challenging. In fact, PPCSlike symptoms are also seen following trauma without brain injury [34], as well as in healthy individuals [35,36]. ...
... Standard Deviation (SD) = 3.72) with an average of 12.63 years of education (range = 12-17 years, SD = 1.25); who were divided into high (n = 19) and low (n = 21) PCSS groups. Based on normative data published by Lovell, Iverson [32], participants were high PCSS scorers if their score was >27 (males) and >44 (females), and these scores were considered to be in the 98th percentile. Participants were low scorers if their score was <5 (below the 74th percentile) and considered broadly normal. ...
... Details regarding the normative database can be accessed at Thatcher, Walker [83] and Thatcher, Walker [84]. The Brodmann areas (BA) comprising each network were preselected by the software program as follows; DMN: bilateral BA 2,7,10,11,19,29,30,31,35,39,40; SN: bilateral BA 8,9,10,13,22,23,24,25,29,30,31,32, 33; FPN: bilateral BA 1,2,3,5,7,8,9,10,39,40,45,46. The degree of brain activation was represented by z scores across all frequencies from 1 to 30 Hz, for each Brodmann area (current source density; CSD), and the degree of connectivity (instantaneous coherence; IC, lagged co-herence; LC, and phase difference; PD) between each pair of Brodmann areas, within the networks of interest. ...
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.
... For PCS assessment in children and adolescents, the CDE recommendations [19] propose the use of the Post-Concussion Symptom Inventory (PCSI) [20,21]. The PCSI is available in age-adjusted pre-TBI and post-TBI forms for children (aged 8-12 years; PCSI-SR8) and adolescents (aged 13-17 years; PCSI-SR13) as well as in a proxy version (e.g., filled in by parents or caregivers) [21]. ...
... The PCSI [20,21] assesses PCS by asking the individuals after TBI to rate the intensity of symptoms relative to before the injury. The age-adapted PCSI-SR13 Rapid Version [21] comprises 21 items relating to symptom severity before (pre-injury) and after (post-injury) TBI forming three scales (cognitive, emotional, and somatic). ...
... This finding points away from the unidimensional structure of the German RPQ for adolescents and their proxies, which is consistent with the results of studies on the English RPQ and its translations in adults [28][29][30][31][32][33][34]. The comparability of the RPQ scores with concurrent PCS assessments was investigated based on the PCSI-SR13, which is an instrument that was itself adapted from the Post-Concussion Scale [20,70] specifically for the use in children and adolescents. Since the correlation between both tools was high for both the self-report and the proxy assessment, it can be concluded that the RPQ is capable of detecting PCS at least on a comparable level to the PCSI-SR13. ...
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The Rivermead Post-Concussion Symptoms Questionnaire (RPQ) assesses post-concussion symptoms (PCS) after traumatic brain injury (TBI). The current study examines the applicability of self-report and proxy versions of the German RPQ in adolescents (13–17 years) after TBI. We investigated reliability and validity on the total and scale score level. Construct validity was investigated by correlations with the Post-Concussion Symptoms Inventory (PCSI-SR13), Generalized Anxiety Disorder Scale 7 (GAD-7), and Patient Health Questionnaire 9 (PHQ-9) and by hypothesis testing regarding individuals’ characteristics. Intraclass correlation coefficients (ICC) assessed adolescent–proxy agreement. In total, 148 adolescents after TBI and 147 proxies completed the RPQ. Cronbach’s α (0.81–0.91) and McDonald’s ω (0.84–0.95) indicated good internal consistency. The three-factor structure outperformed the unidimensional model. The RPQ was strongly correlated with the PCSI-SR13 (self-report: r = 0.80; proxy: r = 0.75) and moderately–strongly with GAD-7 and PHQ-9 (self-report: r = 0.36, r = 0.35; proxy: r = 0.53, r = 0.62). Adolescent–proxy agreement was fair (ICC [2,1] = 0.44, CI95% [0.41, 0.47]). Overall, both self-report and proxy assessment forms of the German RPQ are suitable for application in adolescents after TBI. As proxy ratings tend to underestimate PCS, self-reports are preferable for evaluations. Only if a patient is unable to answer, a proxy should be used as a surrogate.
