Stimulant treatment reduces lapses in attention among children with ADHD: the effects of methylphenidate on intra-individual response time distributions.
ABSTRACT Recent research has suggested that intra-individual variability in reaction time (RT) distributions of children with ADHD is characterized by a particularly large rightward skew that may reflect lapses in attention. The purpose of the study was to provide the first randomized, placebo-controlled test of the effects of the stimulant methylphenidate (MPH) on this tail and other RT distribution characteristics. Participants were 49 9- to 12-year-old children with ADHD. Children participated in a 3-day double-blind, placebo-controlled medication assessment during which they received long-acting MPH (Concerta), with the nearest equivalents of 0.3 and 0.6 mg/kg t.i.d. immediate-release MPH. Children completed a simple two-choice speeded discrimination task on and off of medication. Mode RT and deviation from the mode were used to examine the peak and skew, respectively, of RT distributions. MPH significantly reduced the peak and skew of RT distributions. Importantly, the two medication effects were uncorrelated suggesting that MPH works to improve both the speed and variability in responding. The improvement in variability with stimulant treatment is interpreted as a reduction in lapses in attention. This, in turn, may reflect stimulant enhancement of self-regulatory processes theorized to be at the core of ADHD.
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ABSTRACT: (1) The continuous performance test, a procedure for the detection and study of brain damage in humans, is described. (2) Three groups of Ss, each including a brain-damaged and a non-brain-damaged subgroup, were tested on this procedure. (3) The brain-damaged subgroups were significantly inferior to their non-brain-damaged controls on the measures yielded by the CPT, and these differences were increased when the difficulty of the task was increased. (4) The CPT is sufficiently reliable and yields sufficiently large differences between subgroups to suggest that it might ultimately prove useful as a clinical instrument for the diagnosis of brain damage. (5) An interpretation of the inferior performance of the brain-damaged Ss was offered in terms of impairment in attention or alertness and suggestions were made about future research relating cerebral events and CPT performance.Journal of Consulting Psychology 11/1956; 20(5):343-50. · 4.46 Impact Factor
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ABSTRACT: Research on attention-deficit/hyperactivity disorder (ADHD), a highly prevalent and controversial condition, has, for the most part, been descriptive and atheoretical. The imperative to discover the genetic and environmental risk factors for ADHD is motivating the search for quantifiable intermediate constructs, termed endophenotypes. In this selective review, we conclude that such endophenotypes should be solidly grounded in the neurosciences. We propose that three such endophenotypes — a specific abnormality in reward-related circuitry that leads to shortened delay gradients, deficits in temporal processing that result in high intrasubject intertrial variability, and deficits in working memory — are most amenable to integrative collaborative approaches that aim to uncover the causes of ADHD.Nature reviews. Neuroscience 09/2002; 3(8):617-28. · 31.67 Impact Factor
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ABSTRACT: Although it is generally accepted that the spread of a response time (RT) distribution increases with the mean, the precise nature of this relation remains relatively unexplored. The authors show that in several descriptive RT distributions, the standard deviation increases linearly with the mean. Results from a wide range of tasks from different experimental paradigms support a linear relation between RT mean and RT standard deviation. Both R. Ratcliff's (1978) diffusion model and G. D. Logan's (1988) instance theory of automatization provide explanations for this linear relation. The authors identify and discuss 3 specific boundary conditions for the linear law to hold. The law constrains RT models and supports the use of the coefficient of variation to (a) compare variability while controlling for differences in baseline speed of processing and (b) assess whether changes in performance with practice are due to quantitative speedup or qualitative reorganization.Psychological Review 08/2007; 114(3):830-41. · 9.80 Impact Factor
Stimulant Treatment Reduces Lapses in Attention
among Children with ADHD: The Effects
of Methylphenidate on Intra-Individual Response
Sarah V. Spencer & Larry W. Hawk Jr. &
Jerry B. Richards & Keri Shiels &
William E. Pelham Jr. & James G. Waxmonsky
Published online: 17 March 2009
# Springer Science + Business Media, LLC 2009
Abstract Recent research has suggested that intra-
individual variability in reaction time (RT) distributions of
children with ADHD is characterized by a particularly large
rightward skew that may reflect lapses in attention. The
purpose of the study was to provide the first randomized,
placebo-controlled test of the effects of the stimulant
methylphenidate (MPH) on this tail and other RT distribu-
tion characteristics. Participants were 49 9- to 12-year-old
children with ADHD. Children participated in a 3-day
double-blind, placebo-controlled medication assessment
during which they received long-acting MPH (Concerta®),
with the nearest equivalents of 0.3 and 0.6 mg/kg t.i.d.
immediate-release MPH. Children completed a simple two-
choice speeded discrimination task on and off of medica-
tion. Mode RT and deviation from the mode were used to
examine the peak and skew, respectively, of RT distribu-
tions. MPH significantly reduced the peak and skew of RT
distributions. Importantly, the two medication effects were
uncorrelated suggesting that MPH works to improve both
the speed and variability in responding. The improvement
in variability with stimulant treatment is interpreted as a
reduction in lapses in attention. This, in turn, may reflect
stimulant enhancement of self-regulatory processes theo-
rized to be at the core of ADHD.
