Abstract
Rationale
Ecstasy (±3,4-methylenedioxymethamphetamine) is a widely used recreational drug that may damage the serotonin system and may entail neuropsychological dysfunctions. Few studies investigated predictors for ecstasy use. Self-reported impulsivity does not predict the initiation of ecstasy use; the question is if neuropsychological indicators of impulsivity can predict first ecstasy use.
Objective
This study tested the hypothesis that a neuropsychological indicator of impulsivity predicts initiation of ecstasy use.
Materials and methods
Decision-making strategy and decision-making reaction times were examined with the Iowa Gambling Task in 149 ecstasy-naive subjects. The performance of 59 subjects who initiated ecstasy use during a mean follow-up period of 18 months (range, 11–26) was compared with the performance of 90 subjects that remained ecstasy-naive.
Results
Significant differences in decision-making strategy between female future ecstasy users and female persistent ecstasy-naive subjects were found. In addition, the gap between decision-making reaction time after advantageous choices and reaction time after disadvantageous choices was smaller in future ecstasy users than in persistent ecstasy-naives.
Conclusion
Decision-making strategy on a gambling task was predictive for future use of ecstasy in female subjects. Differences in decision-making time between future ecstasy users and persistent ecstasy-naives may point to lower punishment sensitivity or higher impulsivity in future ecstasy users. Because differences were small, the clinical relevance is questionable.
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Introduction
Ecstasy or ±3,4-methylenedioxymethamphetamine (MDMA) is a popular recreational drug that is used by many teenagers, adolescents, and young adults (Drugs Informatie en Monitoring Systeem 2006; El-Mallakh and Abraham 2007). Given the extensive scientific literature suggesting sustained harmful consequences of ecstasy use on the serotonin system in the brain (Reneman et al. 2006; Ricaurte et al. 2000) and its neuropsychological correlates such as memory impairment (Gouzoulis-Mayfrank and Daumann 2006; Schilt et al. 2007), it seems desirable to investigate factors that predict future ecstasy use.
A few studies focused on predictors for future ecstasy use, looking either at internalizing factors such as anxiety and depression or externalizing factors such as sensation seeking and impulsivity. One prospective, population-based study (Huizink et al. 2006) reported that symptoms of anxiety and depression in childhood were related to use of ecstasy in adolescence and adulthood. These findings are in line with a retrospective study showing a strong association between past-year depressive and panic symptoms and recent-onset ecstasy use (Martins et al. 2006). In addition, Lieb et al. (2002) reported that mental disorders precede ecstasy use (Lieb et al. 2002). On the other hand, our own prospective cohort study indicated that depressive symptoms did not predict future ecstasy use (de Win et al. 2006).
In addition, our prospective study failed to show self-reported sensation seeking or impulsivity to predict future ecstasy use (de Win et al. 2006). However, impulsivity is a complex phenomenon which can be divided into different aspects (Evenden 1999). For example, Patton et al. (1995) distinguish motor impulsivity, cognitive impulsivity, and non-planning impulsivity (Patton et al. 1995), whereas Whiteside and Lynam (2001) describe aspects such as urgency, (lack of) premeditation, (lack of) perseverance, and sensation seeking (Whiteside and Lynam 2001). One may not expect this complexity to be totally expressed in self-report measures, and it is conceivable that other measures, such as neuropsychological indicators of impulsivity, are more predictive of future ecstasy use. For example, decision making or making choices may be considered as an executive function in which behavioral inhibition and impulsivity play a substantial role (Deakin et al. 2004; Monterosso and Ainslie 1999). It has been proposed that high impulsivity and risky decision making are factors that might lead to drug use (Bechara and Damasio 2002; Bechara et al. 2001; Bolla et al. 2003; Ernst et al. 2003; Verdejo-Garcia et al. 2008). Some developmental studies on risks for alcohol abuse indeed show that mild executive dysfunctions in children with familial risk for alcohol or substance dependence enhance the risk for later addictions (Giancola and Tarter 1999; Tarter et al. 2004).
To our knowledge, there are currently no prospective studies on decision-making strategies before first ecstasy use. There are some studies that examined decision making in ecstasy users after the use of ecstasy because the investigators reasoned that altered decision making could be a sustained consequence of reduced serotonin availability (Vollenweider et al. 2005; Morgan et al. 2006; Quednow et al. 2007). Indeed, impaired decision making 90–120 min after MDMA administration was reported in one study (Vollenweider et al. 2005), but this was not replicated by another study (Ramaekers and Kuypers 2006). Two other studies showed impaired decision making in ecstasy users after a minimal abstention period of 3–5 days (Morgan et al. 2006; Quednow et al. 2007). However, no differences between ecstasy users and controls were found after a minimum abstention period of 2 weeks (Fox et al. 2002).
