vol26

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ADHD RESEARCH UPDATE - Vol. 26, December, 1999
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In this issue...

* Math performance in children with ADHD: What are the
difficulties and does stimulant medication help?

* Self-reported depression in mothers of children with
ADHD

* Sensitivity to reward in children with ADHD - Implications
for behavioral management

* Long-term outcomes for children who are persistently
hyperactive, oppositional, or aggressive
____________________________________________________________

NOTE: After each article you will find the corresponding
address for the lead author of the study. I began including
this information in the last issue so that you could write
away to request copies of articles you were especially
interested in. I would encourage you to do this as a way
of developing your own library of studies that are especially
interesting to you. Just don't be discouraged if you don't
always get a reply - it happens. Including a self-addressed
and stamped envelope will increase the odds of a quick
response.
____________________________________________________________

* MATH PERFORMANCE IN CHILDREN WITH ADHD:
WHAT ARE THE DIFFICULTIES AND DOES STIMULANT
MEDICATION HELP?

This is one of the more interesting studies I have seen
in some time. It is based on the fact that performance
difficulties in math for children with ADHD have been
well documented in prior reports, and that children with
attentional deficits but not hyperactivity (i.e. those
children diagnosed with ADHD, Predominantly Inattentive Type,
are at greatest risk for these problems. Although this is
not true for all children with ADHD, children with ADHD
do tend to perform more poorly in math than other children.

Several explanations for the math difficulties in children
with attentional problems have been proposed. One
has to do with failure in "automization" - i.e. the ability
to perform basic math calculations in their head. This
difficulty has been attributed to deficits that many
children with ADHD have in "working memory".

For example, imagine trying to add up 3 different numbers
in your head - 67, 123, and 42. Working memory can be
thought of as that aspect of memory that allows you to
keep these numbers, and the sum you derive for each column,
in your head so that you can accurately calculate the
answer. If you have difficulty keeping the numbers straight
in the first place, there is no way that you can do the
arithmetic manipulations required to get the correct
sum.

Other researchers have suggested that children with ADHD
have difficulty "automatically" recalling math facts like
the multiplication tables because they do not do the
repetitive drilling required to learn them so well that
their answers become "automatic". Most parents who have
tried to help their child with ADHD learn his or her
multiplication tables can attest to how frustrating it
is getting their child to do the drilling that is required.

Although the cause of math difficulty in children with
ADHD is unclear at this time, and is likely to reflect
different factors for different children, it is generally
hoped that reducing the behavioral symptoms of ADHD
(i.e. reducing distractibility, fidgeting, etc.) will
ameliorate a child's difficulties. Thus, there is now
good evidence that treatment with stimulant medication
not only improves the behavior for the majority of
children with ADHD, but that it also enhances their
academic performance, at least in the short term.

Some have argued, however, that the impact of stimulant
medication on academic performance is primarily in the
area of productivity - i.e. how much work a child completes
- rather than improving the actual quality of the work.
It has also been argued that stimulant medication has
only a limited effect, if any, on underlying cognitive
abilities such as working memory and thus does not really
effect a child's difficulties in learning.

The current study (Benedetto-Nasho, E., & Tannock, R.
(1999). Math computation, error patterns and stimulant
medication effects in children with ADHD. Journal of
Attention Disorders, 3, 121-134.) was designed to carefully
evaluate how the math computational skills of children
with ADHD compared to non-ADHD peers. In addition to
comparing how the computational skills of children with
and without ADHD, the authors were also interested in
carefully examining how stimulant medication effected
the computational skills of the ADHD children.

Participants in this study were 15 children with a confirmed
diagnosis of ADHD (13 boys and 2 girls) and 15 comparison
children without ADHD. All participants were between 7
and 11 years old. The authors were careful to match the
two groups of children on IQ, parent education level, and
even results on a standardized test of achievement in math.
This matching was done to insure that any differences in
computational skills between the groups that were detected
could not be attributed to differences in intellectual ability
or parent educational status, or to traditional measures
of academic achievement in math.

