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Dimensions of impulsive behaviour in abstinent alcoholics
Personality and Individual Differences 42 (2007) 465–476 www.elsevier.com/locate/paid
Dimensions of impulsive behaviour in abstinent alcoholics Geert Dom
a,*
, Bieke De Wilde a, Wouter Hulstijn b, Bernard Sabbe
b
a
b
Psychiatric Centre Alexian Brothers, Boechout 2530, Belgium Collaborative Antwerp Psychiatry Research Institute (CAPRI), Antwerp, Belgium Received 5 April 2006; received in revised form 21 July 2006 Available online 10 October 2006
Abstract Impulsivity is a complex multidimensional behavioural construct that has been frequently implicated in the pathogenesis of addictive disorders. Both self-report and behavioural measures have been developed to assess its underlying dimensions but their interrelation is still poorly understood and few studies have employed a comprehensive set of measures within a given population to explore their interrelation. In a stably abstinent alcohol-dependent population we explored the interrelations between two well known personality questionnaires (BIS-11 and SSS), and two behavioural measures reflecting different dimensions of impulsivity, behavioural disinhibition (Go/NoGo task) and delay discounting (DDT). In addition, we included the Iowa Gambling Task (IGT), a neurobehavioural measure of decision-making, a cognitive dimension that is closely related to impulsivity. Strong correlations were found between the different subscales of the self-report measures. However, the correlations between the behavioural measures and the self-report measures were weak, suggesting that they both tap into different aspects of the concept. Finally, a principal component analysis on the data of the behavioural measures revealed that they all loaded on separate factors. These findings support the hypothesis that behavioural disinhibition and delay discounting are two independent dimensions of impulsivity and that decision-making is a third cognitive dimension, independent of both other measures. Ó 2006 Elsevier Ltd. All rights reserved. Keywords: Impulsivity; Behavioural measures; Self-report measures; Decision-making; Alcohol dependence
*
Corresponding author. Tel.: +32 3 455 75 31. E-mail address: [email protected] (G. Dom).
0191-8869/$ - see front matter Ó 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.paid.2006.08.007
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1. Introduction Alcoholism is a very heterogenic disorder and the individual differences with respect to its aetiology, course and severity are considerable. Thus, the identification of elements that constitute an increase in individual vulnerability and mediate the course of the disorder is of paramount importance. Impulsivity has been proposed as an important factor with respect to the initiation and course of addictive processes (Dawe, Matthew, & Loxton, 2004; Dom, Hulstijn, & Sabbe, 2006). For example, prospective studies have shown that individual differences in childhood behavioural disinhibition predict early substance use during adolescence and substance use disorder in young adulthood (e.g., Masse & Tremblay, 1997). Generally, impulsivity is used to describe a broad range of maladaptive behaviours including an inability to inhibit inappropriate action, insensitivity to delayed or uncertain consequences, perception of time as progressing more slowly than actual time, and the perseverance of negatively reinforced actions (McDonald, Schleifer, Richards, & de Wit, 2003; Moeller, Barratt, Dougherty, Schmitz, & Swann, 2001). On a conceptual level, there is now wide agreement that impulsivity consists of a number of different dimensions (Bechara, 2003; Dougherty, Mathias, Marsh, & Jagar, 2005; Evenden, 1999). Dawe et al. (2004) and de Wit and Richards (2004) define two broad dimensions. The first dimension can be labelled as ‘‘behavioural disinhibition or rash impulsiveness’’. This includes problems both in response initiation and response inhibition. In this respect impulsive behaviour can be a consequence of responding prior to complete processing and evaluation of a stimulus (‘‘acting without thinking’’), or can result from a failure to inhibit an already initiated response (response inhibition). A second dimension has been labelled as ‘‘consequence sensitivity or impulsive decision-making’’ (de Wit & Richards, 2004). Here, impulsivity is defined as behavioural choices (‘‘decisions’’) that persist despite negative or less than optimal consequences, i.e., a preference for small immediate rewards over later, larger rewards (‘‘delay discounting’’) or a preference for larger immediate rewards coupled to later, uncertain larger punishments versus smaller immediate rewards associated with smaller, later punishments (‘‘risk discounting’’) (Monterosso, Erhman, Napier, O’Brien, & Childress, 2001). Various measures have been developed to assess impulsive behaviour. Broadly these can be divided into self-report measures of personality that rely on an individual’s self-perception of their behaviour, and behavioural tasks that measure overt behaviour related to specific dimensions of impulsivity. Typically, both types of measurements do correlate only weakly, indicating that they measure different aspects of impulsivity (Dom, D’Haene, Hulstijn, & Sabbe, 2006; Moeller et al., 2001; Reynolds, Ortengren, Richards, & de Wit, 2006). There are few validated behavioural instruments available to measure impulsivity and it remains to be specified which aspect of the concept they tap in and to which degree these measures interrelate (Moeller et al., 2001; Reynolds et al., 2006). Only a few studies have used a comprehensive battery to assess simultaneously the different aspects of impulsivity within a given sample. Reynolds et al. (2006) used four behavioural tasks within a sample of healthy community recruited individuals. Factor analysis of their data indicated that these tasks loaded on two separate components, the first, labelled impulsive disinhibition (Stop Task and Go/NoGo Task) and second, impulsive decision-making (Delay Discounting Task and Balloon Analog Risk Task). In a sample of cocaine dependent patients, Monterosso et al. (2001) compared three behavioural decision-making tasks, i.e., Delay Discounting Task (DDT, Richards, Zhang, Mitchell, & de Wit,
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1999), Iowa Gambling Task (IGT, Bechara, Damasio, Damasio, & Anderson, 1994), and the Roger Decision-Making Task (RDMT, Rogers et al., 1999). Impairments on all three tasks have been reported within substance abusers relative to controls (Bechara, 2003; Bjork, Hommer, Grant, & Danube, 2004; Dom, D’Haene, et al., 2006; Dom, Hulstijn, et al., 2006; Richards et al., 1999). These behavioural decision-making tasks have as communality that task performance involves an evaluation and choices (‘‘decision-making’’) between different consequent outcomes. Although the exact processes that are measured by these tasks remain to be specified, they all measure different aspects of decision-making, i.e., delay and risk-discounting. In the current study we report on the relations between self-report and behavioural measures of impulsivity within a sample of stably abstinent alcohol dependent inpatients. The study consists of two separate analyses. First we explored the correlations among the self-report measures, behavioural measures, and the measures of problem severity. Next we used a principal component analysis to explore the component structure among the behavioural measures. The Barratt Impulsivity Scale (BIS-11; Patton, Stanford, & Barratt, 1995) and the Sensation Seeking Scale (SSS; Zuckerman, Kolin, Price, & Zoob, 1964) were used as self-report measures of impulsivity. Impulsivity, as measured with the BIS is best described as a tendency to act rashly and without consideration of consequences. Sensation seeking is a tendency to seek out intense, novel forms of sensation and experiences, regardless of the risks involved. In a recent factor analysis, the BIS, the SSS and another widely used measure, the Eysencks’ I7 Impulsiveness subscale (Eysenck, Pearson, Easting, & Allsopp, 1985), have been reported to load on the same factor, labelled by Dawe et al. (2004) rash-spontaneous impulsiveness. For the behavioural tasks we used a Go/NoGo task which has been widely used as a measure for response inhibition. In addition, two decision-making tasks were included, i.e., a Delay Discounting Task (Richards et al., 1999) and the Iowa Gambling Task (Bechara et al., 1994). Based on the previous findings, described above, we hypothesized that the correlations among the self-report measures would be high but that the correlations between the self-report measures and behavioural measures would be only poor or modest. Furthermore, we expected that, with respect to the behavioural measures, the correlations between a measure of response inhibition (i.e., Go/NoGo task) and decision-making (i.e., DDT and IGT) would be poor, while correlations between the DDT and IGT would be high. Finally, we expected that separate inhibition and decision-making components would be identified from the principal components analysis.
