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Castellanos FX, Lee PP, Sharp W, et al. Developmental Trajectories of Brain Volume Abnormalities in Children and Adolescents With Attention-Deficit/Hyperactivity Disorder. JAMA. 2002;288(14):1740–1748. doi:10.1001/jama.288.14.1740
Author Affiliations: Child Psychiatry Branch, National Institute of Mental Health (Drs Castellanos, Lee, Greenstein, Clasen, James, Giedd, and Rapoport, Mss Sharp and Ebens, and Messrs Blumenthal and Walter), Biostatistics Branch, National Institute of Neurological Disorders and Stroke (Dr Jeffries), National Institutes of Health, Bethesda, Md; and Montreal Neurological Institute, McGill University, Montreal, Quebec (Drs Zijdenbos and Evans). Dr Castellanos is now with the New York University Child Study Center, New York, NY.
Context Various anatomic brain abnormalities have been reported for attention-deficit/hyperactivity
disorder (ADHD), with varying methods, small samples, cross-sectional designs,
and without accounting for stimulant drug exposure.
Objective To compare regional brain volumes at initial scan and their change over
time in medicated and previously unmedicated male and female patients with
ADHD and healthy controls.
Design, Setting, and Participants Case-control study conducted from 1991-2001 at the National Institute
of Mental Health, Bethesda, Md, of 152 children and adolescents with ADHD
(age range, 5-18 years) and 139 age- and sex-matched controls (age range,
4.5-19 years) recruited from the local community, who contributed 544 anatomic
magnetic resonance images.
Main Outcome Measures Using completely automated methods, initial volumes and prospective
age-related changes of total cerebrum, cerebellum, gray and white matter for
the 4 major lobes, and caudate nucleus of the brain were compared in patients
Results On initial scan, patients with ADHD had significantly smaller brain
volumes in all regions, even after adjustment for significant covariates.
This global difference was reflected in smaller total cerebral volumes (−3.2%,
adjusted F1,280 = 8.30, P = .004) and
in significantly smaller cerebellar volumes (−3.5%, adjusted F1,280 = 12.29, P = .001). Compared with controls,
previously unmedicated children with ADHD demonstrated significantly smaller
total cerebral volumes (overall F2,288 = 6.65; all pairwise comparisons
Bonferroni corrected, −5.8%; P = .002) and
cerebellar volumes (−6.2%, F2,288 = 8.97, P<.001). Unmedicated children with ADHD also exhibited strikingly
smaller total white matter volumes (F2,288 = 11.65) compared with
controls (−10.7%, P<.001) and with medicated
children with ADHD (−8.9%, P<.001). Volumetric
abnormalities persisted with age in total and regional cerebral measures (P = .002) and in the cerebellum (P =
.003). Caudate nucleus volumes were initially abnormal for patients with ADHD
(P = .05), but diagnostic differences disappeared
as caudate volumes decreased for patients and controls during adolescence.
Results were comparable for male and female patients on all measures. Frontal
and temporal gray matter, caudate, and cerebellar volumes correlated significantly
with parent- and clinician-rated severity measures within the ADHD sample
(Pearson coefficients between −0.16 and −0.26; all P values were <.05).
Conclusions Developmental trajectories for all structures, except caudate, remain
roughly parallel for patients and controls during childhood and adolescence,
suggesting that genetic and/or early environmental influences on brain development
in ADHD are fixed, nonprogressive, and unrelated to stimulant treatment.
Attention-deficit/hyperactivity disorder (ADHD), the most common childhood
psychiatric disorder, is thought to reflect subtle abnormalities in central
nervous system functioning.1 For this reason,
ADHD is being studied increasingly with a variety of brain imaging techniques
throughout the life span. Magnetic resonance imaging (MRI) is particularly
suitable for the study of pediatric patients, providing high-resolution images
without ionizing radiation. Previous MRI neuroimaging studies, most with small
samples, have reported smaller anatomic areas and/or volumes in patients with
ADHD in regions of the corpus callosum,2-6 smaller
volumes and/or hypoactivation of prefrontal brain,7-11 basal
a recent study noted inconsistencies in the ADHD neuroimaging literature and
concluded that specific abnormalities have not yet been convincingly demonstrated.19
Although we previously conducted anatomic studies in male (n = 112)20 and female (n = 100)16 patients
with ADHD and controls, we were unable to rigorously contrast or combine the
2 sets of findings because the original measurement techniques used were no
longer available. Moreover, we have continued to recruit new patients, including
a sizable number of patients who had never been previously exposed to psychotropic
The present study was designed to examine brain anatomy using the same
automated measures from cross-sectional scans of a large sample of male and
female patients with ADHD, determine the effect of prior stimulant drug exposure
on anatomic abnormalities in ADHD, and examine brain regional longitudinal
growth trajectories in patients and controls.