Attention-Deficit and Hyperactivity Disorder (ADHD),
characterized by developmentally inappropriate degrees of
inattention and/or hyperactive/impulsive behavior (Barkley
2004), is one of the most commonly diagnosed childhood
disorders (for a review see Smith et al. 2006). To account
for the behavioral symptoms that characterize the disorder,
many theorists have focused on neuropsychological pro-
cesses including inhibitory control, working memory,
planning, set-shifting, and vigilance (e.g., Barkley 2004;
Douglas 1999; Nigg 2006; Wilcutt et al. 2005). Although
research on ADHD and the executive functions has
elucidated several key processes that are impaired, on
average, in groups of children with ADHD, single-deficit
neuropsychological theories fail to account for the hetero-
geneous nature of the disorder (Douglas 1999; Nigg and
In an effort to better account for the heterogeneity in
symptom presentation and neurocognitive functioning
J Abnorm Child Psychol (2009) 37:805–816
S. V. Spencer:L. W. Hawk Jr. (*):K. Shiels:W. E. Pelham Jr.
Department of Psychology, University at Buffalo, SUNY,
Park Hall, Box 604110, Buffalo, NY 14260-4110, USA
J. B. Richards
Research Institute on Addictions, University at Buffalo, SUNY,
Buffalo, NY, USA
W. E. Pelham Jr.
Department of Pediatrics, University at Buffalo, SUNY,
Buffalo, NY, USA
W. E. Pelham Jr.:J. G. Waxmonsky
Department of Psychiatry, University at Buffalo, SUNY,
Buffalo, NY, USA
present in children with ADHD, some researchers have
argued that ADHD symptoms are driven by more general
regulatory or processing deficits rather than specific neuro-
cognitive factors (see Douglas 1999; Sergeant et al. 1999).
For example, Virginia Douglas posits that ADHD is driven
by a dysfunctional self-regulatory system which produces
patterns of inconsistent or erratic allocation of attention and
effort, referred to as deficient cognitive control (Douglas
1999). Similarly, the cognitive-energetic model proposed
by Sergeant and colleagues (Sergeant 2005; Sergeant et al.
1999) implicates executive control and regulatory processes
Interestingly, although the different etiological theories
of ADHD described above emphasize a variety of core
cognitive processes and neuropsychological deficits, one of
the most consistent findings in the ADHD literature is that
these children demonstrate, across a range of measures,
slower and more variable response patterns compared to
children without ADHD (Douglas 1999; Leth-Steensen et
al. 2000). Variable response patterns within the cognitive
literature refer to moment-to-moment fluctuations in task
performance that occur on a time scale of seconds (Russell
et al. 2006). This inconsistency in the performance of
children with ADHD has been described as a ubiquitous
finding across tasks, laboratories, and cultures (Castellanos
and Tannock 2002, p. 624). Although there are a variety of
hypotheses for why children with ADHD have such
variable response patterns, many researchers posit that
variable responding reflects fluctuations and lapses in
attention (Leth-Steensen et al. 2000; Van der Molen
1996). Importantly, the discussion of variability in relation
to ADHD is not limited to the cognitive literature.
Researchers have long noted that ADHD symptoms appear
to interact with the environment as they show considerable
variability and fluctuations across settings, caregivers, and
reinforcement schedules (e.g., Guevremont and Barkely
1992). As a result, an understanding of intra-individual
response variability at the cognitive level may have
important clinical implications for children with ADHD.
However, despite the apparent importance of intra-
individual variability or moment-to-moment fluctuations
in task performance in children with ADHD, the
majority of cognitive and neuropsychological research
on these children has focused on global measures of
performance such as mean differences in response speed
(Castellanos and Tannock 2002; MacDonald et al. 2006).
In addition, when variability is measured, the most
common method is with a single-point estimate of the
standard deviation around the mean for each individual
(Russell et al. 2006). Unfortunately, these global measures
obscure moment-to-moment processes and are limited in
the information they provide. Furthermore, there is strong
covariation between the mean and standard deviation of
the mean (Wagenmakers and Brown 2007) with correla-
tions frequently in the 0.7 to 0.9 range, suggesting that the
two variables do not really measure separate processes.
Recently, researchers have begun to utilize more fine-
grained analyses to examine the overall shapes of
reaction time (RT) distributions (Aase and Sagvolden
2006; Castellanos and Tannock 2002; Douglas 1999;
Leth-Steensen et al. 2000; MacDonald et al. 2006). In
these analyses, separate parameters describe the leading
edge (i.e., speed) as well as the size of the tail (i.e.,
variability) of the distribution (e.g., Acheson and de Wit
2008; Leth-Steensen et al. 2000). In the seminal work in
this area, Leth-Steensen and colleagues (2000) employed a
four-choice RT task and demonstrated that although
children with ADHD were not significantly slower, their
distributions were characterized by a greater rightward
skew (or tail) compared to children without ADHD. This
effect is consistent with theories postulating that children
with ADHD have periodic lapses in attention, character-
istic of an underlying deficit in the allocation of attention
and effort in order to meet task demands (Douglas 1999;
Leth-Steensen et al. 2000). Group differences in RT skew
have been recently replicated by Hervey and colleagues
(2006) using the Conners’ Continuous Performance Test
(CPT; Conners 1994) as well as by Williams and
colleagues (2007) using a stop signal paradigm. Thus, a
small but growing literature supports the hypothesis that
the RT distributions of children with ADHD are charac-
terized by a rightward skew, consistent with a self-
regulatory deficit. An example of the rightward skew that
is apparent in the response distributions of children with
ADHD is illustrated in Fig. 1 (A, D). Notably, the positive
skew of the distributions is driven by a large number of
abnormally slow responses.