2. Method 2.1. Sample Participants were 92 DSM-IV (American Psychiatric Association, 1994) alcohol-dependent individuals consecutively recruited from an inpatient treatment facility. For a full description of recruitment procedure, see Dom, D’Haene, et al. (2006) and Dom, Hulstijn, et al. (2006). Only patients who engaged in long-term inpatient treatment, after being fully detoxified (and whose abstinence could be daily monitored), were eligible for the current study. All participants gave informed consent and the study was reviewed and approved by the medical ethics committee of the Psychiatric Hospitals, Brothers of Charity, Belgium.
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2.2. Procedure All patients completed the self-report questionnaires during the first and second week after admission to the clinic. To exclude confounding due to withdrawal effects, the intelligence tests and the behavioural tasks were administered in weeks 4 and 5, i.e., after a mean of 36.63 days (SD 19.59) of monitored abstinence. Test conditions (room, computer) were the same for all patients. Before the behavioural tasks, the patients provided a breath sample that was screened for alcohol using an Alcometer as well as a urine specimen that was screened for opioids, cocaine, amphetamine, cannabis, and benzodiazepine. 2.3. Measurements 2.3.1. Intelligence The Wechsler Adult Intelligence Scale (WAIS-III, Dutch version, Swets Test Publishers, 2000) consists of an individually administered battery of tests designed to measure verbal (VIQ) and performance (PIQ) intelligence. 2.3.1.1. Personality inventory measures 2.3.1.1.1. Barratt impulsiveness scale (BIS-11). The Dutch adaptation of the Barratt Impulsiveness Scale (BIS-11; Patton et al., 1995) is a 30-item self-report questionnaire with a total score (BIS_T) and three subscales measuring different aspects of impulsiveness: non-planning impulsiveness (BIS_NP), motor impulsiveness (BIS_M), and cognitive impulsiveness (BIS_C). Although the BIS-11 has been translated in many languages showing good psychometric properties, the Dutch BIS-11 has as yet not been validated, so no norm data are available. 2.3.1.1.2. Sensation seeking scale (SSS). The Dutch adaptation (SSS-D) is based on earlier versions of Zuckerman’s Sensation Seeking Scale (Zuckerman et al., 1964). It was tested in a Dutch population and showed good reliability and validity and norm scores for different age groups are available (Feij, Dekker, Koopmans, & Boomsma, 1997). The SSS-D is a 67-item, self-report questionnaire providing a general sensation seeking score (SSS_G) as well as scores on four subscales assessing disinhibition (SSS_DIS), thrill and adventure seeking (SSS_TAS), experience seeking (SSS_ES) and boredom susceptibility (SSS_BS). 2.3.1.2. Behavioural measures 2.3.1.2.1. Go/NoGo task. A classical Go/NoGo paradigm was presented using a computer screen and a writing tablet on which the participant could write or draw with an electronic pen (See also Dom, De Wilde, Hulstijn, van den Brink, & Sabbe, 2006). Pen movements controlled a screen cursor (yellow dot on the screen) (Fig. 11). The participant is asked to move his cursor (yellow dot) as fast and accurate as possible into the newly presented target circle if this circle is coloured dark blue (Go trial) and withhold his reaction if the new target circle is coloured light blue (NoGo trial). Four series each containing 56 trials (ratio Go/NoGo was 1/8) were presented. The dependent variables were the number of errors (Error) in the NoGo trials and the reaction (RT) and in the Go trials. An error on a NoGo signal was defined as any movement away from 1
For interpretation of colour in this figure legend, the reader is referred to the web version of this article.
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Fig. 1. Go/NoGo task; left panel shows an example of a NoGo trial; right panel of a go trial.
the start circle. RT was defined as the time between the appearance of a new target circle and response initiation. 2.3.1.2.2. Delay-discounting task. A classical DDT design, using hypothetical reward money, was presented on a computer screen (Richards et al., 1999). For a full description of the procedure, see also Dom, D’Haene, et al. (2006). Indifference points were determined for an amount of 100€ (hypothetical money) over five different delays: 2, 30, 180, 365, and 730 days, respectively. The indifference points obtained at each of the delays were plotted and discount functions were derived through curve-fitting analysis (Matlab, version 5.3) using Mazur’s formula (Mazur, 1987): V ¼ A=ð1 þ kDÞ: The dependent variable used in the analysis of the DDT task in current study was the natural log transformation of the discount rate (k). 2.3.1.2.3. Iowa gambling task (IGT). We used a computerised version of the original IGT (Bechara et al., 1994; Dom, De Wilde, Hulstijn, van den Brink, & Sabbe, in press). In this gambling task participants choose cards of any of four decks of cards, presented on a computer screen, labelled A, B, C and D. The rewards (hypothetical money) on the A and B decks are twice as high as those for the C and D decks, while the punishments are five times as high. Furthermore A and C decks generate smaller punishments more frequently (i.e., on average, 3 out of 4 times) while the B and D decks generate larger punishments less frequently (i.e., on average 3 out of 5 times). Thus, decks A and B (‘‘disadvantageous decks’’) both resulted in an overall loss due to higher individual rewards with moderate but frequent punishment (A) and higher individual rewards with very large but infrequent punishments (B). Decks C and D (‘‘advantageous decks’’) yielded an overall gain via lower individual returns and frequent, low punishment (C) and lower individual returns and moderate but infrequent punishment (D). The dependent variable in the current study was the overall net score over five blocks of twenty cards. The net score for each block was defined as the total number of cards chosen from decks C and D minus the total number of cards chosen from decks A and B (Bechara et al., 1994; Dom et al., in press). 2.4. Analysis Pearson correlations were used with a Bonferroni correction for multiple comparisons resulting in a significance level (a) of p < 0.003 (=0.05/14).
