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Associations and mechanisms among attention deficit hyperactivity disorder symptoms, cognitive functioning, and drinking habits
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ASSOCIATIONS AND MECHANISMS AMONG
ATTENTION DEFICIT HYPERACTIVITY DISORDER SYMPTOMS,
COGNITIVE FUNCTIONING, AND DRINKING HABITS
by
Sherry A. Span
A Dissertation Presented to
THE FACULTY OF THE GRADUATE SCHOOL
UNIVERSITY OF SOUTHERN CALIFORNIA
In Partial Fulfillment of the
Requirements for the Degree
DOCTOR OF PHILOSOPHY
(PSYCHOLOGY)
May 2000
Copyright 2000 Sherry A. Span
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UMI Number: 3018032
__ _{ § )
UMI
UMI Microform 3018032
Copyright 2001 by Bell & Howell Information and Learning Company.
Ail rights reserved. This microform edition is protected against
unauthorized copying under Title 17, United States Code.
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UNIVERSITY OF SOUTHERN CALIFORNIA
THE GRADUATE SCHOOL
UNIVERSITY PARK
LOS ANGELES, CALIFORNIA 90007
This dissertation, written by
under the direction of h.f.F. Dissertation
Committee, and approved by all its members,
has been presented to and accepted by The
Graduate School in partial fulfillm ent of re
quirements for the degree of
Sherry A. Span
DOCTOR OF PHILOSOPHY
Dean of Graduate Studies
D ate -E ebm aig:.1 23.,..2QQQ...
DISSERTATION COMMITTEE
Chairpers on
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Dedication
To my greatest teachers of all..-
Grandma Ida and Grandpa Lester
Thank you.
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iii
Acknowledgments
I thank my advisor, Mitch Earleywine, and committee
members, Margy Gatz, Beth Meyerowitz, Adrian Raine, and
John Brekke for their helpful comments and assistance in
preparing this manuscript.
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iv
Table of Contents
Dedication.................................................. ii
Acknowledgments........................................... iii
List of Tables...............................................v
List of Figures........................................... vii
Abstract..................................................viii
Introduction ............................................ 1
Previous Research Examining the Link Between ADHD
and Alcoholism......................................... 3
Summary of Findings and the Need for a New Model..16
Hypotheses of the Current Study.....................2 6
Method.......................................................27
Participants.......................................... 27
Measures...............................................27
Results......................................................3 6
The Relation Among Drinking Habits, ADHD Symptoms,
and Cognitive Functioning........................... 36
Confirmatory Factor Analysis........................ 43
Moderator Analysis................................... 4 9
The Role of Coping Strategies..................... 53
The Role of Expectancies...........................65
The Role of Drinking Situations...................69
Discussion.................................................. 71
References.................................................. 85
Appendix.....................................................92
Quantity/Frequency/Maximum Index for Drinking
Habits................................................. 92
DSM-IV Criteria for ADHD Questionnaire.............93
Alcohol Expectancy Questionnaire....................94
Drinking Situations Questionnaire................. 95
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V
List of Tables
Page
Table 1. Follow-back Studies Reviewed.....................6
Table 2. Follow-up Studies Reviewed......................14
Table 3. Means and Standard Deviations for Drinking
Habits Measures........................................... 37
Table 4. Correlations Among the Drinking Habits
Measures................................................... 38
Table 5. Means and Standard Deviations for the ADHD
Measures................................................... 38
Table 6. Means and Standard Deviations for Cognitive
Functioning Measures......................................41
Table 7. Correlations Among the Cognitive Functioning
Measures................................................... 42
Table 8. Correlations Among Drinking Habits, ADHD, and
Cognitive Functioning Measures.......................... 4 4
Table 9. Measures of Fit for Each Model Examining the
Relation Among Drinking Habits, ADHD Symptoms, and
Cognitive Functioning.....................................4 6
Table 10. Comparisons Among Chi-Squares for Alternative
Models Examining the Relation Among Drinking Habits, ADHD
Symptoms, and Cognitive Functioning..................... 4 7
Table 11. Measures of Fit for Each Model Examining the
Underlying Factor Structure of the CSI..................5 6
Table 12. Comparisons Among Chi-Squares for Alternative
Models Examining the Factor Structure of the CSI.......57
Table 13. Means and Standard Deviations of the Three
Coping Scales for High and Low Cognitively Functioning
Individuals................................................5 9
Table 14. Examining Problem-Solving as a Mediator for the
Relation Between ADHD Symptoms and Drinking Habits in
Lower Cognitively Functioning Individuals...............62
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vi
List of Tables (Continued)
Table 15. Examining Problem-Solving as a Suppressor for
the Relation Between ADHD Symptoms and Drinking Habits in
Higher Cognitively Functioning Individuals..............64
Table 16. Examining Alcohol Expectancies as a Mediator
for the Relation Between ADHD Symptoms and Drinking
Habits in Lower Cognitively Functioning Individuals.... 67
Table 17. Examining Alcohol Expectancies as a Suppressor
for the Relation Between ADHD Symptoms and Drinking
Habits in Higher Cognitively Functioning Individuals... 70
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vii
List of Figures
Page
Figure 1. Possible explanatory models for the link
between ADHD and alcohol disorders (NTAAA, 1993}........ 4
Figure 2. The moderational model explaining the link
between ADHD and alcohol disorders....................... 18
Figure 3. (a) Histogram of omission errors on the
continuous performance task. (b) Histogram of commission
errors on the continuous performance task 4 0
Figure 4. Three-factor model of ADHD symptoms, cognitive
functioning, and drinking habits......................... 48
Figure 5. Cognitive functioning moderates the link
between ADHD symptoms and drinking habits.......... 52
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viii
Abstract
The current study first examined the relation among
Attention Deficit Hyperactivity Disorder (ADHD) symptoms,
cognitive functioning, and drinking habits. A
significant relation occurred between drinking habits and
ADHD. Individuals who reported more ADHD symptoms also
reportedly drink more alcohol. Cognitive functioning
moderated the relation between ADHD and drinking habits.
ADHD correlated significantly with drinking habits for
those with lower cognitive performance but not for those
with higher cognitive functioning. These results support
previous work (Span & Earleywine, 1999) and suggest that
higher cognitive functioning may protect these
individuals from drinking in accordance with their ADHD
symptoms. Alcohol expectancies mediated the relation
between ADHD and drinking habits in the lower cognitively
functioning individuals. Positive expectations about
alcohol's effect on ADHD symptoms might be responsible
for the link between alcohol consumption and ADHD
symptoms in this subgroup.
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1
Introduction
Four models may help account for the link between
Attention Deficit Hyperactivity Disorder (ADHD) and an
alcohol disorder (National Institute of Alcohol Abuse and
Alcoholism (NIAAA), 1993). These models include: the
secondary alcohol disorder model, the secondary
psychiatric disorder model, the common factor model, and
the bidirectional model. Figure 1 illustrates each
model.
The secondary alcoholism model suggests that a
psychiatric disorder leads to an alcohol disorder. Thus,
ADHD would precede and cause the alcohol disorder
according to this model. The theory of self-medication is
consistent with this model. Individuals with ADHD may
drink alcohol to relieve their symptoms, potentially
leading to alcohol abuse (Schubiner, et al., 1995) .
The secondary psychiatric disorder model suggests
that an alcohol disorder causes a psychiatric disorder.
This model appears improbable for the link between ADHD
and alcoholism. If this model were true, an alcohol
disorder must precede the presence of ADHD. ADHD is a
disorder that initially appears in childhood; alcohol
disorders appear later in life. Thus, this model does
not effectively describe their association.
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2
The bi-directional model suggests that despite which
condition appears first, each condition worsens the
other. If ADHD symptoms continue into adulthood and an
alcohol disorder is present simultaneously, each
condition would exacerbate the other. Individuals may
drink to relieve symptoms of ADHD, yet their drinking
would cause a worsening of the ADHD symptomatology. One
symptom associated with alcohol withdrawal that may
exacerbate ADHD symptoms is autonomic hyperactivity
(Charness, Simon, & Greenberg, 1989). Other physical
symptoms associated with alcohol withdrawal, such as
shaking and psychomotor agitation, could also exacerbate
the ADHD disorder. At the same time, continued drinking
as self-medication could worsen the alcohol disorder.
Thus, this model may be a tenable one.
The common factor model suggests that an underlying
third variable accounts for both the psychiatric disorder
and the alcohol disorder. A third variable could affect
the association between ADHD disorder and an alcohol
disorder in two ways; it could either mediate or create a
spurious relation between them. When a third variable
operates as a mediator, it acts as the mechanism
underlying the association between the two variables.
For example, ADHD may cause poor peer relations. Poor
peer relations may promote alcohol use to ease
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socialization. This alcohol use may lead to an alcohol
disorder. Thus, the third variable of poor peer
relations serves as the mechanism that constructs the
relation between ADHD and drinking disorders. A third
variable acting as a mediator generates a meaningful
relation among the three variables. Alternatively, a
third variable may cause a spurious relation between a
psychiatric disorder and an alcohol disorder. Brain
injury serves as one possible example. Individuals with
a brain injury may exhibit ADHD symptoms. In addition,
individuals with brain injuries may tend to develop
drinking disorders. Statistically, when partialing out
the effect of the variable of brain injury, the relation
between ADHD and drinking disorders ceases to exist.
Brain injury does not act as the mechanism causing people
with ADHD to develop drinking disorders. Nevertheless,
in this illustration, brain injury creates an artificial
relation between ADHD and alcohol disorders because of
its individual association with each variable.
Previous Research Examining the Link Between ADHD and
Alcoholism
To date, the secondary model of alcoholism has
driven most of the research examining the link between
ADHD and alcohol disorders. Thus, researchers have
investigated whether childhood ADHD leads to alcohol
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Secondary Alcohol Disorder Model
4
ADHD
Alcohol
Disorder
Primary Alcohol Disorder Model
Alcohol
Disorder
ADHD
Common Factor Model
Common
Factor
ADHD
Alcohol
Disorder
Bidirectional Model
ADHD
Alcohol
Disorder
Figure 1. Models that may explain the link between ADHD
and Alcohol Disorders (NIAAA) , 1993, p. 43)
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5
disorders later in life. Follow-back and follow-up
studies have examined this relation. The findings of
these studies appear below.
Review of Follow-Back Studies
Follow-back studies assess available participants'
history of ADHD. This assessment occurs in one of two
ways. One method requires participants or other
informants to recollect childhood history to attempt a
diagnosis of ADHD. Another method requires previous
medical records from the participants to detect the
presence of an ADHD diagnosis.
Prior to reviewing these studies, the reader must
note that the label for the cluster of symptoms including
hyperactivity, impulsivity, and inattention has changed
over time. Different conceptualizations of the syndrome
resulted in these changes in labels (see Wender, 1995 for
a review). Thus, comparison among follow-back studies is
difficult due to the different diagnostic criteria used
for ADHD. For the purpose of this paper, the current
label of ADHD will describe this syndrome. In addition,
several studies about this topic have not employed
control groups (e.g., Alterman, Petrarulo, Tarter, &
McGowan, 1982; Wood, Wender, & Reimherr, 1983). This
review excludes these studies because of their limited
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6
generalizability. Table 1 lists the follow-back studies
reviewed in this section.
Table 1
Follow-back Studies Reviewed
Author(s) Xear Sample .Size Ag.e
Goodwin et al.1 1975 133 23-45
Borland & Heckman 1976 40 30**
Tarter et al.2 1977 142 38.9'
Huessy & Howell 1985 238 35.7*
Biederman et al.3 1995 368 37"
Wilson & Marcotte 1996 85 15.5**
1Goodwin, Schulsinger, Hermansen, Guze, & Winokur (1975)
2Tarter, McBride, Buonpane, Schneider (197 6)
'Biederman, Wilens, Mick, Milberger, Spancer, Faraone (1977)
'Mean age of sample
"Mean age of sample approximated
Inherent weaknesses in the design of follow-back
studies contribute to the interpretation of their
findings. For example, these studies often require both
participants and/or informants whom are close to the
participants to recollect childhood behavior to arrive at
a past diagnosis of ADHD. Relying on an individual's
memory is fraught with difficulties. Asking someone to
remember back several decades may not lead to
particularly accurate data. DSM-IV (APA, 1994) states
that some hyperactive-impulsive or inattentive symptoms
that cause impairment must be present before seven years
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of age to warrant a diagnosis of childhood ADHD. On
average, participants in the studies discussed below
recollected behavior more than twenty years prior to the
study. This lengthy period could affect the reliability
and validity of the retrospective diagnosis.