Instead of looking at the consequences of ecstasy use on decision making, the current study focused on decision-making strategy before the first use of ecstasy. A neuropsychological measure of risk taking, the Iowa Gambling Task, was used in a prospective cohort of at-risk young adults. It was hypothesized that future ecstasy users would show a more risky decision-making strategy on the gambling task than persistent ecstasy-naives, which should become visible in less advantageous choices and shorter reaction times after losses in future ecstasy users compared to persistent ecstasy-naives.
Materials and methods
This study is part of the larger Netherlands XTC Toxicity Study investigating causality, course, and clinical relevance of ecstasy neurotoxicity (de Win et al. 2005).
Participants and design
Between 2002 and 2004, 188 ecstasy-naive volunteers (18–35 years) who considered starting ecstasy use in the near future were recruited by targeted site sampling at colleges and dance events, paper and website advertisements, and through snowball sampling (Vervaeke et al. 2006). Exclusion criteria were ecstasy use in the past (at baseline session); a serious medical, neurological, or mental illness; use of medications that may influence cognition; pregnancy; and intravenous drug use. Subjects had to abstain from using psychoactive substances for at least 2 weeks and from alcohol for at least 1 week prior to examination. Drug use during the days before assessment was checked through urinalysis [enzyme-multiplied immunoassay for amphetamines, MDMA, opiates, benzoylecgonine (cocaine), benzodiazepines, 11-nor-Δ9-THCCOOH, ethanol].
After inclusion, all subjects took part in neuropsychological assessment. Subjects had to complete validated substance use questionnaires at baseline and thereafter every 3 months during a mean follow-up period of 18 months (range, 11–26 months; Van de Wijngaart et al. 1997). Last-year use of alcohol (units/week), tobacco (cigarettes/week), cannabis (number of joints), and amphetamines and cocaine (occasions) were measured.
Verbal intelligence was estimated because correlations between IQ and performance on the Iowa Gambling Task have been reported (Monterosso et al. 2001). For this purpose, the Dutch version of the National Adult Reading Test (Nelson and O’Connell 1978), the Dutch Adult Reading Test (DART), was administered because it is relatively insensitive to cognitive impairment caused by neurological disorders (Schmand et al. 1991). As decision making might be affected by mood (Must et al. 2006; Taylor Tavares et al. 2007), also the Beck Depression Inventory (BDI) was used to compare future ecstasy users and persistent ecstasy-naives on rate of depressive symptoms (Beck and Steer 1984; Beck et al. 1961). The BDI is a 21-item self-report rating inventory which measures characteristic attitudes and symptoms of depression in the week prior to assessment. Each item is scored 0 to 3, with higher scores indicating more depressive symptoms. The BDI showed high levels of reliability and validity (Beck and Steer 1984; Bouman et al. 1985). Total BDI scores were calculated. Scores higher than 13 are indicative for depression.
Subjects were paid for their participation (€100 or €150 per session depending on the number of assessments). Besides the tests described in this paper, subjects took part in more extensive neuropsychological testing and brain imaging, which are described elsewhere (e.g., de Win et al. 2007; Jager et al. 2008; Schilt et al. 2007). The study was approved by the local medical ethics committee. After complete description of the study, each subject gave written informed consent.
Assessments
Outcome variable: ecstasy use
Future first time ecstasy use was categorized in a binary variable (yes = 1, no = 0).
Predictor variable: decision making
A computerized version of the Iowa Gambling Task was used (Bechara et al. 1994, 1999). Four decks of cards are displayed on a screen. Subjects have to choose a card from one of the decks by selecting keyboard numbers 1, 2, 3, or 4. Each choice results in winning or losing money. Two of the four decks give high rewards, but also high losses, and result in a net loss in the long run (disadvantageous decks 1 and 2). The two other decks result in low rewards, but also render lower losses, and result in a net gain in the long run (advantageous decks 3 and 4). The explicit goal of the test is to maximize profit on a loan of play money (Bechara et al. 2000). Standard test instructions were used (Bechara et al. 1999). Subjects were instructed to win as much money as possible, and they were told that some decks were worse than others but that they still could win if they avoided the worst decks. Reaction time was measured after each trial. Each deck consisted of 60 cards, and the task ended after 100 trials. The main measure for general performance was the number of cards picked from the advantageous decks (IGT performance). Because 14 subjects (9.4% of the total sample) finished all the cards in one deck in the last stage of the task, and would therefore bias the total IGT score, it was decided to exclude the last 20 responses of all subjects from the analyses. In addition, the mean difference in decision-making reaction time after net wins and losses was analyzed (dRT: RTwin minus RTloss), indicating reflection following losses or negative feedback. Because the IGT involves a learning component, most of the participants learned to choose particular decks over time. Once subjects have decks of preference, they will be less affected by wins or losses, and therefore, reaction times after losses will decrease during the course of the task. Consequently, difference in reaction time (dRT) will change during the course of the task. In a repeated measures analysis of variance (ANOVA), with reaction time after losses as the dependent measure and stage (stage 1 through 4) as the within-subject factor, the effect of stage on reaction time was significant: F 2.04,301.47 = 18.14, p < 0.001. For this reason, a more valid measurement for reward/loss sensitivity is dRT during the first three stages (0–60) of the task. The first 60 responses were included in the analysis.