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For the principal components analysis, components having eigenvalues P 1 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. All analyses were performed using SPSS-11 statistical software.
3. Results 3.1. Sample characteristics Sample characteristics are presented in Table 1. The participants were predominantly male (74%). Male (n = 68) and female (n = 24) participants were not different in age, education, or number of years of alcohol abuse/dependence. Although alcohol-dependence was the inclusion criterion, a sizable portion (34.8%) of the participants had a history (lifetime) of co-morbid illicit drugs or benzodiazepine dependence. 3.2. Correlation analysis Table 2 shows the correlation matrix for all of the measures of impulsivity. Significant, positive, correlations were found between both self-report measures (BIS-11 and SSS) and between the subscales within each self-report measure. In contrast, none of the behavioural measures correlated with the self-report measures. No significant correlations were found between any of the behavioural measures. Finally, IQ did not correlate significantly with any of the self-report or behavioural measures, with exclusion of the DDT. Given the male dominance in our sample a separate analysis was done within each gender to explore differences in patterns between genders. For both genders the same correlation patterns were found as within the whole, mixed gender, sample. 3.3. Principal-component analysis The principal-component analysis on IQ, self-report and behavioural measures of impulsivity resulted in five principal components (with eigenvalues P 1) explaining 69% of the variance
Table 1 Alcohol-dependent inpatients (n = 92): sample characteristics Mean (SD) Age (yr) Age onset alcoholism (yr) Number of years of alcohol dependence Number years education WAIS (total IQ)
42.3 26.0 16.3 12.7 96.7
(9.6) (9.6) (9.6) (2.8) (12.4)
% of sample Men Nicotine dependence Pure alcohol dependence Alcohol and benzodiazipine Alcohol and illicit drug
74 82 34.7 31.5 34.8
BIS_C BIS_M BIS_NP BIS_T SSS_TAS SSS_ES SSS_BS SSS_DIS SSS_G IGT Error RT DDT IQ *
BIS_C
B_M
B_NP
B_T
1 .563* .303 .741* .025 .030 .197 .238 .117 .003 .126 .143 .149 .271
1 .464* .851* .245* .249 .316 .427* .397* .068 .094 .094 .173 .233
1 .781* .078 .262 .331* .231 .349* .255 .059 .089 .048 .105
1 .133 .199 .363* .378* .378* .151 .115 .134 .154 .256
S_TAS
S_ES
S_BS
S_DIS
S_G
IGT
Error
RT
DDT
1 .468* .029 .044 .042 .142 .040
1 .027 .089 .066 .269 .000
1 .010 .031 .027 .188
1 .090 .044 .136
1 .060 .074
1 .378*
1 .334* .110 .041 .649* .049 .054 .019 .053 .002
1 .165 .049 .647* .002 .058 .057 .130 .171
1 .339* .592* .105 .073 .040 .295 .205
Significant on a Bonferroni, multiple comparisons, corrected significance level of p < 0.003 (=0.05/14).
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Table 2 Correlations among the self-report measures, Barratt Impulsivenes Scale [BIS-11; subscales Cognitive (BIS_C), Motor (BIS_M), Non-planning (BIS_NP), and total score (BIS_T)] and Sensation Seeking Scale [SSS; subscales Thrill and Adventure seeking (SSS_TAS), Experience Seeking (SSS_ES), Boredom Susceptibility (SSS_BS), Disinhibition (SSS_DIS), and General Sensation Seeking (SSS_G)] and behavioural measures on a Go/ NoGo task [number of commission errors (Error) and reaction time on Go trials (RTGO)], a Delay Discounting Task (DDT), the Iowa Gambling Task (DDT), and IQ
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Table 3 Principal components analysis (n = 92) (rotated) for behavioural measures Eigenvalues % Variance explained
3.919 28.0 1
SSS-TAS SSS-ES SSS-BS SSS-DIS SSS_G DDT IGT nogof1 BIS_C BIS_M BIS_NP BIS_T RT IQ
.062 .218 .354 .195 .311 .067 .026 .003 .736* .768* .710* .973* .210 .334
2.064 14.7
1.436 10.3
2 *
.721 .467 .542* .479 .911* .168 .038 .019 .207 .259 .197 .129 .439 .186
1.136 8.1
1.105 7.9
3
4
5
.158 .457 .479 .300 .062 .746* .101 .099 .665* .191 .665* .098 .078 .665*
.106 .002 .097 .367 .070 .083 .858* .027 .186 .097 .392 .083 .003 .295
.161 .393 .010 .336 .035 .237 .035 .839* .108 .131 .048 .010 .163 .153
Number of errors on the NoGo trials (Error), reaction times on the Go trials (RT), Delay Discounting Task (DDT), Iowa Gambling Tasks (IGT), and the subscales of the Barratt Impulsiveness Scale (Cognitive, C; Motor, M; NonPlanning, NP, Total score, T), Sensation Seeking Scale (thrill and adventure seeking, TAS; experience seeking, ES; boredom susceptibility, BS; disinhibition, DIS; general sensation seeking, Gen), and Wais full IQ (IQ). * Component loadings of .500 or higher were considered significant.
(Table 3). One component loaded primarily on the BIS and a separate component on the Sensation Seeking subscales. The third component clustered the DDT negatively with IQ, and the BIS Cognitive and non-Planning subscale. Finally, both the IGT and the behavioural inhibition (error) loaded upon separate components. The three different behavioural tasks each loaded independently on a separate component, which can be labelled ‘‘behavioural inhibition’’ as reflected by the Go/NoGo performance, ‘‘delay-discounting’’ (reflected by high DDT performance), and finally, ‘‘risk-discounting’’ (IGT).
