Dimensions of impulsive behavior: Personality and behavioral measures

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Personality and Individual Differences 40 (2006) 305–315

Dimensions of impulsive behavior: Personality andbehavioral 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 Statesb 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 Statesd 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 2005Available online 8 September 2005

Abstract

Impulsivity as a behavioral construct encompasses a wide range of what are often considered maladap-tive behaviors. Impulsivity has been assessed using a variety of measures, including both self-report person-ality questionnaires and behavioral tasks, and each of these measures has been further subdivided intoseparate components which are thought to represent different underlying processes. However, few studieshave employed both personality measures and behavioral tasks, and so the relations among these measuresare not well understood. In one analysis we examined correlations between three widely used personalitymeasures (i.e., BIS-11, I7, and MPQ) and four laboratory-task measures of impulsive behavior (behavioralinhibition (2), delay discounting, and risk taking) in 70 healthy adult volunteers. The correlations amongthe various self-report measures were high, but self-reports were not correlated with behavioral-task mea-sures. In a second analysis we performed a principal-components analysis using data from the four beha-vioral tasks for 99 participants. Two components emerged, labeled ‘‘impulsive disinhibition’’ (Stop Taskand Go/No-Go task) and ‘‘impulsive decision-making’’ (Delay-Discounting task and Balloon AnalogRisk 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: [email protected] (B. Reynolds), [email protected] (H. de Wit).

306 B. Reynolds et al. / Personality and Individual Differences 40 (2006) 305–315

and behavioral tasks probably measure different constructs, and suggest that even among the behavioralmeasures, 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 Dis-counting; Human

1. Introduction

Impulsivity is a multidimensional concept that has been defined variously as an inability towait, a tendency to act without forethought, insensitivity to consequences, and an inability to in-hibit inappropriate behaviors (e.g., Ainslie, 1975; Barkley, 1997; Barratt & Patton, 1983; Eysenck,1993; Rachlin & Green, 1972). Accordingly, various measures have been developed to assessimpulsive behavior, including self-report measures of personality that rely on an individual�sself-perceptions of their behavior, and behavioral tasks that measure overt behavior related tospecific dimensions of impulsivity. Although both self-report and behavioral measures have beenstudied 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 volun-teers to investigate relations between self-report and behavioral measures of impulsivity, andbetween the subcategories of impulsive behavior that each of these instruments is designedto measure.

Both self-report and behavioral-task studies support the idea that impulsivity is strongly linkedto 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-reportmeasures of impulsivity, sensation seeking, and inattention (Sher & Trull, 1994; Slater, 2003; Terc-yak & Audrain-McGovern, 2003; Zuckerman, Ball, & Black, 1990). Several recent studies alsohave shown that drug users, including smokers, alcoholics, cocaine users, and opiate addicts, per-form more impulsively on behavioral tasks designed to measure impulsivity, such as delay dis-counting 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 understan-ding of the equivalence of different assessment methods and of the factor structure of impulsivebehavior. One basic question is whether self-report and behavioral measures assess the same pro-cesses. The findings from the few studies that have used both types of measure have been equi-vocal. Some studies indicate that performance on delay or probability discounting tasks iscorrelated with self-report measures of sensation seeking, extraversion, or impulsivity and ven-turesomeness (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 behavioralindices (Crean, de Wit, & Richards, 2000; Lane et al., 2003; Mitchell, 1999; Reynolds et al.,

B. Reynolds et al. / Personality and Individual Differences 40 (2006) 305–315 307

2004b; White et al., 1994). There also is relatively little information about interrelations amongdifferent behavioral measures of impulsivity. However, several recent studies suggest that differentbehavioral measures may reflect separate underlying processes. Sonuga-Barke (2002) noted thatsome children with Attention Deficit Hyperactivity Disorder (ADHD; APA, 1994) perform morepoorly than control subjects on one task measure of impulsive behavior, i.e., tasks assessing delayaversion, whereas other ADHD children perform more poorly on a different measure, i.e., a mea-sure of inhibitory control (Solanto et al., 2001). Sonuga-Barke proposed that separate neural sys-tems underlie these different types of impairments. Lane et al. (2003) used a principal-componentsanalysis to examine relations among behavioral measures in 32 healthy adult volunteers andfound that behavioral inhibition was not related to intolerance of delays. It is notable that boththe Sonuga-Barke and Lane analyses led to a similar conclusion that impairments in inhibitionare not related to impairments in delay intolerance. Further analyses of this kind examiningthe 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 impulsivebehavior.