Statistical analyses
Unpaired t tests were performed to examine differences between future ecstasy users and persistent ecstasy-naives in age, DART-IQ, and BDI total score. Group differences in gender were investigated using a chi-square test. In addition, we investigated whether the two groups were similar in the use of cannabis, alcohol, tobacco, cocaine, and amphetamine prior to the use of ecstasy with non-parametric Mann–Whitney tests. This is important because effects of substance abuse on decision making have been reported (Goudriaan et al. 2005, 2007; Grant et al. 2000; Rogers et al. 1999). We also investigated whether drug use at baseline was associated with IGT performance and dRT using Spearman’s r.
A multivariate logistic regression analysis was performed with future ecstasy use (no = 0, yes = 1) as dependent variable and the cognitive measures IGT performance and dRT as predictor variables. Because some studies reported sex differences in IGT general performance (Bolla et al. 2004; Reavis and Overman 2001), we also added gender and the IGT performance by gender and dRT by gender interaction terms as covariates together with DART-IQ and substance use. Because of their skewed distribution, we used the logarithmic transformation for the cannabis, alcohol, and cigarette use variables. Since only a few subjects used cocaine (11%) and a normal distribution could not be reached after log transformation, this variable was dichotomized (no use = 0, use = 1). Only one participant used amphetamine. Therefore, separate analyses for the effects of amphetamine use on decision-making strategies were not performed. The subject was kept in the analyses; excluding this subject from the analyses did not change any of the results. In the multivariate logistic regression model, DART-IQ, gender, and substance use were entered first. After that, the cognitive measures were entered in order to estimate the additive predictive value of these variables on future ecstasy use. Potential collinearity problems were tested using the tolerance factor (TF) and the variance inflation factor (VIF).
All analyses were performed using SPSS statistical software version 12.0.1 (SPSS, Chicago, IL, USA). Values of p < 0.025 were considered statistically significant (Bonferroni correction).
Results
Of the 188 recruited subjects, we acquired sufficient follow-up information on 149 volunteers (79%). Fifty-nine subjects started using ecstasy during the follow-up period, and 90 subjects remained ecstasy-naive. Reasons for not trying ecstasy include: fear of acute effects, knowledge about the harmfulness of the drug, and lack of opportunity. For a detailed description of this part of the study, the reader is referred to Vervaeke et al. (2008). Follow-up information of the other subjects was missing either because the volunteers did not want to participate in the follow-ups or because we could not reach them anymore. The group of subjects that dropped out had a significantly lower estimated DART-IQ (difference of five points between included subjects and dropouts). Age, sex distribution, and drug use did not differ significantly between dropouts and included subjects.
Demographics and substance use characteristics of the included subjects are shown in Table 1. The groups were similar in terms of gender distribution, age, DART-IQ, and BDI sum score. Drug use did not differ significantly between future ecstasy users and persistent ecstasy-naive subjects.
Iowa Gambling Task
A first exploration of Spearman’s correlations between the use of substances other than ecstasy and IGT performance and dRT, respectively, showed only a significant negative correlation between cocaine (number of times last year) and the number of advantageous deck choices (Spearman’s r = −0.28, p < 0.001): More cocaine use was associated with worse deck choices. However, cocaine use ever was not significantly associated with future ecstasy use [χ 2(1) = 2.97, p = 0.09].
A logistic regression model with DART-IQ, gender, and substance use as independent variables did not significantly predict future ecstasy use [χ 2(6) = 7.57, p = 0.27]. In the next step, the cognitive measures (IGT performance and the IGT performance by gender, dRT, and dRT by gender interaction terms) were added to the model. This improved the ability of the model to predict future ecstasy use significantly [χ 2(4,10) = 16.27, p < 0.01] and added 13.3% (Nagelkerke R 2) to the explained variation of the model. Because the dRT by gender interaction term was not significant (p > 0.10), this term was removed from the model (Hosmer and Lemeshow 2000). Repeated analysis showed that IGT performance, IGT performance × gender, and dRT still improved the predictive ability of the model significantly [χ 2(3,9) = 15.28, p < 0.01] with 12.5% (Nagelkerke R 2). In our model, multi-collinearity was not an issue (TF 0.73–0.97, VIF 1.03–1.37). The regression coefficients of IGT performance or gender cannot be interpreted as main effects in a model with a significant IGT by gender interaction term. However, separate analysis without the interaction factor showed no significant effects of gender or IGT performance. For the significance of the predictors, we looked at IGT performance by gender interaction and dRT. The beta coefficients indicated that less advantageous deck choices in female participants and smaller differences in reaction times after wins and losses (in males and females) resulted in a higher likelihood of future ecstasy use (see Figs. 1 and 2 and Table 2).
