459755
5Journal of Attention DisordersPillow et al.
© 2012 SAGE Publications
JAD18310.1177/108705471245975
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Article
Beliefs Regarding Stimulant Medication
Effects Among College Students With
a History of Past or Current Usage
Journal of Attention Disorders
2014, Vol. 18(3) 247­–257
© 2012 SAGE Publications
Reprints and permissions:
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DOI: 10.1177/1087054712459755
jad.sagepub.com
David R. Pillow1, Lavelda J. Naylor1, and Glenn P. Malone1
Abstract
Objective: To examine the beliefs of ADHD college students concerning stimulant medications and to apply the theory
of planned behavior toward better understanding the factors instrumental in decisions regarding stimulant use. Method:
A cross-sectional, correlational design was used, and students completed a survey under controlled laboratory conditions.
Participants were 193 students taking introductory psychology who self-reported receiving a diagnosis of attention
deficit disorder or ADHD and a treatment history of using stimulant medications. Results: Beliefs regarding the effects
of medication use are represented by four factors ((i.e., improved attention/academics, loss of authentic self, social selfenhancement, and common side effects), where the first three significantly and systematically differentiate between those
currently using stimulants and those who are not. Conclusion: To understand decisions regarding stimulant use, it is
important to consider how college students perceive the positive and negative effects of the medication with respect to
sense of self and social relationships. (J. of Att. Dis. 2014; 18(3) 247-257)
Keywords
ADHD, stimulants, medication intentions, attitudes, beliefs
Properly assessed, beliefs and attitudes predict behavior and
comprise the substrate for decision making (Ajzen, 1985,
1991). Previous studies have linked beliefs and attitudes to
medical adherence across a wide range of domains (e.g.,
Bucks et al., 2009; Schuz et al., 2011). That said, not one
reasonably sized, systematic investigation of college student
beliefs concerning the use of stimulant medication to treat
ADHD has been previously reported. This formative study
was designed to describe beliefs about stimulants held by
college students with a history of ADHD and to examine the
link between those beliefs and choices about whether to use
stimulant medications.
Once viewed as a disorder afflicting individuals only during childhood, ADHD is now recognized as a disorder that
can persist throughout the life span (Barkley, 1998).
Approximately 3.3% to 5.3% of American adults live with
the disorder (Barkley, Murphy, & Fischer, 2008) and
between 2% to 4% of college-aged adults are estimated to
suffer from ADHD symptoms (for a review, see DuPaul,
Weyandt, O’Dell, & Varejao, 2009). Before the 1990s, it
was uncommon to diagnose ADHD after childhood, and the
Diagnostic and Statistical Manual of Mental Disorders (4th
ed.; DSM-IV; American Psychiatric Association, 1994) criteria for a valid ADHD diagnosis currently require symptom onset by 7 years of age. The adequacy of this age-related
threshold has been questioned (Barkley et al., 2008), and
emerging qualitative studies with small samples indicate
that a significant proportion of ADHD college students now
seek treatment and begin medical stimulant use in late adolescence (e.g., Loe & Cuttino, 2008). Decisions regarding
treatment seeking and adherence for young children reside
in the province of the parents, and the research examining
parental beliefs and medication decisions for ADHD children is reasonably mature (Hoza, Johnston, Pillow, &
Ascough, 2006); however, little is known about medical
decision making for individuals who are far less likely to be
closely supervised by parents (e.g., older adolescents and
college-aged students).
Meanwhile, the expression of ADHD symptoms among
college students has been linked to a more difficult time
adjusting to college life, academically (Frazier, Youngstrom,
Glutting, & Watkins, 2007; Norvilitis, Sun, & Zhang, 2010),
socially (Shaw-Zirt, Popali-Lehane, Chaplin, & Bergman,
2005), and psychologically (Reaser, Prevatt, Petscher, &
1
University of Texas at San Antonio, USA
Corresponding Author:
David R. Pillow, Department of Psychology, University of Texas at San
Antonio, One UTSA Circle, San Antonio, TX 78249-0652, USA.
Email: [email protected]
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Journal of Attention Disorders 18(3)
Proctor, 2007). Furthermore, it is well established that stimulants are highly efficacious for treating a myriad of ADHD
symptoms among children, adolescents (Barberesi et al.,
2006), and more recently among adults (Berman, Kuczenski,
McCracken, & London, 2009; Meszaros et al., 2009). It is
thus not surprising that prescriptions of stimulant medications for adults increased at an annual growth rate of 15.3%
between 2000 and 2005 (Castle, Aubert, Verbugge, Khalid,
& Epstein, 2007).
Studies that have investigated stimulant use in college
students tend to focus on stimulant misuse (Davis-Berman
& Pestello, 2010; DuPont, Coleman, Bucher, & Wilford,
2008; McCabe, Knight, Teter, & Wechsler, 2005; Rabiner
et al., 2009a, 2009b) rather than stimulant efficacy. As a
result, less is known about the efficacy of stimulants among
ADHD college students than among children. Even less is
known about attrition rates of prescribed medication routines
among ADHD college students. Research on noncollege
samples indicates that individuals generally stay in treatment
for an average of only 34 months (Barberesi et al., 2006).