4. Discussion This study examined the relations among two self-report measures and three behavioural measures of impulsive behaviours. Taken together, our results show that there were significant correlations between several subscales of the self-report measures, but these self-report measures were unrelated to the task measures. Furthermore, no significant correlations were found between the behavioural measures and we found that the task measures fell into three separate components, which can be labelled behavioural disinhibition (Go/NoGo task), delay-discounting (DDT), and risk-discounting (IGT). The self-report measures of impulsivity and sensation seeking were not related to performance on the behavioural tasks. This finding is consistent with earlier studies that have failed to observe substantial correlations between self-report measures and behavioural measures of impulsivity in
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very diverse samples coming from the general population (Reynolds et al., 2006), psychiatric outpatients (Crean, de Wit, & Richards, 2000), and cocaine-dependent patients (Monterosso et al., 2001). These findings suggest that behavioural tasks and self-report measures tap different aspects of impulsivity. Research on impulsivity has generally relied on self-report, or on measurements or observations of behaviour whose impulsivity was open to interpretation. These measures have yielded valuable information about impulsivity as a stable and enduring trait in individuals with a wide range of behavioural disturbances (Bornovalova, Lejuez, Daughters, Rosenthal, & Lynch, 2005; Swann, Bjork, Moeller, & Dougherty, 2002). However, self-report measures do not lend themselves well to pharmacologic or physiologic studies of impulsivity, because they are subjective, measure a relatively stable characteristic, and cannot be related directly to biological models of impulsivity based on animal studies (Swann et al., 2002). In contrast, behavioural approaches have the advantage of being sensitive to transient changes in impulsivity (i.e., state-dependent impulsivity) and may be more amenable to situations where repeated administration in necessary. Behavioural measures of impulsivity have been suggested to have a role in assessing changes during treatment (Bickel & Marsch, 2001; Dougherty et al., 2003), and recent studies indicate that specifically behavioural measures of impulsivity may be a better predictor for relapse risk, than self-report measures (e.g., Bowden-Jones, McPhillips, Rogers, Hutton, & Joyce, 2005; Paulus, Tapert, & Schuckit, 2005). The correlation between the different behavioural measures in our sample was weak and not significant. Poor correlations between the Go/NoGo task performance, a measure of behavioural inhibition, and the DDT was an expected finding. Indeed, both measures have been proposed to reflect independent dimensions of impulsivity (de Wit & Richards, 2004), a hypothesis which is sustained by our results. In contrast, the lack of overlap between the DDT and IGT, as indicated by the weak correlations and the loading on separate factors in the factor-analysis, was unexpected. Indeed, within a cocaine-dependent population, Monterosso et al. (2001) reported earlier significant correlations between IGT and DDT performance (r = .37), suggesting an overlap between both tasks. This inconsistency may be explained by both differences in sample characteristics and the conceptual differences regarding the cognitive constructs that are measured by both tasks. First, an extensive literature has indicated a consistent relation between drug-dependence and high impulsivity on measures both of inhibition and decision-making (Dawe et al., 2004). In contrast, alcoholics may be a more heterogeneous population with some groups high in impulsivity and some groups low (Bjork et al., 2004; Dom, D’Haene, et al., 2006; Dom, Hulstijn, et al., 2006). Second, on a conceptual level, both tasks have been proposed to measure, different aspects of behavioural decision-making processes. Indeed, Ernst and Paulus (2005) suggested that decision-making is a complex (cognitive) construct, reflecting the process of forming preferences, selecting and executing actions, and evaluating outcomes with respect to choices between separate stimuli, each predicting a measurable rewarding or aversive outcome. Delay discounting is likely to be the main measure explored within a DDT paradigm while risk-discounting might represent a characteristic of the IGT. However, it is possible that delay and risk are inherently intertwined and whether such a differentiation is even possible is unclear (Rachlin, Brown, & Cross, 2000). Indeed, a relationship has been observed between steeper delay discounting and a greater tendency to engage in risky behaviour (needle sharing) (Odum, Madden, Badger, & Bickel, 2000). Alternatively, it cannot be excluded that sensitivity for reward underlies poor performance on both tasks, resulting in a
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rapid discounting of future rewards and a discounting of future, uncertain risks. Recent findings suggest that poor IGT performances relates specifically to individual differences in sensitivity for reward (e.g., Franken & Muris, 2005). However, the multiple cognitive processes that are involved during IGT performance make it difficult to consider this task as measuring only one cognitive aspect. Indeed, poor performance on the IGT may result through deficits within different cognitive dimensions, i.e., reward sensitivity, learning processes, cognitive flexibility (i.e., the ability to change strategies in view of changing reward/punishment contingencies), insensitivity for punishment, and the tendency to discount risks. In this line, Bechara (2003) suggested that decision-making, as measured by IGT, constitutes a separate dimension governing behavioural control, closely associated but different from impulsivity. However, given the complexity of the decision-making concept, further differentiation regarding the different underlying processes is warranted (Ernst & Paulus, 2005). Several limitations warrant careful interpretation of our results. First, it needs to be noted that our study is a first approach in exploring the distribution and interrelation of frequently used measures of impulsivity within an alcohol-dependent population. Within this perspective we took a two-dimensional model of impulsivity as a starting base. However, more studies are needed to explore the plausibility of a two-dimensional model for impulsivity. Second and typical of studies within inpatient populations, multiple factors could have confounding effects (e.g., effects of pharmacological treatment, different types of illicit drugs, genetic loading, and psychiatric co-morbidity). However, taking these factors into account would take much larger populations with respect to statistical power. Finally, careful interpretation is warranted when generalizing our findings towards the general population. Indeed, hypothetically the natural spreading of impulsivity scores may be biased by the choice of an alcohol-dependent sample. However, we note that our findings are in line with those within a general, healthy population sample (Reynolds et al., 2006).
5. Conclusion The results of our study suggest that self-report and behavioural measures of impulsivity reflect, at least partially, different aspects of impulsivity and emphasise that impulsivity needs to be approached as a multidimensional construct. When studying impulsivity within the context of psychopathology future studies should explore all dimensions and use a comprehensive set of both self-report and behavioural measures. Acknowledgements This research was made possible by an internal research grant awarded by the Psychiatric Centre, Alexian Brothers, Boechout, Belgium. The report of our research was supported by Vereniging Ambulante Geestelijke Gezondheidszorg Antwerpen (VAGGA, Centre for Ambulatory Health Care, Antwerp, Belgium). The authors are indebted to Dr. de Wit & Dr. Richards and Dr. Bechara for providing us with their computerised version of respectively the Delay Discounting Task (DDT) and the Iowa Gambling Task (IGT).