Figure 2 shows that primarily, the reaction times after losses differed between the two groups, with persistent ecstasy-naives having longer reaction times after losses than future ecstasy users. The overall classification accuracy of the whole model was 66.4%, with a negative predictive accuracy of 80% (persistent ecstasy-naives correctly classified in the ecstasy-naive group) and a positive predictive accuracy of 46% (future ecstasy users correctly classified in the future ecstasy use group).
Discussion
The current study prospectively investigated the association between decision-making strategy and future first ecstasy use. We hypothesized that a risky decision-making strategy on a gambling task would predict future first ecstasy use. In our study population, only in female participants was a relationship found between decision-making strategy and future ecstasy use: Less advantageous deck choices on a gambling task resulted in a higher likelihood of future first ecstasy use. In addition, decision-making reaction time differed significantly between the total group of persistent ecstasy-naives and the total group of future ecstasy users: Future ecstasy users did not prolong their reaction times after punishments, whereas persistent ecstasy-naives did.
A possible explanation for the finding that decision-making strategy only was predictive for future ecstasy use in women and not in men might be sought in differences in working memory capacity. Some studies postulate a role for working memory in decision making (Bechara and Martin 2004; Pecchinenda et al. 2006), and therefore, it could be theorized that the disadvantageous responses in female subjects of our study sample are due to a decreased working memory. At first sight, there are indications that this is true because in our previous study in the same cohort, female future ecstasy users showed lower scores on working memory tasks than male future ecstasy users (Schilt et al. 2007). However, after correction for DART-IQ and substance use, differences turned out to be non-significant (p > 0.17). Consequently, it seems unjustified to ascribe the differences in decision-making performance between male and female future ecstasy users to differences in working memory.
Possibly, initiation of ecstasy use in men is influenced by other factors than in women. In men, external factors like peer influence or availability of opportunities may play a greater role in the initiation of ecstasy use than in women (Van Etten et al. 1999), while in women, the start of using ecstasy might be regulated by more internal factors, like personality characteristics or decision-making strategies. In The Netherlands, the percentage of the population (age 15–64) that ever used ecstasy was higher in men than in women (3.7% versus 2.1% in 2001 and 6.6% versus 1.2% in 2005; Drugs Informatie en Monitoring Systeem 2006), suggesting that for men, ecstasy use is a less unusual thing to do than for women. Women might need to show more deviant behavior to take the first step to ecstasy use.
The finding that future ecstasy users did not prolong their reaction time after punishment may imply higher impulsivity and/or lower punishment sensitivity. Higher impulsivity was also put forward by Goudriaan et al. (2006) as a possible explanation for a lack of difference in reaction time after rewards or after punishments in alcohol-dependents (Goudriaan et al. 2006). However, in our study population, future ecstasy users did not report higher impulsivity on a self-report impulsiveness scale (de Win et al. 2006). This could be due to the lack of an association between self-reported impulsivity and decision-making scores (data not shown). Other studies also failed to find a significant relationship between self-report impulsivity scales and performance on the Iowa Gambling Task (Franken and Muris 2005; Goudriaan et al. 2007; Jollant et al. 2005, 2007). Three other studies, however, did find significant correlations between self-reported impulsivity and performance on the Iowa Gambling Task (Christodoulou et al. 2006; Franken et al. 2008; Zermatten et al. 2005), but in two of these studies, different self-report impulsivity scales were used other than the Barratt Impulsiveness Scale (BIS) used in our study. Possibly, the BIS does not capture the kind of impulsivity that is measured with the Iowa Gambling Task. As stated in “Introduction”, impulsivity is a complex construct that consists of different dimensions (Evenden 1999). In the study of Zermatten (2005) for example, it appeared that only “premeditation” (thinking at forehand about a future action), as part of impulsivity, was related to decision making (Zermatten et al. 2005). Dawe and Loxton (2004) mentioned in their review an association between decision making and “rash unplanned impulsivity” rather than “reward sensitivity/drive” (Dawe and Loxton 2004). The fact that we did not find indications for self-reported impulsivity as an explanation for the shorter reaction times after losses in future ecstasy users does not mean that there is no connection between certain aspects of impulsivity and IGT performance. Instruments other than the self-report questionnaires used in the current study are needed to investigate this more thoroughly.