... The copyright holder for this preprint this version posted March 10, 2023. ; doi: bioRxiv preprint collected via the ImPACT Post-Concussion Symptom Scale (PCSS) 36 at each timepoint, and grouped into four symptom factors: cognitive, somatic, sleep, and affective 37 . ImPACT also creates four composite scores including reaction time, verbal memory, visual memory, and visual-motor speed and was administered at baseline, post-injury, and before clearance to begin return-to-play protocol (recovery) by clinicians in the Department of Athletics. ...
Full-text available
Concussions present with a myriad of symptomatic and cognitive concerns; however, the relationship between these functional disruptions and the underlying changes in the brain are not yet well understood. Hubs, or brain regions that are connected to many different functional networks, may be specifically disrupted after concussion. Given the implications in concussion research, we quantified hub disruption within the default mode network (DMN) and between the DMN and other brain networks. We collected resting-state functional magnetic resonance imaging data from collegiate student-athletes (n = 44) at three timepoints: baseline (prior to beginning their athletic season), acute post-injury (approximately 48 hours after a diagnosed concussion), and recovery (after starting return-to-play progression, but prior to returning to contact). We used self-reported symptoms and computerized cognitive assessments collected across similar timepoints to link these connectivity changes to clinical outcomes. Functional connectivity between regions within in the DMN increased from baseline to post-injury and decreased from post-injury to recovery. The relationship between functional connectivity and symptoms was stronger post-injury than at baseline and recovery. Similarly, the relationship between functional connectivity in the DMN and visual memory performance was stronger post-injury than at baseline and recovery. In addition, functional connectivity between DMN hubs and visual network non-hubs decreased from baseline to post-injury and increased from post-injury to recovery. The relationship between somatic symptoms and functional connectivity between DMN hubs and visual network non-hubs was also stronger post-injury. The relationship between visual memory performance and functional connectivity between DMN hubs and visual network non-hubs was also stronger post-injury. These results highlight a unique relationship between self-reported symptoms, visual memory performance and acute functional connectivity changes involving DMN hubs after concussion in athletes. This may provide evidence for a disrupted balance of within- and between-network communication highlighting possible network inefficiencies after concussion. These results aid in our understanding of the pathophysiological disruptions after concussion and inform our understanding of the associations between disruptions in brain connectivity and specific clinical presentations acutely post-injury.
... 5 A PCSI score 104 >9 was utilized as a minimal standard to ensure participants had not experienced spontaneous 105 recovery within the first 2 weeks following injury prior to enrollment. 21 Control participants 106 were recruited from the surrounding community (i.e., local high school athletes) to match the 107 general characteristics of the concussion group (Table 1). We excluded participants with co- were additionally excluded if they did not intend to return to sports following medical clearance. ...
Context: Reaction time (RT) is a critical element of return to participation (RTP), and impairments have been linked to subsequent injury following a concussion. Current RT assessments have limitations in clinical feasibility, and identification of subtle deficits after concussion symptom resolution. Objective: To examine the utility of RT measurements (clinical drop stick, simple stimulus-response, single-task Stroop, and dual-task Stroop) to differentiate between adolescents with concussion and uninjured control at initial assessment and RTP. Design: Prospective Cohort Study. Setting: Pediatric sports medicine center associated with a regional tertiary care hospital. Patients or other participants: Twenty-seven adolescents with a concussion (mean age=14.8±2.1 years; 52% female; tested 7.0±3.3 days post-concussion) and twenty-one uninjured controls (mean age=15.5±1.6 years; 48% female). Main outcome measure(s): Participants completed the Post-Concussion Symptoms Inventory (PCSI) and battery of RT tests: clinical drop stick, simple stimulus-response, single-task Stroop, and dual-task Stroop. Results: The concussion group demonstrated significantly slower clinical drop stick (β=58.8; 95% CI= 29.2, 88.3, p<0.001) and dual-task Stroop RT (β=464.2; 95% CI= 318.4, 610.0, p<0.001) at the initial assessment than uninjured controls. At the one-month follow-up, the concussion group demonstrated significantly slower clinical drop stick (238.9±25.9 vs. 188.1±21.7 ms; p<0.001; d=2.10), single-task Stroop (1527.8±204.5 vs. 1319.8±133.5 ms; p=0.001; d=1.20), and dual-task Stroop (1549.9±264.7 vs. 1341.5±114.7; p=0.002; d=1.04) RT than controls, while symptom severity was similar between groups (7.4±11.2 vs. 5.3±6.5; p=0.44; d=0.24). Classification accuracy and AUC values were highest for the clinical drop stick (85.1% accuracy, AUC= 0.86, p<0.001) and dual-task Stroop RT (87.2% accuracy, AUC=0.92, p<0.002) measures at initial evaluation. Conclusion: Adolescents recovering from concussion may have initial RT deficits which persist despite symptom recovery. Clinical drop stick and dual-task Stroop RT demonstrate high clinical utility given high classification accuracy, sensitivity, and specificity to detect post-concussion RT deficits, and may be considered for initial and RTP assessment.