Toward understanding why ADHD college students stop
using stimulants as prescribed, a handful of qualitative studies have been conducted. Meaux, Hester, Smith, and Shoptaw
(2006) interviewed 15 college students between the ages of
18 and 21, and found that most of their study participants
were diagnosed and began medication treatment during elementary school; however, more than half (54%) stopped
using stimulants between seventh and ninth grade. According
to Meaux et al., several participants reported moderating
their medication intake in an effort to minimize the negative
effects of stimulants and maximize the positive benefits.
Negative effects included physical side effects (e.g., loss of
appetite, tiredness), psychological effects (e.g., not feeling
like oneself, loss of creativity), and negative social consequences (e.g., withdrawal from social interaction).
Adolescents and college students have also reported
experimenting with medication stoppage to determine
whether they could be successful without medication
(Krueger & Kendall, 2001; Meaux et al., 2006). Along those
lines, a qualitative study of 11 adolescents, ages 13 to 19,
concluded that adolescents assimilated their ADHD diagnosis as an integral and defining aspect of their identity
(Krueger & Kendall, 2001). In addition, Loe and Cuttino
(2008) conducted 16 interviews and concluded that college
students with ADHD perceived that to achieve their academic goals with the aid of stimulant medication, they had
to yield aspects of their genuine self. All 16 respondents
were concerned about when to stop medication. Some
thought they would like to end treatment after college and
return to their “authentic selves.” In all, 2 reported that they
did not intend to ever again use medication.
Understanding the decisions of ADHD college students
to initiate or terminate use of stimulant medications requires
that we first understand their beliefs regarding the effects of
using said medications. The present study was designed to
explore the factors underlying the relevant belief structures
of college students receiving stimulant treatment for ADHD
and to determine whether those beliefs differentiate between
those who are currently using stimulants versus those who
have discontinued use. This study assessed beliefs, attitudes, and related cognitions using a format specified by the
theory of planned behavior (TPB; Ajzen, 1985, 1991). The
TPB posits that the intention to perform a behavior is a
function of personally held general attitudes regarding the
behavior, subjective norms, and perceived control. Attitudes
refer to the general positive and/or negative cognitive/affective
evaluations of the behavior. Subjective norms refer to the
individual’s assessment of what others would want him or
her to do, assuming that the individual considers the opinions of the others to be important. Perceived control refers
to the individual’s assessment of whether he or she has the
capability to perform the behavior. There is abundant
research supporting the application of the TPB to healthrelated behaviors (for a review, see Godin & Kok, 1996).
Moreover, TPB has been used successfully to predict medication compliance (Conner, Black, & Stratton, 1998), illegal substance use (Conner & McMillan, 1999), and exercise
attrition (Yardley & Donovan-Hall, 2007).
TPB specifies that general attitudes are a summative
function of the beliefs one holds regarding the likely effects
of a behavior multiplied by how one evaluates the consequences of those effects. Following the TPB measurement
scheme, participants are asked to make separate judgments
about (a) their beliefs regarding the likelihood of an outcome and (b) their evaluation of the consequence should
that outcome occur. As an example, a participant is asked to
judge the likelihood that using stimulants will cause weight
loss (i.e., a belief assessed on a 7-point scale centered at 0).
A follow-up question is then asked requiring the participant
to make a consequence evaluation (CE) of that outcome
(via a rating scale centered at 0). For example, assuming
that the weight loss occurred, he or she judges whether the
resultant weight loss would be bad or good. After multiplying these ratings together and summing across a large set of
beliefs/consequences, the resultant summative evaluation is
expected to account for general attitudes.
The current study involves the assessment of 50 beliefs
about stimulant medication. The first objective of the study
was to identify the key dimensions underlying these beliefs,
which is where we expected to find evidence of factors
involving perceived medication effects on the autonomy of
the self and participants social relationships. The second
objective was to examine how these key belief structures
differ across current versus past stimulant users. Consistent
with the TPB, we hypothesized that current stimulant
users, compared with past stimulant users, would perceive
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Pillow et al.
the positive effects of stimulant medications as more likely
to occur, and negative effects as less likely. In addition, we
expected that the quantitative analysis conducted here
would shed light on the degree to which college students
vary (or agree) in their beliefs regarding the benefits and
costs of using stimulant medication. Finally, we hypothesized that current stimulant users, compared with past stimulant users, would have more favorable general attitudes,
higher subjective norms, and greater perceived control.
Method
Participants
Participants (N = 193) were undergraduates at a university in
the southwest who completed the study as partial fulfillment
of requirements for an Introductory Psychology course.
Based on prescreening questions, participants self-reported
having previously used stimulant medication to control symptoms of ADHD for a diagnosed disorder. At the outset of a
subsequent data collection session, those who met the initial
screening criteria were again asked to reaffirm their diagnosis
and treatment history. Participants were asked separate questions regarding whether they had been diagnosed with attention deficit disorder (ADD) or ADHD. Separate questions
were asked given that students often fail to recognize that
ADHD refers to general disorder that includes an attentiononly subtype. Only those who confirmed their prescreen
reports and reported having been diagnosed with ADD or
ADHD were included in the analyses.
Participants (60% male) ranged in age from 18 to 28 years
(M = 19.4, SD = 1.81) and were 71% White, non-Hispanic
origin; 22% Hispanic origin; 3% Black; and 4% Asian. These
distributions are generally consistent with those represented
in the broader ADHD literature (e.g., ADHD is relatively
high in males, and samples studied are often pervasively nonHispanic White; Barkley et al., 2008).