As with any proposed core process in ADHD, an
important next question is whether the RT skew is reduced
by treatments for the disorder. To our knowledge, the
present study is the first controlled investigation of the
effects of stimulant medication on RT skew. The stimulant
methylphenidate (MPH) is a first-line pharmacotherapy for
ADHD (American Academy of Pediatrics 2001; Pliszka
2007), with a large literature demonstrating clinical thera-
peutic effects (e.g., Greenhill et al. 2002; Pelham et al.
1998; Schachar et al. 1997). In addition, there is evidence
that MPH improves neurocognitive functioning. For exam-
ple, MPH generally has positive effects on inhibitory
control (Aron et al. 2003; Tannock et al. 1989), visual-
spatial working memory (Bedard et al. 2004), and sustained
attention (see review by Losier et al. 1996) in children with
Although there is a wealth of data on the effects of MPH
on neurocognitive functioning, very little research has
examined stimulant effects on measures of specific aspects
806J Abnorm Child Psychol (2009) 37:805–816
of intra-individual variability. The work that has been done
in this area suggests that stimulant medication has benefi-
cial effects on the speed (e.g., Bedard et al. 2004, Riccio et
al. 2001) and variability (e.g., Boonstra et al. 2005;
Tannock et al. 1995) of responding. However, these studies
have generally relied on the highly correlated mean and
standard deviation indices. As a result, it remains unclear
whether MPH reduces variability in responding by reducing
the positive skew in RT distributions or whether MPH is
speeding responding more generally.
There is currently only one published study that
examined the effects of stimulant medication on intra-
individual RT parameters among children with ADHD.
Epstein and colleagues (2006) addressed this issue using
the Conners’ CPT (Conners 1994), which requires a
response on the vast majority of trials. In this study, RT
skew was reduced among medicated children compared to
un-medicated children, suggesting that stimulants selective-
ly reduced the variability in responding. Similar to Leth-
Steensen et al. (2000), the authors suggested that the
reduction in variability was the result of fewer and less
severe lapses in attention.
Although the study of Epstein and colleagues (2006) is
an important first step in understanding treatment effects on
intra-individual response distribution parameters, the study
was methodologically limited. Most importantly, medica-
tion was not randomized at the time of assessment. Rather,
parents reported whether or not their child had taken a
stimulant on the day of testing, and dosing was not
controlled. Consequently, no cause-and-effect relationship
could be demonstrated.
The goal of the current study was to extend the emerging
literature on intra-individual RT distributions in children
with ADHD by examining the controlled effects of
methylphenidate on intra-individual RT parameters. Specif-
ically, we evaluated the effects of two doses of long-acting
MPH (Concerta®) on the speed of responding and intra-
individual variability using a within-subject, double-blind,
randomized, placebo-controlled assessment. Mode-based
analyses, described in more detail below, were used to
9-year old male
Placebo B. Low MPH
11-year old male
Placebo E. Low MPH F. High MPH
Fig. 1 Reaction time distributions for representative participants. Data are presented for a9 year-old male (upper) and an 11 year-old male (lower)
under Placebo (left), Low MPH (middle), and High MPH (right) conditions
J Abnorm Child Psychol (2009) 37:805–816807
investigate whether MPH affected the peak and/or skew of
intra-individual RT distributions.
Consistent with previous research (see Bedard et al.
2004; Boonstra et al. 2005; Tannock et al. 1989), we
expected that MPH would reduce mean RTand the standard
deviation of RT. More critically, we predicted that MPH
would improve more specific metrics of response speed,
evident in a reduction in modal RT, and would decrease
lapses in attention, evident in a reduction in deviation from
the mode. We also hypothesized that medication effects on
mode-based indices of response speed and variability
would be weakly correlated or uncorrelated, suggesting
separable effects of MPH on processing speed and lapses in
Participants were 49 children between the ages of 9–12 years
diagnosed with ADHD. The majority of participants (76%)
were Caucasian, while the remaining participants were
African-American (14%), mixed race (8%), and American-
Indian or Alaska Native (2%). Most participants were taking
stimulant medication at the time of the study or had taken
stimulants prior to participating (82%). Additional sample
characteristics are listed in Table 1.
Participants were recruited from the Center for Children
and Families at the University at Buffalo as well as from the
community through flyers placed in the offices of pediatri-
cians. All participants were recruited to attend a week-long
summer research program designed to examine the effects of
stimulant medication on neurocognitive processes implicated
in ADHD. Parents were remunerated for their participation in
the form of money. Children were rewarded with toys and gift
cards for their participation in the week-long program. All
parents provided informed consent and all children provided
informed assent, in accordance with procedures approved by
the University at Buffalo Children and Youth Institutional
Exclusion criteria included (1) Full Scale IQ below 801;
(2) history of seizures and/or current medication to prevent
seizures; (3) history of other medical problems for which
psychostimulant treatment may involve considerable risk;
(4) current use of psychotropic medications other than
stimulants or atomoxetine (i.e., antipsychotics, mood
stabilizers, antidepressants, and anxiolytics); (5) history or
concurrent diagnosis of pervasive developmental disorder,
schizophrenia or other psychotic disorders, or other serious
mood/anxiety disorders requiring pharmacological treat-
ment; (6) absence of functional impairment related to
ADHD; or (7) vision or hearing problems that would make
it difficult to complete study tasks.