The results of this study possibly reflect lower punishment sensitivity in future ecstasy users. Individuals that start to use ecstasy may be less sensitive to the possible negative consequences of their choice. Although some studies did not find an association between substance misuse and sensitivity to punishment (Jorm et al. 1998; Leland and Paulus 2005), other studies showed that poor conditioning to signals for punishment is associated with an increased risk of alcohol abuse. This may be a reflection of a weak behavioral inhibition system (Finn et al. 1994; Loxton and Dawe 2001; Loxton et al. 2008). Subjects with low punishment sensitivity may be more prone to try ecstasy because they do not consider the potential negative consequences of drug use.
Some limitations of this study should be mentioned. An important limitation of this study is the selection of the participants. Subjects were selected on the basis of their self-reported wish to start using ecstasy in the near future. Consequently, our study sample was not representative of the general population, which limits the generalizability of the results. This selection process could explain the small effect sizes and lack of associations between decision-making performance and self-report impulsivity questionnaires. Although the effect size for difference in IGT performance between female ecstasy-naives and female future ecstasy users was moderate (Cohen’s d = 0.50), the effect size for dRT between ecstasy-naives and future ecstasy users was rather small (Cohen’s d = 0.37). Another limitation is that we do not know if the persistent ecstasy-naive subjects would remain ecstasy-naive after the follow-up period of our study (11–26 months). Therefore, our results only provide information about prediction of ecstasy use in the near future, but not of ecstasy use ever. The current study provides only limited support for the use of neuropsychological decision-making tests in the prediction of initial ecstasy use. In contrast, neuropsychological measures of executive functioning and decision-making strategies appear to be stronger predictors for relapse in substance dependence or addictive behaviors (Bowden-Jones et al. 2005; Dallery and Raiff 2007; Goudriaan et al. 2008; Paulus et al. 2005). Moreover, neuropsychological tests other than the decision-making test used in our study might capture certain aspects of impulsivity better and subsequently could be superior predictors for future ecstasy use. Perhaps, other factors that we did not include in our study could better predict future ecstasy use. Some studies point at cannabis use as a risk factor for later ecstasy use (de Win et al. 2006; Martins et al. 2007; Pedersen and Skrondal 1999; Zimmermann et al. 2005). However, in the current study, cannabis and cocaine use did not significantly predict future ecstasy use. Possibly, the use of other drugs is especially predictive for frequent ecstasy use rather than for the first incidence of low-dose ecstasy use (mean ecstasy use at final evaluation was 6.3 pills, SD 12.1, median 2.0).
In summary, in this study, decision-making strategy was predictive for first incidental use of ecstasy in female participants within the 11–26 months following baseline assessment. Furthermore, decision-making reaction time differed between future ecstasy users and persistent ecstasy-naives. However, the clinical relevance is limited because effect sizes were small to moderate only. It is conceivable that decision-making strategy is more important in the continuation of ecstasy use than in the initiation of first low-dose ecstasy use. Therefore, it is important to follow this study cohort and to compare decision-making strategy (before first ecstasy use) in the subjects that become frequent ecstasy users with persistent ecstasy-naives.
References
Bechara A, Damasio H (2002) Decision-making and addiction (part I): impaired activation of somatic states in substance dependent individuals when pondering decisions with negative future consequences. Neuropsychologia 40:1675–1689
Bechara A, Martin EM (2004) Impaired decision making related to working memory deficits in individuals with substance addictions. Neuropsychology 18:152–162
Bechara A, Damasio AR, Damasio H, Anderson SW (1994) Insensitivity to future consequences following damage to human prefrontal cortex. Cognition 50:7–15
Bechara A, Damasio H, Damasio AR, Lee GP (1999) Different contributions of the human amygdala and ventromedial prefrontal cortex to decision-making. J Neurosci 19:5473–5481
Bechara A, Damasio H, Damasio AR (2000) Emotion, decision making and the orbitofrontal cortex. Cereb Cortex 10:295–307