In addition, the participants used for follow-back
studies are often chosen from a population exhibiting
psychiatric difficulties. For example, Tarter, McBride,
Buonpane, and Schneider (1977) and Huessy and Howell
(1985) used alcoholics as participants and determined
whether they had a retrospective diagnosis of ADHD. The
characteristics of this group of participants may not be
typical of all individuals with ADHD.
Goodwin, Schulsinger, Hermansen, Guze, and Winokur
(1976) studied 133 male adoptees ranging in age from 23
to 45 years old. The researchers classified 14
participants as alcoholic. Fifty percent of alcoholics
categorized themselves as having ADHD as children while
15% of non-alcoholics classified themselves as having
ADHD, producing a statistically significant difference.
Nevertheless, the small sample of alcoholics (n = 14)
limits the generalizability of these findings.
Borland and Heckman (197 6) obtained the medical
records of 37 men classified as having ADHD 20 to 25
years earlier. Of the 37 men, 20 individuals completed
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8
the follow-up. Participants had a mean age of 30 years
old. The control group consisted of brothers of the
probands. The results indicated that no probands or
brothers were alcoholic at follow-up. Several
methodological weaknesses could have contributed to the
null findings. The retrospective diagnosis performed by
the researchers examining previous medical records cannot
confirm the presence of the disorder at the time of
intake. The diagnosis of ADHD did not exist then.
Medical examiners may not have been looking for those
specific symptoms and did not record them. The authors
stated that the participants did not meet the criteria
for alcoholism, but they failed to state what the
criteria were. Data describing the drinking patterns of
these individuals would help to determine if one group
drank significantly more than another despite the lack of
an alcohol disorder. Finally, approximately 50% (n=17)
of the original 37 potential participants completed the
follow-up study. Perhaps those individuals who completed
this study differed from those who did not.
Tarter et al. (1977) conducted a methodologically
more sound study than Borland and Heckman (1976).
Participants included 38 primary alcoholics, 28 secondary
alcoholics, 4 9 psychiatric controls, and 27 normal
controls. The primary alcoholic group consisted of
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individuals who displayed abnormal drinking prior to age
40, had increased alcohol tolerance, loss of control,
withdrawal symptoms, and personal problems from alcohol
prior to the age of 40. The secondary category consisted
of all other alcoholics. Thus, placement in the primary
category indicated a more severe alcohol disorder. The
alcoholic groups consisted of both inpatients and
outpatients. The researchers did not specify the number
of inpatients and outpatients in each category of
alcoholics. Inpatients who did not have alcohol
disorders constituted the psychiatric control group.
Primary alcoholics reported four times as many ADHD
symptoms than secondary alcoholics. In addition, primary
alcoholics started drinking at a significantly earlier
age and became alcoholics significantly earlier as well.
Secondary alcoholics reported the same number of ADHD
symptoms as the normal controls.
Huessy & Howell (1985) compared three groups of
participants. These groups included: ADHDs, normal
controls, and inpatient alcoholics. The ADHD group
contained 7 0 individuals previously rated by their fifth-
grade teachers as having the highest level of ADHD-like
behavior. The normal control group contained 70
individuals previously rated by their fifth-grade
teachers as having the lowest level of ADHD-like
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10
behavior. The mean age of these two groups was
approximately 22 years old. Of these potential
participants, 57 normal controls and 27 ADHDs completed
the study. The third group consisted of 98 inpatient
alcoholics undergoing treatment. The mean age of the
alcoholics was 36 years old. Participants
retrospectively assessed the presence of ADHD during
childhood. Results indicated that the ADHD and alcoholic
groups did not differ on ADHD symptomatology. Yet, both
the ADHDs and alcoholics endorsed significantly more
childhood ADHD items than the normal controls. Another
interesting finding of this study is the similarity of
drinking behavior by the ADHDs and the controls. These
results suggest that drinking behavior between ADHDs and
controls may not differ when individuals are in their
20's. Instead, maladaptive drinking patterns may occur
during their 30's. Note that only 27 ADDs completed the
study, and no data are available for the 43 ADHDs who
were contacted but did not complete the study. The ADHDs
who completed the study may differ from those who did not
choose to participate.
Biederman, Wilens, Mick, Milberger, Spancer, and
Faraone (1995) compared alcohol and drug use of a group
of 120 adults with a childhood diagnosis of ADHD to a
control group of 286 non-ADHD adults. The mean age of
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11
the participants was approximately 37 years old. Results
indicated that the rate of alcohol abuse and dependence
did not differ between the ADHD and control groups.
Nevertheless, the ADHD group had a significantly greater
prevalence of drug and polysubstance (alcohol and drug)
abuse than the control group. Overall, ADHD adults had a
40% lifetime diagnosis of a substance abuse disorder. Of
all the follow-back studies discussed, this investigation
was the strongest methodologically. The researchers
eliminated ADHD individuals who showed comorbidity with
other psychological disorders. In essence, these
researchers attempted to study "pure" ADHD.
Wilson and Marcotte (1996) compared 48 ADHD
adolescents with a clinical control group of 37
adolescents. The control group consisted primarily of
individuals with learning disabilities and affective
disorders. The average age for both groups was
approximately 15.5 years. The researchers contacted
potential participants by examining the medical records
of individuals originally seen for an assessment at a
neurodevelopmental evaluation clinic. Thirty six percent
of the potential ADHD participants (n=134) completed the
follow-up assessment. The range of time from the initial
assessment to the follow-up was 5 to 12 years. No
statistically significant differences in alcohol
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12
consumption existed among the three groups. The greatest
weakness of this study is the high attrition rate, with
almost two-thirds of potential participants not
completing the follow-up. Also, the participants may
have been too young to have developed a drinking
disorder.
Review of Follow-up Studies
Follow-up studies assess and diagnose individuals
initially. The researchers reassess these individuals
later. In the studies discussed below, individuals
diagnosed with ADHD participated initially. Reassessment
occurred later to determine the presence of an alcohol
disorder. A number of methodological weaknesses
associated with follow-up studies affect the
interpretation of their results. One problem associated
with these studies is the attrition rate. If too many
participants miss the follow-up assessment, the findings
become questionable. A high prevalence of drop-outs may
suggest that the individuals at follow-up differed along
other dimensions from the individuals who completed the
study. For example, Cox, Rutter, and Yule (1977) have
suggested that the drop-outs may comprise a more
pathological group.
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1 3
The disparity of ages at follow-up also creates
difficulty when comparing results. The mean ages at
follow-up of the studies discussed below range from 14 to
25 years old. Younger samples at follow-up may not have
developed an alcohol disorder. Yet, the null findings do
not preclude these probands from developing a disorder in
the future.
In addition, the varied diagnostic criteria prevent
a clear picture of the link between these two disorders.
Each follow-up study discussed below used different
diagnostic criteria for ADHD. The method of assessment
contrasted as well. For example, Andersson, Magnuson,
and Wennberg (1977) used teachers' reports for diagnosis,
and Biederman et al. (1997) interviewed both mother and
child. Several follow-up studies examining this topic
have not employed control groups (e.g., Huessy & Howell,
1985; Laufer, 1971). This review excludes these studies
due to the limited generalizability of their findings.
Table 2 lists the follow-up studies reviewed in this
section.
Blouin, Bornstein, and Trite (1978) studied 23 ADHDs
and 22 individuals who had school difficulties but no
history of ADHD in a five year follow-up study. The mean
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1 4
Table 2
Follow-up Studies Reviewed
Author(s) Year
H
Initial Aae Aae at F.U.
Blouin et al.1 1978 45 9" 14"*
Hechtman et al.2 1984 119 10" 19"
Andersson et al.3 1997 540 13"" 25**
Biederman et al.4 1997 237 11*’ 15*"
‘Blouin, Bornstein, & Trite (1978)
“Hechtman, Weiss, & Perlman (1984)
■ ’ Andersson, Magnusson, & Wennberg (1997)
4Biederman, Wilens, Mick, Faraone, Weber, Curtis, Thornell, Pfister,
Jetton, & Soriano (1997)
"Mean age of sample
"'Mean age of sample approximated
age of the participants was 14 years at follow-up. The
researchers matched both groups on gender, IQ, and age.
Five years later, ADHDs reported drinking
significantly more alcohol than controls, but neither
group reported any alcohol abuse. Only 55% of the
original sample of ADHDs (n=42) completed the follow-up
assessment, and the researchers did not perform an
analysis of attrition. Therefore, the ADHDs who
completed this study may have differed from those
individuals who did not. Nevertheless, the results
obtained for the ADHDs and the controls who completed the
study suggest that the differences between these two
groups may be underestimated.
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Hechtman, Weiss, and Perlman (1984) conducted a 10-
year follow-up that compared 75 ADHDs and 4 4 controls.
The researchers matched the groups on age, gender, and
socioeconomic status. The participants had a mean age of
19 years at follow up. The control group for this study
did not appear to be adequate. Thirty-five of the
original controls began the study 10 years earlier. The
researchers decided to enlarge the size of the control
group at follow-up and recruited friends of the controls.
Thus, approximately 25% of the control group provided
retrospective information. The researchers did not
assess the additional controls for the presence of ADHD.
No significant difference in alcoholic consumption
existed between the two groups during the three month
period prior to the follow-up assessment. Nevertheless,
the findings suggest that ADHDs had more bouts of heavy
drinking in the past five years than controls. Seventy-
five percent of the original sample of ADHDs (n=104)
completed the follow-up assessment. A trend existed for
the drop-outs to have higher initial scores on
aggressiveness (p < .06). No other significant
differences existed between those who completed the study
and those who did not.
Andersson, Magnusson, and Wennberg (1977) performed
a more methodologically sound study than those previously
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16
discussed. These researchers followed a cohort of
Swedish boys (n=540) for 12 years. The researchers
assigned the participants to one of four groups. These
groups included: normal controls (n=4 21), pure
aggressiveness (n=44), pure ADHD (n=32), and combined
aggressiveness/ADHD (n=43). Teachers assessed
participants at the onset of the study. Pure ADHDs
showed significantly more alcohol problems than controls
at follow-up. The major strength of this study is the
very small attrition rate. The loss of participants at
follow-up was less than 1%.
Biederman et al. (1997) performed a four year
follow-up study that compared individuals with ADHD
(n=118) to normal controls (n=107). The mean age of the
participants at follow-up was approximately 15 years old.
Experimenters interviewed both children and mothers to
determine the presence of ADHD. No significant
differences existed between the groups for alcohol
disorders. Nevertheless, the authors noted a trend for
ADHDs using substances at an earlier age than controls.
The primary strength of this study is that the attrition
rate at follow-up was 9%.
Summary of Findings and the Need for a New Model
The most striking conclusion after examining the
results of the follow-back and follow-up studies is the
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17
lack of consistency in reported results. Fifty percent
of the studies reviewed demonstrated a relation between
ADHD and drinking. This inconsistency in the literature
suggests that looking for a categorical relationship
between an ADHD diagnosis and an alcohol disorder may be
too simplistic an approach. Weiss and Hechtman (1993)
have suggested that a subset of hyperactives may develop
drinking problems. If a subset of hyperactives develop
an alcohol disorder, then an underlying third variable
would be moderating the relation between these two
disorders. A moderator indicates a statistical
interaction. At one level of the moderator a relation
would exist between the variables of ADHD and an alcohol
disorder. At another level of the moderator, the
relation would not exist between the two variables.
Figure 2 illustrates the moderational model.
Cognitive functioning may potentially moderate the
relation between ADHD and drinking. Pihl and Peterson
(1991) suggested that cognitive deficits combine with
poor socialization in ADHD children to increase alcohol
abuse in adulthood. Both ADHDs and alcoholics exhibit
cognitive impairments associated with prefrontal area
functioning (Lezak, 1995) . These impairments include:
impersistence, decreased flexibility in thinking,
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18
High
Level of
Moderator
Variable
No
Alcohol
Disorder
ADHD
Low
Level of
Moderator
Variable
Alcohol
Disorder
ADHD
Figure 2. The moderational model explaining the link
between ADHD and alcohol disorders.