All participants had a DSM-IV (APA 1994) diagnosis of
ADHD. The diagnostic assessment involved a structured
computerized clinical interview of one or both parents
(Diagnostic Interview Schedule for Children Version IV
(DISC-IV); Shaffer et al. 2000). In addition, parents and
teachers completed two standardized rating scales: the
Disruptive Behavior Disorder (DBD) rating scale (Pelham
et al. 1992; Pelham et al. 2005) and the Impairment Rating
Scale (Fabiano et al. 2006). The DBD measures all DSM-
3R and -IV symptoms of ADHD, Oppositional Defiant
Disorder (ODD), and Conduct Disorder (CD), on a 0–3
Likert scale. The DBD has been previously shown to have
sound psychometrics and has been used extensively in
studies of children with ADHD (see Pelham et al. 1992,
2005). The IRS is an eight item visual-analogue scale that
evaluates the child’s problem level and need for treatment
in developmentally important areas, such as peer relation-
ships, adult-child relationships, academic performance,
classroom behavior, and self-esteem. The IRS has been
previously shown to be reliable and valid in ADHD and
normative populations (see Fabiano et al. 2006).
In order to meet diagnostic criteria, children were
required to exhibit six or more symptoms of inattention
and/or six or more symptoms of hyperactivity/impulsivity
according to the diagnostic interview and/or the DBD rating
scale based on reports from the parent and teacher.2In
addition, cross-situational impairment had to be present
according to the IRS and/or the DISC. Seventy-one percent
of the children were diagnosed with ADHD-Combined
Type (n=29 boys, 6 girls), 23% were diagnosed with
ADHD-Inattentive Subtype (n=8 boys, 4 girls), and 6%
were diagnosed with ADHD-Hyperactive/Impulsive Sub-
type (n=2 boys). Subtypes were based on examining the
symptoms endorsed across the DBD rating scales and the
DISC. As expected, comorbidity with externalizing disor-
ders was common, with 65% of the sample meeting criteria
for ODD, and 22% of the sample meeting provisional
criteria for CD. Parents also completed the Child Behavior
Checklist (CBCL; Achenbach 1991; see Table 1).
1One child exhibited a marked discrepancy between the verbal and
performance subscales, limiting the reliability of the brief assessment.
Because the estimated IQ of 77 was very near our cutoff, the child was
allowed to participate.
2Teacher reports were missing from 5 children. Analyses were re-run
with these 5 children excluded and results remained the same.Teacher
reports were missing from 5 children. Analyses were re-run with these
5 children excluded and results remained the same.
808J Abnorm Child Psychol (2009) 37:805–816
Standardized measures of intellectual ability and
achievement were administered including the Vocabulary
and Block Design subtests from the Wechsler Intelligence
Scale for Children - Fourth Edition (WISC-IV; Wechsler et
al. 2004) and the Reading, Mathematics, and Spelling
subtests from the Woodcock-Johnson Test of Achievement
(WJTA; Woodcock et al. 2001). Full Scale IQ was
determined by prorating scores based on performance on
the Vocabulary and Block Design subtests from the WISC-
IV. As shown in Table 1, the sample was generally in the
average range on measures of IQ and achievement.3
The Summer Research Camp was held from 7:30 am to 5
pm Monday through Friday and consisted of groups of five
children each week. On Monday through Thursday children
completed a variety of computerized tasks and participated
in three 30-minute academic periods. Recreational activi-
ties, meals, and snacks were intermingled with testing.
Children earned points throughout the day for task
participation and appropriate behavior. These points were
exchanged for toys and gift cards at the end of each day.
Task order was randomized between participants, but it
remained consistent within a child across testing days. Data
from the current analyses is limited to one of these tasks,
the X and O Discrimination Task, described below.
X and O Discrimination Task
Intra-individual response distributions were assessed with a
E-prime (Psychology Software Tools, Pittsburgh, PA). In the
task, childrenwere asked todiscriminatebetween anX and an
O that appeared on the screen by pressing one of two labeled
buttons on a response box as quickly as possible while
maintaining accuracy. The task consisted of 10 practice trials
followed by 100 task trials. Each letter was presented on the
screen for 3,000 ms separated by a 1,000 ms inter-stimulus
interval. Only responses during the 3,000 ms stimulus
presentation were recorded. An audible click occurred the
first time a button was pressed during each trial.
After an initial practice day, each child participated in a
3-day double-blind, placebo-controlled medication assess-
ment. Participants taking stimulant medication were asked
to discontinue their medication at least 24 h prior to the
practice day. Those participants taking Strattera complet-
ed a 1-week washout period prior to participating in the
medication assessment. Active doses were long-acting
MPH (Concerta®) with the nearest commercially avail-
able equivalents of 0.3 and 0.6 mg/kg t.i.d. immediate-
release MPH. The medication was purchased through our
research pharmacy and was not supplied by the manu-
facturer. Doses ranged from 18 to 90 mg (dose was
capped at 90 mg for safety reasons). The mean of the low
dose was 39.24 mg (SD=9.75) and the mean of the high
dose was 73.44 mg (SD=15.78). Sixteen out of 49 children
were order restricted so that they received the low dose
prior to receiving the high dose. These restrictions occurred
with children who were naïve to stimulant medication or in
cases where the low dose provided in the study was two or
more times greater than the child’s current dose. Medication
was administered when the child arrived in the morning,
90 min prior to the initial cognitive task. Subjects were
given the same number of blinded capsules per day
regardless of actual MPH dose to maintain blinding.
Adverse events were rated daily by camp counselors and
parents using the Pittsburgh Side Effect Rating Scale,
3One child met provisional criteria for having a math learning
disability (math standard score 1.5 standard deviation below the mean
for the child’s age; see Martinussen & Tannock, 2006).