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: Prior psychometric research has identified symptom subscales for the Post-Concussion Symptom Scale (PCSS) based on confirmatory factor analysis (CFA), including cognitive, physical, sleep-arousal, and affective symptom factors. Study objectives included: (1) replicate the 4-factor PCSS model in a diverse sample of athletes with concussion, (2) test the model for invariance across race, gender, and competitive level, and (3) compare symptom subscale and total symptom scores across concussed groups with established invariance. Setting: Three regional concussion care centers. Participants: A total of 400 athletes who completed the PCSS within 21 days of concussion (64% boys/men, 35% Black, and 69.5% collegiate athletes). Design: Cross-sectional. Main measures: A CFA tested the 4-factor model and measurement invariance testing was performed across racial, competitive level, and gender groups. Symptom subscales and total symptom severity scores were compared based on demographic groupings with established invariance. Results: The 4-factor model fit well and strong invariance was established across all demographic categories, indicating symptom subscales could be meaningfully compared across groups. Black and White athletes differed on total symptoms (U = 15 714.5, P = .021, r = 0.12), sleep-arousal symptoms (U = 15 953.5, P = .026, r = 0.11), and physical symptoms (U = 16 140, P = .051, r = 0.10), with Black athletes reporting slightly more symptoms. Collegiate athletes reported greater total symptom severity (U = 10 748.5, P < .001, r = 0.30), with greater symptom reporting on the cognitive (U = 12 985, P < .001, r = 0.21), sleep-arousal (U = 12 594, P < .001, r = 0.22), physical (U = 10 959, P < .001, r = 0.29), and emotional (U = 14 727.5, P = .005, r = 0.14) symptom subscales. There were no significant differences by gender in the total symptom score or subscale scores. After controlling for time since injury, no racial differences persisted, but a significant difference by competitive level in physical symptom reporting (F = 7.39, P = .00, η2 = 0.02) and total symptom reporting (F = 9.16, P = .003, η2 = 0.02) remained. Conclusion: These results provide external validation for the PCSS 4-factor model and demonstrate that symptom subscale measurements are comparable across race, genders, and competitive levels. These findings support the continued use of the PCSS and 4-factor model for assessing a diverse population of concussed athletes.
Objective: Assessment of post-concussion symptoms is implemented at secondary, post-secondary, and professional levels of athletics. Network theory suggests that disorders can be viewed as a set of interacting symptoms that amplify, reinforce, and maintain one another. Examining the network structure of post-concussion symptoms may provide new insights into symptom comorbidity and may inform targeted treatment. We used network analysis to examine the topology of post-concussion symptoms using the Post-Concussion Symptom Scale (PCSS) in high school athletes with recent suspected sport-related concussion. Method: Using a cross-sectional design, the network was estimated from Post Concussion Symptom Scale scores from 3,292 high school athletes, where nodes represented symptoms and edges represented the association between symptoms. Node centrality was calculated to determine the relative importance of each symptom in the network. Results: The network consisted of edges within and across symptom domains. "Difficulty concentrating" and "dizziness" were the most central symptoms in the network. Although not highly central in the network, headaches were the highest rated symptom. Conclusions: The interconnectedness among symptoms supports the notion that post-concussion symptoms are interrelated and mutually reinforcing. Given their central role in the network, "difficulty concentrating" and "dizziness" are expected to affect the activation and persistence of other post-concussion symptoms. Interventions targeting difficulties with concentration and dizziness may help alleviate other symptoms. Our findings could inform the development of targeted treatment with the aim of reducing overall symptom burden. Future research should examine the trajectory of post-concussion symptom networks to advance the clinical understanding of post-concussive recovery.