Self-reported age of diagnosis ranged from 2 to 24 years
(M = 11.92, SD = 4.60). The median age of diagnosis was
12 years, and the modal age was 8 years (15.1%). A total of
55% reported receiving a diagnosis during childhood (12
years and younger), 41% during their teen years (13 to 19),
and 4% as adults in their 20s. Participants reported having
spent an average of approximately 6 years “mostly on”
stimulant medication, with responses ranging from 1 to 15
years (M = 6.11, SD = 3.38). Participants reported experience with Adderall (73.6%), Ritalin (44.6%), Concerta
(33.2%), Vyvance (12.4%), Focalin (7.8%), and other stimulant medications (each reported by less than 5% of participants). Strattera, a nonstimulant, was used by 6.2% of the
sample, but rarely exclusively. The few who reported having used Strattera exclusively were not included in the final
sample of 193 participants.
Procedure
Item generation and pilot study. To aid in the construction
of our measures, eight self-reported ADHD undergraduates
who had previously ended medication treatment participated in a qualitative pilot study (Naylor & Pillow, 2007).
Pilot participants were asked to discuss the benefits and the
negative consequences associated with taking medication,
and, most importantly, to explain their reasons for ending
stimulant treatment. All the interviewed participants noted
benefits to taking medication: 100% reported improved
concentration, 88% reported lengthened attention span, and
38% reported improved motivation and more emotional
continuity.
The most commonly reported negative consequences
involved social problems and physical side effects (75%).
Consistent with Meaux et al. (2006), most reported liking
themselves better off the medication (75%), feeling that
they lost highly valued social and psychological characteristics when on medication. All participants reported at
least one complaint about physical side effects such as
sleeplessness (63%), weight loss (38%), and/or irritability (25%). Nonetheless, participants indicated that the
physical side effects were less central to their medication
intentions than social and psychological consequences.
Although, pragmatic factors such as diagnostic problems
(38%) and insurance problems (13%) were also reported,
those factors were given far less weight in accounting for
decisions to end medication. The qualitative data summarized above were combined with previous empirical
research and theory to develop rating scales related to the
belief and perceived control components of Ajzen’s
(1985) TPB.
Primary study. Participants completed a computeradministered survey in a controlled laboratory setting that
included two rooms, each designed to accommodate six
persons per session, where persons sat in cubicles with
dividers designed to provide privacy. Informed consent
was obtained in writing for each participant prior to each
session, and all procedures used were approved by the
Institutional Review Board. Participants completed the
survey via computer (i.e., SurveyMonkey), and most completed the survey in 30 to 40 min.
Data collection was conducted across several semesters
spanning from the fall of 2007 to the spring of 2010. After
the first two semesters of data collection, a brief diagnostic
inventory (i.e., the Mini-International Neuropsychiatric
Interview [MINI]) was added to describe whether those in
the selected population (i.e., students who had received a
prescription for stimulant medications) met standard criteria for an ADHD diagnosis. The final sample of 193 participants was composed of 98 from the first two cohorts and 95
who completed the additional measures.
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Journal of Attention Disorders 18(3)
Measures
Likelihood beliefs and CEs. A total of 50 beliefs regarding
the effects of stimulant medications were assessed using a
format derived from the TPB (Ajzen, 1985) in which each
statement is rated on a 7-point scale from −3 (very unlikely)
to 3 (very likely), with a 0 midpoint. A sample belief item
would be, “For me, I think it is (unlikely/likely) that taking
medication could result in better grades.” In the next section, the 50 beliefs were reevaluated with respect to their
yoked consequences; these CE items assume the outcome
(e.g., “If taking medication led to better grades, this would be
[very bad/very good]”). As with beliefs, CEs were rated on a
7-point scale from −3 (very bad) to 3 (very good) with a
0 midpoint. The 50 beliefs and their yoked CEs were designed
to represent the effects of stimulant medication with respect
to five general domains: (a) core symptoms of ADHD,
(b) academic achievement, (c) sociability/social consequences, (d) self autonomy/psychological consequences, and
(e) physical side effects. In all, 10 items were generated for
each domain, with 5 items representing positive aspects of
each general domain (e.g., reduce anxiety) and 5 items representing negative aspects of each general domain (e.g.,
increase irritability).
Attitudes and intentions. General attitudes were assessed
using four items, each rated on a 7-point Likert-type scale.
Two of the items were on scales anchored unfavorable to
favorable (e.g., “My attitude toward using stimulant medication to treat ADD/ADHD in the next semester is __”).
The other two items were anchored from bad to good (e.g.,
“For me, to NOT take stimulant medication to treat ADD/
ADHD next semester would be ___”). Internal consistency
of the scale was strong, Cronbach’s alpha = .95. Intentions
were assessed with two items, each rated on a 7-point scale
anchored from unlikely to likely (e.g., “I intend to take stimulant medication next semester to treat my ADD/ADHD”),
Cronbach’s alpha = .92.