There were two portions to the study. In the first portion,
children in each group were instructed to work independently
on a computation work sheet containing problems selected to
be sufficiently challenging for their skill level. Both
addition and subtraction problems were included and the
testing time lasted for 10 minutes. Children completed the
work sheets independently with an adult examiner in the
room at all times. Children with ADHD were not on medication
during this test session.

In the second portion of the study, children with ADHD
completed equivalent worksheets over 3 successive days.
For these test sessions, they had received either a placebo,
10 mg of methylphenidate (i.e. the generic form or Ritalin),
or 20 mg of methylphenidate 90 minutes prior to the testing.
Neither the child nor the examiner was aware of what the
child had received.

Three different scores were computed for each child's
performance on the math worksheets. A productivity score
reflected the number of problems attempted divided by the
number of items available; an accuracy score reflected the
percentage of problems attempted that were answered correctly;
and an efficiency score was calculated by dividing the number
of problems answered correctly by the total number of problems
on the worksheet. Separate scores for these variables were
computed for the addition and subtraction items.

In addition to these performance indicators, ratings were also
made of children's behavior during the test (i.e. inattention,
fidgeting, getting out of seat, on-task performance, and finger
counting). The authors also completed a detailed analysis of
the types of errors that children made (i.e. careless errors
such as adding instead of subtracting vs. errors that indicated
a lack of basic understanding of borrowing or carrying).

RESULTS

The first set of results compared children with and without ADHD
when the ADHD children were not receiving medication. As
expected, children with ADHD attempted significantly fewer items.
On average, the ADHD children attempted about 20% of the items
while the comparison children attempted about 45% (Note: the
worksheets were set up to contain more problems than children could
complete in the 10-minute period.)

The accuracy results differed for addition and subtraction. On
the addition items no accuracy differences were found between the
groups. For the subtraction items, however, children with ADHD
made substantially more errors. Efficiency scores for the children
with ADHD were lower for both the addition and subtraction items.

The behavioral ratings and error analyses were also interesting.
During the 10-minute test period, children with ADHD were rated
as being more inattentive and displayed more fidgeting. They were
out of their seat more often and spent less time on-task. What
was particularly interesting is that they also spent much more
time using finger counting to solve problems rather than being
able to do the calculations in their head. Thus, even though
the 2 groups were equivalent in IQ and results on a traditional
test of math achievement, the children with ADHD were still
forced to rely on this less developed way of solving computational
problems. (These ratings were completed, of course, by raters
who did not know whether or not the child being rated had been
diagnosed with ADHD.)

The only difference in error patterns were found for the subtraction
items. On these problems, children with ADHD consistently made
errors that showed a misunderstanding of borrowing. The form
this error generally took was subtracting the smaller number
from the larger number, irrespective of its position in the
problem (e.g. for the problem 17-9, subtracting the 7 from the
9 rather than the 9 from the 7).

THE EFFECT OF MEDICATION

The second part of the study involved comparing the performance
of children with ADHD in the 3 different medication conditions:
placebo, 10 mg methylphenidate, and 20 mg methylphenidate.
What effect, if any, did medication have on their performance?

Several aspects of these results were striking to me. The first
has to do with the importance of attending to placebo effects.
Although the authors did not make direct comparisons of ADHD
children in the placebo and baseline condition (by baseline, I
am referring to their performance in the first part of the study
above) several differences were apparent. Specifically, it
appeared that children displayed less inattentive behavior
in the placebo condition, and, surprisingly, improved their
accuracy scores on subtraction problems from 38% to 64%.
They also more than doubled the number of addition problems
that they attempted.

These placebo results underscore the importance of conducting
careful, placebo-controlled trials when evaluating a child's
response to medication. Apparently, placebo effects may
extend not just to teacher ratings of children's behavior, but
even to more "objective" indices of academic performance
like the number of worksheet problems a child attempts and
the accuracy of their answers. Of course, these results were
obtained based on only a 10-minute sample of test taking
behavior. Whether they would extend for a significantly longer
period of time is unknown.