Bechara A, Dolan S, Denburg N, Hindes A, Anderson SW, Nathan PE (2001) Decision-making deficits, linked to a dysfunctional ventromedial prefrontal cortex, revealed in alcohol and stimulant abusers. Neuropsychologia 39:376–389
Beck AT, Steer RA (1984) Internal consistencies of the original and revised beck depression inventory. J Clin Psychol 40:1365–1367
Beck AT, Ward CH, Mendelsohn M, Mock J, Erbaugh J (1961) An inventory for measuring depression. Arch Gen Psychiatry 4:561–571
Bolla KI, Eldreth DA, London ED, Kiehl KA, Mouratidis M, Contoreggi C, Matochik JA, Kurian V, Cadet JL, Kimes AS, Funderburk FR, Ernst M (2003) Orbitofrontal cortex dysfunction in abstinent cocaine abusers performing a decision-making task. Neuroimage 19:1085–1094
Bolla KI, Eldreth DA, Matochik JA, Cadet JL (2004) Sex-related differences in a gambling task and its neurological correlates. Cereb Cortex 14:1226–1232
Bouman TK, Luteijn F, Albersnagel FA, Van der Ploeg FAE (1985) Enige ervaringen met de Beck Depression Inventory (BDI). Gedrag 13:13–24
Bowden-Jones H, McPhillips M, Rogers R, Hutton S, Joyce E (2005) Risk-taking on tests sensitive to ventromedial prefrontal cortex dysfunction predicts early relapse in alcohol dependency: a pilot study. J Neuropsychiatry Clin Neurosci 17:417–420
Christodoulou T, Lewis M, Ploubidis GB, Frangou S (2006) The relationship of impulsivity to response inhibition and decision-making in remitted patients with bipolar disorder. Eur Psychiatry 21:270–273
Dallery J, Raiff BR (2007) Delay discounting predicts cigarette smoking in a laboratory model of abstinence reinforcement. Psychopharmacology (Berl) 190:485–496
Dawe S, Loxton NJ (2004) The role of impulsivity in the development of substance use and eating disorders. Neurosci Biobehav Rev 28:343–351
Deakin J, Aitken M, Robbins T, Sahakian BJ (2004) Risk taking during decision-making in normal volunteers changes with age. J Int Neuropsychol Soc 10:590–598
de Win MM, Jager G, Vervaeke HK, Schilt T, Reneman L, Booij J, Verhulst FC, den Heeten GJ, Ramsey NF, Korf DJ, van den Brink W (2005) The Netherlands XTC Toxicity (NeXT) Study: objectives and methods of a study investigating causality, course, and clinical relevance. Int J Methods Psychiatr Res 14:167–185
de Win MM, Schilt T, Reneman L, Vervaeke H, Jager G, Dijkink S, Booij J, van den Brink W (2006) Ecstasy use and self-reported depression, impulsivity, and sensation seeking: a prospective cohort study. J Psychopharmacol 20:226–235
de Win MM, Reneman L, Jager G, Vlieger EJ, Olabarriaga SD, Lavini C, Bisschops I, Majoie CB, Booij J, den Heeten GJ, van den Brink W (2007) A prospective cohort study on sustained effects of low-dose ecstasy use on the brain in new ecstasy users. Neuropsychopharmacology 32:458–470
Drugs Informatie en Monitoring Systeem (2006) Jaarbericht 2006. DIMS/Trimbosinstituut. Utrecht, The Netherlands. Report
El-Mallakh RS, Abraham HD (2007) MDMA (ecstasy). Ann Clin Psychiatry 19:45–52
Ernst M, Grant SJ, London ED, Contoreggi CS, Kimes AS, Spurgeon L (2003) Decision making in adolescents with behavior disorders and adults with substance abuse. Am J Psychiatry 160:33–40
Evenden JL (1999) Varieties of impulsivity. Psychopharmacology (Berl) 146:348–361
Finn PR, Kessler DN, Hussong AM (1994) risk for alcoholism and classical conditioning to signals for punishment: evidence for a weak behavioral inhibition system? J Abnorm Psychol 103:293–301
Fox HC, McLean A, Turner JJ, Parrott AC, Rogers R, Sahakian BJ (2002) Neuropsychological evidence of a relatively selective profile of temporal dysfunction in drug-free MDMA (“ecstasy”) polydrug users. Psychopharmacology (Berl) 162:203–214
Franken IHA, Muris P (2005) Individual differences in decision-making. Pers Individ Differ 39:991–998
Franken IH, Van Strien JW, Nijs I, Muris P (2008) Impulsivity is associated with behavioral decision-making deficits. Psychiatry Res 158:155–163
Giancola PR, Tarter RE (1999) executive functioning and risk for substance abuse. Psychol Sci 10:203–205
Goudriaan AE, Oosterlaan J, De Beurs E, van den Brink W (2005) Decision making in pathological gambling: a comparison between pathological gamblers, alcohol dependents, persons with Tourette syndrome, and normal controls. Cogn Brain Res 23:137–151
Goudriaan AE, Oosterlaan J, De Beurs E, van den Brink W (2006) Neurocognitive functions in pathological gambling: a comparison with alcohol dependence, Tourette syndrome and normal controls. Addiction 101:534–547
Goudriaan AE, Grekin ER, Sher KJ (2007) Decision making and binge drinking: a longitudinal study. Alcohol Clin Exp Res 31:928–938