Subjective norms and normative beliefs. Following Ajzen
(1985), subjective norms were assessed with a single item
as follows: “Most people who are important to me think I
should use stimulant medication to treat ADD/ADHD next
semester.” This item was measured on a 7-point scale
anchored, unlikely to likely. Evidence of strong convergent
validity was obtained by correlating this single item with a
measure of normative beliefs, r = .75, p < .001. Participants
provided normative belief ratings for up to 14 persons (e.g.,
mother, father, sibling, best friend, doctor) by completing
each item as follows: “My ___ thinks I (should/should not)
stay medicated next semester.” These normative beliefs
were weighted by a set of yoked ratings expressing the
extent to which participants desire to behave as these persons think they should.
Perceived control. Following Ajzen (1985), seven items
were constructed to assess perceived control (e.g., “I am
confident that I will be able to use stimulants next semester.”) Each of these items were rated on a 7-point Likerttype scale, anchored strongly disagree to strongly agree.
One item was dropped given its low interitem correlation,
average r = .09, leaving six items judged to be internally
consistent, Cronbach’s alpha = .80. Two other subscales
were constructed that tap into the construct of perceived
control by assessing barriers (both scales were rated on a
7-point Likert-type scale): One scale assessed insurance
and financial barriers with four items, Cronbach’s alpha =
.78, and the other assessed time barriers with three items,
Cronbach’s alpha = .49.
ADHD history and diagnostic checks. Background information regarding the participants’ diagnoses and experience
with stimulant medications was obtained via a series of
questions. Regarding their diagnostic history, participants
were asked if they had been diagnosed with either ADD or
ADHD and at what age/grade level they were diagnosed.
Participants were then asked to check—from a list—all
medications used to treat their ADD/ADHD in the past, and
if applicable, to check all medications currently being used.
Each report was examined to verify that all participants
retained in the final data set had clinically relevant experience with stimulant medications. To aid in verifying the
self-reported diagnosis, the protocol was modified midway
through the study by adding a symptom checklist based on
the MINI (Sheehan et al., 1997, 1998).
Demographics. Demographic questions gathered typical
information about age, gender, marital status, and so on.
These items were included to evaluate the characteristics of
our sample as a match to the general ADHD population.
Results
Preliminary Analyses:The Relation
of Beliefs and CEs to Attitudes
Before exploring the nature of the beliefs assessed, it is
important to demonstrate that the set of measured beliefs
correlate strongly with general attitudes. The TPB postulates that general attitudes are a function of the sum total of
each relevant
Belief (B) weighted by its corresponding CE
n
(i.e., ∑ i =1 Bi ∗ CE i ). Using SPSS, the correlation between
the sum total of each CE weighted B with general attitudes
was found to equal .61, p < .001. This confirms the relevance of the items selected; however, the multiplicative
weighting makes item interpretation extremely difficult,
especially when attempting to identify constructs using factor analysis (e.g., double negatives, confounding). Further
investigation supported using beliefs alone. Entering all 50
CE weighted beliefs as predictors in a regression equation
accounted for 55.8% of the variance in general attitudes,
multiple R = .75, p < .001. By comparison, no predictive
utility is lost, but is instead gained when entering the
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Pillow et al.
unweighted beliefs, multiple R = .78, p < .001. In contrast,
entering the consequence evaluations alone results in a multiple R of .61, p < .001. Interestingly, there is almost twice
as much variance in the beliefs (MVariance of Beliefs = 3.28) than
in the consequence evaluations (MVariance of CEs = 1.67).
Factor Analysis of Stimulant Beliefs
To identify the key structures that underlie college students’
general attitudes and decisions regarding stimulant use, a
factor analysis of the 50 beliefs was conducted using maximum likelihood estimation, followed by an oblique (i.e.,
Oblimin) rotation of the data structure. The number of factors retained was determined based on examination of the
scree plot, the number of items with high loadings per factor, and the simplicity of the resultant solution. Four factors, as shown in Table 1, were identified accounting for
44.37% of the variance in the items. These four factors,
computed from factor regression scores in SPSS, predict
general attitudes regarding stimulant use with a multiple
R of .69 via regression analysis. Comparing multiple solutions across extraction methods, rotations, and criteria for
number of factors extracted reveals robust evidence for the
organization of items on the first three factors. These three
factors each account for unique variance in general attitudes, ps < .01, and entered simultaneously yield a multiple
R of .68. The fourth factor accounts for only 0.7% of the
variance in general attitudes, p = .11. Competing solutions
that break up the fourth factor into smaller factors are possible; however, these factor structures involve highly complex loadings and small numbers of items per factor.
Items with loadings below .40 were deleted in constructing scale scores for further analyses. Based on the content
of the items within each factor, we labeled the factors as
follows: (a) improved attention/academics (IAA), (b) loss
of authentic self (LAS), (c) social self-enhancement (SSE),
and (d) common side effects (CSE). The fourth factor—
CSE—was so named as it included a mix of items long recognized to be stimulant byproducts, where some were direct
physical manifestations of stimulants (e.g., loss of appetite,
wakefulness) and some were psychological in nature (e.g.,
increased irritability). Table 1 displays the top factor loadings, and also includes the means for each B and CE. It is
interesting to note that the items clustered with respect to
CEs even though CEs were not used in the factor analysis;
participants perceived the IAA and SSE items to have positive consequences if they occurred, whereas they perceived
the consequences of the LAS and CSE items as largely
negative.