Objective: To determine whether sleep behavior (e.g., duration, timing) and/or physical activity (steps/day, or exercise frequency, duration, intensity) in the first month after adolescent sports-related concussion are associated with developing Persisting Post-Concussion Symptoms (PPCS). Design: Case-control SETTING: Outpatient sports medicine clinic PARTICIPANTS: We prospectively enrolled adolescent athletes who sustained a concussion (N=49, age=14.8±1.8 years; 51% female) who were evaluated within 14 days of concussion (mean=6.7±2.7 days) and followed via sleep/physical activity monitoring for the subsequent two weeks. Main outcome measures: Participants wore a monitor to track sleep (sleep time, wake time, and time spent awake in bed at night) and physical activity (average steps/day, exercise frequency, exercise duration) behavior for two weeks after initial assessment. Participants were followed until symptom resolution, and the main outcome interest was development of PPCS (symptom duration >28 days). We then used a multivariable logistic regression model to examine associations between physical activity and sleep behavior with PPCS. Results: Of the 49 participants, 47% (n=23, mean symptom resolution=57±23 days post-injury) developed PPCS and 53% (n=26, mean symptom resolution=15±7 days post-injury) did not. Univariable analysis showed that the PPCS group took fewer steps/day (7526±2975 vs. 9803±3786 steps/day; p=0.02), exercised less frequently (2.5±2.2 vs. 4.4±2.1 days/week; p=0.005), and spent more time in bed awake (1.2±0.3 vs. 0.8±0.3 hours/night; p=0.03) than the no PPCS group. Multivariable results indicated the odds of developing PPCS significantly increased with fewer exercise session/week (adjusted odds ratio=1.96, 95% confidence interval=1.09, 3.51, p=0.024). Conclusions: More exercise sessions that were >15 minutes in duration during concussion recovery was associated with a lower risk of developing PPCS, while sleep and other physical activity measures were not. Further studies regarding exercise duration and intensity are needed. Clinicians may consider advising patients to optimize sleep and physical activity during concussion recovery. This article is protected by copyright. All rights reserved.
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.
1. Preliminary Measurement Considerations in Clinical Neuropsychology. 2. General and Theoretical Considerations in the Assessment of Reliabilty. 3. Practical and Methodological. 4. Elemental Considerations in Validity. 5. Validity as Applied to Neuropsychological Assessment. 6. The Wechsler Adult Intelligence Scale-Revised and Wechsler Adult Intelligence Scale-III. 7.The Wechsler Intelligence Scale for Children-Revised and Wechsler Intelligence Scale for Children-III. 8. Test of General Intelligence. 9. The Halstead-Reitan Neuropsychological Battery and Luria-Nebraska Neuropsychological Battery. 10. Benton's Neuropsychological Assessment. 11. The Minnesota Multiphasic Personality Inventory. 12. The Rorschach Inkblots. 13. The Wechsler Memory Scale and its Revisions. 14. Tests of Memory. 15. Tests of Visual and Construction Function. 17. Tests of Higher Cognitive Function. 18. Screening Devices. 19. Tests of Aptitude and Achievement. 20. Methods for Evaluating the Validity of Test Scores. 21. The Assessment of Child Neuropsychological Function. Postscript. References.
Background Recent concussion management guidelines have suggested that athletes with mild (grade 1) concussions may be returned to play if asymptomatic for 15 minutes. The purpose of this study was to assess the utility of a current concussion management guideline in classifying and managing mild concussion. Hypothesis High school athletes diagnosed with a grade 1 concussion will demonstrate measurable decline in neuropsychological functioning that persists during the 1st week of recovery. Study Design Prospective study designed to evaluate neuropsychological functioning both prior to and following concussion. Methods Forty-three high school athletes completed neuropsychological test performance and symptom ratings prior to the season and at two times during the 1st week following mild concussion. Results Thirty-six hours after injury, mildly concussed high school athletes demonstrated a decline in memory (P < 0.003) and a dramatic increase in self-reported symptoms (P < 0.00001) compared to baseline performance. Conclusions Athletes with grade 1 concussion demonstrated memory deficits and symptoms that persisted beyond the context in which they were injured. These data suggest that current grade 1 return-to-play recommendations that allow for immediate return to play may be too liberal. Clinical Relevance A reconsideration of current concussion grading systems appears to be warranted.