Table 1 Participant Characteristics
Age, mean (SD) 10.5 (1.1)
WISC Full Scale IQ, mean (SD)
WJ Test of Achievement, mean (SD)
DBD rating scale
Hyp/Imp, mean (SD)
Inattentive, mean (SD)
CBCL, t-score mean (SD)
Note. The observed range of estimated IQ scores on the WISC was
77–135. The observed ranges on the WJ subtests were as follows;
Reading: 87–126, Math: 75–147, Spelling: 82–137. The values on the
DBD represent the total score of the items (rated 0–3) within each
subtype domain on the rating scale. The observed ranges were as
follows; Parent-rated hyperactivity/impulsivity: 1–27, Teacher-rated
hyperactivity/impulsivity: 0–27, Parent-rated inattention: 2–27,
Teacher-rated inattention: 1–27
J Abnorm Child Psychol (2009) 37:805–816809
which inquires about common side effects seen with
stimulants (rated none to severe) (Pelham 1993). Blood
pressure and pulse were also measured daily during times
of peak medication effects. Any subject reporting signifi-
cant distress or exhibiting marked side effects was
evaluated by the study nurse or physician.
Children were brought in to the testing rooms and were
reminded of the laboratory rules. Children were told that
they would earn 100 points for following the rules and
completing the tasks during the activity period. These rules
included 1) follow directions, 2) stay in your assigned area,
3) use material and possessions appropriately, and 4) try
your best. Children were also informed that, following a
single warning, they would lose 25 points per rule
RT for each of the 100 trials was the basic unit of data.
Only responses for correct discriminations were included in
the analyses. Responses that occurred within the first
150 ms of stimulus presentation were considered anticipa-
tory responses and excluded from analyses. Omissions were
replaced with a value of 3,000 ms (total trial length).
The primary dependent variables of interest included
within-subject mode and deviation from the mode. However,
we also computed mean RT and standard deviation of RT
given their common usage in the literature. Accuracy,
anticipatory responses, and omissions were examined in
Several studies that have examined the shapes of RT
distributions have used ex-Gaussian models to examine
response distributions in ADHD (Douglas 1999; Epstein et
al. 2006; Hervey et al. 2006; Leth-Steensen et al. 2000).
These models utilize a theoretical distribution characterized
as a convolution of the normal and exponential distribution
functions (see Castellanos et al. 2006). Parameter values are
chosen that best describe the leading edge (i.e., speed) as
well as the size of the tail (i.e., variability) of the distribution
(Douglas 1999; Leth-Steensen et al. 2000). However, in the
current study we used a mode-based approach rather than the
ex-Gaussian method to examine RT distributions. This
decision was based on a number of limitations of the ex-
Gaussian method including 1) ex-Gaussian distributions do
not always adequately fit individual data (e.g., 13% in Leth-
Steensen et al. 2000), 2) the ex-Gaussian method makes
specific assumptions about the shape of the distribution (e.g.
the inclusion of an exponential distribution) which may not
be true of the data set, and 3) the ex-Gaussian method
involves fairly complex computations and curve-fitting
procedures (Hausknecht et al. 2005), with no apparent
advantage resulting from this complexity.
Modeand deviation fromthe modeprovide a usefulway to
quantify the typical speed of an individual’s responses (e.g.,
the peak of the distribution) and the variability of responses
(e.g., the skew of the distribution), respectively (Acheson and
de Wit 2008; Hausknecht et al. 2005; Sabol et al. 2003). The
mode is a preferred measure of speed as it is unaffected by
distributional skew. Conversely, deviation from the mode
assesses the skew of the distribution and is easily calculated
by subtracting the modal RT from the mean RT (Hausknecht
et al. 2005; Sabol et al. 2003). To estimate the mode of
response distributions, we used the Half-Range Mode
method (HRM), as in other recent work (Acheson and de
Wit 2008; Hausknecht et al. 2005; Sabol et al. 2003). The
HRM method produces mode values that are asymptotically
unbiased and are more resistant to distributional skew
(Bickel 2002; Bickel 2003; Hedges and Shah 2003). HRM
involves dividing a data set into two halves and selecting the
densest side (e.g. the side with the greatest number of data
points). This side is then split in half, the density of the halves
is evaluated, and the densest side is again selected. The
splitting ofthe data continues until the half-sample isless than
three data points. The mean of this final sample is the mode of
the original data set (Hedges and Shah 2003). In the current
study, HRM was programmed in Microsoft Excel.
Bivariate correlations were used to examine the relations
between the dependent variables within each of the different
medication conditions as well as between the different
medication effects. To examine the effects of MPH on the
dependent variables, separate repeated measures ANOVAs
were conducted. Orthogonal contrasts of placebo vs. both
active medication doses and of low vs. high doses were
employed to assess medication effects.4Effect sizes were
computed as Cohen’s d (Cohen 1988).
4As a result of the relatively small number of girls (n=10) and
children with ADHD-Inattentive (n=12) and ADHD-Hyperactive/
Impulsive subtype (n=2) we conducted only exploratory tests of sex
and subtype differences. Girls were slower and more variable overall,
and unpredicted interactions with medication dose suggested that the
higher dose of MPH was necessary to achieve similar reductions in
mode RT and deviation from the mode in girls compared to the low
dose of MPH for boys. Exploratory analyses with subtype (ADHD-C
vs. ADHD-I) revealed no reliable differences between subtypes for
mode RT and deviation from the mode; of course, the present study
was underpowered to detect such effects. It is important to note that
40% of girls (n=4) but only 22% of males (n=8) were of the
inattentive subtype, further muddying the interpretation of the sex
effects above. Future work with larger samples will be necessary to
thoroughly evaluate sex and subtype differences.
