Dimensions of impulsive behavior: Personality and behavioral measures

Brady Reynolds a, Amanda Ortengren b, Jerry B. Richards c, Harriet de Wit d,*
a Department of Pediatrics, Columbus Children
s Research Institute, The Ohio State University, 700 Children
s Drive, J1401 Columbus, OH 43205, United States b Olin
Neuropsychiatry Research Center, Institute of Living at Hartford Hospital, United States c Research Institute on Addictions, University at Buffalo, State University of
New York, United States d Department of Psychiatry, The University of Chicago, MC3077, 5841 S. Maryland Ave., Chicago, IL 60637, United States
Received 13 September 2004; received in revised form 21 March 2005; accepted 22 March 2005 Available online 8 September 2005
Abstract
Impulsivity as a behavioral construct encompasses a wide range of what are often considered maladaptive behaviors. Impulsivity has been assessed using a variety of
measures, including both self-report personality questionnaires and behavioral tasks, and each of these measures has been further subdivided into separate components
which are thought to represent different underlying processes. However, few studies have employed both personality measures and behavioral tasks, and so the relations
among these measures are not well understood. In one analysis we examined correlations between three widely used personality measures (i.e., BIS-11, I7, and MPQ) and
four laboratory-task measures of impulsive behavior (behavioral inhibition (2), delay discounting, and risk taking) in 70 healthy adult volunteers. The correlations
among the various self-report measures were high, but self-reports were not correlated with behavioral-task measures. In a second analysis we performed a principal-
components analysis using data from the four behavioral tasks for 99 participants. Two components emerged, labeled ‘‘impulsive disinhibition’’ (Stop Task and Go/No-Go
task) and ‘‘impulsive decision-making’’ (Delay-Discounting task and Balloon Analog Risk Task). Taken collectively, these analyses support other recent findings
indicating that self-report
0191-8869/$ – see front matter
2005 Elsevier Ltd. All rights reserved. doi:10.1016/j.paid.2005.03.024
* Corresponding author. E-mail addresses: reynoldb@ccri.net (B. Reynolds), hdew@midway.uchicago.edu (H. de Wit).
www.elsevier.com/locate/paid
Personality and Individual Differences 40 (2006) 305–315
and behavioral tasks probably measure different constructs, and suggest that even among the behavioral measures, different tasks measure different, perhaps unrelated,
components of impulsive behavior.
2005 Elsevier Ltd. All rights reserved.
Keywords: Impulsivity; Laboratory measures; Self-report measures; Correlation; Principal component; Delay Discounting; Human
1. Introduction
Impulsivity is a multidimensional concept that has been defined variously as an inability to wait, a tendency to act without forethought, insensitivity to consequences,
and an inability to inhibit inappropriate behaviors (e.g., Ainslie, 1975; Barkley, 1997; Barratt & Patton, 1983; Eysenck, 1993; Rachlin & Green, 1972). Accordingly,
various measures have been developed to assess impulsive behavior, including self-report measures of personality that rely on an individual
s self-perceptions of
their behavior, and behavioral tasks that measure overt behavior related to specific dimensions of impulsivity. Although both self-report and behavioral measures have
been studied extensively in separate research contexts, they are rarely used together in the same study, and relatively little is known about their relation to each
other (Lane, Cherek, Rhodes, Pietras, & Techeremissine, 2003; White et al., 1994). The present analyses used a sample of healthy volunteers to investigate relations
between self-report and behavioral measures of impulsivity, and between the subcategories of impulsive behavior that each of these instruments is designed to measure.