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19
simplistic problem-solving strategies, and perseveration
(Lezak, 1995; Woods & Ploof, 1997). For example,
alcoholics and ADHDs perseverate on tests of mental
flexibility such as the Wisconsin Card Sort (Gorenstein,
Mammato, & Sandy, 198 9; Chelune, Ferguson, Koon, &
Dickey, 1986).
Span and Earleywine (1999) did find that cognitive
functioning moderated the relation between ADHD and
drinking habits in a sample of 100 college students. No
participants had diagnoses of either ADHD or an alcohol
disorder. Instead, the researchers examined a range of
ADHD symptoms. Individuals who displayed more ADHD
symptoms and performed poorly on tasks assessing
prefrontal area functioning drank in accordance with
their ADHD symptoms. For these lower cognitively
functioning individuals, increased drinking occurs with
greater A.DHD symptoms. On the other hand, individuals
who performed better on these neuropsychological tasks
did not show a relation between drinking and symptoms of
ADHD. For these higher cognitively functioning
individuals, the amount of ADHD symptoms experienced does
not impact drinking behavior. No main effects confounded
this finding. The low and high cognitively functioning
groups did not show any significant differences in
drinking habits. Thus, a higher level of cognitive
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20
functioning may buffer individuals with ADHD from
developing an alcohol disorder.
The current study proposes to replicate and extend
Span and Earleywine's (1999) findings. The present study
will employ all of the measures of the previous study
with additional measures for each of the three latent
constructs of ADHD, drinking habits, and cognitive
functioning. Four measures will assess drinking habits,
four measures will assess ADHD symptoms, and six measures
will assess cognitive functioning.
In addition, this study goes further than the Span
and Earleywine (1999) study and investigates two
potential mediating variables that may account for the
positive correlation between drinking habits and ADHD
symptoms in lower cognitively functioning individuals.
Here, a mediating variable is the mechanism through which
ADHD symptomatology influences drinking habits. Two
potential mediating variables include: coping strategies
and alcohol expectancies.
Coping Strategies
Span and Earleywine (1999) speculated that
individuals with prefrontal-type cognitive impairment
drink alcohol in an effort to decrease their symptoms
because they are unable to plan alternative coping
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21
strategies. Higher cognitively functioning individuals
may be more successful creating other options to cope
with their ADHD symptoms. For example, engaging in
physical exercise prior to attempting a task requiring
sustained focused attention has reduced ADHD
symptoms(Molloy, 1989).
Using an alternative method to cope with ADHD
symptoms such as exercising indicates a problem-solving
coping style. Problem-solving strategies attempt to
alter the source of stress to alleviate the difficulty.
Conversely, drinking alcohol to cope with the
difficulties imposed by ADHD symptoms indicates an
avoidant coping style. Avoidance coping strategies aim
at escaping the problem. Amirkhan (1990) hypothesized
that problem-solving and avoidance coping strategies may
illustrate of the primitive tendencies of "fight or
flight" when encountering a threatening situation. Thus,
high cognitively functioning individuals might attempt to
"fight" their ADHD symptoms, and low cognitively
functioning individuals might attempt to "flee" their
ADHD symptoms.
Previous research has linked problem-solving ability
and ADHD. For instance, Barkley (1997) described ADHD as
a disorder resulting in executive functioning deficits.
These functions include: purposive action, planning,
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22
initiation, self-monitoring, and self-regulation (Lezak,
1995) . Deficits in these areas could prevent individuals
from developing adequate problem-solving skills.
Furthermore, research examining the academic coping
strategies of college students reporting high versus low
amounts of ADHD symptoms demonstrated that high
symptomatic individuals approached studying in a less
organized way. They procrastinated more and used fewer
self-disciplinary behaviors. Apparently, the high
symptomatic individuals engaged in less problem-solving
strategies and more avoidant strategies (Tarnock, Rosen,
& Kaminski, 1998).
Nevertheless, not all individuals with ADHD are
unable to cope effectively with their symptoms. Hechtman
(1991) noted that some adults diagnosed with ADHD employ
coping strategies that deal with their symptoms more
effectively than others. Thus, effective coping
strategies may predict a positive outcome only in a
certain subgroup of individuals with ADHD and not in
another subgroup. This example suggests a case of
moderated-mediation. The current study will examine the
coping strategies used by both levels of the moderating
variable cognitive functioning. Perhaps poorer problem
solving ability mediates the relation between ADHD
symptoms and drinking habits in lower cognitively
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23
functioning individuals. Because they are unable to plan
a more effective means of coping, these individuals drink
to alleviate ADHD symptoms. This self-medication with
alcohol may eventually lead to alcohol abuse (Schubiner,
et al., 1995). On the other hand, greater problem-solving
ability may suppress the relation between ADHD and
drinking in higher cognitively functioning individuals.
The ability to plan alternative strategies to cope with
ADHD symptoms might allow these individuals a number of
more appealing options and eliminate self-medication with
alcohol.
Alcohol Expectancies
Another potential mechanism underlying the relation
between ADHD symptoms and drinking habits might be the
beliefs that people hold about how alcohol affects their
symptoms. These alcohol expectancies may be either
positive or negative consequences of drinking (Walters,
1998).
Initially, researchers hypothesized that only
positive expectancies predicted drinking behavior (Jones
& McMahon, 1998) . An example of a positive expectancy
is: "I would expect to feel happy upon drinking." The
Alcohol Expectancy Questionnaire (AEQ; Brown, Goldman,
Inn, & Anderson, 1980), one of the most often used
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24
assessments of alcohol expectancies, consists solely of
positive items. Later, Jones & McMahon (1994) developed
the Negative Alcohol Expectancy Questionnaire (NAEQ) in
response to the growing concern that negative
expectancies might predict drinking behavior as well. An
example of a negative expectancy is: "I would expect to
get into a fight upon drinking."
Earleywine (1995) found that positive expectancies
correlate significantly with intentions to drink. In
addition, further research has shown that individuals
appear to follow through with their intentions to drink.
Generally, a higher number of positive expectancy items
endorsed correlates positively with the reported amount
of alcohol consumed (Jones & McMahon, 1998) . Negative
expectancies have not shown the same predictive power.
Earleywine (1995) did not find a relation between
negative expectancies and intentions to drink.
Investigations of the link between negative expectancies
and alcohol consumption have yielded mixed results (Jones
& McMahon, 1998).
The above questionnaires (AEQ and NAEQ) assess
general expectancies about alcohol consumption. In other
words, these questionnaires attempt to determine how
individuals expect alcohol to affect them under all
circumstances. Other studies have focused on how
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25
individuals expect alcohol to influence specific
behaviors. For example, Tran, Haaga, and Chambless
(1997) studied the relation between alcohol expectancies,
social anxiety, and alcohol consumption. They found that
expectations of reduced anxiety from drinking alcohol in
social situations moderated the relation between social
anxiety and alcohol consumption. High and low socially
anxious individuals who expected anxiety reduction from
alcohol did not differ in alcohol consumption.
Nevertheless, those high in social anxiety who did not
expect anxiety reduction from alcohol drank significantly
less than those low in social anxiety who also did not
expect anxiety reduction. Some other specific areas of
focus regarding alcohol expectancies have included
parents' beliefs on parent-child interactions (Molina,
Pelham, & Lang, 1997) and beliefs about risky sexual
behavior (O'Hare, 1998) .
The current study is the first to focus on alcohol
expectancies concerning ADHD symptoms. Individuals will
report on how they believe being a little intoxicated
will affect each of the 18 symptoms listed for ADHD in
the DSM-IV (APA, 1994) . Both positive and negative
expectancies will be assessed. A 9-point Likert-type
scale ranging from much worse (-4) to much better (+4)
will accomplish this task.
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26
Hypotheses of the Current Study
The following hypotheses are proposed for the
current study.
Hypothesis 1: Cognitive functioning will moderate the
relationship between ADHD and drinking habits, supporting
Span and Earleywine's (1999) findings. Individuals who
function at a lower level cognitively will drink in
accordance with their ADHD symptoms. Individuals who
function at a higher level cognitively will not show a
relation between their drinking habits and ADHD symptoms.
Hypothesis 2: Individuals who display increased ADHD
symptoms as well as higher cognitive functioning will use
significantly more problem-solving strategies for coping
with their ADHD symptoms. Individuals who display
increased ADHD symptoms as well as lower cognitive
functioning will use significantly more avoidant
strategies for coping with their ADHD symptoms.
Hypothesis 3: Problem-solving coping strategies as
measured by the Coping Strategy Indicator (Amirkhan,
1990) will act as a mediator for the relation between
ADHD symptoms and drinking habits in lower cognitively
functioning individuals. Conversely, problem-solving
coping strategies will act as a suppressor variable for
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27
the relation between ADHD symptoms and drinking habits in
higher cognitively functioning individuals.
Hypothesis 4: Alcohol expectancies concerning ADHD
symptoms will act as a mediator for the relation between
ADHD symptoms and drinking habits in lower cognitively
functioning individuals. Conversely, alcohol
expectancies concerning ADHD symptoms will act as a
suppressor variable for the relation between ADHD
symptoms and drinking habits in higher cognitively
functioning individuals.
Method
Participants
One hundred seven students (25 males, 8 2 females)
participated for extra credit in their undergraduate
psychology classes. Ages ranged from 17 to 3 9 years
(mean = 20.82, SD = 4.18). Fifty-one (48%) identified
themselves as Caucasian, 26 (24%) as Asian, 16 (15%) as
Hispanic, 4 (4%) as African American, and 1 (1%) as
Native American. Nine students (8%) chose not to
identify race.
Measures
In a two-hour session, participants completed
assessments for drinking habits, ADHD, cognitive
functioning, coping strategies, alcohol expectancies, and
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28
the types of situations in which they drink. Individual
measures appear below.
Drinking Habits
1. Quantity/Frequency/Maximum Index. Participants
reported the average number of standard drinks (i.e., 12
oz. beer, 4 oz. glass of wine, 12 oz. wine cooler, mixed
drink, or 1 H oz. liquor) they consumed per drinking
occasion in the past three months, the average number of
drinking occasions per week in the past three months, and
the maximum number drinks consumed on one occasion in the
last three months. Earleywine and Martin (1993) used a
similar measure, and it appears to be a valid index of
alcohol consumption. See Appendix for a copy of this
measure.
2. Time Line Follow Back (Sobell, Sobellr Leor &
Cancilla, 1988). Participants indicated the number of
drinks consumed each day for the previous three months.
To accomplish this task, experimenters provided calendars
for the previous three months including memory cues that
might be helpful (e.g., Labor Day Weekend was September
5-7; the fall semester began Wednesday August 26th) .
Participants started from the date of participation in
the experiment and worked backwards to include a three-
month period. The experimenter marked off the starting
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29
and stopping points on the calendar to facilitate this
task. Participants wrote the number of standard drinks
(i.e., 12 oz. beer, 4 oz. glass of wine, 12 oz. wine
cooler, mixed drink, or 1 ^ oz. liquor) consumed each day
on the calendar. They used their personal date books
when necessary to help remember specific occasions (e.g.,
friends' birthdays, campus parties).
Attention-Deficit Hyperactivity Disorder (ADHD)
1. Utah Criterion (lender, Wood, & Reimherr, 1985).
Participants completed questionnaires assessing
retrospective childhood ADHD symptoms and current ADHD
symptoms. The items assessed the symptoms listed on the
Utah Criterion. Wender et al. (1985) designed the Utah
Criterion to diagnose ADHD in adults with better inter
rater reliability than the DSM-IIIR (Wender, 1995) . In
addition, subsequent research has supported the validity
of this scale (Weyandt, Linterman, & Rice, 1995).
Participants circled statements that applied to them.
Examples of statements from the child form include: "As a
child, I daydreamed a lot and was distractible", and "As
a child, I was always on the go." Examples of statements
from the adult form include: "I have trouble with my mind
wandering", and "I feel a constant need to be doing
things."
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30
2. DSM-IV Criteria. Participants completed an 18-item
questionnaire assessing the presence of DSM-IV symptoms
for Attention Deficit Hyperactivity Disorder (ADHD).
Statements of symptoms were presented in a 7-point
Likert-type scale. Participants circled the number that
best described them, with zero indicating never and six
indicating always. Examples of statements include: “I
often don't give close attention to details and make
careless mistakes.", and "I find that I often interrupt
others." See Appendix for a copy of this measure.
3. Continuous Performance Task (CPT). The CPT was
programmed in BASIC using an IBM-compatible computer.