We hypothesized that patients with ADHD would have smaller brain regional
volumes, particularly in caudate nucleus,8,13 cerebellum,16-18 and frontal lobe8,9; previously unmedicated children and
adolescents with ADHD would demonstrate similar brain abnormalities as medicated
patients16; and caudate anatomic abnormalities
would diminish with age. Examination of age-related changes in other brain
regions was exploratory.
A total of 89 male (mean initial age, 10.5 years; range, 5.1-18.4) and
63 female (mean initial age, 9.4; range, 5.3-16.0) children and adolescents
with Diagnostic and Statistical Manual of Mental Disorders,
Fourth Edition (DSM-IV21)–defined
ADHD were recruited from the surrounding community. Inclusion criteria were:
hyperactive, inattentive, and impulsive behaviors that were impairing in at
least 2 settings and a Conners' Teacher Hyperactivity rating greater than
2 SD above age- and sex-specific means.22,23 The DSM-IV diagnosis of ADHD was based on the Parent Diagnostic
Interview for Children and Adolescents,24 Conners'
Teacher Rating Scales,22,23 and
the Teacher Report Form.25 A clinical psychologist
administered the Wechsler Intelligence Scale for Children–Revised26 to 110 patients with ADHD and the Wechsler Intelligence
Scale for Children–III27 to 41 patients
(1 was too young to be tested). Exclusion criteria were a full-scale IQ of
less than 80, evidence of medical or neurological disorders on examination
or by clinical history, Tourette disorder, or any other axis I psychiatric
disorder requiring treatment with medication at study entry.
A total of 56 unrelated healthy female (mean initial age, 10.0 years;
range, 5.2-16.1) and 83 male (mean initial age, 10.9; range, 4.5-19.0) controls
were recruited from the community via the National Institutes of Health Normal
Volunteer Office and outreach to local schools. Screening included an initial
telephone interview, parent and teacher rating scales,25 in-person
assessment including physical and neurological examinations including handedness,28 and clinical history obtained by a child and adolescent
psychiatrist (J.N.G.). Vocabulary and block design subtests from the Wechsler
Intelligence Scale for Children–Revised (n = 80), Wechsler Intelligence
Scale for Children–III (n = 23), Wechsler Abbreviated Scale of Intelligence29 (n = 20), Wechsler Preschool and Primary Scale of
Intelligence30 (n = 10), and Wechsler Adult
Intelligence Scale–Revised31 (n = 1)
were obtained. Five controls were not tested but were within the healthy range
by reported academic history. Approximately 4 candidates were screened for
every 1 accepted,32 with the most common exclusions
being positive family psychiatric history and possible psychiatric diagnosis
based on teacher report.
This study was conducted at the Child Psychiatry Branch of the National
Institute of Mental Health in Bethesda, Md, between 1991 and 2001. The institutional
review board approved the research protocol, and written informed consent
and assent to participate in a study of brain development were obtained from
parents and children, respectively, at study entry and at each subsequent
MRI examination. Healthy volunteers and patients not currently participating
in treatment studies were paid to participate.
Primary symptom severity measures were those that remained constant
across the study decade using the Attention Problems Factors from the Child
Behavior Checklist and Teacher Report Form25 and
the Clinical Global Impressions scale for Severity of Illness.33 Medication
status was obtained from parental history.
All patients and controls were studied on the same 1.5-T General Electric
Signa scanner (Milwaukee, Wis). T1-weighted images with contiguous 1.5-mm
slices in the axial plane and 2.0-mm slices in the coronal plane were obtained
using 3-dimensional spoiled gradient recalled echo in the steady state. Imaging
parameters were echo time of 5 ms, repetition time of 24 ms, flip angle of
45°, acquisition matrix of 256 × 192, number of excitations equals
1, and 24 cm field of view. Head placement was standardized as previously
T2-weighted images were obtained for evaluation by a clinical neuroradiologist.