Medication was also found to result in some clear
performance changes above and beyond any placebo effects.
In the behavioral realm, medication yield significant
reductions - relative to the placebo condition - in
fidgeting, inattention, and finger counting. In all 3 of
these areas, in fact, the children with ADHD on meds
were no longer any different from the non-ADHD comparison
children. The finger counting results are especially
interesting as they indicate that medication enabled
the children with ADHD to consistently utilize the more
sophisticated computational strategy of solving problems
in their head.

In terms of the performance measures, the main finding was
that medication improved productivity scores overall (i.e.
on medication, the children with ADHD attempted more
problems than in the placebo condition), and that efficiency
scores in subtraction were also higher. Even so, however,
productivity and efficiency scores (i.e. number problems
correct divided by total number of problems) were still more
than 50% lower than scores for the comparison children.
Accuracy scores did not change, however, nor did the types
of errors that children with ADHD made.

SUMMARY AND IMPLICATIONS

Several results from this study seem important to me. First
and foremost, the results clearly indicate that many children
with ADHD will underperform their peers on typical
math assignments even when they are just as bright and do
just as well on traditional standardized achievement tests.

The exact reasons for this are unclear, and the authors did
not specifically address this issue in the discussion of
their results. It seems to me, however that at least several
different things may contribute to this. First, when not on
medication, they complete substantially fewer problems and
often rely on finger counting to solve basic calculation
problems. In addition, many of the children with ADHD do
not seem to understand the concept of borrowing very well.

Although medication helped in decreasing finger counting
and improving productivity, even when on meds they attempted
fewer subtraction problems than other children and continued
to make more errors with borrowing.

Two things seem important here. First, these data clearly
suggest the need for many children with ADHD to either
receive additional time to complete math assignments - especially
tests - or, to reduce the number of problems they must complete.
These are both accommodations that can be part of a child's
504 plan or IEP (Click here for a discussion of these possibilities).

Second, the findings suggest that teachers be made aware of
the specific difficulties that children with ADHD are likely
to have in math computation. The children in this study
consistently made errors on subtraction problems that reflected
an incomplete understanding of borrowing. The authors suggest
that this may occur because borrowing places greater demands
on working memory and attention. In any case, paying careful
attention to the errors consistently made by an individual
child can thus reveal important gaps in the child's knowledge
of arithmetic operations that need to be remedied.

Finally, although medication was shown to provide some important
benefits to math computation performance, the difficulties
experienced by the children with ADHD were certainly not
fully remedied. This underscores the important need to clearly
identify the academic difficulties a child is having even
after benefits from medication may have been provided, and to
then make sure these remaining difficulties are being specifically
targeted in the child's educational program.

As always, the results of any single study require replication,
so please keep this in mind. This was a very instructive paper,
however, and I hope it will lead to follow up research that
will provide even more understanding of these important issues.

Reprint requests to:

Dr. Rosemary Tannock
Brain and Behavior Research Program (Psychiatry)
The Hospital for Sick Children
555 University Ave.
Toronto, Ontario
Canada M5G 1X8

* SELF-REPORTED DEPRESSION IN MOTHERS OF CHILDREN
ADHD

The current issue of the Journal of Attention Disorders
contained a second interesting study that I wanted to
include in this issue of ADHD RESEARCH UPDATE. The focus
of this study is on the reports of depression among mothers
who have one or more child with ADHD (West, J. et al.,
(1999). Levels of self-reported depression among mothers
of children with ADHD. Journal of Attention Disorders, 3,
135-140).

The authors of this study begin by noting that prior
research on this topic has indicated that mothers of
children with ADHD report higher levels of depressive
symptoms than other mothers. They note, however, that
these studies all predate the publication of the DSM-IV
diagnostic criteria for ADHD. In addition, none of these
studies have examined whether depression in mothers varies
according to the subtype of ADHD (i.e. Predominantly Inattentive,
Predominantly Hyperactive/Impulsive, or Combined Type)
their child was diagnosed with. Because the behavior
patterns of children with different subtypes of ADHD differ,
it is reasonable to expect that self-reported depression
among their mothers would differ as well. (Click here for a complete
discussion of the specific diagnostic criteria for each subtype).