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Dimensions of impulsive behaviour in abstinent alcoholics Geert Dom
a,*
, Bieke De Wilde a, Wouter Hulstijn b, Bernard Sabbe
b
a
b
Psychiatric Centre Alexian Brothers, Boechout 2530, Belgium Collaborative Antwerp Psychiatry Research Institute (CAPRI), Antwerp, Belgium Received 5 April 2006; received in revised form 21 July 2006 Available online 10 October 2006
Abstract Impulsivity is a complex multidimensional behavioural construct that has been frequently implicated in the pathogenesis of addictive disorders. Both self-report and behavioural measures have been developed to assess its underlying dimensions but their interrelation is still poorly understood and few studies have employed a comprehensive set of measures within a given population to explore their interrelation. In a stably abstinent alcohol-dependent population we explored the interrelations between two well known personality questionnaires (BIS-11 and SSS), and two behavioural measures reflecting different dimensions of impulsivity, behavioural disinhibition (Go/NoGo task) and delay discounting (DDT). In addition, we included the Iowa Gambling Task (IGT), a neurobehavioural measure of decision-making, a cognitive dimension that is closely related to impulsivity. Strong correlations were found between the different subscales of the self-report measures. However, the correlations between the behavioural measures and the self-report measures were weak, suggesting that they both tap into different aspects of the concept. Finally, a principal component analysis on the data of the behavioural measures revealed that they all loaded on separate factors. These findings support the hypothesis that behavioural disinhibition and delay discounting are two independent dimensions of impulsivity and that decision-making is a third cognitive dimension, independent of both other measures. Ó 2006 Elsevier Ltd. All rights reserved. Keywords: Impulsivity; Behavioural measures; Self-report measures; Decision-making; Alcohol dependence
*
Corresponding author. Tel.: +32 3 455 75 31. E-mail address: [email protected] (G. Dom).
0191-8869/$ - see front matter Ó 2006 Elsevier Ltd. All rights reserved. doi:10.1016/j.paid.2006.08.007
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1. Introduction Alcoholism is a very heterogenic disorder and the individual differences with respect to its aetiology, course and severity are considerable. Thus, the identification of elements that constitute an increase in individual vulnerability and mediate the course of the disorder is of paramount importance. Impulsivity has been proposed as an important factor with respect to the initiation and course of addictive processes (Dawe, Matthew, & Loxton, 2004; Dom, Hulstijn, & Sabbe, 2006). For example, prospective studies have shown that individual differences in childhood behavioural disinhibition predict early substance use during adolescence and substance use disorder in young adulthood (e.g., Masse & Tremblay, 1997). Generally, impulsivity is used to describe a broad range of maladaptive behaviours including an inability to inhibit inappropriate action, insensitivity to delayed or uncertain consequences, perception of time as progressing more slowly than actual time, and the perseverance of negatively reinforced actions (McDonald, Schleifer, Richards, & de Wit, 2003; Moeller, Barratt, Dougherty, Schmitz, & Swann, 2001). On a conceptual level, there is now wide agreement that impulsivity consists of a number of different dimensions (Bechara, 2003; Dougherty, Mathias, Marsh, & Jagar, 2005; Evenden, 1999). Dawe et al. (2004) and de Wit and Richards (2004) define two broad dimensions. The first dimension can be labelled as ‘‘behavioural disinhibition or rash impulsiveness’’. This includes problems both in response initiation and response inhibition. In this respect impulsive behaviour can be a consequence of responding prior to complete processing and evaluation of a stimulus (‘‘acting without thinking’’), or can result from a failure to inhibit an already initiated response (response inhibition). A second dimension has been labelled as ‘‘consequence sensitivity or impulsive decision-making’’ (de Wit & Richards, 2004). Here, impulsivity is defined as behavioural choices (‘‘decisions’’) that persist despite negative or less than optimal consequences, i.e., a preference for small immediate rewards over later, larger rewards (‘‘delay discounting’’) or a preference for larger immediate rewards coupled to later, uncertain larger punishments versus smaller immediate rewards associated with smaller, later punishments (‘‘risk discounting’’) (Monterosso, Erhman, Napier, O’Brien, & Childress, 2001). Various measures have been developed to assess impulsive behaviour. Broadly these can be divided into self-report measures of personality that rely on an individual’s self-perception of their behaviour, and behavioural tasks that measure overt behaviour related to specific dimensions of impulsivity. Typically, both types of measurements do correlate only weakly, indicating that they measure different aspects of impulsivity (Dom, D’Haene, Hulstijn, & Sabbe, 2006; Moeller et al., 2001; Reynolds, Ortengren, Richards, & de Wit, 2006). There are few validated behavioural instruments available to measure impulsivity and it remains to be specified which aspect of the concept they tap in and to which degree these measures interrelate (Moeller et al., 2001; Reynolds et al., 2006). Only a few studies have used a comprehensive battery to assess simultaneously the different aspects of impulsivity within a given sample. Reynolds et al. (2006) used four behavioural tasks within a sample of healthy community recruited individuals. Factor analysis of their data indicated that these tasks loaded on two separate components, the first, labelled impulsive disinhibition (Stop Task and Go/NoGo Task) and second, impulsive decision-making (Delay Discounting Task and Balloon Analog Risk Task). In a sample of cocaine dependent patients, Monterosso et al. (2001) compared three behavioural decision-making tasks, i.e., Delay Discounting Task (DDT, Richards, Zhang, Mitchell, & de Wit,
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1999), Iowa Gambling Task (IGT, Bechara, Damasio, Damasio, & Anderson, 1994), and the Roger Decision-Making Task (RDMT, Rogers et al., 1999). Impairments on all three tasks have been reported within substance abusers relative to controls (Bechara, 2003; Bjork, Hommer, Grant, & Danube, 2004; Dom, D’Haene, et al., 2006; Dom, Hulstijn, et al., 2006; Richards et al., 1999). These behavioural decision-making tasks have as communality that task performance involves an evaluation and choices (‘‘decision-making’’) between different consequent outcomes. Although the exact processes that are measured by these tasks remain to be specified, they all measure different aspects of decision-making, i.e., delay and risk-discounting. In the current study we report on the relations between self-report and behavioural measures of impulsivity within a sample of stably abstinent alcohol dependent inpatients. The study consists of two separate analyses. First we explored the correlations among the self-report measures, behavioural measures, and the measures of problem severity. Next we used a principal component analysis to explore the component structure among the behavioural measures. The Barratt Impulsivity Scale (BIS-11; Patton, Stanford, & Barratt, 1995) and the Sensation Seeking Scale (SSS; Zuckerman, Kolin, Price, & Zoob, 1964) were used as self-report measures of impulsivity. Impulsivity, as measured with the BIS is best described as a tendency to act rashly and without consideration of consequences. Sensation seeking is a tendency to seek out intense, novel forms of sensation and experiences, regardless of the risks involved. In a recent factor analysis, the BIS, the SSS and another widely used measure, the Eysencks’ I7 Impulsiveness subscale (Eysenck, Pearson, Easting, & Allsopp, 1985), have been reported to load on the same factor, labelled by Dawe et al. (2004) rash-spontaneous impulsiveness. For the behavioural tasks we used a Go/NoGo task which has been widely used as a measure for response inhibition. In addition, two decision-making tasks were included, i.e., a Delay Discounting Task (Richards et al., 1999) and the Iowa Gambling Task (Bechara et al., 1994). Based on the previous findings, described above, we hypothesized that the correlations among the self-report measures would be high but that the correlations between the self-report measures and behavioural measures would be only poor or modest. Furthermore, we expected that, with respect to the behavioural measures, the correlations between a measure of response inhibition (i.e., Go/NoGo task) and decision-making (i.e., DDT and IGT) would be poor, while correlations between the DDT and IGT would be high. Finally, we expected that separate inhibition and decision-making components would be identified from the principal components analysis.