All raters were blind to demographic characteristics. Quantification of MRI
images was performed via a 3-part fully automated image analysis process that
determines the volumes of gray and white matter compartments in frontal, temporal,
parietal, and occipital lobes as well as basal ganglia and cerebellum with
excellent test-retest reliability as described elsewhere in detail.34-36
Visual inspection of each scan revealed that 544 of 594 total scans
(92%) were processed successfully; 50 were excluded because of classification
and segmentation errors due to motion. Failure rate was significantly higher
(χ21 with Yates correction = 4.08, P = .04) in 34 of 317 patients (11%) than in 16 of 277 controls (6%).
All remaining scans from patients with ADHD (283 scans) were used. The comparison
group was selected from a pool of healthy controls after excluding siblings
in order not to violate the statistical assumption of independence. The remaining
139 potential controls (ie, no more than 1 per family within the age range
of our patients) were selected by the data manager (L.S.C.) to best match
each target patient for sex, age, and longitudinal intervals, prior to morphometric
analyses. Whenever precise matching on all parameters was not possible, patients
and controls were matched on average-age across their own scans. Because we
were unable to match all patients and controls 1-to-1, we made every effort
to maintain proportional scan-densities across the entire age-range of the
Demographic and clinical measures were compared by 2-way analyses of
variance (testing main effects of diagnoses and sex and their interaction)
or 2-sample t tests for continuous measures, and
with χ2 or Fisher exact test for nominal measures. Analyses
of variance of the 10 regional brain measures and 3 summary measures obtained
at initial scan (n = 291 independent participants) were initially performed
with diagnoses and sex as between-participant factors. Because we did not
obtain full-scale IQ scores from controls, Wechsler vocabulary standard score
was used, as it is the single best predictor of full-scale IQ.27 To
account for between-group differences in vocabulary, height, weight, handedness,
and medication status, analyses of covariance were performed with these potential
covariates. Nonsignificant covariates were deleted from the final models.
Pearson correlations were computed for symptom severity measures and brain
volumes in the patient sample.
To examine the influence of medications more closely we compared patients
with ADHD who were never previously treated with psychotropic medications
(unmedicated ADHD), medicated patients (medicated ADHD), and controls. The
unmedicated ADHD patients were significantly younger than the medicated ADHD
and controls; thus, we confirmed findings in age-matched subgroups (n = 128).
All pairwise comparisons were conducted with Bonferroni corrections.
Finally, longitudinal analytic methods37,38 were
used to examine growth patterns of caudate, cerebellum, total cerebrum, and
the white and gray components of the 4 major lobes. The initial full longitudinal
growth model was expressed as a cubic:
The model parameters (intercept and β coefficients) were initially
allowed to reflect interactions between sex and diagnostic group. To account
for within-person correlations, intercepts were treated as normally distributed
random effects that varied by individual, while β coefficients for age,
age-squared, and age-cubed terms were modeled as fixed effects. The full cubic
model was compared with simpler quadratic, linear, and constant models with
interactions. Once the order of the model was established, testing was performed
to determine whether an additive model could replace the interactions between
sex and diagnostic group for the height and shape parameters of the curves.
With respect to shape of the curves, there were neither significant sex differences
nor sex by diagnosis interactions for any structure. Consequently, final models
allowed for sex and diagnosis effects in the height parameters (intercept)
of the curves and included only diagnostic differences in shape parameters.
Hypothesis tests and model selection were based on F statistics. We
included data from individuals who had only a single scan (about 40% of both
groups), because single scans provide additional information about between-participant
variation and overall curve shape. These methods have been useful for combining
cross-sectional and longitudinal anatomic MRI data.39-41 Statistical
power exceeded 80% at P = .05 for all brain measures.
Minimally detectable adjusted differences ranged from 2.7% (caudate and cerebellum)
to 5% for occipital gray matter, and averaged 3% for cortical volumes. Statistical
analyses were performed using SPSS version 10.0 (SPSS Inc, Chicago, Ill),
except for the mixed-model random regression analyses, which were performed
with SAS version 8.02 (SAS Institute Inc, Cary, NC), and the power analyses,
which were conducted with PASS 2000 (NCSS Statistical Software, Kaysville,
Utah). Two-tailed significance levels were defined as P≤.05.
