Original article

Impulsivity profile and cocaine abuse in polysubstance abusers receiving opioid maintenance treatment

DOI: https://doi.org/10.4414/sanp.2022.w10067
Publication Date: 14.07.2022
Swiss Arch Neurol Psychiatr Psychother. 2022;173:w10067

Julie Giustiniania, Stéphane Rothena,b, Louise Penzenstadlera,c, Gerard Calzadaa,c, Gabriel Thorensa,c, Daniele Zullinoa,c

a Addictology Division, Mental Health and Psychiatry Department, Geneva University Hospitals, Geneva, Switzerland

b Research Centre for Statistics, University of Geneva, Switzerland

c Faculty of Medicine, Geneva University, Geneva, Switzerland

Summary

Opioid maintenance treatment (OMT) is the most effective treatment for opioid use disorder (OUD). However, persistence of cocaine abuse in the population receiving OMT can be a considerable clinical concern. The primary aim of our study was to determine whether individuals with OUD receiving OMT exhibit higher impulsivity when presenting concurrent cocaine use. Twenty-three patients with OUD receiving OMT for at least 3 months were included. Each participant was assigned to a group based on his/her level of cocaine use as assessed by the ASSIST, i.e. low risk and moderate–high risk cocaine use. The different components of impulsivity were assessed through the UPPS-P and three laboratory tasks, the stop signal reaction time (SSRT), the balloon analogue risk task (BART) and the Delay Discounting Task. The two groups were compared regarding their levels of impulsivity. Only the SSRT showed a significant difference between the two groups, with a higher time of reaction, i.e., a motor inhibition deficit, for the low-risk cocaine use group compared with the moderate–high-risk cocaine use group. Polysubstance use appears to be associated with a global high impulsivity. Thus, cocaine use is not considered a cause of higher risk-taking behaviours in our sample. Based on these results and previous literature it can be hypothesised that cocaine use could be an attempt to self treat.

Introduction

Opioid maintenance treatment (OMT) is the most effective treatment for opioid use disorder (OUD) [1], allowing the reduction or disappearance of withdrawal and craving symptoms [2]. On the one hand, OMT is effective in reducing illicit opioid use [3, 4] and improving general health [5]; on the other hand many patients receiving OMT are polysubstance users [6, 7]. Specifically, many heroin users also report using cocaine [8]. Concurrent use of cocaine and heroin is known to increase the risk of death from overdose, as this combination leads, among others, to an increase in the amount and frequency of opioid use [9]. Persistence of cocaine use during OMT is therefore of considerable clinical concern [1, 10, 11].

Addictions, regardless of the substances used, are conceptualised as a unitary phenomenon because of their many clinical and biological similarities. However, stimulants such as cocaine and opiates may be differently associated with impulsivity [12]. Although impulsivity is a common feature of all addictions [13], it seems that different levels of impulsivity lead to different types of risky behaviours and use. Notably, it is recognised that high levels of impulsivity are associated with the use of multiple substances [14, 15]. In heroin and cocaine users, high levels of impulsivity and risky behaviour have been extensively reported [6, 16]. The literature is, though, not unequivocal, as some studies found individuals with cocaine use more impulsive and with a higher propensity to take risks than heroin users [17], whereas others did not find such differences [7, 18]. These inconsistencies may be due to significant methodological differences in the way impulsivity is assessed, for example, by psychometric tests or by laboratory tasks [6, 17, 18]. Impulsivity has several components, for each of which an assessment tool has been developed [19].