Both self-report and behavioral-task studies support the idea that impulsivity is strongly linked to substance abuse, both as a determinant and a consequence of drug-
taking (de Wit & Richards, 2004; Jentsch & Taylor, 1999; McGue, Iacono, Legrand, Malone, & Elkins, 2001; Tarter et al., 1999). Numerous studies have shown that drug
users score higher than non-users on self-report measures of impulsivity, sensation seeking, and inattention (Sher & Trull, 1994; Slater, 2003; Tercyak & Audrain-
McGovern, 2003; Zuckerman, Ball, & Black, 1990). Several recent studies also have shown that drug users, including smokers, alcoholics, cocaine users, and opiate
addicts, perform more impulsively on behavioral tasks designed to measure impulsivity, such as delay discounting and behavioral inhibition tasks (Bickel, Odum, &
Madden, 1999; Fillmore & Rush, 2002; Lejuez et al., 2003; Madden, Petry, Badger, & Bickel, 1997; Mitchell, 1999; Petry & Casarella, 1999; Reynolds, Richards, Horn, &
Karraker, 2004b; Vuchinich & Simpson, 1998). These studies support the idea that impulsive behavior is related to substance abuse. Further investigation of the role of
impulsivity in substance abuse requires a better understanding of the equivalence of different assessment methods and of the factor structure of impulsive behavior. One
basic question is whether self-report and behavioral measures assess the same processes. The findings from the few studies that have used both types of measure have
been equivocal. Some studies indicate that performance on delay or probability discounting tasks is correlated with self-report measures of sensation seeking,
extraversion, or impulsivity and venturesomeness (Kirby, Petry, & Bickel, 1999; Richards, Zhang, Mitchell, & de Wit, 1999; Swann, Bjork, Moeller, & Dougherty, 2002),
but in other studies self-reports are not related to behavioral indices (Crean, de Wit, & Richards, 2000; Lane et al., 2003; Mitchell, 1999; Reynolds et al.,
306 B. Reynolds et al. / Personality and Individual Differences 40 (2006) 305–315
2004b; White et al., 1994). There also is relatively little information about interrelations among different behavioral measures of impulsivity. However, several recent
studies suggest that different behavioral measures may reflect separate underlying processes. Sonuga-Barke (2002) noted that some children with Attention Deficit
Hyperactivity Disorder (ADHD; APA, 1994) perform more poorly than control subjects on one task measure of impulsive behavior, i.e., tasks assessing delay aversion,
whereas other ADHD children perform more poorly on a different measure, i.e., a measure of inhibitory control (Solanto et al., 2001). Sonuga-Barke proposed that
separate neural systems underlie these different types of impairments. Lane et al. (2003) used a principal-components analysis to examine relations among behavioral
measures in 32 healthy adult volunteers and found that behavioral inhibition was not related to intolerance of delays. It is notable that both the Sonuga-Barke and
Lane analyses led to a similar conclusion that impairments in inhibition are not related to impairments in delay intolerance. Further analyses of this kind examining
the interrelations among additional behavioral measures, as well as other self-report measures, will help to characterize the underlying component structure of the
different subtypes of impulsive behavior. Here we report on relations between personality inventories and behavioral measures of impulsivity in a sample of healthy
volunteers. The report consists of two separate analyses. First, we explore correlations among three widely used self-report measures of impulsivity and four
behavioral tasks purported to assess impulsivity. Second, we explore the component structure among the four behavioral impulsivity tasks using a principal-components
analysis. The personality measures for the first analysis included the Barratt Impulsiveness Scale-11 (BIS-11, Patton, Stanford, & Barratt, 1995), I7 (Eysenck, Pearson,
Easting, & Allsopp, 1985), and the Multidimensional Personality Questionnaire (MPQ, Patrick, Curtin, & Tellegen, 2002). The behavioral tasks included two measures of
behavioral inhibition, a delay-of-reward measure, and a measure of risk taking. Based on the previous findings described above, we hypothesized that correlations among
the various personality measures would be high, but that personality measures would be only modestly or poorly correlated with the behavioral measures. Further, we
expected that separate inhibition and delay-related components would be identified from the principal-components analysis. Risk taking has elements of both inhibition
and reward delay, and therefore this analysis was more exploratory in nature.
2. Method
2.1. Participant recruitment
The participants for these analyses were recruited from a university environment. The 70 participants in the correlation analysis participated in a single session in
which they performed all measures. The principal-components analysis included these 70 participants as well as 29 participants from a study examining effects of
diazepam on impulsive behavior (Reynolds, Richards, Dassinger, & de Wit, 2004a). The data for the present analysis used their scores on the session when they received
placebo. All participants were recruited via posters, advertisements in newspapers, and word-of-mouth referrals. Eligible candidates completed a psychiatric symptom
checklist (SCL-90; Derogatis,
B. Reynolds et al. / Personality and Individual Differences 40 (2006) 305–315 307
1977) and a health questionnaire that included a detailed section on current and lifetime recreational drug use and history. A semi-structured psychiatric interview
was conducted to rule out potential participants who met criteria for major DSM IV diagnoses (APA, 1994). The exclusion criteria included a history of an Axis I
psychiatric disorder (including substance use disorder), less than a high-school education, smoking more than five cigarettes per day, and a lack of English fluency. The
University of Chicago Hospital Institutional Review Board approved the protocol.