Final study participants consisting of 152 children and adolescents
with ADHD and 139 controls were each successfully scanned up to 4 times over
a decade. As Table 1 shows, there
were several group differences between male and female patients (females were
younger, shorter, and weighed less), and between patients and controls. Patients
were shorter and weighed less, had lower vocabulary standard scores, and a
lower percentage of individuals were strongly right-handed (scoring 10 or
more of 12 items). Sex and diagnosis did not interact significantly for any
demographic measure. Female and male patients with ADHD were comparable on
vocabulary, handedness, parent and teacher attention problem scores, and prevalence
of learning disorders.42 Physician's Clinical
Global Impressions ratings reflected significantly greater severity in females,
who also had a higher percentage of combined-type ADHD, mood disorder (history
of major depression and/or dysthymia) and lower prevalence of conduct disorder
and tic disorder not otherwise specified. At the time of the first scan, 103
patients (68%) were being treated with psychostimulants.
The 49 patients with ADHD (22 females) who were successfully scanned
before ever being treated with psychotropic medications (unmedicated ADHD)
were significantly younger than the medicated patients (medicated ADHD) and
controls (Table 2). Unmedicated
patients with ADHD were rated as comparable in severity by parents, but as
significantly less severely affected by physicians and teachers. They also
tended to score higher on the vocabulary IQ subtest, but not significantly
(P = .06).
Sixty-one patients (40%) were scanned once, 61 (40%) twice, 20 (13%)
3 times, and 10 (7%) 4 times. Fifty-two controls (37%) were scanned once,
55 (40%) twice, 29 (21%) 3 times, and 3 (2%) 4 times. Mean ages at each scan
did not differ significantly between diagnostic groups (at first scan, F1,289 = 2.28, P = .13; at second scan, F1,176 = 0.08, P = .78; at third scan, F1,60 = 0.02, P = .89; at fourth scan, F1,11 = 1.06, P = .32). Female participants
(mean, 9.7 years [SD, 2.6]) were significantly younger than male participants
(mean, 10.7 years [SD, 3.3]; P = .006), regardless
of diagnosis. Mean intervals between scans did not differ significantly between
diagnostic groups (mean for patients with ADHD, 2.6 years [1.1]; mean for
controls, 2.4 years [1.0]; T229 = 1.60; P =
Table 3 contains the unadjusted
means (SDs) of the 291 initial cross-sectional scans by diagnosis as well
as the means (SEs) adjusted for all significant covariates. Three summary
measures were obtained for the cerebrum, defined by excluding cerebellum,
brainstem, and cerebrospinal fluid.
As expected,43,44 all measures
were significantly smaller in female participants (F1, 287 ranged
from 10.65 for parietal gray matter to 98.61 for cerebellum; P<.001), but sex did not interact significantly with diagnosis for
any brain anatomy measure. Accordingly, mean values for sex and corresponding
statistics are not presented here (they can be found at http://intramural.nimh.nih.gov/research/chp/index2.html). A significant main effect of diagnosis was found between patients
with ADHD and controls for all measures with small-to-medium effect sizes
ranging from 0.30 to 0.46, which remained significant or were somewhat enhanced
(eg, adjusted effect size for temporal white matter = 0.64) when adjusted
for the significant covariates of vocabulary, height, or medication status.
When we adjusted for the significant group differences in total cerebral volume,
the only brain region that remained significantly smaller in ADHD was the
cerebellum (d = .27; 95% confidence interval [CI], 0.03-0.50; F1,287 = 4.97; P = .03).
Table 4 displays the contrasts
between 3 nonoverlapping groups consisting of 49 unmedicated patients with
ADHD, 103 medicated patients with ADHD, and 139 healthy controls. Unmedicated
patients with ADHD did not differ significantly from medicated patients with
ADHD on any gray matter measures, or in caudate or cerebellum. By contrast,
unmedicated patients with ADHD had strikingly smaller white matter volumes
(F2,288 = 11.65) compared with controls (−10.7%, P<.001) and with medicated children with ADHD (−8.9%; P<.001; all pairwise comparisons Bonferroni corrected).