Goudriaan AE, Oosterlaan J, De Beurs E, van den Brink W (2008) The role of self-reported impulsivity and reward sensitivity versus neurocognitive measures of disinhibition and decision-making in the prediction of relapse in pathological gamblers. Psychol Med 38:41–50
Gouzoulis-Mayfrank E, Daumann J (2006) Neurotoxicity of methylenedioxyamphetamines (MDMA; ecstasy) in humans: how strong is the evidence for persistent brain damage? Addiction 101:348–361
Grant S, Contoreggi C, London ED (2000) Drug abusers show impaired performance in a laboratory test of decision making. Neuropsychologia 38:1180–1187
Hosmer DW, Lemeshow S (2000) Applied logistic regression. Wiley, New York
Huizink AC, Ferdinand RF, van der EJ, Verhulst FC (2006) Symptoms of anxiety and depression in childhood and use of MDMA: prospective, population based study. BMJ 332:825–828
Jager G, de Win MM, van der Tweel I, Schilt T, Kahn RS, van den Brink W, van Ree JM, Ramsey NF (2008) Assessment of cognitive brain function in ecstasy users and contributions of other drugs of abuse: results from an fMRI study. Neuropsychopharmacology 33:247–258
Jollant F, Bellivier F, Leboyer M, Astruc B, Torres S, Verdier R, Castelnau D, Malafosse A, Courtet P (2005) Impaired decision making in suicide attempters. Am J Psychiatry 162:304–310
Jollant F, Guillaume S, Jaussent I, Bellivier F, Leboyer M, Castelnau D, Malafosse A, Courtet P (2007) Psychiatric diagnoses and personality traits associated with disadvantageous decision-making. Eur Psychiatry 22:455–461
Jorm AF, Christensen H, Henderson AS, Jacomb PA, Korten AE, Rodgers B (1998) Using the BIS/BAS scales to measure behavioural inhibition and behavioural activation: factor structure, validity and norms in a large community sample. Pers Individ Differ 26:49–58
Leland DS, Paulus MP (2005) Increased risk-taking decision-making but not altered response to punishment in stimulant-using young adults. Drug Alcohol Depend 78:83–90
Lieb R, Schuetz CG, Pfister H, von Sydow K, Wittchen H (2002) Mental disorders in ecstasy users: a prospective-longitudinal investigation. Drug Alcohol Depend 68:195–207
Loxton NJ, Dawe S (2001) Alcohol abuse and dysfunctional eating in adolescent girls: the influence of individual differences in sensitivity to reward and punishment. Int J Eat Disord 29:455–462
Loxton NJ, Wan VLN, Ho AMC, Cheung BKL, Tam N, Leung FYK, Stadlin A (2008) Impulsivity in Hong Kong-Chinese club-drug users. Drug Alcohol Depend 95:81–89
Martins SS, Mazzotti G, Chilcoat HD (2006) Recent-onset ecstasy use: association with deviant behaviors and psychiatric comorbidity. Exp Clin Psychopharmacol 14:275–286
Martins SS, Ghandour LA, Chilcoat HD (2007) Pathways between ecstasy initiation and other drug use. Addict Behav 32:1511–1518
Monterosso J, Ainslie G (1999) Beyond discounting: possible experimental models of impulse control. Psychopharmacology (Berl) 146:339–347
Monterosso J, Ehrman R, Napier KL, O’Brien CP, Childress AR (2001) Three decision-making tasks in cocaine-dependent patients: do they measure the same construct? Addiction 96:1825–1837
Morgan MJ, Impallomeni LC, Pirona A, Rogers RD (2006) Elevated impulsivity and impaired decision-making in abstinent Ecstasy (MDMA) users compared to polydrug and drug-naive controls. Neuropsychopharmacology 31:1562–1573
Must A, Szabo Z, Bodi N, Szasz A, Janka Z, Keri S (2006) Sensitivity to reward and punishment and the prefrontal cortex in major depression. J Affect Disord 90:209–215
Nelson HE, O’Connell A (1978) Dementia: the estimation of premorbid intelligence levels using the New Adult Reading Test. Cortex 14:234–244
Patton JH, Stanford MS, Barratt ES (1995) Factor structure of the Barratt impulsiveness scale. J Clin Psychol 51:768–774
Paulus MP, Tapert SF, Schuckit MA (2005) Neural activation patterns of methamphetamine-dependent subjects during decision making predict relapse. Arch Gen Psychiatry 62:761–768
Pecchinenda A, Dretsch M, Chapman P (2006) Working memory involvement in emotion-based processes underlying choosing advantageously. Exp Psychol 53:191–197
Pedersen W, Skrondal A (1999) Ecstasy and new patterns of drug use: a normal population study. Addiction 94:1695–1706
Quednow BB, Kuhn KU, Hoppe C, Westheide J, Maier W, Daum I, Wagner M (2007) Elevated impulsivity and impaired decision-making cognition in heavy users of MDMA (“ecstasy”). Psychopharmacology (Berl) 189:517–530
Ramaekers JG, Kuypers KP (2006) Acute effects of 3,4-methylenedioxymethamphetamine (MDMA) on behavioral measures of impulsivity: alone and in combination with alcohol. Neuropsychopharmacology 31:1048–1055