810 J Abnorm Child Psychol (2009) 37:805–816
Correlational analyses demonstrated that mean RT and
standard deviation of RT were significantly and positively
MPH (0.6 mg/kg/day) conditions, rs=0.90, 0.82, and 0.83,
respectively, ps<.001. These correlations indicated that
across medication conditions mean RT and standard devia-
tion of RT share on average 72% of their variance with one
another. In contrast, and consistent with our predictions,
mode RTand deviation from the mode were not significantly
correlated in the placebo, low MPH, or high MPH
conditions, r=−0.03, −0.09, and 0.27, respectively, ps>
0.06. These correlations indicated that across medication
conditions mode RT and deviation from the mode share on
average only 2.7% of their variance with one another.
As expected, mean RT and standard deviation of RT
were significantly reduced under active medication con-
ditions compared to placebo, Fs (1, 48)=83.01 and 64.64,
ps<0.001, ds=0.88 and 0.94, respectively (see Fig. 2A, B).
Moreover, the high dose of MPH resulted in significantly
lower mean RT and standard deviation of RT than did the
low dose of MPH, Fs (1, 48)=8.14 and 6.64, ps<0.007 and
0.02, ds=0.24 and 0.34, respectively. Lastly, an examina-
tion of correlations between the medication effects (mean of
low and high doses of MPH vs. placebo) for mean RT and
standard deviation of RT revealed that they were signifi-
cantly and positively related, r=0.80, p<0.001. Scatter
plots were examined in order to see whether these effects
were driven by outliers, defined as any participants with
medication effects that were three standard deviations
above or below the mean. No participants met this criterion.
As expected, mode RT was significantly reduced under
active medication compared to placebo,F (1, 48)=19.23, p<
0.001, d=0.46 (see Fig. 2C). Although the means were in
the expected direction, the high dose of MPH did not result
in a significantly lower mode RT compared to the low dose
of MPH, F (1, 48)=2.55, p=0.12, d=0.2. Most importantly
and as predicted, deviation from the mode was significantly
attenuated under active medication conditions compared to
placebo, F (1, 48)=35.37, p<0.001, d=0.89 (see Fig. 2D).
The high dose of MPH did not significantly reduce
deviation from the mode compared to the low dose of
MPH, F (1, 48)=0.692, p=0.41, d=0.14.
Although Fig. 2 illustrates the average effect, it is also
interesting to examine the actual RT distributions for
individual subjects. Figure 1 presents such distributions
for a 9-year-old male (first panel) and an 11-year-old male
(second panel) for each of the medication conditions.
Consistent with our inferential statistics, you can see at
the individual level that medication reduces both the mode
and the deviation from the mode RT, relative to placebo. In
Fig. 2 Mean Reaction Time
(Panel a), Standard Deviation
of Reaction Time (Panel b),
Mode Reaction Time (Panel c),
and Deviation from the Mode
(Panel d) for each of the medi-
J Abnorm Child Psychol (2009) 37:805–816 811
addition, a developmental trend is suggested, with both
mode and deviation from the mode reduced in the older
child relative to the younger child. Consistent with the
pattern suggested by Fig. 1, age in the overall sample was
negatively correlated with deviation from the mode during
the placebo session, r=−.34, p<.02 although it was not
significantly correlated with mode RT, r=−0.18, p=0.22.
As done for the mean and standard deviation, we
examined the correlation between the medication effects
(mean of high and low MPH vs. placebo) on mode RT
and deviation from the mode. Contrary to expectations,
the medication effects were moderately negatively
correlated, r=−0.36 p<0.02, though not nearly as highly
as for the mean and standard deviation of RT. However,
after excluding the two children who had medication
effects on mode RT or deviation from the mode that were
greater than three standard deviations above the mean, the
medication effect on mode RT was no longer significantly
correlated with the medication effect on deviation from the
mode, r=−0.13, p=0.38.
Supplementary analyses examined accuracy and the
numbers of anticipatory responses and omitted responses
in order to evaluate whether beneficial effects of MPH on
speed were the result of a speed-accuracy tradeoff.
Compared to accuracy during the placebo session (M=
0.94), accuracy improved significantly under active medi-
cation, F (1, 48)=4.31, p<0.05 and tended to be better
during the high compared to the low dose of MPH (Ms=
0.97 and 0.96, respectively, F (1, 48)=3.27, p=0.08. The
mean numbers of anticipatory responses and omitted
responses were low in all conditions (for anticipatory
responses, Ms=0.5, 0.3, and 0.1; for omissions, Ms=1.2,
0.4, and 0.2, for placebo, low MPH, and high MPH,
respectively). The reductions during active medication
compared to placebo were marginally significant, Fs (1,
48)=3.15 and 3.65, ps=0.08 and 0.06, for anticipatory
responses and omissions, respectively, but the differences
between the high and low dose of MPH did not approach
traditional levels of statistical significance, ps>0.2. Thus,
there did not appear to be any speed-accuracy tradeoff;
rather, children were faster, less variable, and more accurate
under active MPH.
Intra-individual variability has been increasingly discussed
in the literature as an important regulatory deficit in
children with ADHD (e.g., Castellanos et al. 2006;
Castellanos and Tannock 2002; Douglas 1999; Leth-
Steensen et al. 2000). However, despite the apparent
importance of intra-individual variability in children with
ADHD, there is a paucity of research on the effects of
common treatments for ADHD, such as stimulant medica-
tion, on intra-individual response speed and variability. The
current study was the first study to date to examine the
placebo-controlled effects of the stimulant medication
methylphenidate (MPH) on the peak and skew of intra-
individual response time (RT) distributions.