Participants in this study were 150 mothers of children
with ADHD from Western Australia. Names and addresses
of mothers with an ADHD child were selected at random
from a local ADHD support group organization data base,
and a packet of information and ratings forms was mailed
to these mothers. Mothers were asked to provide information
about their child's diagnosis (i.e. age when diagnosed,
source of the diagnosis, subtype information - if any -
that they were provided). They were also asked to complete
the Beck Depression Inventory (BDI), a widely used and
well-validated self-report depression rating scale.

Because the authors were primarily interested in comparing
rates of self-reported depression among mothers according
to the subtype of ADHD of their child, a comparison group
of mothers without an ADHD child was not included. In
addition, the BDI has an extensive normative data base
against which the reports of these mothers could be evaluated.

The requested information was returned by 80 mothers. These
mothers reported having a total of 103 children with ADHD -
81 males and 22 females - ranging in age from 5-18. All
had been diagnosed with ADHD by a pediatrician. Twenty-seven
were Predominantly Inattentive, 34 were Hyperactive/Impulsive,
and 42 had been diagnosed with the Combined Type. Almost
90% of these children were currently taking medication.

Self-reported depression scores were calculated and compared
for mothers of children with each subtype of ADHD. In
addition, a fourth group of mothers who had more than one
child with ADHD was included in the comparisons. Average
scores on the BDI for mothers with each type of ADHD child
are shown below. To put these scores in perspective, scores
between 10-18 fall in the mild to moderate range of depression
on the BDI and scores between 19 and 29 fall in the moderate
to severe range. These ranges are based on the normative data
that has been collected for the BDI.

Mother's category # of Mothers Mean BDI score

Inattentive 17 6.59

Hyperactive/ 19 9.74
Impulsive

Combined 26 14.54

More than 1 18 18.06
ADHD child

As seen above, mothers of one child with the Combined Type
diagnosis and mothers of more than one child with ADHD both
had average scores falling in the mild to moderate range
of depression. Average scores for mother's of a
hyperactive/impulsive child were near the bottom end of
this range, while mothers of inattentive children had
an average score within normal limits. Please note
that the scores above are group averages and substantial
variability within each group of mothers was found.
Collectively, over 50% of the mothers had BDI scores
falling in at least the mild range of depressive symptoms.

Overall, the scores coincide in order with the degree of behavioral
difficulty and resulting stress that mothers in each group might be
expected to have to deal with. Thus, mothers of inattentive children
who typically display the fewest overt behavior problems have the
lowest scores. In contrast, mothers with more than one ADHD
child, who are likely to have the most challenging situation to cope
with, have the highest. No behavioral rating data was collected on
the children of these mothers, however, so this is just speculation.

LIMITATIONS AND IMPLICATIONS

There are important limitations to this study which the
authors certainly acknowledged. First, these data are
based on mothers who had participated in a support
organization for ADHD and may not be representative
of mothers with an ADHD child more generally. Second,
the accuracy of the ADHD diagnosis and the particular
subtype is unknown. In particular, the prevalence of the
hyperactive/impulsive subtype is higher in this sample
than is generally found. Third, it should not be assumed
that the elevated rates of depressive symptoms in these
mothers were "caused" by having a child with ADHD.
Certainly, this is one possibility but a number of
other factors could have contributed to higher than
typical reports of depressive symptoms. Finally, it
would have been interesting to have collected similar
information been collected from fathers so that
comparisons between moms and dads could have been made.

These concerns withstanding, the results of this study
have important implications. First, mothers of a child
with ADHD should be aware that they may be at greater
risk for depression because of the stresses that are
often associated with parenting a child with ADHD.
Efforts to obtain support and assistance for oneself
may thus be quite important in reducing depressive
symptoms or perhaps even preventing them from developing.