Here we report on relations between personality inventories and behavioral measures of impul-sivity in a sample of healthy volunteers. The report consists of two separate analyses. First, weexplore correlations among three widely used self-report measures of impulsivity and four beha-vioral tasks purported to assess impulsivity. Second, we explore the component structure amongthe four behavioral impulsivity tasks using a principal-components analysis. The personality mea-sures 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 Per-sonality Questionnaire (MPQ, Patrick, Curtin, & Tellegen, 2002). The behavioral tasks includedtwo 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 var-ious personality measures would be high, but that personality measures would be only modestlyor poorly correlated with the behavioral measures. Further, we expected that separate inhibitionand delay-related components would be identified from the principal-components analysis. Risktaking has elements of both inhibition and reward delay, and therefore this analysis was moreexploratory in nature.

2. Method

2.1. Participant recruitment

The participants for these analyses were recruited from a university environment. The 70 par-ticipants in the correlation analysis participated in a single session in which they performed allmeasures. The principal-components analysis included these 70 participants as well as 29 partic-ipants 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 sessionwhen they received placebo.

All participants were recruited via posters, advertisements in newspapers, and word-of-mouthreferrals. Eligible candidates completed a psychiatric symptom checklist (SCL-90; Derogatis,

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1977) and a health questionnaire that included a detailed section on current and lifetime recrea-tional drug use and history. A semi-structured psychiatric interview was conducted to rule out po-tential participants who met criteria for major DSM IV diagnoses (APA, 1994). The exclusioncriteria included a history of an Axis I psychiatric disorder (including substance use disorder), lessthan a high-school education, smoking more than five cigarettes per day, and a lack of Englishfluency. The University of Chicago Hospital Institutional Review Board approved the protocol.

2.2. Procedure

2.2.1. Correlation analysesParticipants (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 scree-nings were positive. Participants completed the personality measures (see below) and then relaxedfor 20 min before performing the laboratory behavioral tasks (see below). The order of the taskswas counterbalanced across participants. After the tasks, participants were debriefed and receivedtheir payment.

2.2.2. Principal-components analysisIn 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 anal-ysis only data from the placebo session were used, after determining that there were no carry-overeffects 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 person-

ality. 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 tothink’’?), venturesomeness (e.g., ‘‘Would you enjoy fast driving’’?) and empathy (e.g., ‘‘Does itaffect 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 thepresent analysis focuses on impulsivity, only scores from the Constraint factor will be reportedhere.

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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 withholdthis response when an auditory stop signal is presented. The stop signal is presented on 25% oftrials at varying delays (in milliseconds) following the go signal. The delay to the stop signal isvaried systematically across trials according to the participant�s performance until a delay is foundat which the participant inhibits his or her responses on approximately 50% of trials. The stopreaction time (SRT) can be inferred from the delay by subtracting the final mean delay at whichthe tone is presented from the mean go reaction time (GRT). Both GRT and SRT are measured inmilliseconds. Longer SRTs are taken to indicate more impulsive responding, or poor behavioralinhibition.

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 re-

sponses. 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. Theyare 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’’ stimulusis presented) and errors of commission/false alarms (responding to an ‘‘incorrect’’ stimulus). Par-ticipants received the amount of money earned at the end of the session. The measure of impulsivebehavior in this task was the number of errors of commission, which indicate an inability to in-hibit inappropriate responses.

2.4.3. Delay-discounting task (Richards et al., 1999)Delay-Discounting measures the relative value of immediate versus delayed rewards. This ver-

sion of the task uses a computerized adjusting-amount procedure to measure discounting of de-layed 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, depen-ding on the participant�s response on the previous trial, until an immediate amount is reached thatthe participant chooses equally often as the delayed reward ($10). This value is referred to as theindifference point. The indifference points determined for five different delays (0, 2, 30, 180 and365 days) are plotted, and a discount function is derived using a curve-fitting analysis. Thecurve-fitting analysis yields a k-value, which provides a quantitative index of the steepness ofthe discount curve: Higher k-values reflect greater discounting by delay and therefore greaterimpulsivity. In the procedure used in this study, participants received the money from one of theirchoices, on a probabilistic basis. At the end of the session participants rolled a die, and if a 1 or 6was 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