Impulsivity reflects a tendency to act prematurely without foresight [20, 21]. Psychometric measures evaluate impulsivity as a personality trait, whereas laboratory tasks are considered to measure state impulsivity [21, 22]. The UPPS-P is a self-report questionnaire which assesses the impulsivity facets Positive Urgency (PU), Negative Urgency (NU), Lack of Premeditation (LPr), Lack of Perseverance (LPe) and Sensation Seeking (SS) [23, 24]. Laboratory tasks address such behavioural aspects as the inability to suppress inappropriate behaviour (motor impulsivity), risk-taking (risky behaviours), and the inability to defer a gratification (impulsive choice) [25]. Motor impulsivity, evaluated by the stop signal reaction time (SSRT), refers to the ability to inhibit a prepotent motor response [26]. The delay discounting task is designed to assess impulsive decision-making. Accepting a smaller reward in order to obtain the reward immediately is associated with highly impulsive subjects [27]. The balloon analogue risk task (BART) is an assessment of risk-taking behaviours. Through this task, as in real-world situations, risk-taking is rewarded up until a certain point, beyond which excessive risk-taking leads to greater negative consequences [28, 29]. Addictions have been found to correlate with all these impulsivity components, but cocaine users were reported to present more significant deficits in response inhibition compared with heroin users [6].

The OUD population is known to engage in polysubstance abuse [30]. Indeed, many people who use heroin also report using cocaine [8]. Concurrent use of cocaine and heroin, such as “speedball”, is known to increase the risk of death from overdose, as this combination leads to an increase in the amount and frequency of opioids used [9]. In addition, polysubstance abuse such as heroin and cocaine, is associated with poor clinical outcomes [1, 10]. Thus, additional cocaine use appears to be a risky behaviour in itself. In addition, if cocaine use is frequently associated with heroin use, its consumption persists after people have engaged in OMT. Indeed, persistence of cocaine use in the OUD population receiving OMT during treatment initiation and after is a long-known fact and still a clinical concern [11]. The pursuit of studies on what distinguishes people with a cocaine use disorder (CUD) and those without among the OUD population, is necessary.

Regarding these different findings, we  hypothesised that in patients with OUD receiving OMT, those with additional cocaine use would show a higher impulsivity level and risk taking. Answering this question in naturalistic conditions can lead to a better comprehension of their addictive trajectory and also help to define a therapeutic strategy. To determine whether cocaine users in the OUD population receiving OMT are more impulsive, we included a group of patients with OUD receiving the same OMT, slow release oral morphine (SROM). SROM is a recently developed OMT available in Switzerland. It has been suggested as an alternative treatment in OUD, especially for individuals who do not tolerate other OMT [31]. The choice of SROM over other OMTs was made in view of its lesser side effects [32, 33], and its wide use in our department. In addition, limiting our inclusions to one type of OMT helped to limit bias. We assessed impulsivity state (BART, Stop Signal Task, and Delay Discounting Task) and trait (UPPS-P), and compared them according to their cocaine status.

Materials and methods

Study sample

Twenty-three patients were recruited from the Division of Addiction Psychiatry (Service d’Addictologie) of the University Hospital of Geneva (Switzerland), where they receive care for an OUD, more precisely to illicit heroin. They were eligible if they fulfilled all the following inclusion criteria: informed consent as documented by signature; able to communicate in French; age over 18 years; on a stable dose of slow release oral morphine (SROM) not modified at least 14 days prior to inclusion. Non-inclusion/exclusion criteria included unstable psychiatric disorders and acute withdrawal syndrome. Participants received CHF 50 vouchers for their participation. The study was approved by the ethics committee of the canton of Geneva and was carried out in accordance to the protocol and with principles enunciated in the Declaration of Helsinki and the guidelines of Good Clinical Practice (GCP) issued by the ICH.

Psychometric measures

UPPS-P

Whiteside and Lynam [23] have identified distinct traits of impulsivity. The short UPPS-P impulsive behavior scale [34] is a 20-item scale (four items per dimension) that assesses five reliable impulsivity facets labelled as: Positive Urgency (tendency to act rashly in positive emotional contexts); Negative Urgency (tendency to act rashly in negative emotional contexts); (lack of) Perseverance (difficulty to remain focused on difficult or boring tasks); (lack of) Premeditation (difficulty to take into account the consequences of an act before engaging in that act); and Sensation Seeking (tendency to enjoy and pursue new/exciting activities). All items are scored on a Likert scale ranging from 1 (I agree strongly) to 4 (I disagree strongly). Higher scores designate higher impulsivity.