Participants viewed a target consisting of a large white
circle with a small black circle inside and at the top of
the larger circle. They were supposed to press the space
bar whenever the target appeared on the screen. The
stimulus was presented for .1 seconds with a two-second
delay between stimulus presentations. The computer
recorded an error of omission for each target missed, and
an error of commission for a response made to a nontarget
stimulus. This task required 20 minutes.
Neuropsychological Battery
Participants completed three neuropsychological
tasks on an IBM-compatible PC and two paper and pencil
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31
tasks. For each of these tasks, the experimenter
instructed the participants to work as quickly as
possible. Participants completed practice trials when
appropriate. The statistical analyses did not include
practice trials. The computer recorded both speed and
accuracy for each task. Cognitive efficiency measures
[number correct/reaction time for correct responses] were
calculated for the following measures discussed below:
The Little Men Test, both levels of the visual Spatial
Analysis, and the Bexley-Maudsley Category Sorting Test.
This dependent measure was used because previous
researchers (Glenn & Parsons, 1990; Span & Earleywine,
1999) have suggested that assessing the speed of
performance as well as accuracy may improve detection of
subtle cognitive deficits.
Paper and Pencil Tasks: The following two tasks are
dependent on sustained behavior and suggest frontal lobe
functioning (Lezak, 1995). Individuals who perseverate
show impairment on these tasks (Mesulam, 1985).
1. Trails A and B. (Reitan, 1959). Part A required
participants to draw a line connecting a series of
randomly arranged numbers in a numerical sequence. Part
B required participants to draw a line connecting letters
and numbers in an alternating sequence. The connecting
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32
line should go from 1 to A to 2 to B to 3 to C and so on.
A modified version of Trails B increased the difficulty
of the task (Mesulam, 1985). The experimenter timed each
task. The subsequent analyses only included Trails B
because the inability to shift from number to letter
indicates impulsivity and perservation associated with
impaired frontal lobe functioning (Lezak, 1995) . The
dependent measure for Trails B consisted of time taken to
complete the task.
2. Stroop Color Word Interference Test (Golden, 1978).
This task consists of three separate trials. Trial one
required participants to read words printed in black ink.
Trial two required participants to name printed colors.
Trial three required participants to name the color of
ink that words were printed in while ignoring the word
itself. The word "red" written in blue ink illustrates
this condition. For this example, participants should
respond "blue". This task allocates 45 seconds per
trial. The dependent measure for the Stroop Color Word
test was the number of words in which the color of the
ink was correctly identified in 45 seconds. The number
of words was then multiplied by -1 to create scaling
consistency among all of the cognitive functioning
measures. Thus, as the value of each cognitive
/
r
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33
functioning measure increased, the participant's
performance decreased.
Computerized tasks: Previous research showed that
detoxified alcoholics performed less efficiently than
controls on the following battery of computerized
neuropsychological tasks (Glenn & Parsons, 1990; 1991).
1. Little Men Test (Acker & Acker, 1982) . Participants
made left/right discriminations regarding a manikin
rotated along two axes. The manikin held a briefcase,
and the participant determined which hand was holding
the briefcase. The manikin faced the participant or
faced away, stood on his feet or stood upside down. Each
position reflected one of four levels of difficulty of
the task. This task assessed visuospatial orientation
and consisted of 32 trials.
2. Visual Perceptual Analysis (Acker & Acker, 1982).
Participants attempted to detect differences in geometric
patterns. The task consisted of twenty-four trials.
Three five-by-four matrices consisting of 20 blocks
appeared on the screen. Matrix patterns differed by 2 or
4 blocks creating two levels of difficulty. Participants
identified the one matrix that differed from the other
two. This task assessed complex visual inspection.
Tracy and Bates (1994) suggested that current
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3 4
neuropsychological instruments are incapable of detecting
the potentially subtle cognitive impairment of social
drinkers. Therefore, both levels of the Visual
Perceptual Analysis task were analyzed separately in an
effort to increase the sensitivity of these measures.
3. Bexley-Maudsley Category Sorting Test (Acker & Acker,
1982). This task is a computerized version of the
Wisconsin Card Sort (Berg, 1948) . Participants developed
sorting criteria based on abstract concepts (orientation,
number, color, and type of elements). As the computer
altered the solutions, participants should have modified
their sorting techniques. For example, the computer may
have initially reinforced sorting by color, but then
reinforced sorting by number without alerting the
participant in advance. After each sort, participants
received feedback regarding the accuracy of their
response. Participants successfully completed a category
after six consecutive correct responses. Successful
completion involved sorting six categories comprising two
levels of difficulty. Level one consisted of successful
completion of categories 1-3. Level two consisted of
successful
completion of categories. 4-6. This task assessed
flexibility in problem solving.
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35
Coping Strategies
Coping Strategy Indicator (CSI; Amirkhan, 1990).
Participants read the following problem: "Think of a time
when you were feeling restless, distracted, and unable to
keep your mind on finishing a very important task that
you began. Indicate to what extent you..." The
participant then read a list of 33 specific coping
behaviors. They indicated the extent that they would use
each of the behaviors to cope with the situation.
Participants circled one of three responses: "a lot", "a
little", and "not at all". Responses were summed to form
three scales: Problem Solving (i.e., thought about what
needed to be done to straighten things out.), Seeking
Social Support (i.e., let your feelings out to a friend),
and Avoidance (i.e., watched television more than usual).
Amirkhan (1994) illustrated the reliability and validity
of this measure in previous work. One additional
question added to the questionnaire assessed whether
participants would drink alcohol in response to this
problem.
Alcohol Expectancies
Participants imagined that they drank enough alcohol
to feel a little intoxicated. Subsequently, they
indicated to what extent being a little intoxicated would
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3 6
affect each of the 18 ADHD symptoms listed in the DSM-IV.
Participants circled answers using a 9-point Likert
scale, with -4 indicating much worse, 0 indicating no
change, and +4 indicating much better. See Appendix for
a copy of this measure.
Drinking Situations
This 13-item questionnaire determined which
situations participants were more or less likely to
drink alcohol. After reading about a situation, they
indicated on a 5-point Likert scale how likely they were
to drink alcohol. Responses ranged from 1 indicating
"never" to 5 indicating "always". Examples of settings
included: "at a bar with a few friends" and "in my
dorm/apartment alone". See Appendix for a copy of this
measure.
Results
The Relation Between Drinking Habits. ADHD Symptoms, and
Cognitive Functioning
Thirteen measures were analyzed to determine the
relation between drinking habits, cognitive functioning,
and ADHD symptoms. These measures included: four
measures for drinking habits (quantity, frequency,
maximum, and Time Line Followback), four measures for
ADHD (DSM-IV criteria, Utah Criteria for both childhood
and adult symptoms, and a continuous performance task) ,
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37
and six measures for cognitive functioning (Stroop Color-
Word, Trails B, Little Men test, both levels of the
Visual Perceptual Analysis, and the Bexley-Maudsley
Category Sorting Test. Descriptive statistics for each
of the measures follow.
Drinking Habits
Table 3 presents the means and standard deviations
for the four drinking measures.
Table 3
Means and Standard Deviations for Drinking Habits Measures
Measure
Q. M
Frequency 107 1.16 1.07
Quantity 107 2.80 2.07
Maximum 107 5.28 3.88
Time Line Followback 107 42.46 50.89
Frequency = the average number of drinking occasions per week in the
past 3 months.
Quantity = the average number of standard drinks (i.e. 12-oz. Beer,
5-oz. Glass of wine, 12-oz. Wine cooler, mixed drink, or 1 oz.
liquor) consumed per drinking occasion in the past three months.
Maximum = the maximum number of drinks consumed on one occasion in
the last three months.
Time Line Followback = the total number of standard drinks consumed
during the past three months.
In addition, each drinking measure significantly
correlated with every other drinking measure suggesting
that each of these measures assessed the same construct.
Table 4 shows the correlations.
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38
Table 4
Correlations Among the Drinking Habits Measures
Frequency Quantity Maximum TLFB
Frequency
Quantity .55**
Maximum .61** .85**
TLFB .79** .69** .72**
TLFB = Time Line Followback
**p< .01
ADHD
Table 5 displays means and standard deviations for
the DSM-IV criteria, the Utah adult criteria, and the
Utah child criteria.
Table 5
Means and Standard Deviations for the ADHD Measures
Measure q M
Utah Criterion Adult 107 41.98 16.23
Utah Criterion Child 107 16.18 9.60
DSM -IV Criteria 107 8.18 5.35
adult criteria was .59 (p < .01); the DSM-IV criteria
and the Utah child criteria was .29 (p < .01); and the
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39
adult and child forms of the Utah criteria was .44 (p <
.01). These significant correlations between the
measures suggest that they assess the same construct.
Further examination of the DSM-IV questionnaire was
performed to determine how many participants might
qualify for the diagnosis of ADHD. At least six
inattentive symptoms or six hyperactive-impulsive
symptoms must be present for diagnostic purposes. When a
participant endorsed greater than the midpoint on the
Likert scale for a particular item on the DSM-IV
questionnaire, this response suggested the presence of
the symptom associated with the item. In this sample, 13
individuals (males = 4 and females = 9) might qualify for
the diagnosis. Note that the DSM-IV also states that
some inattentive or hyperactive-impulsive symptoms must
be present before the age of seven. In addition, these
symptoms must cause impairment in two or more settings.
Thus, these data cannot unequivocally conclude the
presence of ADHD.
Analysis of the CPT suggested the insensitivity of
this measure to detect potentially subtle differences in
performance. Figures 3a and 3b illustrate ceiling
effects. Figure 3a shows the number of omission errors.
The computer recorded an error of omission for each
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40
Std. Dev = 34.13
Mean = 7.9
N = 102.00
0.0 50.0 100.0 150.0 200.0 250.0 300.0 350.0
cpt omission
Std. Dev = 11.18
Mean = 9.6
_ N = 102.00
0.0 10.0 20.0 30.0 40.0 50.0 60.0 70.0 80.0
cpt commision
Figure 3. (a) Histogram of omission errors on the
continuous performance task. (b) Histogram of commission
errors on the continuous performance task.
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4 1
target missed. Figure 3b shows the number of commission
errors. The computer recorded an error of commission for
a response to a nontarget stimulus. Further analyses
excluded the CPT measure because of its inability to
distinguish minimal variation in performance.
Cognitive Functioning
Table 6 presents descriptive statistics for the
cognitive performance measures.
Table 6
Means and Standard Deviations for Cognitive Functioning Measures
Measure n
M SJ2
Little Man 107 .70 sec. .32 sec.
Visual Analysis Level 1 107 2.96 sec. .80 sec.
Visual Analysis Level 2 107 4.24 sec. 1.05 sec.
BMS 107 1.73 sec. .80 sec.
Trails B 107 49.23 sec 13.70 sec.
Stroop Color-Word 107 53.26 words 8.77 words*
BMS = Bexley-Maudsley Category Sorting Test
*The number of words was multiplied by -1 to create scaling
consistency among the cognitive functioning measures.
Table 7 lists the correlations among the measures. All
measures correlated significantly in the predicted
direction except those with the Little Man task.
Nevertheless, this task was included in subsequent
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4 2
analyses because Span and Earleywine (1999) used it as a
measure in the original study.
Table 7
Correlations Among the Cognitive Functioning Measures
LM Vis 1 Vis 2 BMS Trail Stroop
LM
Vis 1 -.13
Vis 2 -.19 . 66**
BMS -.12 .28** .28**
Trails B
I
•
H
. 41** .41**
Stroop -.21* .27** .31**
LM = Little Man
Vis 1 = Visual Analysis 1
Vis 2 = Visual Analysis 2
BMS = Bexley-Maudsley Category Sorting Test
Stroop = Stroop Color Word Test
Table 8 lists the correlations among the 13
measures. A number of correlations are statistically
significant. Nevertheless, data are easier to interpret
using confirmatory factor analysis. In addition,
confirmatory
factor analysis allows correction for attenuation due to
error.
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4 3
Confirmatory Factor Analysis
The data were analyzed using EQS for Windows 5.7b
(Bentler & Wu, 1995). Confirmatory factor analyses
determined which of three possible models was most
consistent with the data. The possible models included a
3-factor model, a single factor model, and a null model.
Descriptions of each model follow.