Unmedicated patients with ADHD had smaller cerebellar volumes (−6.2%, P<.001), smaller temporal gray (−4.6%, P = .02), and smaller total cerebral volumes (−5.8%, P = .002) compared with controls. Differences between unmedicated patients
with ADHD and controls in frontal (−3.8%) and parietal gray matter (−4.1%)
would also have been significant if not corrected for multiple comparisons.
Medicated patients with ADHD did not differ significantly from controls on
any white matter measure. Robust differences from controls remained for all
gray matter measures (ranging from −3.4% to −6.6%), caudate (−4.3%),
cerebellum (−3.6%), and the summary measures of total cerebral volume
(−3.3%) and total gray volume (−3.9%).
Because the unmedicated patients with ADHD were significantly younger
than the other 2 subgroups, and white matter increases with increasing age
throughout the age range,45 we performed secondary
analyses restricted to an age-matched subset of 128 participants (consisting
of 24 unmedicated patients with ADHD, 50 medicated patients with ADHD, and
54 controls [61 females]). All measures remained essentially unchanged.
We examined correlations between the 10 regional measures and behavioral
ratings. Within the patient group, smaller volumes were significantly correlated
in the expected direction with greater symptom severity. Frontal and temporal
gray matter, caudate, and cerebellar volumes were significantly and negatively
correlated with physician's Clinical Global Impressions rating (n = 139, Pearson
coefficients ranged between −0.16 for frontal gray and −0.26 for
cerebellum, all P<.05). The same 4 regions were
also significantly and negatively correlated with parent-rated child behavior
checklist attention problems with Pearson coefficients between −0.16
and −0.22 (all P<.05). Correlations were
largely unaffected when adjusted for age.
Wechsler vocabulary standard score was significantly and positively
correlated with all anatomic volumes in patients with ADHD (n = 151; r ranged from 0.19-0.35; all P<.02),
and in frontal and occipital gray and white matter and cerebellar volumes
in controls (n = 134; r ranged from 0.18-0.24; all P<.02). Although the magnitude of the correlations was
greater in patients than in controls, none of the coefficients differed significantly
from each other, and all regional volumes correlated significantly with the
vocabulary score when the 2 groups were combined (n = 285; eg, for total cerebral
volume, r = 0.31; P<.001).
Sixty percent of all participants had at least 2 scans (n = 178), including
62 (21%), who had at least 3 scans and 13 (4%), who had 4 scans obtained at
2- to 3-year intervals. Data from all 544 resulting scans were used to derive
longitudinal growth curves for patients and controls of both sexes. The age
range for male participants extended between 4.6 and 19.0 years, while female
participants ranged between 5.2 and 16.3 years, reflecting our initial focus
on males with ADHD.20
Predicted longitudinal growth curve parameters did not differ significantly
between male and female participants except for the height of each curve (intercept)
at the corresponding age midpoint, which were significantly higher for males
for all measures, regardless of diagnosis (empirical P<.001,
derived from F statistics confirmed with permutation tests with 1000 iterations).
There were no significant interactions between sex and diagnosis for any developmental
growth patterns (intercepts or curve parameters β1-3). Figure 1 shows the predicted developmental
growth curves along with 95% CIs for each group's average total cerebral volume.
Developmental curves were significantly higher in controls than in patients
with ADHD for total cerebral volume and for all other brain measures. Diagnostic
differences in curve height remained significant after adjusting for vocabulary
standard score (total cerebral volume, P = .002).
There were no significant differences in curve shape between patients and
controls, except for caudate. After adjustment for diagnostic differences
in total cerebral volume, only caudate (P = .02)
and cerebellum (P = .003) remained significantly
smaller in patients with ADHD.
Figure 2 depicts unadjusted
predicted growth curves for caudate nucleus and cerebellum. Caudate was the
only region in which the developmental trajectories did not remain statistically
parallel for patients and controls (adjusted, P =
.05). These differences in shape represent a normalization of caudate volume
for patients by midadolescence. By contrast, diagnostic differences in cerebellar
curves continue throughout our age range (unadjusted, P<.001; adjusted, P = .003), with a nonsignificant
tendency toward a greater difference in late adolescence (unadjusted, P = .10). The general absence of diagnostic differences
in curve shapes indicates that developmental curves for patients with ADHD,
although significantly lower, were essentially parallel to curves for healthy
controls, with the exception of the caudate nucleus.