PLEASE note that there is no intent here to imply that
parenting a child with ADHD is not a rewarding or wonderful
experience. These data do not suggest that in the least.
Instead, the special challenges that such parenting
may entail suggests that additional efforts to obtain
support and assistance when needed should be taken seriously.

For providers, these data highlight the need to carefully
attend to mothers' psychological and emotional state as
part of their overall evaluation of a child for ADHD.
In particular, mothers' of children showing the full
spectrum of ADHD symptoms (i.e. Combined Type) and
mothers with more than one ADHD child may be at
particular risk for experiencing emotional distress.
The most helpful interventions for these families may
thus need to carefully attend to this possibility as
opposed to dealing more exclusively with a child's
symptoms and associated difficulties.

Reprint request to:

John West
Graduate School of Education
Univ. of Western Australia
Nedlands, Perth 6009
Western Australia

* SENSITIVITY TO REWARD IN CHILDREN WITH ADHD:
IMPLICATIONS FOR BEHAVIORAL MANAGEMENT

Among the different ideas that have been proposed for
factors contributing to the symptoms of ADHD, abnormal
responsivity to behavioral rewards has a long history.
Some researchers have suggested that children with ADHD
have a reduced sensitivity to reward, which requires that
they be rewarded more often to maintain good behavior.
Others suggest that they actually have a heightened
sensitivity to reward - specifically that they show an
increased tendency to seek immediate rewards. As a result,
they become more easily distracted and pulled off tasks
that require long-term effort before any reward is obtained.

In this interesting experimental study the authors tried
to test these competing ideas about sensitivity to reward
in children with ADHD (Tripp, G., & Alsop, B. (1999).
Sensitivity to reward frequency in boys with ADHD. Journal
of Clinical Child Psychology, 28, 366-375.) This is very
much a laboratory-type experiment rather than a more "real
world" type study, but is one that seems to have important
applications for the day to day management of children with
ADHD.

Fifteen boys with ADHD and 15 matched control children with
an average age of 10 served as participants. All the ADHD
children were probably of the Combined Type - i.e. they had
both inattentive and hyperactive/impulsive symptoms.
As in many studies of ADHD, girls were unfortunately not
included.

The task for participants in the study was to sit in front
of a computer screen on which either of 2 highly similar
stimuli were repeatedly displayed for a very brief instant.
After each presentation, children were required to press a
button to indicate which stimulus they had seen. Correct
responses were signaled by the computer and children knew
that they would be awarded points that they could later
use to purchase a desirable prize.

Not every correct response was rewarded, however. Instead,
the computer was programmed so that a correct response for one
of the two stimuli would be rewarded 3 times as often as the
other. Thus, during the task, the children learned that a
correct response for one of the stimuli was more likely to
produce a reward than a correct response for the other.

RESULTS

Because of this differential rate of reward for correct
identifications of the 2 stimuli, a bias developed to select
the stimuli that was most likely to be rewarded. This simply
means that children developed a tendency to select the more-
frequently rewarded stimulus more often, even though the two
were presented an equal number of times.

What was interesting, however, is that for children with and
without ADHD, the strength of this bias was found to depend
heavily on which stimulus had been most recently rewarded.
Consider the situation in which the child was just rewarded
for correctly identifying the stimulus that had been consistently
rewarded more often throughout the test session. In this
scenario, children with and without ADHD showed a similar
tendency to select this stimulus on the next trial, even if
this was the incorrect choice.

What about when the most-recently rewarded choice was for the
stimulus that had been rewarded less often? For children
without ADHD, the "bias" they displayed on the very next trial
was still heavily in favor of the more-frequently rewarded
stimulus. In other words, they did not allow their most-recently
rewarded choice to alter what they had learned was more likely
to be the "best bet". For children with ADHD, however, the results
were quite different and the strong bias in favor of the more
consistently rewarded choice disappeared on the next trial.
In other words, the behavior of the children with ADHD was
influenced less by their overall experience of reward on the
task and more by the very last reward that they had obtained.
What's more, this same tendency was evident - although to a
slightly lesser degree - even when the children with ADHD
were tested while on medication.