2.2. Procedure
2.2.1. Correlation analyses Participants (N = 70) completed a 4-h session between 12:00 and 20:00 h. Upon arrival at the laboratory, they provided a urine sample that
was tested for recent drug use. None of these screenings were positive. Participants completed the personality measures (see below) and then relaxed for 20 min before
performing the laboratory behavioral tasks (see below). The order of the tasks was counterbalanced across participants. After the tasks, participants were debriefed
and received their payment.
2.2.2. Principal-components analysis In addition to the 70 participants just described, data were used from 29 additional participants who participated in a 3-session
drug study with diazepam (Reynolds et al., 2004a). For this analysis only data from the placebo session were used, after determining that there were no carry-over
effects from previous drug sessions.
2.3. Personality inventory measures
2.3.1. Barratt Impulsiveness Scale-11 (BIS-11, Patton et al., 1995) The BIS is a widely used and well-validated personality measure of impulsivity. It consists of 30
statements, which form six factors determined by principal-components analyses: attention, motor impulsivity (e.g., ‘‘I do things without thinking’’), self-control,
cognitive complexity (e.g., ‘‘I make up my mind quickly’’), perseverance, and cognitive instability.
2.3.2. I7 (Eysenck et al., 1985) The I7 is designed to measure impulsivity within the framework of Eysenck
s theory of personality. It consists of 54 items
categorized into three scales based on principal-components analyses. The three scales are impulsiveness (e.g., ‘‘Do you generally do or say things without stopping to
think’’?), venturesomeness (e.g., ‘‘Would you enjoy fast driving’’?) and empathy (e.g., ‘‘Does it affect you very much when one of your friends seems upset’’?).
2.3.3. Multidimensional personality questionnaire (MPQ, Patrick et al., 2002) The MPQ is a comprehensive personality questionnaire, which has three super factors
(Positive Emotionality, Negative Emotionality, and Constraint) and eight primary factors. Because the present analysis focuses on impulsivity, only scores from the
Constraint factor will be reported here.
308 B. Reynolds et al. / Personality and Individual Differences 40 (2006) 305–315
2.4. Laboratory behavioral tasks
2.4.1. Stop Task (Logan, Schachar, & Tannock, 1997) The Stop Task is designed to assess participants
ability to inhibit a prepotent motoric response. Participants
are instructed to respond to a visual go signal as quickly as possible, but to withhold this response when an auditory stop signal is presented. The stop signal is
presented on 25% of trials at varying delays (in milliseconds) following the go signal. The delay to the stop signal is varied systematically across trials according
to the participant
s performance until a delay is found at which the participant inhibits his or her responses on approximately 50% of trials. The stop reaction time
(SRT) can be inferred from the delay by subtracting the final mean delay at which the tone is presented from the mean go reaction time (GRT). Both GRT and SRT are
measured in milliseconds. Longer SRTs are taken to indicate more impulsive responding, or poor behavioral inhibition.
2.4.2. Go/No-Go Task (Newman, Widom, & Nathan, 1985) The Go/no-go task is a learning task designed to assess the ability to inhibit inappropriate responses. In this
task, participants are presented with eight numbers, of which four are designated ‘‘correct’’ and four ‘‘incorrect.’’ They are instructed to respond only to the
correct numbers. They are rewarded for correct responses (+10 cents) and penalized for incorrect responses (
10 cents). The outcome measures are errors of omission
(withholding a response when a ‘‘correct’’ stimulus is presented) and errors of commission/false alarms (responding to an ‘‘incorrect’’ stimulus). Participants
received the amount of money earned at the end of the session. The measure of impulsive behavior in this task was the number of errors of commission, which indicate an
inability to inhibit inappropriate responses.