Reavis R, Overman WH (2001) Adult sex differences on a decision-making task previously shown to depend on the orbital prefrontal cortex. Behav Neurosci 115:196–206
Reneman L, de Win MM, van den BW, Booij J, den Heeten GJ (2006) Neuroimaging findings with MDMA/ecstasy: technical aspects, conceptual issues and future prospects. J Psychopharmacol 20:164–175
Ricaurte GA, Yuan J, McCann UD (2000) (+/−)3,4-Methylenedioxymethamphetamine (‘ecstasy’)-induced serotonin neurotoxicity: studies in animals. Neuropsychobiology 42:5–10
Rogers RD, Everitt BJ, Baldacchino A, Blackshaw AJ, Swainson R, Wynne K, Baker NB, Hunter J, Carthy T, Booker E, London M, Deakin JF, Sahakian BJ, Robbins TW (1999) Dissociable deficits in the decision-making cognition of chronic amphetamine abusers, opiate abusers, patients with focal damage to prefrontal cortex, and tryptophan-depleted normal volunteers: evidence for monoaminergic mechanisms. Neuropsychopharmacology 20:322–339
Schilt T, de Win MM, Koeter M, Jager G, Korf DJ, van den Brink W, Schmand B (2007) Cognition in novice ecstasy users with minimal exposure to other drugs: a prospective cohort study. Arch Gen Psychiatry 64:728–736
Schmand B, Bakker D, Saan R, Louman J (1991) [The Dutch Reading Test for adults: a measure of premorbid intelligence level]. Tijdschr Gerontol Geriatr 22:15–19
Tarter RE, Kirisci L, Habeych M, Reynolds M, Vanyukov M (2004) Neurobehavior disinhibition in childhood predisposes boys to substance use disorder by young adulthood: direct and mediated etiologic pathways. Drug Alcohol Depend 73:121–132
Taylor Tavares JV, Clark L, Cannon DM, Erickson K, Drevets WC, Sahakian BJ (2007) Distinct profiles of neurocognitive function in unmedicated unipolar depression and bipolar II depression. Biol Psychiatry 62:917–924
Van de Wijngaart G, Braam R, de Bruin D, Fris M, Maalsté N, Verbraeck H (1997) Ecstasy in het uitgaanscircuit [Ecstasy and the Dutch rave scene: a socio-epidemiologic study on the nature and extent of, and the risks involved in using ecstasy and other party drugs at dance events]. Addiction Research Institute, Utrecht. Report
Van Etten ML, Neumark YD, Anthony JC (1999) Male–female differences in the earliest stages of drug involvement. Addiction 94:1413–1419
Verdejo-Garcia A, Lawrence AJ, Clark L (2008) Impulsivity as a vulnerability marker for substance-use disorders: review of findings from high-risk research, problem gamblers and genetic association studies. Neurosci Biobehav Rev 32:777–810
Vervaeke HK, Korf DJ, Benschop A, van den BW (2007) How to find future ecstasy-users: Targeted and snowball sampling in an ethically sensitive context. Addict Behav 32:1705–1713
Vervaeke H, Benschop A, Korf DJ (2008) Fear, rationality and opportunity: reasons and motives for not trying ecstasy. Drugs: Education, Prevention & Policy 15:350–364
Vollenweider FX, Liechti ME, Paulus MP (2005) MDMA affects both error-rate dependent and independent aspects of decision-making in a two-choice prediction task. J Psychopharmacol 19:366–374
Whiteside SP, Lynam DR (2001) The five factor model and impulsivity: using a structural model of personality to understand impulsivity. Pers Individ Differ 30:669–689
Zermatten A, Van der Linden M, d’Acremont M, Jermann F, Bechara A (2005) Impulsivity and decision making. J Nerv Ment Dis 193:647–650
Zimmermann P, Wittchen HU, Waszak F, Nocon A, Hofler M, Lieb R (2005) Pathways into ecstasy use: the role of prior cannabis use and ecstasy availability. Drug Alcohol Depend 79:331–341
Acknowledgments
This study was supported by a grant of The Netherlands Organization for Health Research and Development, as part of their Addiction Program (ZonMw 310-00-036). A. Goudriaan is supported by a Veni research grant (#91676084) of The Netherlands Organisation for Scientific Research. Questionnaires on drug use were obtained by courtesy of the Addiction Research Institute of the University of Utrecht. We thank Hylke Vervaeke for subject recruitment and Ivo Bisschops and Sarah Dijkink for their assistance with the logistics and data collection.
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Open Access This is an open access article distributed under the terms of the Creative Commons Attribution Noncommercial License (https://creativecommons.org/licenses/by-nc/2.0), which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
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Schilt, T., Goudriaan, A.E., Koeter, M.W. et al. Decision making as a predictor of first ecstasy use: a prospective study. Psychopharmacology 203, 519–527 (2009). https://doi.org/10.1007/s00213-008-1398-y
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DOI: https://doi.org/10.1007/s00213-008-1398-y