Alcohol, smoking and substance involvement screening test

The alcohol, smoking and substance involvement screening test (ASSIST) is a short screening questionnaire developed by the World Health Organization (WHO) to assess the use of different substances (tobacco products, alcohol, cannabis, cocaine, amphetamine-type stimulants, sedatives and sleeping pills, hallucinogens, inhalants, opiates, and “other drugs”) and the associated consequences [35, 36]. The ASSIST in its current French version (ASSIST V3.0) [28] is composed of eight questions that determine a risk score for each substance, which allows a conclusion on the most appropriate intervention for that level of use. The score for each substance is categorised as low risk (occasional or non-harmful use), moderate risk (more regular or harmful use), or high risk (frequent risky use or suggestive of dependence). The ASSIST is therefore a well-validated screening test for substance use disorder in an adult population [37].

Experimental tasks

Stop signal task

The stop signal paradigm is an impulsivity inhibitory control model. The stop task [26] is the prototypical task used to assess capacity of inhibitory mechanisms, measuring the ability to inhibit a pre-potent response (i.e., a dominant or automatic motor response).

The task consists in responding to a visual signal (go signal) as fast as possible (go task), but to refrain from this (stop task) when an auditory signal (stop signal) is heard. The frequency of this stop signal is set on one trial out of four (25%), but the delay between the go signal and this stop signal varies, and is successively adjusted to make it tend towards the median reaction time. The latency of the response to the stop signal (stop-signal reaction time) is calculated as a quantitative measure of inhibitory control. Longer stop-signal reaction times are associated with higher impulsivity [26].


Delay discounting task

The delay discounting task is designed to assess impulsive decision-making [27]. This task uses a computerised adjusting-amount procedure to measure how a delay impinging a granted reward decreases the attractiveness of this reward, hence the term “discount”. In a series of choice trials, participants have to decide repeatedly between two options: a smaller amount of money (hypothetically) available immediately or a larger amount of money available after a delay (e.g., $100 immediately or $1000 in one year). The two amounts are presented on a computer screen and the participants are asked to press one of two buttons to indicate their first choice (less money immediately versus more money, time delayed). On successive trials, manipulation of parameters (e.g., the long delay) allows estimation of the rate of discounting, which allows the delay at which the large and the smaller amount of reward would be valued equally, namely the "equivalence point", to be found. The equivalence point is calculated by averaging the ascending and descending values for each time period. The equivalence point is the value of the last immediate amount when a participant ceases to prefer the immediate amount and choose the deferred amount, i.e., the point at which the immediate and deferred amounts have the same subjective value for the participant [38].

Balloon analogue risk task

The balloon analogue risk task (BART) is a computerised laboratory-based assessment of risk-taking tendencies. Through the task, as in real-world situations, risk-taking is rewarded up until a point at which excessive risk-taking leads to greater negative consequences, which outweigh the positives [28]. In this task, a small, simulated balloon with a balloon pump is displayed on the computer screen. Participants may inflate the balloon by clicking on the pump in exchange for a monetary reward for each pump. With each click, the balloon inflates, and 10 points are added to the participant’s temporary bank. At any point, the participant may decide to stop inflating the balloon and collect the sum collected on this balloon. The sum is banked in the permanent bank. However, each balloon is set to explode at random with a "pop" sound effect resulting in the loss of all money accumulated for that balloon. Each balloon has a different explosion point and is programmed to pop anywhere between 1 and 64 pumps (maximum number of clicks per balloon), with an average breakpoint at 32 pumps.

The participants are only informed that the balloon can explode anywhere from the first pump all the way to the point where it fills the whole screen. After each balloon explosion or money collection, another balloon appears until a total of thirty balloons have spawned. The main dependent measure on the BART is the average number of pumps delivered in balloons that did not explode, which is referred to as the mean adjusted pumps (i.e., the average number of pumps on each balloon prior to earning money) [28]. Higher scores imply a higher risk-taking predilection.