2.4.3. Delay-discounting task (Richards et al., 1999) Delay-Discounting measures the relative value of immediate versus delayed rewards. This version of the task uses
a computerized adjusting-amount procedure to measure discounting of delayed monetary reinforcers. In a series of choice trials, participants are offered the choice
between $10 available after a delay (0, 2, 30, 180 and 365 days) or a smaller amount available immediately. On successive trials, the amount of immediate money is
adjusted in increments of $0.50, depending on the participant
s response on the previous trial, until an immediate amount is reached that the participant chooses
equally often as the delayed reward ($10). This value is referred to as the indifference point. The indifference points determined for five different delays (0, 2, 30, 180
and 365 days) are plotted, and a discount function is derived using a curve-fitting analysis. The curve-fitting analysis yields a k-value, which provides a quantitative
index of the steepness of the discount curve: Higher k-values reflect greater discounting by delay and therefore greater impulsivity. In the procedure used in this
study, participants received the money from one of their choices, on a probabilistic basis. At the end of the session participants rolled a die, and if a 1 or 6 was
rolled, one of their answers was randomly selected and they were rewarded accordingly.
2.4.4. Balloon analogue risk task (BART, Lejuez et al., 2002) The BART is a measure of risk taking, in which participants can earn or lose points redeemable for money.
Participants ‘‘pump up’’ a balloon presented on a screen by clicking a computer
B. Reynolds et al. / Personality and Individual Differences 40 (2006) 305–315 309
mouse. For each pump, a counter on the screen increases by a certain amount of money (1/2, 1, or 5 cents). Participants may transfer the money in this counter to a
bank
at any time but this also terminates the trial and starts the next balloon. After an unpredictable number of pumps
the balloon may explode,
resulting in
a loss of the money accumulated in the counter (but not the bank). As a balloon expands and money accumulates, the risk of explosion and money loss increases.
Participants who emit more pumps before banking (at the risk of losing their accumulated earnings on the trial) are considered more impulsive. In this study
participants received a portion of their accumulated earnings at the end of the session, based on a random drawing.
2.5. Analyses
For ease of analysis and interpretation, all outcome scores for the personality and behavioral tasks were converted so that higher values represented greater
impulsivity. In addition, the k-values derived from the delay-discounting procedure were log-transformed to improve normalization of the scores (e.g., Richards et al.,
1999). Data were analyzed using SPSS version 11.5. Correlations were analyzed using Pearson Correlation Coefficients with a significance criterion of p < .05, two-tailed
tests. For the principal-components analysis, components having eigenvalues P1 were retained. Component loadings of .5 or higher within identified components were
considered significant loadings. We also used a varimax rotation method with Kaiser Normalization to maximize each measure
s loading on a single component. As a
secondary analysis, we also compared impulsivity scores for all the measures across females and males using independentsamples t-tests.
3. Results
3.1. Participants
Table 1 shows the demographic data for the participants. Participants were primarily young Caucasian adults in their early 20s. Roughly equal numbers of males and
females participated, and most were either full time college students or recent college graduates.
3.2. Correlation analyses
Table 2 shows the correlation matrix for all of the measures of impulsivity. Most of the self-report measures were positively correlated with other self-report
measures, both between subscales of the same instruments (e.g., BIS-11) and between instruments (i.e., BIS-11, I7 and MPQ). By contrast, of the 40 correlations
conducted between self-report and behavioral measures, only one correlation was significant. There was a positive correlation between Cognitive Complexity of the BIS-11
and errors of commission on the Go/No-Go Task. With reverse coding of Cognitive Complexity, participants who were less ‘‘cognitively complex’’ made more false alarms
on the Go/ No-Go Task. Notably, there also was only one significant correlation among the behavioral measures. Participants with longer Stop RTs on the Stop Task made
more false-alarm errors on the Go/No-Go Task.