2. Method 2.1. Sample Participants were 92 DSM-IV (American Psychiatric Association, 1994) alcohol-dependent individuals consecutively recruited from an inpatient treatment facility. For a full description of recruitment procedure, see Dom, D’Haene, et al. (2006) and Dom, Hulstijn, et al. (2006). Only patients who engaged in long-term inpatient treatment, after being fully detoxified (and whose abstinence could be daily monitored), were eligible for the current study. All participants gave informed consent and the study was reviewed and approved by the medical ethics committee of the Psychiatric Hospitals, Brothers of Charity, Belgium.
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2.2. Procedure All patients completed the self-report questionnaires during the first and second week after admission to the clinic. To exclude confounding due to withdrawal effects, the intelligence tests and the behavioural tasks were administered in weeks 4 and 5, i.e., after a mean of 36.63 days (SD 19.59) of monitored abstinence. Test conditions (room, computer) were the same for all patients. Before the behavioural tasks, the patients provided a breath sample that was screened for alcohol using an Alcometer as well as a urine specimen that was screened for opioids, cocaine, amphetamine, cannabis, and benzodiazepine. 2.3. Measurements 2.3.1. Intelligence The Wechsler Adult Intelligence Scale (WAIS-III, Dutch version, Swets Test Publishers, 2000) consists of an individually administered battery of tests designed to measure verbal (VIQ) and performance (PIQ) intelligence. 2.3.1.1. Personality inventory measures 2.3.1.1.1. Barratt impulsiveness scale (BIS-11). The Dutch adaptation of the Barratt Impulsiveness Scale (BIS-11; Patton et al., 1995) is a 30-item self-report questionnaire with a total score (BIS_T) and three subscales measuring different aspects of impulsiveness: non-planning impulsiveness (BIS_NP), motor impulsiveness (BIS_M), and cognitive impulsiveness (BIS_C). Although the BIS-11 has been translated in many languages showing good psychometric properties, the Dutch BIS-11 has as yet not been validated, so no norm data are available. 2.3.1.1.2. Sensation seeking scale (SSS). The Dutch adaptation (SSS-D) is based on earlier versions of Zuckerman’s Sensation Seeking Scale (Zuckerman et al., 1964). It was tested in a Dutch population and showed good reliability and validity and norm scores for different age groups are available (Feij, Dekker, Koopmans, & Boomsma, 1997). The SSS-D is a 67-item, self-report questionnaire providing a general sensation seeking score (SSS_G) as well as scores on four subscales assessing disinhibition (SSS_DIS), thrill and adventure seeking (SSS_TAS), experience seeking (SSS_ES) and boredom susceptibility (SSS_BS). 2.3.1.2. Behavioural measures 2.3.1.2.1. Go/NoGo task. A classical Go/NoGo paradigm was presented using a computer screen and a writing tablet on which the participant could write or draw with an electronic pen (See also Dom, De Wilde, Hulstijn, van den Brink, & Sabbe, 2006). Pen movements controlled a screen cursor (yellow dot on the screen) (Fig. 11). The participant is asked to move his cursor (yellow dot) as fast and accurate as possible into the newly presented target circle if this circle is coloured dark blue (Go trial) and withhold his reaction if the new target circle is coloured light blue (NoGo trial). Four series each containing 56 trials (ratio Go/NoGo was 1/8) were presented. The dependent variables were the number of errors (Error) in the NoGo trials and the reaction (RT) and in the Go trials. An error on a NoGo signal was defined as any movement away from 1
For interpretation of colour in this figure legend, the reader is referred to the web version of this article.
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Fig. 1. Go/NoGo task; left panel shows an example of a NoGo trial; right panel of a go trial.
the start circle. RT was defined as the time between the appearance of a new target circle and response initiation. 2.3.1.2.2. Delay-discounting task. A classical DDT design, using hypothetical reward money, was presented on a computer screen (Richards et al., 1999). For a full description of the procedure, see also Dom, D’Haene, et al. (2006). Indifference points were determined for an amount of 100€ (hypothetical money) over five different delays: 2, 30, 180, 365, and 730 days, respectively. The indifference points obtained at each of the delays were plotted and discount functions were derived through curve-fitting analysis (Matlab, version 5.3) using Mazur’s formula (Mazur, 1987): V ¼ A=ð1 þ kDÞ: The dependent variable used in the analysis of the DDT task in current study was the natural log transformation of the discount rate (k). 2.3.1.2.3. Iowa gambling task (IGT). We used a computerised version of the original IGT (Bechara et al., 1994; Dom, De Wilde, Hulstijn, van den Brink, & Sabbe, in press). In this gambling task participants choose cards of any of four decks of cards, presented on a computer screen, labelled A, B, C and D. The rewards (hypothetical money) on the A and B decks are twice as high as those for the C and D decks, while the punishments are five times as high. Furthermore A and C decks generate smaller punishments more frequently (i.e., on average, 3 out of 4 times) while the B and D decks generate larger punishments less frequently (i.e., on average 3 out of 5 times). Thus, decks A and B (‘‘disadvantageous decks’’) both resulted in an overall loss due to higher individual rewards with moderate but frequent punishment (A) and higher individual rewards with very large but infrequent punishments (B). Decks C and D (‘‘advantageous decks’’) yielded an overall gain via lower individual returns and frequent, low punishment (C) and lower individual returns and moderate but infrequent punishment (D). The dependent variable in the current study was the overall net score over five blocks of twenty cards. The net score for each block was defined as the total number of cards chosen from decks C and D minus the total number of cards chosen from decks A and B (Bechara et al., 1994; Dom et al., in press). 2.4. Analysis Pearson correlations were used with a Bonferroni correction for multiple comparisons resulting in a significance level (a) of p < 0.003 (=0.05/14).