IMPLICATIONS

What are the implications of these results for understanding
the day-to-day, moment-to-moment behavior of children with
ADHD? To me, it seems that these results underscore the
extent to which children with ADHD live much more "in the
moment" than do other children. As demonstrated in this
experiment, their behavior is much more likely to be influenced
by their most recent experience with being "rewarded", even
when this recently rewarded behavior is inconsistent with a
more long-standing learning history. Thus, when a behavior
meets with some success (i.e. it results in obtaining some type
of desired response) they may tend to forget that this is not
what has typically occurred before and back away from behaviors
that have been more consistently rewarded.

It is not difficult to imagine how this could play itself out in
"real life". Based on these findings, a parent could be doing
a really excellent job of consistently praising and rewarding
behaviors that they are working to promote in their child and
ignoring or even punishing a particular unwanted behavior like
whining. As a result, their child is learning that the desired
behaviors are more likely to result in the kinds of social and
even tangible outcomes they desire, and begin to display this
behavior with greater frequency.

Consistently standing firm in response to a child's whining is
difficulty for anyone, however, and there are bound to be instances
when a parent "gives in" to their child's demands in an attempt
to obtain some quick relief and needed peace. Unfortunately, as
the data from this study indicate, the result for many children
with ADHD is that when this whining behavior has been "rewarded"
by the parent's giving in, it becomes increasingly likely that
they will engage in this behavior again soon.

In other words, unlike other children who would be more likely to
recognize that this was an isolated and unlikely-to-be-repeated
event (i.e. based on the history of what has been rewarded in the
past), the child with ADHD may tend to disregard the history
and base their next "behavioral choice" on what has been
most recently successful. Unfortunately, this "choice" may
often reflect behavior you are trying to discourage that has
been inadvertently rewarded.

This "heightened sensitivity" to the most-recently rewarded
behavior underscores the important need for consistency in
behavioral interventions designed for a child with ADHD. It
also helps in understanding why behavioral interventions for
a child with ADHD can be, at times, so difficult and frustrating
to implement effectively.

On the positive side, the sensitivity that children with ADHD
show to recently rewarded behavior suggests it may be possible
to alter long-standing patterns of negative behavior by being
consistent and vigilant about rewarding the new types of behavior
you are trying to promote. You just have to be really careful
to reward the new behavior consistently, and do your best to
avoid the "slip ups" noted above.

In my experience, and corroborated in a variety of studies on this
topic, it can be difficult for parents to do this when they are
under undue stress themselves, and when they do not have the
necessary supports in place to help in following through on a
well -designed behavioral treatment plan. This is where consulting
with an experienced child mental health professional, and enlisting
the support of other parents struggling with similar issues, can
be so helpful. This is hard work, but can make a substantial
difference in children's ability to be successful both at home
and at school.

Reprint requests to:

Gail Tripp
Dept. of Psychology
University of Otago
P.O. Box 56
Dunedin, New Zealand

* LONG-TERM OUTCOMES FOR CHILDREN WHO ARE
PERSISTENTLY HYPERACTIVE, OPPOSITIONAL, OR
AGGRESSIVE

The recent issue of Child Development contains a very interesting
study on the long-term outcomes for children who are persistently
hyperactive, persistently oppositional, or persistently aggressive
(Nagin, D., & Tremblay, R.E. (1999). Trajectories of boys'
physical aggression, opposition, and hyperactivity on the path to
physically violent and nonviolent juvenile delinquency (1999).
Child Development, 70, 1181-1196. This study highlights the
importance of considering separately hyperactivity, oppositional
behavior, and actual aggression - three different aspects of
children's behavior that often are incorrectly lumped together as
being reflective of ADHD.

This is a complex study in which some very arcane statistical
techniques are employed. What follows is my best effort to
present these important data in a simple and straight-forward
way.