310 B. Reynolds et al. / Personality and Individual Differences 40 (2006) 305–315
3.3. Principal-components analysis
The principal-components analysis, which used only behavioral measures, resulted in two principal components with eigenvalues P1(Table 3). For the first component,
loadings were
Table 1 Participant demographics
Correlational analyses (N = 70) Age (mean, SD years) 22.92 (3.67) Sex (male/female) 35/35 Race (Cauc/Black/Asian/Unknown) 48/5/16/1 Education (n) High school/partial
college 1/10 College degree/advanced degree 18/18 Full time student 23
Principal-components analysis (N = 99) Age (mean, SD years) 22.90 (3.12) Sex (male/female) 51/48 Race (Cauc/Black/Asian/Unknown) 68/9/19/4 Education (n) High
School/partial college 2/14 College degree/advanced degree 24/19 Full time student 40
Table 2 Correlation matrix (N = 70) comparing all measures of impulsivity 1 2 3 4 5 6 7 8 9 10 Behavioral tasks 11 12 13 14 1 1.0 .505** .605** .477** .520** .536**
.555** .130 .174 .332**
.080 .134 .172 .003 2 1.0 .589** .265* .451** .515** .731** .270* .157 .576**
.004
.140
.067 .105 3 1.0 .512** .595** .357** .655**
.282* .093 .625** .025 .112 .187 .048 4 1.0 .484** .110 .402**
.050 .024 .123 .042 .030 .254*
.230 5 1.0 .531** .492** .145 .144 .516**
.022 .131 .116
.042 6
1.0 .460** .191 .346** .389**
.075 .090
.023 .170 7 1.0 .260* .233 .580** .021 .021 .121 .034 8 1.0 .013 .446**
.045 .023
.016 .164 9 1.0 .168 .116 .062
.200
.018 10 1.0
.110 .002 .162 .162 11 1.0
.035
.083
.049 12 1.0 .278* .014 13 1.0 .074
1. BIS-11: Attention ++; 2. BIS-11: Motor Impulsivity; 3. BIS-11: Self-Control ++; 4. BIS-11: Cognitive Complexity ++; 5. BIS-11: Perseverance ++; 6. BIS-11: Cognitive
Instability; 7. I7: Impulsivity; 8. I7: Venturesome; 9. I7: Empathy ++; 10. MPQ: Constraint ++; 11. Delay-Discounting Task; 12. Stop Task; 13. Go/No Go Task; 14. BART.
Note: ++ = reverse coded. * p < .05 (two-tailed test). ** p < .01 (two-tailed test).
B. Reynolds et al. / Personality and Individual Differences 40 (2006) 305–315 311
significant for the Stop Task and the Go/No-Go Task (.809 and .767, respectively) but not for the Delay-Discounting task or the BART. This first component might be
labeled ‘‘impulsive disinhibition’’ because both the Stop Task and Go/No-Go Task can be considered measures of inhibition. For the second, component loadings were
significant for the Delay-Discounting task and the BART (.768 and .644, respectively) but not the Stop Task or Go/No-Go Task. This component might be labeled
‘‘impulsive decision-making’’ because each measure involves an evaluation and decision between different consequent outcomes. Men and women scored similarly on all
measures except the Empathy subscale of the I7 and the Delay-Discounting measure. The mean Empathy score for females was 14.03 (SD = 2.69) and for males 12.65 (SD =
2.79), meaning that women were more empathic than men. This difference was significant, t(68) = 2.11, p = .039, two-tailed test. The mean non-logged k-value on the
Delay-Discounting measure was 0.0697 (SD = .097) for women and 0.0434 (SD = .108) for men. Using a log-transformed version of these data, this difference was
significant, t(97) = 2.99, p = .004, two-tailed test. Women discounted more (i.e., performed more impulsively) than men.
4. Discussion
This analysis examined relations among three self-report inventories and four behavioral-task measures of impulsive behavior. There were two main findings. First, we
found there were correlations between several of the subscales of the self-report measures, but these self-report measures were generally unrelated to the task
measures. Second, we found the task measures fell into two components, or categories. One component included the Stop Task and Go/No-Go Task, corresponding to measures
of ‘‘impulsive disinhibition,’’ and the second component included Delay Discounting and the BART, which could be referred to as ‘‘impulsive decision-making.’’ These
findings add to a growing literature suggesting that self-report measures and behavioral measures assess different forms of impulsivity, and that behavioral measures of
impulsivity reflect at least two apparently unrelated subtypes of impulsive behavior. Few sex differences were observed in the present study, either on self-report
measures of impulsivity or on the behavioral tasks. The only behavioral measure on which men and women differed was the Delay-Discounting task, on which women responded
in a more impulsive manner (i.e.,
Table 3 Principal-components analysis (N = 99) for four behavioral measures Rotated components 12 Eigenvalues 1.30 1.06 Variance 32.5% 26.4% Stop Task .809
.149
Go/No-Go Task .767 .229 Delay-Discounting Task
.114 .768 BART .158 .644
Note: Component loadings of .5 or higher were considered significant and are in bold.