Consistent with previous research, we observed robust
MPH effects on mean RT and standard deviation of the
mean RT (Bedard et al. 2004; Boonstra et al. 2005; Riccio
et al. 2001; Tannock et al., 1989). Importantly, however,
correlational analyses demonstrated that the medication
effects on mean RT and standard deviation of RT were very
strongly and positively correlated, suggesting that mean RT
and standard deviation of RT do not reflect dissociable
Our focus was on the mode RT and deviation from the
mode in order to quantify the average speed and variability,
respectively, of an individual’s responses (Hausknecht et al.
2005; Sabol et al. 2003). Specifically, mode is thought to
reflect sensory motor processing whereas deviation from
the mode is thought to reflect distributional skew (Sabol et
al. 2003). Mode and deviation from the mode are thought to
be more precise measures of speed and variability,
respectively, given that the mode is believed to be
unaffected by distributional skew (Hausknecht et al.
2005). In support of this idea, we found that mode RT
and deviation from the mode were not reliably correlated
with one another.
We hypothesized that MPH would reliably speed
responses evident in faster modal RT. As expected, we
found that modal RT was reliably reduced under active
medication suggesting that MPH speeds sensory motor
processing. In addition, this decrease in response speed was
not consistent with a speed-accuracy trade-off as accuracy
also improved under active medication. The effect of
medication on modal RT is clearly depicted in Fig. 1 and
illustrates the leftward distributional shift that occurred
when children were medicated. Interestingly, this leftward
shift was more pronounced for the older child suggesting
that medication may be more effective at improving speed
and reducing lapses in attention in older samples. Impor-
tantly, however, our sample included a narrow age range
(9–12 years) and all children were diagnosed with ADHD.
As a result, future work is needed to fully understand
developmental trends associated with medication. Although
the effect of MPH on sensory motor processing has been
previously demonstrated (Bedard et al. 2004; Boonstra et
al. 2005; Tannock et al. 1989), our focus on the effect of
MPH on mode-based RT measures allowed us to examine
whether MPH was specifically affecting response speed.
Although we examined the effects of MPH on both the
speed and variability of RT distributions, our primary
interest was on the effect that medication had on intra-
812J Abnorm Child Psychol (2009) 37:805–816
individual response variability, or distributional skew, as
measured by deviation from the mode. As expected,
deviation from the mode was reliably reduced under active
medication. As evident in Fig. 1, children displayed fewer
abnormally slow responses when medicated which caused
an overall reduction in the positive skew of their distribu-
tions. In addition and consistent with previous research
indicating that variability in responding is particularly
prominent in children with ADHD (see Leth-Steensen et
al. 2000), medication had a large effect on deviation from
the mode (d=0.89). In fact, the medication effect size on
deviation from the mode was more than four times the
effect size of medication on mode RT. Given that
distributional skew in children with ADHD is thought to
result from abnormally long responses or lapses in attention
(see Leth-Steensen et al. 2000), our results suggest that
MPH is particularly effective at reducing lapses in attention,
relative to speeding general motor processing, at least in
Although research on the effect of MPH on lapses in
attention as assessed by intra-individual variability is
limited, the effectiveness of MPH in improving sustained
attention in children with ADHD is supported by a wealth
of research (see reviews by Brown et al. 1986; Losier et al.
1996; Riccio et al. 2001). However, these studies have
primarily focused on performance (e.g., target hits, omis-
sion errors, and reaction time) during versions of the
Continuous Performance Task (CPT; Rosvold et al. 1956).
Our data provides initial evidence that MPH also specifi-
cally reduces lapses in attention during a simple discrim-
ination task as indicated by a significant reduction in the
positive skew of intra-individual response distributions.
Consistent with the interpretation of skew as reflecting
lapses in attention, data from the current sample, which also
completed an A-X CPT each day of the summer research
camp, demonstrates that deviation from the mode is
significantly and positively correlated with target misses
on a CPT paradigm under placebo conditions, r=0.40, p<
0.007.Misses are typically thought to measure lapses in
sustained attention (Riccio et al. 2001). Thus, this relation-
ship provides further evidence that greater deviations from
the mode are indicative of lapses in attention.Although
these results provide initial evidence of convergent validity,
future work will need to investigate whether and how
deviation from the mode is associated with other measures
Interestingly, although the means were in the expected
direction, we did not find significant differences between
the low and high dose of MPH on mode RT and deviation
from the mode, but such differences were observed for
mean RT and standard deviation of RT. The reason for the
discrepancy is not clear, but the pattern of effects suggests
that the high dose is exerting a stronger effect on motor
speed compared to lapses in attention, with only deviation
from the mode reflecting the latter process. More generally,
the findings with mode and deviation from the mode are
consistent with the broader literature demonstrating a lack
of dose effects across multiple higher-order cognitive
processes such as inhibitory control and focused attention
(see review by Pietzak et al. 2006). In addition, our results
suggest that a relatively low dose of MPH may be effective
at speeding responses and improving lapses in attention.
This finding is consistent with evidence that even lower
doses of MPH can have a substantial impact on children
and adolescents’ behavior and performance in the class-
room or laboratory settings (Evans et al. 2001; Gorman et
al. 2006). Conversely, it is also notable that no child
received a high dose that was greater than 90 mg. Although
this upper limit was important for safety, it limited the
separation of low and high doses for heavier children.Thus,
further work is needed to better elucidate the dose-response
function for MPH effects on RT parameters. Given the
above discussion, such work should consider doses lower
than the 0.3 mg/kg dosing provided in the present study.