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For the principal components analysis, components having eigenvalues P 1 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. All analyses were performed using SPSS-11 statistical software.
3. Results 3.1. Sample characteristics Sample characteristics are presented in Table 1. The participants were predominantly male (74%). Male (n = 68) and female (n = 24) participants were not different in age, education, or number of years of alcohol abuse/dependence. Although alcohol-dependence was the inclusion criterion, a sizable portion (34.8%) of the participants had a history (lifetime) of co-morbid illicit drugs or benzodiazepine dependence. 3.2. Correlation analysis Table 2 shows the correlation matrix for all of the measures of impulsivity. Significant, positive, correlations were found between both self-report measures (BIS-11 and SSS) and between the subscales within each self-report measure. In contrast, none of the behavioural measures correlated with the self-report measures. No significant correlations were found between any of the behavioural measures. Finally, IQ did not correlate significantly with any of the self-report or behavioural measures, with exclusion of the DDT. Given the male dominance in our sample a separate analysis was done within each gender to explore differences in patterns between genders. For both genders the same correlation patterns were found as within the whole, mixed gender, sample. 3.3. Principal-component analysis The principal-component analysis on IQ, self-report and behavioural measures of impulsivity resulted in five principal components (with eigenvalues P 1) explaining 69% of the variance
Table 1 Alcohol-dependent inpatients (n = 92): sample characteristics Mean (SD) Age (yr) Age onset alcoholism (yr) Number of years of alcohol dependence Number years education WAIS (total IQ)
42.3 26.0 16.3 12.7 96.7
(9.6) (9.6) (9.6) (2.8) (12.4)
% of sample Men Nicotine dependence Pure alcohol dependence Alcohol and benzodiazipine Alcohol and illicit drug
74 82 34.7 31.5 34.8
BIS_C BIS_M BIS_NP BIS_T SSS_TAS SSS_ES SSS_BS SSS_DIS SSS_G IGT Error RT DDT IQ *
BIS_C
B_M
B_NP
B_T
1 .563* .303 .741* .025 .030 .197 .238 .117 .003 .126 .143 .149 .271
1 .464* .851* .245* .249 .316 .427* .397* .068 .094 .094 .173 .233
1 .781* .078 .262 .331* .231 .349* .255 .059 .089 .048 .105
1 .133 .199 .363* .378* .378* .151 .115 .134 .154 .256
S_TAS
S_ES
S_BS
S_DIS
S_G
IGT
Error
RT
DDT
1 .468* .029 .044 .042 .142 .040
1 .027 .089 .066 .269 .000
1 .010 .031 .027 .188
1 .090 .044 .136
1 .060 .074
1 .378*
1 .334* .110 .041 .649* .049 .054 .019 .053 .002
1 .165 .049 .647* .002 .058 .057 .130 .171
1 .339* .592* .105 .073 .040 .295 .205
Significant on a Bonferroni, multiple comparisons, corrected significance level of p < 0.003 (=0.05/14).
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Table 2 Correlations among the self-report measures, Barratt Impulsivenes Scale [BIS-11; subscales Cognitive (BIS_C), Motor (BIS_M), Non-planning (BIS_NP), and total score (BIS_T)] and Sensation Seeking Scale [SSS; subscales Thrill and Adventure seeking (SSS_TAS), Experience Seeking (SSS_ES), Boredom Susceptibility (SSS_BS), Disinhibition (SSS_DIS), and General Sensation Seeking (SSS_G)] and behavioural measures on a Go/ NoGo task [number of commission errors (Error) and reaction time on Go trials (RTGO)], a Delay Discounting Task (DDT), the Iowa Gambling Task (DDT), and IQ
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Table 3 Principal components analysis (n = 92) (rotated) for behavioural measures Eigenvalues % Variance explained
3.919 28.0 1
SSS-TAS SSS-ES SSS-BS SSS-DIS SSS_G DDT IGT nogof1 BIS_C BIS_M BIS_NP BIS_T RT IQ
.062 .218 .354 .195 .311 .067 .026 .003 .736* .768* .710* .973* .210 .334
2.064 14.7
1.436 10.3
2 *
.721 .467 .542* .479 .911* .168 .038 .019 .207 .259 .197 .129 .439 .186
1.136 8.1
1.105 7.9
3
4
5
.158 .457 .479 .300 .062 .746* .101 .099 .665* .191 .665* .098 .078 .665*
.106 .002 .097 .367 .070 .083 .858* .027 .186 .097 .392 .083 .003 .295
.161 .393 .010 .336 .035 .237 .035 .839* .108 .131 .048 .010 .163 .153
Number of errors on the NoGo trials (Error), reaction times on the Go trials (RT), Delay Discounting Task (DDT), Iowa Gambling Tasks (IGT), and the subscales of the Barratt Impulsiveness Scale (Cognitive, C; Motor, M; NonPlanning, NP, Total score, T), Sensation Seeking Scale (thrill and adventure seeking, TAS; experience seeking, ES; boredom susceptibility, BS; disinhibition, DIS; general sensation seeking, Gen), and Wais full IQ (IQ). * Component loadings of .500 or higher were considered significant.
(Table 3). One component loaded primarily on the BIS and a separate component on the Sensation Seeking subscales. The third component clustered the DDT negatively with IQ, and the BIS Cognitive and non-Planning subscale. Finally, both the IGT and the behavioural inhibition (error) loaded upon separate components. The three different behavioural tasks each loaded independently on a separate component, which can be labelled ‘‘behavioural inhibition’’ as reflected by the Go/NoGo performance, ‘‘delay-discounting’’ (reflected by high DDT performance), and finally, ‘‘risk-discounting’’ (IGT).