312 B. Reynolds et al. / Personality and Individual Differences 40 (2006) 305–315
discounted more steeply). This finding is not consistent with previous studies using this type of measure, in which men either discounted more than women (e.g., Kirby &
Marakovic, 1996), or performed similarly (Logue & Anderson, 2001; Reynolds, Karraker, Horn, & Richards, 2003). An important finding of this study was that self-report
measures of the trait of impulsivity were not related to performance on specific behavioral tasks. Here, only one relatively weak correlation was observed between
Go/No-Go performance and Cognitive Complexity (BIS). It is notable that several other previous studies have failed to observe relations between self-report and
behavioral measures of impulsive behavior (e.g., Crean et al., 2000; Lane et al., 2003; Mitchell, 1999; Reynolds et al., 2004b; White et al., 1994; but see also Kirby
et al., 1999; Richards et al., 1999; Swann et al., 2002). The findings suggest that the behavioral tendencies detected with self-report scales are not the same as those
detected with the behavioral tasks. It should also be noted that self-report measures differ from behavioral measures in several fundamental ways. With self-report
measures, participants must recognize and report on their own behavioral tendencies in various contexts relative to other individuals, and these self-perceptions may
not always accurately reflect their behavior. In contrast, performance on behavioral tasks is objective and thus less sensitive to biased self-perceptions. On the other
hand, the behavioral tasks typically measure only one specific dimension of behavior (e.g., the value of delayed rewards or the ability to inhibit a prepotent
response), which may have limited generality to broader behavioral contexts. Thus, it is possible that correlations between self-report measures and behavioral tasks
would be greater if the tasks measured more general impulsive behaviors or if the questionnaires assessed the specific processes identified by the behavioral procedures.
The primary finding from the principal-components analysis was that the participants
behavior fell into two categories. The first component, labeled ‘‘impulsive
disinhibition,’’ consisted of the Stop RT of the Stop Task and false alarms on the Go/No-Go Task. This component resembles the dimension reported by Lane et al. (2003)
consisting of immediate memory and DRL tasks. The second component, labeled ‘‘impulsive decision-making,’’ consisted of the Delay-Discounting Task and BART. The
Delay-Discounting aspect of this component resembles the ‘‘delay-ofreward’’ dimension reported by Lane et al. using tasks measuring self-control choice, contingent
delay discounting and hypothetical delay discounting. However, in our study the second component also included a measure of risk-taking, which did not involve delay.
Thus, this second component appears to reflect processes more general than delay-of-reward. Although it is not clear yet how the Delay-Discounting task and BART are
related conceptually, these measures may be distinguishable from the inhibition tasks because they involve deliberate choices involving the evaluation of outcomes
(e.g., delayed versus immediate outcomes or gains and potential losses). We have labeled this second component ‘‘impulsive decision-making’’ to reflect the more general
choice quality featured by both of these measures. Much work remains to be done to characterize the behavioral components of different forms of impulsive behavior.
These studies using a handful of behavioral tasks suggest that there are at least two forms of impulsive behavior, but additional, more specific tasks are needed to
understand both normal variations in behavior and extremes on these dimensions that result in problem behavior. Ultimately, identifying different components of
impulsive behavior will allow researchers to investigate the physiological systems underlying the behaviors. Knowledge about the physiological processes underlying
impulsive behavior will help in developing treatments for pathological behaviors relating to impulsivity.
B. Reynolds et al. / Personality and Individual Differences 40 (2006) 305–315 313
References
Ainslie, G. (1975). Specious reward: a behavioral theory of impulsiveness and self-control. Psychological Bulletin, 82, 463–496. American Psychiatric Association
(1994). Diagnostic and statistical manual of mental disorders IV (DSM-IV) (4th ed.). Washington, DC: APA Press. Barkley, R. A. (1997). Behavioral inhibition, sustained
attention, and executive functions: constructing a unifying theory of ADHD. Psychological Bulletin, 121, 65–94. Barratt, E. S., & Patton, J. H. (1983). Impulsivity:
cognitive, behavioral and psychophysiological correlates. In M. Zuckerman (Ed.), Biological bases of sensation seeking, impulsivity and anxiety (pp. 77–116).