The resulting four scales were found to be internally
consistent, with Cronbach’s alphas of .92, .89, .90, and
.83 for the IAA, LAS, SSE, and CSE, respectively. IAA
correlated significantly with SSE (r = .46) and CSE (r =
.25), ps < .01, but was independent of LAS (r = .01).
LAS correlated inversely with SSE, r = −.20, p < .01,
indicating that there is substantial divergence in the content of these two scales concerning the social self. In
addition to correlating positively with IAA, CSE also
correlated positively with LAS (r = .41) and SSE (r =
.21), ps < .01. The finding that CSE correlated positively
with IAA and SSE is consistent with the notion that stimulant use involves trade-offs between positive and negative consequences.
Past Versus Current Stimulant Users’
Beliefs and consequence evaluations
Regarding Stimulants
The mean beliefs and consequence evaluations were examined across the resultant factor domains and between current and past stimulant users. Specifically, we conducted
two mixed ANOVAs, one treating beliefs as the dependent
variable (DV) and the other treating consequence evaluations as the DV. The first 4 × 2 × 2 ANOVA examined
beliefs about the effects of stimulants treating belief
domain as a within-participant factor (i.e., IAA, LAS, SSE,
and CSE) and current medication status (two levels: current
vs. past) and gender as between-participant factors. A second ANOVA treated consequence evaluations as the DV.
No gender effects were obtained, and hence, gender was
dropped from the analyses.
What do ADHD college students believe are the most likely
effects of using stimulant medications? This question was
answered by probing a main effect that was obtained for the
belief domain, F(3, 184) = 303.51, p < .001. Participants
reported that IAA performance is the most likely effect (M =
1.65). CSE (M = −0.004) were rated on average as neither
likely nor unlikely. SSE (M = −0.66) and LAS (M = −0.81)
were perceived to be somewhat unlikely on average. With a
Bonferroni correction, pairwise comparisons between
means revealed that all differences were statistically significant but one, p < .05 (there was not a reliable difference
between SSE and LAS).
Do those currently using stimulant medications differ from
past users in their beliefs regarding the likelihood of various
stimulant medication effects? Yes. A main effect for medication status was obtained (MCurrent users = 0.19, MPast users =
−0.10), F(1, 186) = 5.98, p < .05; however, this effect was
qualified by a belief domain by medication status interaction effect, F(3, 184) = 5.35, p = .001. As shown in Table 2,
those currently using stimulant medications perceived a
greater likelihood of IAA and SSE than did past users. In
contrast, past users (compared with current users) perceived
a greater likelihood of negative effects consistent with loss
of one’s spontaneous self (LAS). The two groups did not
differ in their overall estimation of whether CSE are likely
or not likely.
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Journal of Attention Disorders 18(3)
Table 1. Summary of Exploratory Factor Analysis for ADHD Beliefs About Stimulant Medication Use Using Maximum Likelihood
Factor Analysis (N = 193).
Factor loadings
IAA
Improve my grades
Improve my concentration and focus
Help me stay on task
Help me achieve my academic goals
Help me keep my school-related priorities balanced
Help me to listen when spoken to directly
Improve my organization
LAS
Make me less expressive in artistic pursuits
Make me feel like I am not myself
Take away important parts of who I am
Decrease my ability to laugh and joke around with others
Lead me to isolate myself from others
Keep me from being creative
Keep from being successful at things other than academics
Keep me from pursuing multiple interests
SSE
Help me get along well with others
Improve my general mood
Improve my social interactions
Allow my true personality to shine
Make me approachable
Enable me to foster friendship
Enable me to get others to see me as I see myself
CSE
Decrease my ability to get a good night of sleep
Cause me to talk excessively
Make me more impulsive
Help me stay awake
Make me restless and fidgety
Improve my energy level
Cause me to lose my appetite
MB
MCE
.872
.840
.829
.795
.694
.651
.632
2.07
2.26
2.05
1.98
1.61
1.70
1.45
2.70
2.63
2.48
2.58
2.31
2.18
2.33
.797
.788
.734
.650
.648
.647
.640
.626
−0.81
−0.01
−0.58
−0.71
−0.31
−1.17
−1.15
−0.89
−2.18
−2.61
−2.62
−2.38
−2.36
−2.45
−2.12
−1.90
.786
.750
.702
.690
.690
.664
.635
−0.18
−0.39
−0.41
−1.28
−0.43
−0.90
−1.16
2.03
2.09
1.99
1.95
1.52
1.49
1.34
−.622
−.615
−.610
−.599
−.555
−.522
−.447
0.067
−0.053
−0.076
1.52
0.23
0.23
1.42
−2.21
−1.06
−0.68
1.14
−2.11
2.04
−1.36
Note: IAA = improved attention/academics; LAS = loss of authentic self; SSE = social self-enhancement; CSE = common side effects. To conserve
space, the seven items with the highest loadings on each factor are shown above. The full list of items is available from the authors on request. The
means for each belief (MB) and consequence evaluation (MCE) are provided for the reader’s information. The higher the MB, the more likely participants
perceived that the effect would occur; the higher the MCE, the more positive the consequence of having the associated effect occur.