4. Discussion This study examined the relations among two self-report measures and three behavioural measures of impulsive behaviours. Taken together, our results show that there were significant correlations between several subscales of the self-report measures, but these self-report measures were unrelated to the task measures. Furthermore, no significant correlations were found between the behavioural measures and we found that the task measures fell into three separate components, which can be labelled behavioural disinhibition (Go/NoGo task), delay-discounting (DDT), and risk-discounting (IGT). The self-report measures of impulsivity and sensation seeking were not related to performance on the behavioural tasks. This finding is consistent with earlier studies that have failed to observe substantial correlations between self-report measures and behavioural measures of impulsivity in
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very diverse samples coming from the general population (Reynolds et al., 2006), psychiatric outpatients (Crean, de Wit, & Richards, 2000), and cocaine-dependent patients (Monterosso et al., 2001). These findings suggest that behavioural tasks and self-report measures tap different aspects of impulsivity. Research on impulsivity has generally relied on self-report, or on measurements or observations of behaviour whose impulsivity was open to interpretation. These measures have yielded valuable information about impulsivity as a stable and enduring trait in individuals with a wide range of behavioural disturbances (Bornovalova, Lejuez, Daughters, Rosenthal, & Lynch, 2005; Swann, Bjork, Moeller, & Dougherty, 2002). However, self-report measures do not lend themselves well to pharmacologic or physiologic studies of impulsivity, because they are subjective, measure a relatively stable characteristic, and cannot be related directly to biological models of impulsivity based on animal studies (Swann et al., 2002). In contrast, behavioural approaches have the advantage of being sensitive to transient changes in impulsivity (i.e., state-dependent impulsivity) and may be more amenable to situations where repeated administration in necessary. Behavioural measures of impulsivity have been suggested to have a role in assessing changes during treatment (Bickel & Marsch, 2001; Dougherty et al., 2003), and recent studies indicate that specifically behavioural measures of impulsivity may be a better predictor for relapse risk, than self-report measures (e.g., Bowden-Jones, McPhillips, Rogers, Hutton, & Joyce, 2005; Paulus, Tapert, & Schuckit, 2005). The correlation between the different behavioural measures in our sample was weak and not significant. Poor correlations between the Go/NoGo task performance, a measure of behavioural inhibition, and the DDT was an expected finding. Indeed, both measures have been proposed to reflect independent dimensions of impulsivity (de Wit & Richards, 2004), a hypothesis which is sustained by our results. In contrast, the lack of overlap between the DDT and IGT, as indicated by the weak correlations and the loading on separate factors in the factor-analysis, was unexpected. Indeed, within a cocaine-dependent population, Monterosso et al. (2001) reported earlier significant correlations between IGT and DDT performance (r = .37), suggesting an overlap between both tasks. This inconsistency may be explained by both differences in sample characteristics and the conceptual differences regarding the cognitive constructs that are measured by both tasks. First, an extensive literature has indicated a consistent relation between drug-dependence and high impulsivity on measures both of inhibition and decision-making (Dawe et al., 2004). In contrast, alcoholics may be a more heterogeneous population with some groups high in impulsivity and some groups low (Bjork et al., 2004; Dom, D’Haene, et al., 2006; Dom, Hulstijn, et al., 2006). Second, on a conceptual level, both tasks have been proposed to measure, different aspects of behavioural decision-making processes. Indeed, Ernst and Paulus (2005) suggested that decision-making is a complex (cognitive) construct, reflecting the process of forming preferences, selecting and executing actions, and evaluating outcomes with respect to choices between separate stimuli, each predicting a measurable rewarding or aversive outcome. Delay discounting is likely to be the main measure explored within a DDT paradigm while risk-discounting might represent a characteristic of the IGT. However, it is possible that delay and risk are inherently intertwined and whether such a differentiation is even possible is unclear (Rachlin, Brown, & Cross, 2000). Indeed, a relationship has been observed between steeper delay discounting and a greater tendency to engage in risky behaviour (needle sharing) (Odum, Madden, Badger, & Bickel, 2000). Alternatively, it cannot be excluded that sensitivity for reward underlies poor performance on both tasks, resulting in a
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rapid discounting of future rewards and a discounting of future, uncertain risks. Recent findings suggest that poor IGT performances relates specifically to individual differences in sensitivity for reward (e.g., Franken & Muris, 2005). However, the multiple cognitive processes that are involved during IGT performance make it difficult to consider this task as measuring only one cognitive aspect. Indeed, poor performance on the IGT may result through deficits within different cognitive dimensions, i.e., reward sensitivity, learning processes, cognitive flexibility (i.e., the ability to change strategies in view of changing reward/punishment contingencies), insensitivity for punishment, and the tendency to discount risks. In this line, Bechara (2003) suggested that decision-making, as measured by IGT, constitutes a separate dimension governing behavioural control, closely associated but different from impulsivity. However, given the complexity of the decision-making concept, further differentiation regarding the different underlying processes is warranted (Ernst & Paulus, 2005). Several limitations warrant careful interpretation of our results. First, it needs to be noted that our study is a first approach in exploring the distribution and interrelation of frequently used measures of impulsivity within an alcohol-dependent population. Within this perspective we took a two-dimensional model of impulsivity as a starting base. However, more studies are needed to explore the plausibility of a two-dimensional model for impulsivity. Second and typical of studies within inpatient populations, multiple factors could have confounding effects (e.g., effects of pharmacological treatment, different types of illicit drugs, genetic loading, and psychiatric co-morbidity). However, taking these factors into account would take much larger populations with respect to statistical power. Finally, careful interpretation is warranted when generalizing our findings towards the general population. Indeed, hypothetically the natural spreading of impulsivity scores may be biased by the choice of an alcohol-dependent sample. However, we note that our findings are in line with those within a general, healthy population sample (Reynolds et al., 2006).
5. Conclusion The results of our study suggest that self-report and behavioural measures of impulsivity reflect, at least partially, different aspects of impulsivity and emphasise that impulsivity needs to be approached as a multidimensional construct. When studying impulsivity within the context of psychopathology future studies should explore all dimensions and use a comprehensive set of both self-report and behavioural measures. Acknowledgements This research was made possible by an internal research grant awarded by the Psychiatric Centre, Alexian Brothers, Boechout, Belgium. The report of our research was supported by Vereniging Ambulante Geestelijke Gezondheidszorg Antwerpen (VAGGA, Centre for Ambulatory Health Care, Antwerp, Belgium). The authors are indebted to Dr. de Wit & Dr. Richards and Dr. Bechara for providing us with their computerised version of respectively the Delay Discounting Task (DDT) and the Iowa Gambling Task (IGT).
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