Confirmatory factor analyses were performed first to
ensure that the three factors of cognitive functioning,
drinking habits, and ADHD best fit the data before
moderator analyses were performed. Several indices were
used to evaluate the magnitude of the overall fit for
each of the models. These included: chi-square, ratio of
chi-square to degrees of freedom (RATIO), and Akaike's
Information Criterion (AIC). Chi-square illustrates the
magnitude of the difference between the model and the
data. RATIO, and AIC illustrate the magnitude of the
difference between the model and the data with respect to
the number of degrees of freedom. Smaller chi-square,
RATIO, or AIC values indicate better overall fit of the
model. Specific aspects of each model were also
evaluated. T-values were computed for each parameter to
determine which associations between variables were
contributing significantly to the fit of the model.
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Table 8
Correlations among Drinking Habits. ADHD, and Cognitive Functioning Measures
Freq Quan Max TLFB Trail Strp Card Vis2 Visl LM DSM UA UC
Freq
Quan .55**
Max . 61** .85**
TLFB .79** .69** .72**
Trail -.08 -.01 .01 -.12
Strp -.12 -.15 -.23*
-K
o
CM
1
.30**
Card
CM
1
00
o
1
-.02 -.08 .39** .26**
Vis2 -.12 -.02 -.06 -.08 .41** .31** .28**
Visl -.12 -.16 -.08 -.12 .41** .27** .28** . 66**
LM .23 -.10 -.08 -.06 -.14 -.21* -.12 -.19 -.13
DSM .25* .14 .15 .16 -.18 -.01 .03 -.06 -.18 -.01
UA .24* .12 .17 .26** -.20*
CM
1
.05 -.07 -.10 -.01 .59**
UC .12 .05 .07 .12 -.12 .03 -.11 -*.01 -.04 .07 .29** 14 4 * *
*p<.05 **p<.01 Cognitive Measures: (LM=Little Man,Vis l=Visual Analysis l,Vis 2=Visual Analysis 2, card=
Bexley-Maudsley Category Sorting Test, Trail = Trails B, Strp=Stroop Color Word Test) Drinking Measures:
(Freq=frequency, Quant=quantity, Max=Maximum, TLFB=Time Line Followback)ADHD Measures:(DSM = DSM-IV
criteria, UA=Utah Criterion Adult, UC=Utah Criterion Child)
45
2. Three-factor model. The 3-factor model specified
that each of the thirteen measures would weigh on only-
one of three underlying factors. The three factors
included: drinking habits, ADHD symptoms, and cognitive
functioning. Thus, quantity, frequency, and maximum
measures of alcohol consumption and the time line follow
back served as indicators of drinking habits. Both forms
of the Utah Criterion, (Wender, Wood, & Reimherr, 1985),
and the DSM-IV criteria served as indicators of ADHD
symptoms. The Little Men Test, both levels of Visual
Perceptual Analysis, the Bexley-Maudsley Category Sorting
Test (Acker & Acker, 1982), Trails B, and the Stroop
Color Word Test served as indicators of
neuropsychological functioning. An illustration of the
model appears in Figure 4. Measures of fit appear in
table 9. The factor loadings were all significant. The
estimated correlation between the factors of ADHD and
drinking habits was significant (r = .23, p < .05).
Therefore, as alcohol consumption increased, reported
ADHD symptoms increased as well. The correlations
between ADHD and cognitive functioning and between
drinking habits and cognitive functioning were not
significant (r= -.15 and r= -.12 respectively).
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4 6
2. Single-factor model. The single-factor model tested
whether the thirteen measures were actually measuring a
single underlying construct such as disinhibitory
disorder. Measures of fit appear in table 9.
3. Null model. Each measure was assumed to measure its
own, independent, underlying factor in the null model.
Measures of fit appear in table 9.
Table 9
Measures of Fit for Each Model Examining the Relation Among Drinking
Habits, ADHD Symptoms, and Cognitive Functioning
Model Chi-square (d.f.) RATIO AIC BBNFI:
3-Factor 107.81 (62) 1.74 -16.19 .81
1-Factor 281.74 (65) 4 .33 151.74 .52
Null 580.36 (78) 7.44 424.36 +
RATIO = Chi square/d.f.
AIC = Chi square - 2*(no. of estimated parameters)
d.f. = degrees of freedom
BBNFI1: Bentler-Bonett Normed Fit Index
BBNFI = (Chi square null - Chi square model)/Chi square null
+ Cannot be computed because fit index is based on null model.
Comparisons Among Models.
Simple comparisons of model fits were made by
examining the chi-squares, ratio of chi sguare to degrees
of freedom (RATIO), and Bentler-Bonett Normed Fit values
in table 9. RATIO values illustrate the magnitude of the
difference between the model and the data with respect to
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4 7
the number of degrees of freedom. Bentler-Bonett values
do not exceed one, and larger values indicate better
overall fit of the model. Values exceeding .8 are
desirable. These measures indicated that the three-
factor model fit the data better than any of the
alternative models. Models were also compared by
subtracting their chi-squares. A significant difference
in chi-squares indicated a better fit of the model to the
data. These measures appear in table 10. The three-
factor model fit significantly better than any of the
alternative models. Figure 4 illustrates this model.
Table 10
Relation Amoncr Drinkina Habits, ADHD SvmDtoms, and Coanitive
Functioning
Comparison DIFF (d.f.)
3 Factor vs. 1 Factor 173.93 (3)*
3 Factor vs. Null 472.55 (16)*
1 Factor vs. Null CANNOT BE COMPUTED’
DIFF = CHI SQUARE MODEL 2 - CHI SQUARE MODEL 1
*p < .001
’ 'Degrees of freedom are equal for both models.
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48
E2
E3
drink
E4
E5
E11
E12
ADHD
E13
E6
E7
E8
Cog Funct
E9
E10
E14
stroop
vis anal 1
cardsort
vis anal 2
trailsb
I'rtm an
quant
utahC
ttfb
utahA
max
dsm
freq
Figure 4. Three-factor model of ADHD symptoms, cognitive
functioning, and drinking habits.
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49
Moderator Analysis
Because only the ADHD and Drinking Habits factors
correlated significantly, a moderator analysis was
appropriate. Statistically, moderators are simply
interactions. The relation between the independent and
dependent variable may correlate highly at one level of
the moderator and not at all at another level. Baron and
Kenny (198 6) stated that moderator analyses are most
easily interpreted when the moderating variable is not
correlated with either the independent or dependent
variables. In this study, cognitive functioning did not
correlate with either ADHD symptoms or drinking habits,
and earlier work (Span & Earleywine, 1999) found that
cognitive functioning moderated the relation between ADHD
and drinking habits. Therefore, stacked two-group
analyses (Hayduk, 1987) were performed in the current
study to determine whether cognitive functioning
moderated the link between ADHD and drinking habits. The
analyses allowed the separate assessment of the
correlation between ADHD and drinking habits for both the
low and high cognitively functioning participants. The
stacked two-group analyses estimated the relation between
ADHD and drinking habits between the high and low groups
in two different ways. The stacked model with equality
constraints set the correlation between the factors of
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50
ADHD and drinking habits equal for both the high and low
cognitive groups. If cognitive functioning did not
moderate the link, the model with equality constraints
would fit the data better. Thus, the high and low
cognitive groups would have the same correlation between
ADHD and drinking habits. The stacked model without
equality constraints allowed the correlation between ADHD
and drinking habits to be freely estimated for both the
high and low cognitive groups. If cognitive functioning
moderated, the model without equality constraints would
fit the data better. Thus, the correlations between ADHD
and drinking habits would differ at each level of
cognitive functioning. A single goodness of fit chi-
square was calculated for each model. Smaller chi-
squares indicated better overall fit of the data to the
model. Subtracting the obtained chi-squares determined
whether there was a significant difference in the fit of
the models.
To perform the analysis, the six scores of cognitive
performance were transformed into standard scores. These
standard scores were summed to form a composite cognitive
efficiency index (CCEI), and a median split was
calculated on the CCEI. The stacked model without
equality constraints fit the data better than the stacked
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51
model with equality constraints, [chi-square = 213.35
(124) vs. 218.69 (125)]. The chi-square difference
between the models was significant (chi-square difference
= 5.34(1), p < .05 ), suggesting that cognitive
functioning moderated the relation between ADHD and
drinking habits. The unconstrained model revealed an
estimated correlation between ADHD and drinking habits of
.472 (p < .05) for individuals low on cognitive
performance which was significantly different from the
correlation between these constructs for individuals high
on cognitive performance [.169 (n.s.)]. Figure 5
illustrates this moderator effect.
The high CCEI group consisted of 53 participants (7
males and 4 6 females). The low CCEI group consisted of
54 participants (18 males and 36 females). Note that a
significant correlation with one half of the original
sample size suggests the robustness of this relation.
Nevertheless, generalizability is limited with this small
sample size as well. T-tests comparing the high and low
CCEI groups on all measures of drinking habits and ADHD
revealed no significant differences. Thus, the
moderating variable of cognitive functioning was not
confounded by any main effects. Nevertheless, ADHD's
diagnostic criteria consist of symptom clusters for the
factors of hyperactivity, impulsivity, and inattention.
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52
Cognitive Functioning Moderates the Link
Between ADHD Symptoms and Drinking Habits
High
Cognitive
Functioning
Drinking
Habits
ADHD
Symptoms
Low
Cognitive
Functioning
Drinking
Habits
ADHD
Symptoms
*p<.05
Figure 5. Cognitive functioning moderates the link
between ADHD symptoms and drinking habits.
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53
Therefore, a more detailed investigation of these factors
was performed. The DSM-IV questionnaire consisting of 18
questions assessed each of these factors. Six questions
assessed hyperactivity. Three questions assessed
impulsivity, and nine questions assessed inattention.
Responses to all questions that assessed a particular
cluster of symptoms were summed to represent the factor
score. T-tests comparing the high and low cognitively
functioning groups on all three factors revealed no
significant differences. These results suggest that both
the high and low cognitively functioning groups displayed
similar clusters of symptoms for ADHD. Closer
examination of the opposite ends of the continuum of
drinking habits revealed similar distributions for both
the high and low CCEI groups. The high cognitively
functioning group included nine non-drinkers, and the low
cognitively functioning group included 11 non-drinkers.
For the purposes of this study, consumption of an average
of 5 or more drinks per occasion indicated binge
drinking. Both the high and low cognitively functioning
groups each contained 11 binge drinkers.
The Role of Coping Strategies
The CSI (Amirkhan, 1990) consists of three proposed
factors that indicate three distinct coping strategies.
These factors include: problem-solving, social-support
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seeking, and avoidance. The CSI has 33 questions, and 11
questions are intended to measure each of the above
factors. Prior to examining the relation between the CSI
and other variables, confirmatory factor analyses were
performed to determine if the data supported the three
proposed underlying factors for this instrument.
Confirmatory factor analyses were carried out using EQS
for Windows 5.7b (Bentler & Wu, 1995) to compare the fit
of this three factor model to one of five other models.
A description of each of the models follows.
1. Three-factor model. The 3-factor model tested
whether the 11 suggested items for problem-solving
weighed on one factor, the 11 suggested items for social-
support seeking weighed on a second factor, and the 11
suggested items for avoidance weighed on a third factor.
Measures of fit appear in Table 11.
2. Two-factor model A. This 2-factor model tested
whether the 11 suggested items for problem-solving and
the 11 suggested items for social-support seeking weighed
on one factor, and the 11 suggested items for avoidance
weighed on a second factor. Measures of fit appear in
Table 11.
3. Two-factor model B. This 2-factor model tested
whether the 11 suggested items for problem-solving and
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55
the 11 suggested items for avoidance weighed on one
factor, and the 11 suggested items for social-support
seeking weighed on a second factor. Measures of fit
appear in Table 11.
4. Two-factor model C. This 2-factor model tested
whether the 11 suggested items for social-support seeking
and the 11 suggested items for avoidance weighed on one
factor, and the 11 suggested items for problem-solving
weighed on a second factor. Measures of fit appear in
Table 11.
5. Single-factor model. The single-factor model tested
whether all 33 items were measuring a single underlying
construct. Thus, the CSI would be measuring a general
coping ability. Measures of fit appear in table 11.
6. Null Model. Each of the 33 items was assumed to
measure its own, independent, underlying factor in the
null model. Measures of fit appear in table 11.