Do college students currently using stimulant medication differ
from past users in their evaluation of the consequences of stimulant effects? No. In a second mixed ANOVA using consequence evaluations as the DV, there was neither a main effect
for medication status nor a significant CE type by medication
status interaction. There was, however, a main effect for CE
domain, F(3, 184) = 807.63, p < .001. Participants perceived IAA very positively (M = 2.37), followed by a favorable evaluation of positive social enhancement (M = 1.65).
Participants perceived CSE as having somewhat negative
consequences on average (M = −.89) and perceived LAS as
having very negative consequences (M = −2.29). Each of
these pairwise comparisons, conducted with a Bonferroni
correction, was significant, p < .05.
Differences Between Past
and Current Users on the TPB Constructs
A multivariate ANOVA was conducted to examine differences between past and current stimulant users on the core
constructs of the TBP (i.e., general attitudes, subjective
norms, perceived control, and future medication intentions)
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Pillow et al.
Table 2. Mean Differences Between Past and Current Users of Stimulant Medications on Beliefs About Medication Effects and Core
Constructs in the Theory of Planned Behavior.
Past users (n = 117)
M (SD)
Current users (n = 76)
X>0
Beliefs
Improved attention/academics
1.20 (1.20)
89.5%
Loss of authentic self
−0.55 (1.43)
38.2%
Social self–enhancement
−0.92 (1.21)
21.1%
CSE
−0.01 (1.28)
48.7%
Positively valenced items from the CSE factor
Improves energy
−0.23 (1.89)
Helps me stay awake
1.11 (1.89)
Theory of planned behavior constructs and auxiliary measures of barriers
General attitudes about stimulants
3.50 (1.84)
Subjective norms favoring use
2.57 (1.81)
4.20 (1.47)
Perceived control over use
2.88 (1.98)
Future intentions to use stimulants
Financial barriers to use
2.26 (1.38)
Time barriers to use
3.49 (1.24)
M (SD)
X>0
rpb
2.01 (0.75)**
−0.94 (1.28)*
−0.37 (1.29)*
0.11 (1.17)
97.4%
22.2%
38.5%
51.3%
.38
−.14
.21
.05
0.53 (1.90)**
1.79 (1.56)**
.19
.19
5.86 (1.17)**
5.88 (1.43)**
6.09 (0.98)**
5.88 (1.43)**
1.97 (1.10)
3.03 (1.20)*
.62
.58
.61
.66
−.12
−.18
Note: CSE = common side effects. Percentages are provided to describe how many had scale scores (i.e., “X”) of 0 or above. Point biserial correlations
(rpb) are provided as estimates of effect size.
*p < .05. **p < .01.
as well as two ancillary measures of barriers considered
relevant to using stimulant medications. A significant multivariate effect was obtained for medication status, F(6, 185) =
28.11, p < .001, partial η2= .48. Subsequent univariate tests
indicated significant differences between past and current
stimulant users. Compared with past stimulant users, current stimulant users had more favorable attitudes, higher
subjective norms, greater perceived control, and fewer perceived barriers involving time demands, ps < .01; differences on financial barriers approached significance, p = .08
(see Table 2 for means, standard deviations, and effect
sizes). Notably, the effect sizes for measures of time- and
financial-related barriers were small compared with effects
of the core TPB constructs.
Supplemental Analyses
Individual differences in beliefs about stimulant medications.
Examining the averages alone, current and past stimulant
users evaluated the likelihood of LAS as relatively unlikely,
denoted by means obtained on the negative end of the scale.
That said, not all participants had scale scores in the negative range on LAS, and indeed, there was substantial evidence of individual differences. We calculated the
proportion of persons who evaluated the loss of one’s
authentic self as more likely than not, defined by scale
scores greater than 0. (We similarly examined individual
differences in the other belief domains by using the same
cut point.) Doing so, we found that 38.2% of past users perceive some LAS as more likely than not (compared with
22.2% of current users). In contrast, 38.5% of current users
perceive positive SSE effects as at least somewhat likely
(compared with 21.1% of past users). These percentage
breakdowns are provided for descriptive purposes; note that
any implied proportional differences between groups were
found to be redundant with the corresponding inferential
tests of mean differences shown in Table 2.
Although approximately 48% to 51% of the participants
perceived CSE as more likely than not (i.e., scores greater
than 0), the likelihood of such effects did not differ significantly between current and past stimulant users overall.
However, it is noteworthy that only two of the items in this
cluster were perceived as generally positively valenced via
participant reports of consequence evaluations. On examining these two items in isolation, differences between current
and past users were observed. Specifically, current users
were more likely than past users to report that stimulant
medication would help them stay awake and improve
energy levels. The relevant means and differential proportions are shown in Table 2, where the items are displayed as
breakouts from the general CSE scale score. Interestingly,
current users did not differ from past users in their evaluation of the favorability of these effects.
Is it possible that the items on the CSE scale would better
predict general attitudes and differentiate between past and
present users if not averaged to form a single scale score?