Hillsdale, NJ: Erlbaum. Bickel, W., Odum, A., & Madden, G. (1999). Impulsivity and cigarette smoking: delay discounting in current, never, and ex-smokers.
Psychopharmacology, 146, 447–454. Crean, J. P., de Wit, H., & Richards, J. B. (2000). Reward discounting as a measure of impulsive behavior in a psychiatric outpatient
population. Experimental and Clinical Psychopharmacology, 8, 155–162. Derogatis, L. R. (1977). Symptom check list—90 Revised. Administration scoring and procedures
manual, Baltimore. de Wit, H., & Richards, J. B. (2004). Dual determinants of drug abuse: reward and impulsivity. Nebraska Symposium on Motivation, 50, 19–55. Eysenck,
S. B. G., Pearson, P. R., Easting, G., & Allsopp, J. F. (1985). Age norms for impulsiveness, venturesomeness and empathy in adults. Personality and Individual
Differences, 6, 613–619. Eysenck, H. J. (1993). The nature of impulsivity. In W. G. McCown, J. L. Johnson, & M. B. Sure (Eds.), The impulsive client: Theory, research
and treatment. Washington, DC: American Psychological Association. Fillmore, M. T., & Rush, C. R. (2002). Impaired inhibitory control of behavior in chronic cocaine
users. Drug and Alcohol Dependence, 66, 265–273. Jentsch, J. D., & Taylor, J. R. (1999). Impulsivity resulting from frontostriatal dysfunction in drug abuse:
implications for the control of behavior by reward-related stimuli. Psychopharmacology (Berl), 146, 373–390. Kirby, K. N., & Marakovic, N. N. (1996). Delay-discounting
probabilistic rewards: rates decrease as amounts increase. Psychological Bulletin Review, 3, 100–104. Kirby, K. N., Petry, N. M., & Bickel, W. K. (1999). Heroin
addicts have higher discount rates for delayed rewards than non-drug-using controls. Journal of Experimental Psychology—General, 128, 78–87. Lane, S., Cherek, D. R.,
Rhodes, H. M., Pietras, C. J., & Techeremissine, O. V. (2003). Relationships among laboratory and psychometric measures of impulsivity: implications in substance abuse
and dependence. Addictive Disorders and Their Treatment, 2, 33–40. Lejuez, C. W., Aklin, W. M., Jones, H. A., Richards, J. B., Strong, D. R., Kahler, C. W., et al.
(2003). The balloon analogue risk task (BART) differentiates smokers and nonsmokers. Experimental and Clinical Psychopharmacology, 11, 26–33. Lejuez, C. W., Read, J.
P., Kahler, C. W., Richards, J. B., Ramsey, S. E., Stuart, G. L., et al. (2002). Evaluation of a behavioral measure of risk taking: the Balloon Analogue Risk Task
(BART). Journal of Experimental Psychology: Applied, 8, 75–84. Logan, G. D., Schachar, R. J., & Tannock, R. (1997). Impulsivity and inhibitory control. Psychological
Science, 8, 60–64. Logue, A., & Anderson, Y. (2001). Higher education administrators: when the future does not make a difference. Psychological Science, 12, 276–281.
Madden, G. J., Petry, N. M., Badger, G. J., & Bickel, W. K. (1997). Impulsive and self control choices in opioid dependent patients and non-drug-using control
participants: drug and monetary rewards. Experimental and Clinical Psychopharmacology, 5, 256–262. McGue, M., Iacono, W. G., Legrand, L. N., Malone, S., & Elkins, I.
(2001). Origins and consequences of age at first drink. I. Associations with substance-use disorder, disinhibitory behavior and psychopathology, and P3 amplitude.
Alcoholism: Clinical and Experimental Research, 25, 1156–1165. Mitchell, S. (1999). Measures of impulsivity in cigarette smokers and non-smokers. Psychopharmacology,
146, 455–464. Newman, J. P., Widom, C. S., & Nathan, S. (1985). Passive avoidance in syndromes of disinhibition: psychopathology and extraversion. Journal of
Personality and Social Psychology, 48, 1316–1327.