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mouse. For each pump, a counter on the screen increases by a certain amount of money (1/2, 1, or5 cents). Participants may transfer the money in this counter to a �bank� at any time but this alsoterminates the trial and starts the next balloon. After an unpredictable number of �pumps� the bal-loon 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 ear-nings on the trial) are considered more impulsive. In this study participants received a portionof 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 behavioraltasks were converted so that higher values represented greater impulsivity. In addition, the k-val-ues derived from the delay-discounting procedure were log-transformed to improve normalizationof the scores (e.g., Richards et al., 1999). Data were analyzed using SPSS� version 11.5. Correla-tions 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 wereretained. Component loadings of .5 or higher within identified components were considered sig-nificant loadings. We also used a varimax rotation method with Kaiser Normalization to maxi-mize each measure�s loading on a single component. As a secondary analysis, we alsocompared impulsivity scores for all the measures across females and males using independent-samples t-tests.

3. Results

3.1. Participants

Table 1 shows the demographic data for the participants. Participants were primarily youngCaucasian 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-re-port measures were positively correlated with other self-report measures, both between subscalesof the same instruments (e.g., BIS-11) and between instruments (i.e., BIS-11, I7 and MPQ). Bycontrast, of the 40 correlations conducted between self-report and behavioral measures, onlyone correlation was significant. There was a positive correlation between Cognitive Complexityof the BIS-11 and errors of commission on the Go/No-Go Task. With reverse coding of CognitiveComplexity, 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 mea-sures. Participants with longer Stop RTs on the Stop Task made more false-alarm errors on theGo/No-Go Task.

Table 1Participant demographics

Correlational analyses (N = 70)

Age (mean, SD years) 22.92 (3.67)Sex (male/female) 35/35Race (Cauc/Black/Asian/Unknown) 48/5/16/1Education (n)High school/partial college 1/10College degree/advanced degree 18/18Full time student 23

Principal-components analysis (N = 99)

Age (mean, SD years) 22.90 (3.12)Sex (male/female) 51/48Race (Cauc/Black/Asian/Unknown) 68/9/19/4Education (n)High School/partial college 2/14College degree/advanced degree 24/19Full time student 40

Table 2Correlation 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 .0032 1.0 .589** .265* .451** .515** .731** .270* .157 .576** �.004 �.140 �.067 .1053 1.0 .512** .595** .357** .655** .282* .093 .625** .025 .112 .187 .0484 1.0 .484** .110 .402** �.050 .024 .123 .042 .030 .254* �.2305 1.0 .531** .492** .145 .144 .516** �.022 .131 .116 �.0426 1.0 .460** .191 .346** .389** �.075 .090 �.023 .1707 1.0 .260* .233 .580** .021 .021 .121 .0348 1.0 .013 .446** �.045 .023 �.016 .1649 1.0 .168 .116 .062 �.200 .01810 1.0 �.110 .002 .162 .16211 1.0 �.035 �.083 �.04912 1.0 .278* .01413 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).

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3.3. Principal-components analysis

The principal-components analysis, which used only behavioral measures, resulted in twoprincipal components with eigenvalues P1 (Table 3). For the first component, loadings were

Table 3Principal-components analysis (N = 99) for four behavioral measures

Rotated components

1 2

Eigenvalues 1.30 1.06Variance 32.5% 26.4%

Stop Task .809 �.149Go/No-Go Task .767 .229Delay-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

significant for the Stop Task and the Go/No-Go Task (.809 and .767, respectively) but not for theDelay-Discounting task or the BART. This first component might be labeled ‘‘impulsive disinhi-bition’’ because both the Stop Task and Go/No-Go Task can be considered measures of inhibi-tion. For the second, component loadings were significant for the Delay-Discounting task and theBART (.768 and .644, respectively) but not the Stop Task or Go/No-Go Task. This componentmight be labeled ‘‘impulsive decision-making’’ because each measure involves an evaluation anddecision between different consequent outcomes.