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Journal of Attention Disorders 18(3)
Before concluding that CSE items have little, if any, predictive value, we considered the possibility that these
items—especially the negatively valenced items—might
have greater predictive utility if treated individually. This
possibility was examined by repeating an earlier presented
regression analyses in which the first three factor scores
representing IAA, LAS, and SSE were entered in Step 1,
accounting for 46.8% of the variance in general attitudes
about stimulant medications, multiple R = .684, F(3, 189) =
55.43, p < .001, where the standardized betas were .48,
−.38, and .15, respectively, ps < .01. However, instead of
adding the CSE factor as before, we subsequently entered
all the items that loaded on the CSE factor in Step 2. This
set of items resulted in a marginally significant R2 change of
.058, ΔF(13, 176) = 1.65, p = .08. Further inspection
revealed that three items were related to general attitudes:
(a) concerns about losing “more weight than I need to,”
β = −.16, t = −2.45, p < .05; (b) reduced “desire to join
others at meal time,” β = −.14, t = −1.97, p = .05; and
(c) “improve my energy level,” β = −.17, t = −2.20, p < .05.
However, the two negative side effects concerning loss of
appetite did not differentiate between past and current stimulant users, ps > .20. As noted earlier, current stimulant
users were more likely to report improved energy levels.
Are the effects the same for those meeting diagnostic criteria
for ADHD? To answer this question, a series of ANOVAs
were conducted to compare effects across participants who
(a) completed the MINI and qualified for either a childhood
diagnosis or an adult diagnosis of ADHD (n = 59) and
(b) those who were not administered the MINI (n = 98) or
did not qualify for a diagnosis based on the MINI (n = 36).
The two mixed ANOVAs and the MANOVA conducted as
the primary analyses above were each repeated entering
diagnostic status as a factor, but no statistically significant
interactions involving diagnostic status were obtained.
Discussion
The present research advances the literature by delineating
the nature of the beliefs underlying the attitudes of ADHD
college students toward stimulant use, thereby providing a
framework for better understanding their decisions to initiate or terminate the use of stimulants. A few qualitative
studies have previously explored the reasons college students with ADHD give for using or avoiding stimulant
medication (e.g., Meaux et al., 2006), therein alluding to
possible beliefs about stimulants (e.g., the loss of sense of
self). There are also a few studies that have explored reasons for stimulant use among the general population (e.g.,
Rabiner et al., 2009b). However, the present study is the
first to combine (a) a comprehensive assessment of beliefs
about the effects of stimulant medications, (b) a theory
guided and quantitative measurement/analytical approach,
and (c) a reasonably sized sample of individuals self-
reporting a diagnosis of ADHD with a history of using
prescribed stimulants.
It has been argued that decisions regarding stimulant use
involve trade-offs between benefits and costs (Meaux et al.,
2006). This study found evidence that the benefits can generally be described with respect to two factors summarized
as IAA and SSE. Not surprisingly, improvement in core
ADHD symptoms and academic performance was found to
have the largest effect in differentiating between current and
past stimulant users. However, given previous reports of individuals feeling “not themselves” on stimulants (Loe &
Cuttino, 2008), it was surprising that approximately 38.5% of
the current stimulant users in our study perceived that stimulant use improved their social self (e.g., improves mood,
“allows (their) true personality to shine,” and enables them to
foster friendships). Although it is well established that ADHD
children behave more appropriately in social interactions as a
result of using stimulant medication (Hinshaw, 1991),
research exploring the related social benefits of medication
in adults with ADHD is lacking.
On the other side of the equation, the costs of using stimulant medication can also be summarized with respect to
two factors: LAS and CSE. As the label implies, “common”
side effects involving issues such as appetite, sleeplessness,
and irritability are likely to be readily recognized by physicians and patients, and regularly discussed as issues
involved in adjusting medications. It is unclear whether
physicians are likely to talk about issues involving identity
adjustment, personality changes, and psychological autonomy; however, our findings make clear that these issues are
important to a substantial minority of patients. That is,
issues involving one’s social identity distinguish between
those who have decided to continue using stimulants and
those who have decided to suspend or terminate medication, whereas negative CSE items do not. In this respect, our
findings are consistent with reports that the physical side
effects of stimulants used for treating those with ADHD are
marginal and manageable (Connor, 2002; Efron, Jarman, &
Barker, 1997). Interestingly, our analysis of consequence
evaluations indicates that ADHD college students largely
agree that LAS, if experienced, is more aversive than CSE
consequences (e.g., increased irritability, weight loss, etc.).
The weight given to LAS is understandable given the developmental concerns of those transitioning between late adolescence and young adulthood, an age when constructing
one’s identity and developing intimate relationships are
paramount (Erikson, 1956). Moreover, these quantitative
findings complement previous qualitative studies detailing
the personal stories of students who express concerns
regarding losing one’s true self and/or one’s natural capacity for social fluidity on stimulants (Loe & Cuttino, 2008).
Although current users did not differ from past users in their
beliefs about the likelihood of negatively evaluated CSE
items, current users believed stimulants would help them
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Pillow et al.
stay awake and provide extra energy more than past users.
This is in keeping with studies reporting that students with
and without ADHD have taken stimulants to aid with study
demands (Davis-Berman & Pestello, 2010; DuPont et al.,
2008; Rabiner et al., 2009a, 2009b). Consistent with this
interpretation, “stay awake” correlated .32 with the IAA
factor and was perceived to have largely positive consequences; however, stay awake correlated even more
strongly with the item assessing decreased “ability to get
a good night of sleep,” r = .52, ps < .01. This suggests that
the benefit was tightly coupled with adverse effects, thereby
accounting for its loading on the CSE factor.