314 B. Reynolds et al. / Personality and Individual Differences 40 (2006) 305–315
Patrick, C. J., Curtin, J. J., & Tellegen, A. (2002). Development and validation of a brief form of the multidimensional personality questionnaire. Psychological
Assessment, 14, 150–163. Patton, J. H., Stanford, M. S., & Barratt, E. S. (1995). Factor structure of the Barratt Impulsiveness Scale. Journal of Clinical Psychology,
51, 768–774. Petry, N., & Casarella, T. (1999). Excessive discounting of delayed rewards in substance abusers with gambling problems. Drug and Alcohol Dependence, 56,
25–32. Rachlin, H., & Green, L. (1972). Commitment, choice and self-control. Journal of The Experimental Analysis of Behavior, 17, 15–22. Reynolds, B., Karraker, K.,
Horn, K., & Richards, J. B. (2003). Delay and probability discounting as related to different stages of adolescent smoking and non-smoking. Behavioural Processes, 64,
333–344. Reynolds, B., Richards, J. B., Dassinger, M., & de Wit, H. (2004a). Therapeutic doses of diazepam do not alter impulsive behavior in humans. Pharmacology,
Biochemistry and Behavior, 79, 17–24. Reynolds, B., Richards, J. B., Horn, K., & Karraker, K. (2004b). Delay discounting and probability discounting as related to
cigarette smoking status in adults. Behavioural Processes, 65, 35–42. Richards, J. B., Zhang, L., Mitchell, S., & de Wit, H. (1999). Delay and probability discounting
in a model of impulsive behavior: effect of alcohol. Journal of the Experimental Analysis of Behavior, 71, 121–143. Sher, K. J., & Trull, T. J. (1994). Personality and
disinhibitory psychopathology: alcoholism and antisocial personality disorder. Journal of Abnormal Psychology, 103, 92–102. Slater, M. D. (2003). Sensation-seeking as
a moderator of the effects of peer influences, consistency with personal aspirations, and perceived harm of marijuana and cigarette use among younger adolescents.
Substance Use and Misuse, 38, 865–880. Solanto, M. V., Abikoff, H., Sonuga-Barke, E. J., Schachar, R., Logan, G. D., Wigal, T., et al. (2001). The ecological validity
of delay aversion and response inhibition as measures of impulsivity in AD/HD: a supplement to the NIMH multimodal treatment study of AD/HD. Journal of Abnormal Child
Psychology, 29, 215–228. Sonuga-Barke, E. J. (2002). Psychological heterogeneity in AD/HD—A dual pathway model of behavior and cognition. Behavior and Brain Research,
130, 29–36. Swann, A. C., Bjork, J. M., Moeller, F. G., & Dougherty, D. M. (2002). Two models of impulsivity: relationship to personality traits and psychopathology.
Biological Psychiatry, 51, 988–994. Tarter, R., Vanyukov, M., Giancola, P., Dawes, M., Blackson, T., Mezzich, A., et al. (1999). Etiology of early age onset substance
use disorder: a maturational perspective. Developmental Psychopathology, 11, 657–683. Tercyak, K. P., & Audrain-McGovern, J. (2003). Personality differences associated
with smoking experimentation among adolescents with and without comorbid symptoms of ADHD. Substance Use and Misuse, 38, 1953–1970. Vuchinich, R., & Simpson, C.
(1998). Hyperbolic temporal discounting in social drinkers and problem drinkers. Experimental and Clinical Psychopharmacology, 6, 292–305. White, J. L., Moffitt, T. E.,
Caspi, A., Bartusch, D. J., Needles, D. J., & Stouthamer-Loeber, M. (1994). Measuring impulsivity and examining its relationship to delinquency. Journal of Abnormal
Psychology, 103, 192–205. Zuckerman, M., Ball, S., & Black, J. (1990). Influences of sensations seeking, gender, risk appraisal, and situational motivation on smoking.
Addictive Behaviors, 15, 209–220.
B. Reynolds et al. / Personality and Individual Differences 40 (2006) 305–315 315

TO GET YOUR ASSIGNMENTS DONE AT A CHEAPER PRICE,PLACE YOUR ORDER WITH US NOW