Recommendations for the improvement of safety and health of athletes who may suffer concussive injuries In November 2001, the first International Symposium on Concussion in Sport was held in Vienna, Austria. This symposium was organised by the International Ice Hockey Federation (IIHF), the Federation Internationale de Football Association Medical Assessment and Research Centre (FIFA, F-MARC), and the International Olympic Committee Medical Commission (IOC). The aim of the symposium was to provide recommendations for the improvement of safety and health of athletes who suffer concussive injuries in ice hockey, football (soccer), and other sports. To this end a range of experts were invited to address specific issues of epidemiology, basic and clinical science, grading systems, cognitive assessment, new research methods, protective equipment, management, prevention, and long term outcome, and to discuss a unitary model for understanding concussive injury. At the conclusion of the conference, a small group of experts were given a mandate by the conference delegates and organising bodies to draft a document describing the agreement position reached by those in attendance at that meeting. For the purpose of this paper, this group will be called the Concussion in Sport Group (CISG). This review seeks to summarise the findings of the Vienna conference and to provide a working document that will be widely applicable to sport related concussion. This document is developed for use by doctors, therapists, health professionals, coaches, and other people involved in the care of injured athletes, whether at the recreational, elite, or professional level. During the course of the symposium, a persuasive argument was made that a comprehensive systematic approach to concussion would be of potential benefit to aid the injured athlete and direct management decisions.1 This protocol represents a work in progress, and, as with all other guidelines or proposals, it must undergo revision …
OBJECTIVE: To conduct a topic review of studies related to cerebral concussion in athletes, as an aid to improving decision-making and outcomes. METHODS: We review the literature to provide an historical perspective on the incidence and definition of and the management guidelines for mild traumatic brain injury in sports. In addition, metabolic changes resulting from cerebral concussion and the second-impact syndrome are reviewed, to provide additional principles for decision-making. Neuropsychological testing, as it applies to athletes, is discussed in detail, to delineate baseline assessments, the characteristics of the neuropsychological evaluation, the neuropsychological tests used, and the methods for in-season identification of cerebral concussion. Future directions in the management of concussions are presented. RESULTS: The incidence of cerebral concussions has been reduced from approximately 19 per 100 participants in football per season to approximately 4 per 100, i.e., 40,000 to 50,000 concussions per year in football alone. The most commonly used definitions of concussion are those proposed by Cantu and the American Academy of Neurology. Each has associated management guidelines. Concussion or loss of consciousness occurs when the extracellular potassium concentration increases beyond the upper normal limit of approximately 4 to 5 mmol/L, to levels of 20 to 50 mmol/L, inhibiting the action potential and leading to loss of consciousness. This phenomenon helps to explain the delayed effects of symptoms after trauma. CONCLUSION: Neuropsychological testing seems to be an effective way to obtain useful data on the short-term and long-term effects of mild traumatic brain injury. Moreover, knowledge of the various definitions and management strategies, as well as the utility of neuropsychological testing, is essential for those involved in decision-making with athletes with mild traumatic brain injuries.
A general formula (α) of which a special case is the Kuder-Richardson coefficient of equivalence is shown to be the mean of all split-half coefficients resulting from different splittings of a test. α is therefore an estimate of the correlation between two random samples of items from a universe of items like those in the test. α is found to be an appropriate index of equivalence and, except for very short tests, of the first-factor concentration in the test. Tests divisible into distinct subtests should be so divided before using the formula. The index [`(r)]ij\bar r_{ij} , derived from α, is shown to be an index of inter-item homogeneity. Comparison is made to the Guttman and Loevinger approaches. Parallel split coefficients are shown to be unnecessary for tests of common types. In designing tests, maximum interpretability of scores is obtained by increasing the first-factor concentration in any separately-scored subtest and avoiding substantial group-factor clusters within a subtest. Scalability is not a requisite.
The application of neuropsychological assessment procedures to the evaluation of athletes has recently become an area of intense interest and debate and has led to the development of research initiatives at both the amateur and the professional level. However, to date, only a handful of research studies have been completed that have addressed the special issues that accompany the use of neuropsychological assessment instruments with athletes. This article reviews the past use of psychological testing in sports and presents a model of neuropsychological assessment that is currently being utilized in the National Football League. In addition, the extension of this approach to major college football is discussed and test-retest data from a sample presented to provide the basis for comparison of athletes who have suffered a concussion. Recommendations of a national panel of neuropsychologists who are involved in the evaluation of athletes are presented in hopes of encouraging new research initiatives in this area.