Comparisons Among Models
An examination of the goodness of fit criteria in
Table 11 suggests that the 3-factor model fit the data
better than the other models. In addition, Table 12
includes the differences in chi-squares between the
proposed models. These calculations also demonstrated
that the 3-factor model fit the data significantly better
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5 6
Table 11
Measures of Fit for Each Model Examining the Underlying Factor
Structure of the CSI (Amirkhan, 1990)
Model Chi-square (d.f.) RATIO AIC BBNFI'
3-Factor 863.08 (492) 1.75 -120.92 .60
2-Factor A 1203.69 (494) 2.44 215.69 .44
2-Factor B 976.92 (494) 1. 98 -11.08 .55
2-Factor C 979.87 (494) 1.98 -8.13 .54
1-Factor 1362.00 (495) 2.75 372.00 .37
Null 2149.86 (528) 4.07 1093.86 +
RATIO = Chi-square/d.f.
AIC = Chi-square - 2*(no. of estimated parameters)
d.f. = degrees of freedom
BBNFIi: Bentler-Bonett Normed Fit Index
BBNFI = (Chi square null - Chi square model)/Chi square null
+ Cannot be computed because fit index is based on null model.
than any of the alternative models. Therefore, these
data support that the CSI consists of three separate
scales that measure problem-solving, social-support
seeking, and avoidance. Cronbach/s coefficient alpha for
problem-solving, social-support seeking, and avoidance
were .87, .93, and .77 respectively, suggesting adequate
internal consistency for each of the scales.
As discussed above, an additional question was
included on the CSI that assessed whether participants
would drink alcohol in response to feeling restless and
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57
being unable to finish an important task. Pearson r
correlations were calculated to examine the relation
between the additional question and the three scales of
the CSI. The drinking question and the avoidance scale
correlated significantly in the positive direction (r =
.36, p < .01), suggesting that drinking alcohol may be an
Table 12
Comparisons Among Chi-sauares for Alternative Models Examining the
Factor Structure of the CSI (Amirkhan, 1990)
Comparison DIFF (d.f.)
3 Factor vs. 2 Factor A" 340.61 (2) *
3 Factor vs. 2 Factor B" 113.84 (2) *
3 Factor vs. 2 Factor C" 116.79 (2) *
3 Factor vs. 1 Factor" 498.92 (3) *
3 Factor vs. Null' 1286.78 (36) *
2 Factor A vs. 1 Factor 158.31 (1) *
2 Factor B vs. 1 Factor 385.08 (1) *
2 Factor C vs. 1 Factor 382.13
(1) *
2 Factor A vs. Null 946.17 (34) *
2 Factor B vs. Null 1172.94 (34) *
2 Factor C vs. Null 1169.99 (34) *
1 Factor vs. Null CANNOT BE COMPUTED'
DIFF = CHI SQUARE MODEL 2 - CHI SQUARE MODEL 1
*p < .01
‘Degrees of freedom are equal for both models.
"3-factor model is superior to all others.
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58
avoidant coping strategy. In addition, the drinking
question and the problem-solving scale correlated
significantly in the negative direction (r = -.21, p<
. 05) .
Thus, those individuals who drink as a response to this
type of stressor also engage in less problem-solving
behavior. The drinking question and the social-support
seeking scale did not correlate significantly.
Comparison of Coping Strategies Between Higher and Lower
Cognitively Functioning Individuals
T-tests were performed to determine whether higher
cognitively functioning individuals differed from lower
cognitively functioning individuals on each of the three
scales of the CSI. All t-tests revealed no significant
differences. Therefore, higher and lower cognitively
functioning individuals did not differ on their scores
for the problem-solving, social-support seeking, and
avoidant scales. Thus, these data did not support the
hypothesis that higher cognitively functioning
individuals would endorse significantly more problem
solving strategies. In addition, these data did not
support the hypothesis that lower cognitively functioning
individuals would endorse significantly more avoidant
coping strategies. Means and standard deviations of the
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59
three coping scales for both the high and low cognitively-
functioning individuals appear in Table 13.
Analyzing Moderated-Mediation
Problem-Solving Coping as a Mediator in Lower Cognitively
Functioning Individuals
As discussed above, cognitive functioning moderated
the relation between ADHD symptoms and drinking habits.
Lower cognitively functioning individuals drank in
Table 13
Means and Standard Deviations of the Three Coping Scales for High
and Low Coanitivelv Functioning Individuals
Low Cognitive High Cognitive
Coping Scale M £D n
M SD n
Problem-Solving 27.61 4.29 54 26.77 4.68 53
Social-Support Seeking 24.02 6.35 54 25.74 5.20 53
Avoidant 20.42 4.82 54 19.87 3.70 53
No significant differences were found between the low and high
cognitive groups for each of the three coping scales.
accordance with their ADHD symptoms. Thus, as ADHD
symptoms increased, individuals reportedly consumed more
alcohol. Baron and Kenny's (1986) framework for
detecting mediators was used to determine if problem
solving coping as measured by the CSI mediated the
relation between ADHD symptoms and drinking habits for
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60
lower cognitively functioning individuals. This
situation suggests that problem-solving coping would
covary with both drinking habits and ADHD symptoms. When
problem-solving coping was taken into account, the
relationship between drinking habits and ADHD symptoms
would be significantly reduced. Therefore, ADHD symptoms
would not explain drinking habits when problem-solving
coping was included. For the subsequent analyses, the sum
of standardized scores for the DSM-IV criteria for ADHD,
the Utah criteria for adults, and the Utah criteria for
children was used as the measure of ADHD. The time-line
follow back was used as the measure for drinking habits
because it gave the most complete picture of an
individual's drinking for the previous three months.
Baron and Kenny (1986) suggest that three separate
regression models should be analyzed to determine whether
mediation occurs. First, the mediator is regressed on
the independent variable. In this case, problem-solving
coping was regressed on ADHD symptoms. Second, the
dependent variable is regressed on the independent
variable. Drinking habits was then regressed on ADHD
symptoms. Third, the dependent variable is regressed on
both the independent variable and the mediator.
Therefore, drinking habits was regressed on both ADHD
symptoms and problem-solving coping.
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In order for mediation to occur, Baron and Kenny
(198 6) state that the independent variable must
significantly affect the mediator in the first regression
equation. Second, the independent variable must
significantly affect the dependent variable in the second
regression equation. Third, the mediator must affect the
dependent variable in the third regression equation, and
the effect of the independent variable must be less in
the third equation than the second equation. As
illustrated in table 14, the variable of problem-solving
coping did not meet the criteria to be considered a
mediator. ADHD symptoms did significantly affect
problem-solving coping, and ADHD symptoms also
significantly affected drinking habits. These
significant effects are shown in regression equations 1
and 2 respectively. Nevertheless, no significant effect
of problem-solving coping was found when drinking habits
was regressed on both ADHD symptoms and problem-solving
coping, as demonstrated in regression equation 3. Thus,
the relation between ADHD symptoms and drinking habits
for lower cognitively functioning individuals cannot be
explained by the variable of problem-solving coping.
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6 2
Problem-Solving Coping as a Suppressor in Higher
Cognitively Functioning Individuals
Problem-solving coping was also hypothesized to act
as a suppressor for the relation between ADHD symptoms
and drinking habits. A suppressor variable is the
opposite of a mediator, and it masks a relationship
between two variables. In this situation, problem-
solving coping covaries with both drinking habits and
Table 14
Examining Problem-Solvincr as a Mediator for the Relation Between
ADHD Symptoms and Drinking Habits in Lower Cognitively Functioning
Individuals
D.V. I.V.(s) Beta
(Standardized)
£ E
R2
Regression 1
Prob-Solving ADHD -.393 -3.083 .003
. 155
Regression 2
Drinking Habits ADHD .413 3.268 .002
.170
Regression 3
Drinking Habits ADHD .393 2.834 .007
. 173
Prob-Solve -.051 -.371 .712
ADHD: sum of standardized scores for DSM criteria, Utah Adult
Criteria, and Utah Child Criteria
Drinking Habits: as measured by the Time Line Follow-Back
Prob-Solve: Problem-solving as measured by the CSI
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63
ADHD symptoms. However, when the effects of problem
solving coping are taken into account, a previously non
significant relation between drinking habits and ADHD
symptoms becomes significant. Thus, the effect of
problem-solving coping would suppress higher cognitively
functioning individuals from drinking in accordance with
their ADHD symptoms. The existence of this suppressor
could therefore explain why the correlation between
drinking habits and ADHD symptoms was not significant for
higher cognitively functioning individuals. Problem
solving coping ability would shield these individuals
from drinking in response to their ADHD symptoms. Once
again for the subsequent analyses, the sum of
standardized scores for the DSM-IV criteria for ADHD, the
Utah criteria for adults, and the Utah criteria for
children was used as the measure of ADHD. The time-line
follow back was used as the measure for drinking habits.
The same three regression equations discussed above
for detecting mediators were used. In order for a
suppressor variable to exist, the independent variable
must significantly affect the suppressor in the first
regression equation. Second, the independent variable
must not significantly affect the dependent variable in
the second regression equation. Third, the effect of the
independent variable must now become significant in the
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64
third regression equation that includes both the
suppressor variable and the independent variable as
predictors. As shown in table 15, problem-solving coping
did not meet the criteria to be considered a suppressor
variable. ADHD symptoms did not significantly affect
problem-solving coping in the first regression equation.
In addition, a non-significant relation between ADHD
symptoms and drinking habits in the second regression
equation was not made significant with the addition of
problem-solving coping as a predictor in the third
Table 15
ADHD Svmotoms and Drinkina Habits in Hiaher Coanitivelv Functionina
Individuals
D.V. I.V. (s) Beta
(Standardized)
£ B. R2
Regression 1 .012
Prob-Solving ADHD -.112 -.801 .427
Regression 2 .000
Drinking Habits ADHD .003 .018 .986
Regression 3 .003
Drinking Habits ADHD .009
Prob-Solve .059
.034
.415
.949
. 680
ADHD: sum of standardized scores for DSM criteria, Utah Adult
Criteria, and Utah Child Criteria
Drinking Habits: as measured by the Time Line Follow-Back
Prob-Solve: Problem-solving as measured by the CSI
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6 5
regression equation. Thus, the lack of a relation
between ADHD symptoms and drinking habits for higher
cognitively functioning individuals
cannot be explained by the variable of problem-solving
coping.
The Role of Expectancies
The alcohol expectancies questionnaire addressed how
individuals felt that being a little intoxicated would
affect each of the 18 symptoms for ADHD listed in the
DSM-IV. These questions were summed to form an
expectancy score (M= 68.02 , SD = 16.01). Due to missing
data, 84 participants were included in these analyses
(High cognitive group: n= 43, Low cognitive group: n=
41). A significant correlation between DSM-IV criteria
for ADHD and alcohol expectancy scores was found (r=.24,
p<.05). This positive correlation suggests that
individuals who reported greater ADHD symptomatology also
reported greater expectations that alcohol would relieve
their ADHD symptoms. An independent samples t-test
comparing the expectancy scores between the high and low
cognitively functioning individuals was significant, t
(79) = -2.50, p < .05). Interestingly, higher
cognitively functioning individuals expected alcohol to
relieve their ADHD symptoms significantly more than lower
cognitively functioning individuals. Nevertheless, as
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indicated above no significant differences on any of the
four drinking variables was found between both groups.
Therefore, higher cognitively functioning individuals may
believe that being intoxicated will relieve their
symptoms of ADHD, but they do not actually drink more.
For the subsequent mediator and suppressor analyses, the
variable of ADHD symptoms is measured by the DSM-IV
criteria, and the variable of drinking habits is measured
by the time-line followback.