Fully automated measures of brain cortical and subcortical volumes from
the initial scans of 291 male and female patients show that the cerebrum as
a whole and the cerebellum are smaller in children and adolescents with predominantly
combined-type ADHD. Rather than reflecting a selective frontal-striatal effect,
volumes were decreased to a comparable extent in all 4 lobes and were statistically
more prominent only in the cerebellum. Our findings were not ascribable to
differences in cognitive level, height, age, weight, or handedness and were
not related to comorbid diagnoses (data not shown).
This is the first neuroimaging study to our knowledge to include a substantial
number (n = 49) of previously unmedicated children and adolescents with ADHD.
We attempted to recruit children with equivalent severity of ADHD symptoms
by using identical diagnostic and symptom severity criteria. Unmedicated patients
with ADHD did not differ from medicated children with ADHD on parent-rated
attention problems, but they had significantly lower teacher and physician
ratings, and higher vocabulary standard scores. These differences should have
minimized anatomic brain differences between unmedicated patients with ADHD
and controls. In fact, findings were generally as striking for the unmedicated
patients with ADHD as for those who were being treated with medications, and
were more pronounced for white matter volumes. Thus, our analyses show that
decreased brain volumes in ADHD in both white and gray matter compartments
are not due to drug treatment. Conversely, we have no evidence that stimulant
drugs cause abnormal brain development.46
Patients with ADHD had developmental trajectories for nearly all brain
regions that paralleled growth curves for controls but on a lower track. The
one exception, foreshadowed by an earlier cross-sectional study,13 was
the caudate nucleus, for which differences between patients and controls became
negligible by midadolescence. As the caudate nucleus reaches its maximum volume
around 10 years, the potential relationship between normalization of caudate
volume in ADHD and decreased ratings of hyperactivity/impulsivity in children
with ADHD,47 as well as in quantitative measures
of movement in normative samples,48 should
be addressed in future studies.
Longitudinal follow-up of functional outcome is continuing; hence, we
cannot report definitively on the relationship between continuing anatomic
deviance or normalization vs outcome. Preliminarily, global functional outcome
in 64 patients with ADHD (20 females) evaluated 4 years after initial scan
does not suggest any significant relationships between continuing anatomic
deviance and clinical follow-up status.
We did not find evidence of a primarily frontal abnormality in ADHD.
Instead, we found the smallest diagnostic effect sizes in frontal lobes. However,
these results cannot be interpreted as definitive evidence against the frontal-striatal
hypothesis of ADHD pathogenesis, because our units of analysis, while highly
reliable, were too large. These methods have been useful in detecting age-,
sex-, and diagnosis-specific differences in growth curves,39-41,49 and
their application to ADHD was warranted. Alternate approaches, such as unbiased
pixel-based analyses,50 may be needed to detect
more localized anatomic abnormalities in regions such as cingulate, orbitalfrontal,
or dorsolateral prefrontal cortex in patients with ADHD.51 However,
these methods may also require even larger or more closely matched contrast
groups (eg, twin or sibling controls) given the mostly modest effect sizes
and substantial between-subject variations in brain anatomy.52
Limitations of this study include the use of referred samples for patients
and highly screened controls that may not be optimally representative. We
recruited female patients with ADHD who were comparable in severity with our
previous samples of males,53 but in so doing
may have selected females who are atypical of most community and clinical
samples. We lost significantly more scans from children with ADHD because
of excessive motion, but again, this bias should have removed the most symptomatic
In conclusion, ADHD is associated with about a 3% (adjusted; 4% unadjusted)
decrease in volume throughout the brain. Intriguingly, this decrease is most
marked in white matter of unmedicated patients. Furthermore, with the exception
of caudate nucleus, longitudinal growth curves are roughly parallel, suggesting
that the fundamental developmental processes active during late childhood
and adolescence are essentially healthy in ADHD, and that neuropsychiatric
symptoms appear to reflect fixed earlier neurobiological insults or abnormalities.
Future studies should focus on younger patients being enrolled into controlled
treatment studies while in preschool and on the development of improved quantitative
measures of brain anatomy and of the component endophenotypes of ADHD.54 Finally, despite the importance of these findings,
anatomic MRI studies remain appropriate only for research, as they cannot
yet contribute to the diagnostic assessment of ADHD.
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