Here's what the authors did. At the start of the study, behavior
ratings on almost 1200 boys were obtained from their kindergarten
teachers at the end of the school year. These ratings were used
to classify boys as being high, moderate, or low on three different
types of behavior: hyperactivity (i.e. symptoms of ADHD such as
being fidgety and unable to be still), oppositionality (e.g.
irritable, disobedient, refuses to share), and aggressive (e.g.
bullies others, fights with others, kicks or hits others. Boys
were considered to be high, moderate, or low on these 3 types
of problem behaviors based on how their score on each compared
to the overall group average.

Several years later the authors tracked down over 1000 of these
boys, and had their current teachers complete these same
behavioral ratings again. These behavior ratings were then
obtained annually from boys' teachers until they turned 15.
All told, therefore, ratings for aggression, oppositionality,
and hyperactivity were obtained on the boys a total of 7
different times from 7 different teachers. As best the authors
could tell, there were no major differences between the boys they
were able to track down and the ones who were lost to
the study.

Finally, subsequent to these 7 waves of teacher behavior ratings,
each boy was interviewed at 15, 16, and 17 and asked about their i
nvolvement in a variety of delinquent and antisocial acts during
the past 12 months. All in all, this was a monumental data
collection effort and an exceptionally rich longitudinal set.
(Too bad, however, that girls were not included).

RESULTS

The first question the authors were interested in concerns
how children's scores on the 3 types of problem behaviors
tended to change over the course of their development.
Using a very complicated set of statistical tests, the
authors first identified the most commonly occuring "pathways"
for each of the 3 problem behaviors. (By "pathway", I
simply mean how children's problems in these 3 areas
changed over time - e.g. did they get worse, stay the
same, or get better?)

Four different pathways were identified. These were:

1. Persistently high - children who had high scores compared
to their peers at each assessmet;

2. High decliners - children who started out high compared
to their peers but whose scores declined into an average
range over time.

3. Moderate decliners - children who stared out moderately
high compared to peers but who also declined over time.

4. Persistently low - children who received low scores compared
to their peers at each assessment.

(Interestingly, there was no group of boys that started out
with low ratings on any of the 3 problem behaviors and then
increased over time. This may certainly have occurred for
some boys, but not enough for this to show up as a common
pathway like those noted above. It may also reflect problems
in how the behaviors were measured in this study.)

Each child was then assigned to 1 of these 4 pathways for each
behavior. Thus, it is possible for a child to have been in the
persistently high group for aggression, and in the persistently
low group for hyperactivity and oppositionality. Or, a child
could have been in the high group for all 3 behaviors. A number
of different combinations are of course possible.

To begin with, it is interesting to note the percentage of the
sample that fell into the different groups (i.e. persistently
low, moderate decliners, high decliners, and persistently high
for each of the 3 behaviors. Across the 3 types of behavior,
the percentages were as follows:

Persistently high - about 5% of the sample for each behavior;

High decliners - between 20-30%, depending on which behavior
is being considered;

Moderate decliners - about 50% of the sample for each behavior;

Persistently low - between 15-25% of the sample depending on
the behavior;

Thus, it was quite unusual for a child to show consistent
elevations - relative to his peers - on teacher ratings of
hyperactivity, oppositional behavior, or physical aggression.

Next, the authors examined the degree of overlap that existed
across the behaviors for children in the different groups. In
other words, how likely was it for a child to be in the
same grouping for each type of problem behavior?

Of particular interest here is the overlap that existed between
children who were in the persistently high group for any of the
3 behaviors. Let's focus on children who were persistently high
for hyperactivity. How likely were these children to also show
persistently elevated levels for either oppositional behavior or
physical aggression?

The answer is more than children who were not persistently
high for hyperactivity, but not nearly so often as you might
expect. Only 13% of the boys who were persistently high on
hyperactivity were also persistently high for physically aggression.
Only 23% were persistently high on oppositional behavior. These
data make it clear that the vast majority of persistently
hyperactive boys were not showing persistent difficulties in
either of the other two problem behaviors.