We chose to use mode RT and deviation from the mode
as measures of speed and skew, respectively, following the
previous argument that the two measures were distinct from
one another (Hausknecht et al. 2005; Sabol et al. 2003). As
noted earlier, correlational analyses in the current study
provided evidence that mode RT and deviation from the
mode measure distinct processes. Furthermore, the two
medication effects were not significantly correlated with
one another once two outliers were removed. The lack of a
relationship between the two medication effects suggests
that the effect of MPH on deviation from the mode was not
simply due to a speeding up of overall RT values. Rather,
these correlations suggest that MPH works to decrease the
peak and reduce the skew of RT distributions and that these
two effects reflect dissociable processes.
Although our findings clearly demonstrate that MPH is
effective at speeding responses and reducing distributional
skew, questions remain as to whether other treatments for
ADHD, such as behavioral interventions, can reduce child-
ren’s speed and variability in responding. There is strong
empirical support for the effectiveness of behavioral
therapy as well as the combination of behavioral therapy
and stimulant medication in the treatment of ADHD
(American Academy of Pediatrics 2001). Specifically,
contingencies, in the form of reinforcement and response
cost, which are central in behavioral treatments of ADHD
(Pelham and Waschbusch 1999) have been clearly shown to
improve the functioning of children with ADHD across
home and school settings (Pelham and Fabiano 2008;
Pelham et al. 1998). In addition, research has demonstrated
that incentives can improve some neurocognitive processes
including response speed (measured by mean RT) and
J Abnorm Child Psychol (2009) 37:805–816813
behavioral inhibition (see review by Luman et al. 2005) as
well as working memory (Shiels et al. 2008). Although no
published studies have examined the effects of such
behavioral techniques on intra-individual speed and vari-
ability, we are currently testing whether incentives improve
response speed and skew.
Results from the current study extend the current
literature on intra-individual RT measures and clearly
indicate that MPH, the first-line pharmacotherapy for
ADHD, is effective at speeding responses and reducing
positive distributional skew in children. However, this
study is not without limitations. Like many samples of
ADHD children, ours was predominately boys with
combined subtype and marked comorbidity with other
disruptive behavior disorders (see Table 1). This limits the
generalizability of the results and leaves open several
potential moderators of stimulant effects on RT parameters.
Beyond characteristics of the sample, characteristics of
the task should also receive further attention. Specifically,
future research studies should examine the effects of task
type and event rate on RT distribution characteristics given
the hypothesized role of these factors in ADHD (Scheres et
al. 2001). For example, previous research has demonstrated
that slow trial rates tend to elicit slow and variable
responding (Scheres et al. 2001) whereas fast trials rates
may contribute to impulsive response styles (see Hervey et
al. 2006). Although we did not observe a speed-accuracy
trade-off in the current study, it is possible that this would
emerge in tasks with faster trial rates. In addition, it may be
important to use simple discrimination tasks, such as those
used in the current study and by Leth-Steensen et al.
(2000), rather than tasks that require inhibition, as they may
shift children’s response distributions. For example, recall
that Epstein et al. (2006) used the Connors CPT, during
which children respond 90% of the time but inhibit
responses to targets (10%), to compare children taking
stimulants to those who were not taking medication at the
time of testing. In that study, the leading edge of the
distribution was slower, not faster, among children who
were medicated. The authors suggested that the result
reflected a beneficial effect of medication on impulsive
responding. Although the study by Epstein was not a
controlled medication study, the data suggest that the
addition of task demands, such as inhibition, may influence
the size and even the direction of medication effects on RT.
This may also complicate the interpretation of “go trials” on
the frequently used stop signal paradigm, as several studies
indicate that participants change response strategies when
the stop signal is introduced, frequently trading speed for
inhibitory success (see review by Verbruggen and Logan
2008). Thus, we echo the call of Tannock (1998) and others
to use measures that most simply and directly assess the
processes of interest.
In summary, our data contribute to the growing literature
on intra-individual RT distribution characteristics in
ADHD. This literature is relevant to both etiology and
intervention. Regarding etiology, leading theories of ADHD
have shifted the emphasis from single neurocognitive
deficits to either multi-process models (e.g., Sonuga-Barke
2005) or to more general, regulatory processes (e.g.,
Douglas 1999; Sergeant et al. 1999). As proposed by
Douglas, the large tail in the RT distribution of children
with ADHD reflects lapses in attention that result from
problems in these regulatory processes. The present study
builds on this perspective, demonstrating that response
variability is improved by a leading pharmacotherapy, and
that this effect is dissociable from the stimulant enhance-
ment of overall motor speed. This study, like others in this
area, focused on a single task in a laboratory setting.
Importantly, there is evidence that children with ADHD
display behavioral variability outside of the laboratory
including notable symptom, mood, and arousal fluctuations
(e.g., Guevremont and Barkely 1992; Shea and Fisher
1996). In addition, recent research has demonstrated that
children with ADHD display significantly greater variabil-
ity in attentive behavior in clinical settings, such as the
classroom, compared to their peers (Kofler et al. 2008). It
will be exciting to examine whether individual differences
in treatment effects on laboratory measures of intra-
individual variability predict improvement in real-world
assistance, Rosemary Tannock for comments on the design of the
study, and all of the families that participated in the Summer Research
Camp. This research was supported by grant MH069434 from the
National Institute of Mental Health.
We thank Mark Kutgowski for programming
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