Analyzing Moderated-Mediation
Alcohol Expectancies as a Mediator in Lower Cognitively
Functioning Individuals
Once again, the series of three regression equations
suggested by Baron and Kenny (1986) were used to
determine if alcohol expectancies mediated the relation
between ADHD symptoms and drinking habits. If mediation
did occur, alcohol expectancies would covary with both
drinking habits and ADHD symptoms. When alcohol
expectancies was taken into account, the relationship
between drinking habits and ADHD symptoms would be
significantly reduced. Therefore, ADHD symptoms would
not explain drinking habits when alcohol expectancies was
included. As shown in table 15, alcohol expectancies
was first regressed on ADHD symptoms. For this first
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67
regression equation, ADHD symptoms significantly affected
alcohol expectancies. Drinking habits was then regressed
on ADHD symptoms. This second regression equation shows
that ADHD symptoms significantly affected drinking
habits. Finally, drinking habits was regressed on both
ADHD symptoms and alcohol expectancies. In this third
regression equation, alcohol expectancies significantly
affected drinking habits. In addition, a previously
significantly relation between ADHD symptoms and drinking
Table 16
Examining Alcohol Expectancies as a Mediatior for the Relation
getweap ADHD Symptoms and Drinking Habits in Lower Cognitively
Functioning Individuals
D.V. I.V.(s) Beta
(Standardized)
£ U
R2
Regression 1
Alcohol Expect ADHD .412 2.860 .007
.170
Regression 2
Drinking Habits ADHD .369 2.886 .006
.136
Regression 3
Drinking Habits ADHD .24 0 1.628 .112
.298
Ale Expect .402 2.728 .010
ADHD: sum of standardized scores for DSM-IV criteria for ADHD, Utah
Adult Criteria, and Utah Child Criteria
Drinking Habits: as measured by the Time Line Follow-Back
Ale Expect: Alcohol expectancies as measured by questionnaire
designed to assess how being intoxicated would affect each of the 18
ADHD symptoms listed in the DSM-IV
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68
habits became non-significant. Thus, alcohol
expectancies met the three criteria and can be considered
a mediating variable. In lower cognitively functioning
individuals, the relation between ADHD symptoms and
drinking habits can be explained as a function of their
expectancies about alcohol. Perhaps, these individuals
drink in accordance with their ADHD symptoms because they
expect alcohol to improve these symptoms.
Alcohol Expectancies as a Suppressor in Higher
Cognitively Functioning Individuals
Alcohol expectancies was examined to determine if it
acted as a suppressor for the relation between ADHD
symptoms and drinking habits. If this case was correct,
alcohol expectancies would covary with both drinking
habits and ADHD symptoms. However, when the effect of
alcohol expectancies was taken into account, a previously
non-significant relation between drinking habits and ADHD
symptoms would become significant. The existence of this
suppressor could therefore explain why the correlation
between drinking habits and ADHD symptoms was not
significant for higher cognitively functioning
individuals. In effect, expectancies about alcohol
consumption would suppress the relation between drinking
and ADHD symptoms. As shown in table 17, alcohol
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6 9
expectancies was first regressed on ADHD symptoms.
Second, drinking habits was regressed on ADHD symptoms.
Third, drinking habits was regressed on both ADHD
symptoms and alcohol expectancies. In all three of these
regression equations, the dependent variables were not
significantly affected by the independent variables.
Therefore, alcohol expectancies did not meet the criteria
for a suppressor variable. Apparently, the non
significant relation between ADHD symptoms and drinking
habits in higher cognitively functioning individuals
cannot be explained by the variable of alcohol
expectancies.
The Role of Drinking Situations
The 13 item-questionnaire assessed what situations
an individual was more or less likely to drink. Due to
missing data, these analyses included 84 participants.
The items were summed to form a drinking situations
score. Lower scores indicate drinking more often in
different situations while higher scores indicate
drinking less often in different situations. The
drinking situations score correlated significantly with
drinking habits as measured by the time line followback
(r=-.58). This results suggests that heavier drinkers
consume alcohol more frequently in different situations.
An independent samples t-test comparing high and low
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70
Table 17
Examining Alcohol Expectancies as a Suppressor for the Relation
Betwen ADHD Symptoms and Drinking Habits in Higher Cognitively
Functioning Individuals
D.V. I.V.(s) Beta
(Standardized)
£ U
Regression 1
Alcohol Expect ADHD -.001 -.009 .993
.000
Regression 2
Drinking Habits ADHD -.089 -.640 .525
.008
Regression 3
Drinking Habits ADHD -.064 -.388 .700
.011
Ale Expect -.082 -.495 .623
ADHD: sum of standardized scores for DSM criteria, Utah Adult
Criteria, and Utah Child Criteria
Drinking Habits: as measured by the Time Line Follow-Back
Ale Expect: Alcohol expectancies as measured by questionnaire
designed to assess how being intoxicated would affect each of the 18
ADHD symptoms listed in the DSM-IV
cognitively functioning individuals revealed no
significant difference. Correlations between each of the
13 items and the 3 coping scales of the CSI (Amirkhan,
1990) were calculated. The social-support seeking scale
correlated significantly with five of the items(p < .05).
The items included drinking: at a party where most
people are drinking (r = .27); at a party where only
some people are drinking (r =.26); in my dorm/apartment
with my roommates (r =.27); in the evening (r =.24); and
to celebrate something good (r =.21). These correlations
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71
suggest that those individuals who do endorse more
social-support seeking coping strategies also report
engaging in more social drinking type behavior. The
avoidance scale correlated significantly with the item
that assessed whether individuals drank to relieve
stress(r =.31). This finding once again supports the
idea that drinking can be considered an avoidant coping
strategy in a stressful situation.
Discussion
When examining the relation between the variables of
ADHD symptoms, cognitive functioning, and drinking
habits, confirmatory factor analysis indicated that the
three-factor model fit the data better than any of the
alternative models. As hypothesized, the thirteen
measures weighed on only one of the three latent
variables stated above. This model fit the data better
than a single-factor model or a null model. Therefore,
the data did not suggest that a single construct such as
disinhibition was assessed.
In addition, the data did not indicate the assessment of
thirteen unique, orthogonal factors either.
Although all factor loadings in the three-factor
model were significant, only the factors of ADHD and
drinking habits correlated significantly. This positive
correlation indicated that individuals who reportedly
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7 2
drank more also reported more ADHD symptoms as well.
Also, as hypothesized, cognitive functioning moderated
the relation between hyperactivity and drinking habits,
supporting previous work (Span & Earleywine, 1999).
Individuals who performed more poorly on
neuropsychological tasks indicated a significant positive
correlation between drinking habits and ADHD symptoms.
Thus, lower cognitively functioning individuals
reportedly drink more as they report more ADHD symptoms.
In contrast, individuals who performed better on
neuropsychological tasks did not have a significant
relation between drinking habits and ADHD symptoms. For
higher cognitively functioning individuals, the number of
ADHD symptoms reported had no impact on drinking
behavior. These data suggest that higher cognitive
functioning may act as a buffer preventing individuals
from drinking more in accordance with their ADHD
symptoms. T-tests revealed no significant differences on
all measures of ADHD and drinking habits between the low
and high cognitively functioning groups. Therefore, no
main effects confounded these findings. Both groups
reported equivalent ADHD symptoms and drinking habits.
Instead, the relation between these two variables differs
among the groups. Furthermore, the both the high and low
cognitively functioning groups displayed comparable
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7 3
variances for the ADHD and drinking measures so
heteroscedasticity did not cause the moderation effect.
This moderator effect illustrates that a third
variable may shield a particular subgroup from
potentially developing a drinking problem. In this case,
higher cognitive functioning prevents the formation of a
link between ADHD symptoms and drinking habits. The
amount of ADHD symptoms experienced by the individuals in
this subgroup has no bearing on the amount of alcohol
they drink. In contrast, the lower cognitively
functioning subgroup does drink in relation to ADHD
symptoms. More alcohol is reportedly consumed when these
individuals experience an increased number of ADHD
symptoms. Nevertheless, the data also show that both
subgroups report the same number of ADHD symptoms and
amount of alcohol consumed. Thus, the results of this
study do not indicate that the individuals in the lower
cognitively functioning group necessarily suffer from
drinking problems. Instead, these findings only reveal
that this lower cognitively functioning subgroup drinks
in accordance with ADHD symptoms. To further illustrate
this point, ADHD symptoms can be viewed as a stressor,
and these individuals drink in response to that stressor.
Whenever an individual drinks in response to a stressor,
the risk for developing an alcohol problem is heightened.
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7 4
The neuropsychological tasks used in this study
measure executive functioning. This cognitive domain
includes effective problem solving, purposive action,
planning, initiation, self-monitoring, and self
regulation (Lezak, 1995). The expectation that alcohol
will relieve ADHD symptoms shows poor planning and self-
monitoring skills. Perhaps these individuals have not
hypothesized that they place themselves at higher risk
for developing an alcohol problem if they drink in
response to their symptoms. Furthermore, poor self
monitoring skills may impair the capacity to note the
temporary effects of alcohol. Alcohol may relieve their
symptoms in the short-term, but long-term relief is
absent. Finally, poor performance on the tasks in this
study may suggest that these individuals are not capable
of planning alternative responses to their symptoms. In
effect, the perseverative responses exhibited by these
individuals on neuropsychological tasks such as the
Wisconsin Card sort are displayed in real-life settings.
These individuals may expect that alcohol is a long-term
solution to their problem despite the potentially
negative effects encountered during long-term drinking.
As hypothesized, alcohol expectancies mediated the
relation between ADHD and drinking habits for lower
cognitively functioning individuals. This finding
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7 5
suggests that positive expectations concerning alcohol's
alleviation of ADHD symptoms may be the mechanism that
drives this subgroup to drink in accordance with ADHD
symptoms. Contrary to what was hypothesized, negative
alcohol expectancies did not suppress the relation
between ADHD and drinking in the higher cognitively
functioning individuals. No significant effects for
coping strategies were observed. The low and high
cognitively functioning individuals did not differ on the
types of coping strategies employed. Problem-solving
coping did not mediate the relation between ADHD and
drinking in the lower cognitively functioning
individuals. Furthermore, problem-solving coping did not
suppress the relation between these two variables in the
higher cognitively functioning individuals.
Several limitations of this study must be noted.
This convenience sample consisted of young college
students. Studies of older adults and individuals who do
not attend college would help to increase
generalizability. This sample also consisted primarily
of light drinkers with the majority (63%) reporting
consumption of three drinks or fewer per week. A sample
with a broader spectrum of drinking habits would also
increase generalizability. In addition, none of the
participants reported a previous diagnosis of ADHD. This
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7 6
research focused on the continuum of ADHD symptoms
present in a normative population. Future research
warrants studying individuals diagnosed with ADHD.
Nevertheless, this research is important because a
continuum of ADHD symptomatology undoubtedly exists in a
clinical population as well. The DSM—IV (APA, 1994)
indicates that an individual must possess a minimum
number of symptoms to warrant a diagnosis of ADHD. Thus,
some individuals will meet the minimum number while
others will exceed that. Although the DSM is categorical
in nature, a spectrum of severity underlies all
disorders.
Previous research has found a significant relation
between the constructs of cognitive functioning with both
drinking habits (Ryback, 1971; Wilkinson, 1987) and ADHD
(Gorenstein et al., 1989). Nevertheless, the current
study did not find a significant link between cognitive
functioning and either ADHD or drinking habits. A number
of reasons possibly contributed to these null findings.
Methodological differences between the previous studies
and the current study may account for the different
outcomes. ADHD children between the ages of 8 and 12
participated in the Gorenstein et al. (198 9) study.
College students with a mean age of 21 participated in
the current study. In addition, Gorenstein et al. (1989)
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77
used different neuropsychological instruments than the
current study. Ryback (1971) hypothesized that a
continuum of cognitive impairment existed with the
Korsakoff's patient at one end and the heavy social
drinker at the other end of the spectrum. The sample in
the current study consisted mainly of lighter drinkers.
Perhaps, cognitive impairment could not result from the
amount of drinks consumed on average by this sample.
Wilkinson (1987) discussed the link between cognitive
performance and the alcoholic as well. He did not
discuss the cognitive impairment of light social
drinkers. Also, a number of measurement issues could
account for the null results in this study. Perhaps the
neuropsychological measures used in this study could not
detect the subtle differences in performance exhibited by
the participants. Previous researchers have noted this
insensitivity of current neuropsychological instruments
to detect subtle cognitive impairment(Tracy & Bates,
1994).
Measurement issues may also contribute to the null
findings regarding coping strategies. Perhaps the CSI
(Amirkhan, 1990) could not detect subtle differences in
coping styles. This measure requires participants to
indicate to what extent they would engage in 33 different
behaviors when faced with a stressful situation. Each of
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78
these behaviors indicates one of three distinct coping
styles: problem-solving, avoidance, and social-support
seeking. This list of behaviors cannot be exhaustive of
all of the possibilities that an individual has in
his/her repertoire. Furthermore, this instrument has not
previously examined coping with ADHD symptoms. Perhaps
this instrument does not capture the range of behaviors
that an individual actually engages in when confronted
with ADHD symptoms. In addition, individuals rate each
behavior on a three-point scale that may not be sensitive
enough to detect subtle variations in coping.