The message here is simple and very important: oppositional
behavior and aggression often develop and persist for reasons
that have little or nothing to do with a child's having ADHD.
When a child with ADHD also displays these other behaviors
it should not be understood as being "part of the child's ADHD".

In the second set of analyses the authors examined how well
children's classification on hyperactivity, oppositional
behavior, and aggression (e.g. were they persistently high
or persistently low) predicted their involvement in antisocial
and delinquent behavior at age 17. For children in the high
and low groups for hyperactivity, oppostionality, and physical
aggression the average number of offenses reported during the
prior 12 months were as shown below:

Hyperactivity Oppositionality Aggression

High 2.34 6.38 7.17

Low .33 .01 .06

An examination of these numbers clearly indicates that persistently
hyperactive boys actually reported far fewer offenses than boys
who were persistently oppositional or persistently aggressive.
(Note: It would have been nice to consider these outcomes for
boys who were persistently high on 2 or 3 of the different
problem behaviors. This was not done, however, primarly because
even with such a large sample, the number of children required
to do this type of analysis were not sufficient.)

Even more telling are results of analyses in which boys' grouping
on all 3 behaviors were used simultaneously to predict their
involvement in delinquent and antisocial behavior at ages 15,
16, and 17. These results are a bit complicated but here is
an overall summary:

* Boys' classification for physical aggression was the only
significant predictor of both self-reported violence and
self-reported serious delinquency. What this means is that
boys' classification on either hyperactivity or oppositional
behavior did not really matter when trying to predict these
outcomes - only their classification for aggressive behavior
mattered.

* For self-reported theft, only boys' classification on the
oppositional behavior dimension was a significant predictor.

* Boys who show high levels of hyperactivity from kindergarten
through high school are at much less risk of juvenile delinquency
than those who show high levels of physical aggression or
oppositional behavior.

IMPLICATIONS

These results have very important implications. The very good
news, I think, is that hyperactivity by itself does not increase
a child's risk for the types of antisocial outcomes considered
in this study. Now, it is important to recognize that the
ratings of hyperactivity that were used in this study were not
sufficient to determine whether a child had ADHD, but I think
it is reasonable to extend the conclusion above to make this
statement:

"When a male child has ADHD but does not also show persistently
high levels of either oppositional or aggressive behavior, he
is not likely to become involved in any serious antisocial
behavior as an adolescent."

I make this statement recognizing that it is going a bit beyond
what can be clearly concluded from the data of this study, but
it is a stretch that is supported by the efforts of other
researchers as well.

There are a number of reasons why this is quite important but
the one that really sticks out in my mind concerns just how often
parents may confuse oppositional and/or aggressive behavior with
ADHD. Typically, what I have seen happen is that after a child
has been diagnosed with ADHD, these other types of behavior
get explained away as being part of the child's ADHD. This
is incorrect, however. These other behaviors are not symptoms
of ADHD, and as this study clearly indicates, high levels of
these other behaviors are often not even associated with
ADHD and lead to very different outcomes than do ADHD symptoms
alone.

The take-home message from this study is that if a child with
ADHD is also displaying high levels of oppositional and/or
aggressive behavior, do not assume that treating the ADHD by
whatever means is tantamount to addressing these other
difficulties as well. Instead, it is essential to make sure
that these other problems are being specifically targeted in
a child's treatment plan, and these difficulties need to
be treated every bit as aggressively as the child's primary
ADHD symptoms themselves.

Reprint requests to:

Daniel Nagin
2105 Hamburg hall
Carnegie Mellon University
Pittsburgh, PA 15213
_________________________________________________________

That's all for this month...

I hope that you enjoyed this issue of ADHD RESEARCH
UPDATE and found it to be informative.

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See you next month - and best wishes for a safe and happy
holiday and start to the new year.

Sincerely,

David Rabiner, Ph.D.
Licensed Psychologist
Duke University

P.S. I continue to offer individual consultation via
phone for parents who are seeking suggestions about
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