Although this study focused largely on beliefs as the
basis for general attitudes, the variables most strongly differentiating current from past stimulant users were general
attitudes, subjective norms, perceived control, and future
intentions. The measures of general attitudes and perceived
control have in common with our assessment of specific
beliefs that they focus on the individual’s intrapersonal cognitions and affective states. Subjective norms, however,
highlight concerns for how others (e.g., parents, friends,
relatives, the individual’s physician, etc.) feel about using
stimulant medication, and may suggest, consistent with the
TPB, that interpersonal processes play an important role in
the medication decisions made by college students. These
subjective norms may contribute independently of beliefs
and general attitudes to influence medication decisions, but
the fact that subjective norms correlate strongly with general attitudes (r = .66) suggests that individuals also develop
or change their beliefs and attitudes about stimulants based
on their associations with others. Simply knowing others
who use stimulant medications may influence decisions,
where the positive experiences of others likely increase
medication compliance; if friends and relatives have negative experiences with stimulants, individuals may be prone
to formulate negative beliefs and cease medication. Of
course, it should also be noted that the direction of causality
may be reversed such that either beliefs or the behavioral
decisions influence one’s perceptions of the subjective
norms. Although the opinions of close others do have bearing, clearly more research is needed to sort out the role that
subjective norms play in the medication decisions of college students.
The primary purpose of the present study was to examine the nature of beliefs accounting for general attitudes
about stimulant use. Our findings highlight that these
beliefs can be organized around four important dimensions to be considered in further research, with the three
factors representing improvements in academics and
attention, LAS, and SSE accounting for most of the variance in general attitudes. CSE were not found here to
account for substantial variance in general attitudes, and
negative side effects did not differentiate between past and
current users, whether CSE were averaged across items
or examined as single predictors. Furthermore, this
research indicates that there are substantial individual differences in general attitudes about stimulant use, the opinions of others regarding whether to use stimulants, and
perceptions of control. The mean differences between current and past stimulant users on core TBP constructs were
very large, suggesting that these measures may have predictive and clinical utility.
The current research provides an important assessment
of the beliefs that differentiate current stimulant users from
past users, but clearly, future research is needed to specify
the temporal or causal sequence relating those beliefs to
behavioral decisions. This will require a longitudinal design
to determine whether those beliefs have predictive utility or
emerge as post hoc rationalizations. The dimensions identified here also have import for exploring interaction effects
consistent with the view that decisions regarding stimulant
medications involve trade-offs (e.g., LAS beliefs may moderate the predictive utility of IAA beliefs).
A limitation of the study concerns whether our participants had a valid diagnosis of ADHD. Only a small percentage of the sample fully qualified for a diagnosis of
ADD or ADHD based on testing using the MINI (Sheehan
et al., 1997). Similar findings have been noted by Barkley
et al. (2008) who argued that criteria for diagnosing adult
ADHD may be overly stringent and that symptom count
cutoffs are, to some extent, arbitrary. That said, no substantial differences in the pattern of results obtained when
we examined the data for only those who, based on a retrospective assessment, met criteria on the MINI either as
children or as adults.
Although additional research will be necessary to answer
the questions raised above, the present study sheds light on
important individual differences to be considered in how selfreported ADHD college students understand the effects of
stimulant medication. This study identifies important tradeoffs that self-reported ADHD college students perceive: On
one hand, there are benefits with respect to symptom control,
academic progress, and—in some cases—facilitation of a
positive social image, and on the other hand, students must
weigh the possible loss of their autonomous and natural sense
of self, along with commonly experienced side effects.
Acknowledgments
The authors would like to thank Tamara Leyva and Cristina
Cadena for their help in collecting this data and background
research. They also thank Michael Baumann, Robert Fuhrman,
Michelle Little, and Jonathan Pillow for comments and suggestions on previous drafts of this manuscript.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with
respect to the research, authorship, and/or publication of this
article.
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Journal of Attention Disorders 18(3)
Funding
The author(s) received no financial support for the research,
authorship, and/or publication of this article.
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Author Biographies
David R. Pillow is an associate professor at the University of
Texas at San Antonio. He trained as a social/quantitative psychologist
at Arizona State University and subsequently completed postdoctoral work on the self-perceptions of ADHD children at the
Western Psychiatric Institute and Clinic. He conducts research in
the interface of social and clinical psychology, focusing broadly
on issues of self-evaluation and identity negotiation. One line of
his current work focuses on the self-perceptions of college students with ADHD; a second line focuses on belongingness/rejection. He teaches psychological statistics at the undergraduate and
graduate levels. He enjoys traveling with his wife and children,
visiting wineries, and long weekend walks with his dog.
Lavelda J. Naylor graduated summa cum laude from the
University of Texas at San Antonio and has a BA in psychology.
Her honor’s thesis generated part of the data reported in this article under the direction of David Pillow. She is pursuing a master’s
of arts in marriage and family therapy at St. Mary’s University in
San Antonio and enjoys spending time with her family. For contact information, publications, and current research interests, visit
laveldanaylor.wordpress.com
Glenn P. Malone recently completed his master’s degree in psychology at the University of Texas at San Antonio and has primary
interests in positive psychology. His thesis included the construction of a general belongingness scale and testing the belongingness hypothesis. In addition to his master’s degree, he has a
bachelor of science in education from Texas State University. He
is currently pursuing a career in research. He enjoys sports and
vacationing.
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