Finally, multiple self-report measures assessed
drinking habits and ADHD symptoms. Four measures
assessed drinking habits, and three measures assessed
ADHD. The high correlations obtained among the measures
for both of these constructs suggested consistency in
participants' self-reports. Previous research suggested
the validity of self-report measures for ADHD (Weyandt et
al., 1995) and drinking (Sobell et al., 1988),
Nevertheless, collaterals might improve the accuracy of
these measures.
Despite the limitations of this study, the observed
relation between ADHD and drinking habits suggests
favorable implications for intervention. The results
indicate that ADHD symptoms may contribute to problem
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79
drinking, supporting previous research (Tarter et al ,
1977; Tarter & Edwards, 1988). Furthermore, this study
found that ADHD individuals with poorer cognitive
functioning are at greatest risk for problem drinking.
These findings could aid in effectively targeting the
appropriate subgroup of individuals most at risk for
ADHD-induced drinking. In addition, alcohol expectancies
mediated the relation between ADHD symptoms and drinking
in this subgroup of lower cognitively functioning
individuals. Thus, lower cognitively functioning
individuals expect drinking to alleviate ADHD symptoms.
This finding can further assist in developing
interventions.
Specific types of manipulations of alcohol
expectancies have effectively reduced alcohol consumption
(Walters, 1998). For example, Darkes and Goldman (1993)
challenged individuals'' expectancies of alcohol's effects
on social and sexual situations. Individuals drank
either alcohol or placebo for three sessions and
participated in situations with social or sexually
related content. Participants then indicated whether
they drank alcohol or placebo during the session. These
individuals only correctly identified the beverage they
drank at chance level (50%). This demonstration
attempted to show participants that behavioral effects of
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80
alcohol result from expectations just as much as
alcohol's chemical properties. Participants subsequently-
decreased their positive alcohol expectancies regarding
sexual and social effects and decreased alcohol
consumption as recorded in diaries. Sharkansky and Finn
(1998) further supported these findings. They
manipulated expectancies in the laboratory and measured
ad lib alcohol consumption. Experimenters either told
participants that drinking alcohol would have no effect,
an unknown effect, or impair their performance on a
specific cognitive task. Participants also understood
that task performance determined the financial incentive
received, with higher performance leading to greater
incentives. Prior to engaging in the task, participants
waited for 20 minutes in a room containing a cooler
filled with beer. Experimenters instructed participants
to drink as much as they wanted and to ask for more beer
if necessary. The group told to expect impairment
reported more negative alcohol expectancies regarding
task performance and consumed significantly less alcohol
than the other groups. In contrast to the findings of
the above studies, previous work indicated that
traditional didactic approaches do not alter alcohol
expectancies nor reduce alcohol consumption (Darkes &
Goldman, 1993). Therefore, educating people about the
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81
potentially harmful effects of alcohol does not appear to
be a particularly fruitful intervention aimed at reducing
consumption.
These previous investigations (Darkes & Goldman,
1993; Sharkansky & Finn, 1998) indicate that the most
efficacious intervention involves directly challenging
alcohol expectancies. Thus, lower cognitively
functioning individuals who report ADHD symptoms, the
high-risk group focused on in the current study, may
benefit from directly challenging their beliefs that
alcohol relieves their symptoms. An intervention could
include bringing these individuals into the laboratory
and having them drink placebo or alcohol. Participants
would then report the effects of the beverage on their
ADHD symptoms while engaging in a task that requires
focused attention. Because Darkes & Goldman (1993)
showed that individuals cannot reliably determine whether
they drank alcohol or placebo, some of these participants
may realize that their ADHD symptoms lessen as a result
of expectancies rather than the pharmacologic effects of
alcohol.
This study also raises interesting questions that
warrant further investigation. Lower cognitively
functioning individuals expect that drinking will
decrease their ADHD symptoms. Yet, the specific property
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82
of alcohol underlying this expectation is unclear.
Although alcohol is classified as a depressant, alcohol's
effects vary on both the ascending and descending limbs
of the blood alcohol curve (BAC). Stimulant effects are
more prominent than sedative effects on the ascending
limb, and sedative effects are more prominent than
stimulant effects on the descending limb (Martin,
Earleywine, Perrine, & Swift, 1993). In addition,
Earleywine and Martin (1993) found that expectancies are
linked to the limb of the BAC. Individuals expect more
stimulant effects on the ascending limb and more
depressant effects on the descending limb.
One possibility underlying the link between ADHD and
drinking habits is that these individuals seek the
stimulant effects of alcohol. Psychostimulants represent
the traditional therapeutic approach for ADHD individuals
(Rapport & Kelly, 1991). Wender (1995) reports that
treatment with stimulant medication has the effect of
almost complete remission of ADHD symptoms. In addition,
ADHD children medicated with Methylphenidate (a
stimulant) have been shown to perform significantly
better on cognitive tasks than controls on placebo
(Rapport & Kelly, 1991) . Therefore, the stimulant
effects of alcohol may lead to the subjective experience
of an alleviation of ADHD symptoms.
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83
Another possibility underlying the link between ADHD
and drinking habits is that individuals seek the sedative
properties of alcohol. Peterson and Pihl (1990)
suggested that ADHD individuals might consume alcohol to
lessen increased physiological reactivity that interferes
with their responses to novel stimuli. Thus, the
sedative effects of alcohol may help to dampen the
increased physiological response. Those individuals who
enjoy the decrease in ADHD symptoms may continue to drink
to maintain a calmer state. This calmer state could lead
to the subjective experience of an alleviation of ADHD
symptoms.
Replicating this study and assessing for
expectancies using the Anticipated Biphasic Alcohol
Effects Scale (Earleywine & Martin, 1993) would help
clarify whether these individuals generally seek the
stimulant or sedative property of alcohol. Also, more
detailed information could be obtained by asking whether
individuals expect the stimulant or depressant effects of
alcohol to alleviate each of the 18 ADHD symptoms listed
in the DSM-IV. Thus, individuals may endorse that
stimulant effects alleviate symptoms of inattentiveness
while depressant effects alleviate symptoms of
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84
hyperactivity. This information could further aid in the
design of effective interventions to prevent problem
drinking.
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85
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92
Appendix
Quantity/Frequency/Maximum Index for Drinking Habits.
We would like to ask about your drinking habits over the last three months.
Please write the appropriate number in the blank.
1. A pproxim ately h o w m any tim es per w eek do you drink alcohol (beer, wine,
liquor, mixed drinks, w ine coolers, etc.)? 0-7. ______
2. A pproxim ately h o w m any tim es per m onth do you drink alcohol
(beer, wine, liquor, m ixed drinks, wine coolers, etc.)? 0-30. ______
In the next questions, assum e I drink = 1 beer, 4 oz. wine, 1 w ine cooler, 1 mixed
drink, o r 1 !/> oz. liquor.
3. H ow many drinks did y o u usually have on an average occasion over the last
three m onths? ________ .
4. W hat's the largest num ber o f drinks you ev er drank o n one occasion in the last
three m onths? ____________.
Reproduced with permission of the copyright owner. Further reproduction prohibited without permission.
Reproduced with permission o f th e copyright owner. Further reproduction prohibited without permission.
DSM-IV Criteria for ADHD Questionnaire.
Please circle the number that best describes you.
1 . I often don’t give close attention to details and make
careless mistakes.
2. 1 often have difficulty keeping my attention when doing tasks.
3. People tell me that 1 don’t listen when they are speaking to m e.
4. I often start things and don’t finish them.
5. I often have difficulty organizing tasks and activities.
6. I don’t like to do things that require me to think for a really
long time.
7. I often lose things.
8. I am easily distracted.
9. I am often forgetful.
10.1 am fidgety.
11. 1 find it difficult to sit for long periods of time even in situations
where I am expected to.
12. I feel restless a lot of the time.
13. 1 don’t enjoy doing quiet leisure activities.
14. I am always “on the go.”
15. I talk a lot.
16. When people ask me questions and I know the answer, 1 often
say the answer before they even finish asking the question.
17. It bothers me when I have to wait my turn
(For example, when waiting in line or playing a game.)
1 8. I find that I often interrupt others.
NEVER ALWAYS
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0 2 3 4 5 6
CJ
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Alcohol Expectancy Questionnaire.
For the next section, please imagine that you drank enough alcohol to feel a little intoxicated. How would being a little
intoxicated affect each of the following for you? Please circle the number that best describes you.
How would being a little intoxicated affect....
Much No Much
Worse Change Better
1 . My ability to pay attention to details. ■ 4 ■ 3 -2 -1 0 +1 +2 +3 +4
2. My ability to keep my attention on a task. -4 -3 -2 -1 0 +1 +2 +3 +4
3. Listening to others. -4 -3 -2 -1 0 +1 + 2 +3 +4
4. Finishing things I start. -4 -3 -2 -I 0 +1 +2 +3 +4
5. Organizing tasks and activities. -4 -3 -2 -1 0 +1 +2 +3 +4
6. Doing things requiring me to think for a really long time. -4 -3 -2 -1 0 +1 +2 +3 +4
7. Keeping track of where I put things. •4 -3 -2 -1 0 +1 +2 +3 +4
8. Not getting distracted easily. •4 -3 -2 -1 0 +1 +2 +3 +4
9. Remembering things. -4 -3 -2 -1 0 +1 +2 +3 +4
lO.Fidgeting. -4 -3 -2 -1 0 +1 +2 +3 +4
1 1 .Sitting for long periods of time. -4 -3 -2 -1 0 +1 +2 +3 +4
12.Feeling restless. -4 -3 -2 -1 0 +1 +2 +3 +4
13.My ability to enjoy doing quiet leisure activities. -4 -3 -2 -1 0 +1 +2 +3 +4
M.Slowing down and not always being on the go. -4 -3 -2 -1 0 +1 +2 +3 +4
IS.Talkinga lot. -4 -3 -2 -1 0 +1 +2 +3 +4
16. Answering questions before people even finish asking. -4 -3 -2 -1 0 +1 +2 +3 +4
17.My ability to wait my turn, (i.e., when waiting in line.) -4 -3 -2 -1 0 +1 +2 +3 +4
18.Interrupting others. -4 -3 -2 -1 0 +1 +2 +3 +4
ro
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Drinking Situations Questionnaire.
Please circle the response that most accurately reflects your behavior.
What are the occasions in which you are more and less likely to drink?
Always
At a party where most people are drinking................ 1
At a party where only some people are drinking 1
At a bar with a large group....................................... 1
At a bar with a few friends....................................... 1
On a date................................................................ I
In my dorm/apartment with a crowd...................... 1
In my dorm/apartment with my roommates I
In my dorm/apartment alone.................................. 1
In the morning....................................................... 1
In the afternoon..................................................... 1
In the evening........................................................ 1
To celebrate something good................................ 1
To relieve stress..................................................... 1
Most of Sometimes Rarely Never
the time
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2 3 4 5
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Asset Metadata
Creator
Span, Sherry A.
(author)
Core Title
Associations and mechanisms among attention deficit hyperactivity disorder symptoms, cognitive functioning, and drinking habits
School
Graduate School
Degree
Doctor of Philosophy
Degree Program
Psychology
Publisher
University of Southern California
(original),
University of Southern California. Libraries
(digital)
Tag
OAI-PMH Harvest,psychology, behavioral,Psychology, clinical,psychology, cognitive
Language
English
Contributor
Digitized by ProQuest
(provenance)
Advisor
Earleywine, Mitchell (
committee chair
), Brekke, John (
committee member
), Gatz, Margaret (
committee member
), Meyerowitz, Beth E. (
committee member
), Raine, Adrian (
committee member
)
Permanent Link (DOI)
https://doi.org/10.25549/usctheses-c16-67656
Unique identifier
UC11338336
Identifier
3018032.pdf (filename),usctheses-c16-67656 (legacy record id)
Legacy Identifier
3018032.pdf
Dmrecord
67656
Document Type
Dissertation
Rights
Span, Sherry A.
Type
texts
Source
University of Southern California
(contributing entity),
University of Southern California Dissertations and Theses
(collection)
Access Conditions
The author retains rights to his/her dissertation, thesis or other graduate work according to U.S. copyright law. Electronic access is being provided by the USC Libraries in agreement with the au...
Repository Name
University of Southern California Digital Library
Repository Location
USC Digital Library, University of Southern California, University Park Campus, Los Angeles, California 90089, USA
Tags
psychology, behavioral
psychology, cognitive