Men and women scored similarly on all measures except the Empathy subscale of the I7 and theDelay-Discounting measure. The mean Empathy score for females was 14.03 (SD = 2.69) and formales 12.65 (SD = 2.79), meaning that women were more empathic than men. This difference wassignificant, t(68) = 2.11, p = .039, two-tailed test. The mean non-logged k-value on the Delay-Dis-counting measure was 0.0697 (SD = .097) for women and 0.0434 (SD = .108) for men. Using alog-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-taskmeasures of impulsive behavior. There were two main findings. First, we found there were corre-lations between several of the subscales of the self-report measures, but these self-report measureswere generally unrelated to the task measures. Second, we found the task measures fell into twocomponents, or categories. One component included the Stop Task and Go/No-Go Task, corre-sponding to measures of ‘‘impulsive disinhibition,’’ and the second component included DelayDiscounting and the BART, which could be referred to as ‘‘impulsive decision-making.’’ Thesefindings add to a growing literature suggesting that self-report measures and behavioral measuresassess different forms of impulsivity, and that behavioral measures of impulsivity reflect at leasttwo apparently unrelated subtypes of impulsive behavior.

Few sex differences were observed in the present study, either on self-report measures of impul-sivity or on the behavioral tasks. The only behavioral measure on which men and women differedwas the Delay-Discounting task, on which women responded in a more impulsive manner (i.e.,

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discounted more steeply). This finding is not consistent with previous studies using this type ofmeasure, 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 werenot related to performance on specific behavioral tasks. Here, only one relatively weak correlationwas observed between Go/No-Go performance and Cognitive Complexity (BIS). It is notable thatseveral other previous studies have failed to observe relations between self-report and behavioralmeasures of impulsive behavior (e.g., Crean et al., 2000; Lane et al., 2003; Mitchell, 1999; Rey-nolds et al., 2004b; White et al., 1994; but see also Kirby et al., 1999; Richards et al., 1999; Swannet al., 2002). The findings suggest that the behavioral tendencies detected with self-report scalesare not the same as those detected with the behavioral tasks. It should also be noted that self-re-port measures differ from behavioral measures in several fundamental ways. With self-report mea-sures, participants must recognize and report on their own behavioral tendencies in variouscontexts relative to other individuals, and these self-perceptions may not always accurately reflecttheir behavior. In contrast, performance on behavioral tasks is objective and thus less sensitive tobiased self-perceptions. On the other hand, the behavioral tasks typically measure only one spe-cific dimension of behavior (e.g., the value of delayed rewards or the ability to inhibit a prepotentresponse), which may have limited generality to broader behavioral contexts. Thus, it is possiblethat correlations between self-report measures and behavioral tasks would be greater if the tasksmeasured more general impulsive behaviors or if the questionnaires assessed the specific processesidentified by the behavioral procedures.

The primary finding from the principal-components analysis was that the participants� behaviorfell into two categories. The first component, labeled ‘‘impulsive disinhibition,’’ consisted of theStop RT of the Stop Task and false alarms on the Go/No-Go Task. This component resemblesthe 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-DiscountingTask and BART. The Delay-Discounting aspect of this component resembles the ‘‘delay-of-reward’’ dimension reported by Lane et al. using tasks measuring self-control choice, contingentdelay discounting and hypothetical delay discounting. However, in our study the second compo-nent also included a measure of risk-taking, which did not involve delay. Thus, this second com-ponent appears to reflect processes more general than delay-of-reward. Although it is not clear yethow the Delay-Discounting task and BART are related conceptually, these measures may be dis-tinguishable from the inhibition tasks because they involve deliberate choices involving the eval-uation of outcomes (e.g., delayed versus immediate outcomes or gains and potential losses). Wehave labeled this second component ‘‘impulsive decision-making’’ to reflect the more generalchoice quality featured by both of these measures.

Much work remains to be done to characterize the behavioral components of different forms ofimpulsive behavior. These studies using a handful of behavioral tasks suggest that there are atleast two forms of impulsive behavior, but additional, more specific tasks are needed to under-stand both normal variations in behavior and extremes on these dimensions that result in problembehavior. Ultimately, identifying different components of impulsive behavior will allow research-ers to investigate the physiological systems underlying the behaviors. Knowledge about the physi-ological processes underlying impulsive behavior will help in developing treatments forpathological behaviors relating to impulsivity.

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