Procedure

This study was observational. Participants had to complete questionnaires about their sociodemographic status and to report other substances used with the ASSIST rating questionnaire. All participants had OUD, and experiments were conducted before administration of their regular dose of SROM. Each participant was assigned to one of two groups depending on his/her risk of cocaine use, as evaluated by the ASSIST rating questionnaire, i.e. to the moderate–high risk cocaine use group (MHR cocaine use ) when they had an ASSIST-cocaine score >3 or the low risk cocaine use group (LR cocaine use) when they had an ASSIST-cocaine score ≤3. The experimental procedure consisted of the administration of three experimental tasks (stop signal, delay discounting and BART).

Data analysis

Statistical analyses were conducted using R (R Core Team (2020). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/). Variables were described as frequencies or mean values and standard deviations. A Fisher test was used to test potential differences in categorical variables (e.g., gender, employment, partnership, psychiatric disease and medication) between the two groups. Scores of UPPS, delay discounting, stop signal and BART, and number of substances used obtained for both groups (MHR and LR cocaine use) were compared using the t-test for independent samples with the false discovery rate (FDR) correction. All statistical tests were considered significant if p <0.05.

Results

Twenty-three patients were recruited. Their mean age was 43.8 years (SD 8.7). Twenty were males (87%) and 3 females (13%). They met a mean of 9.9 DSM‐5 diagnostic criteria for opioid dependence out of maximum 13 (SD 3.9). Twelve of the 23 participant were assigned to the LR cocaine use group and 11 to the MHR cocaine use group. Table 1 shows participant’s sociodemographic data.

Table 1:

Descriptive variables including sociodemographics, diagnostic characteristics and use of other substances, comparison between low-risk (LR) and medium–high-risk (MHR) cocaine use groups.

 LR cocaine use (n = 12)MHR cocaine use (n = 11)p-value
Age (years), mean ± SD46.1 ± 8.7641.3 ± 8.280.19 (t-test)
Gender male , n (%)10 (83.3%)10 (90.9%)1.00 (Fisher)
Partnership, n (%)6 (50%)6 (54.4%)1.00 (Fisher)
Employment, n (%)1 (8.3%)3 (27.3%)0.32 (Fisher)
Stable housing during the last 30 days, n (%)12 (100%)11 (100%)1.00 (Fisher)
Children, n (%)5 (41.7%)6 (54.5%)0.33 (t-test)
Positive DSM-5 criteria, mean ± SD9.4 ± 4.610.4 ± 3.20.57 (t-test)
Doses of SROM (mg/day), mean ± SD553 ± 229501 ± 3530.67 (t-test)
Duration of SROM treatment (days), mean ± SD996 ± 391790 ± 5320.30 (t-test)
Psychiatric diseases, n (%)6 (50%)7 (63.6%)0.68 (Fisher)
– Major depressive disorder, n (%)3 (25%)2 (18.2%)1.00 (Fisher)
– Anxiety disorder, n (%)1 (8.3%)01.00 (Fisher)
– Bipolar disorder, n (%)1 (8.3%)1 (9.1%)1.00 (Fisher)
– ADHD, n (%)01 (9.1%)0.48 (Fisher)
– Other, n (%)2 (16.7%)1 (9.1%)1 (Fisher)
Psychiatric medication, n (%)6 (50%)5 (45.5%)1 (Fisher)
– Antidepressant, n (%)4 (33.3%)1 (9.1%)0.32 (Fisher)
– Antipsychotic, n (%)2 (16.7%)2 (18.2%)1.00 (Fisher)
– Benzodiazepine, n (%)5 (41.7%)4 (36.4%)1.00 (Fisher)
– Antihistamine, n (%)0.001 (9.1%)0.48 (Fisher)

ADHD: attention deficit hyperactivity disorder; SD: standard deviation; SROM: slow release oral morphine

Statistical analyses applied to our two groups did not identify any statistical difference either in socio-demographic data or in clinical characteristics (DSM-5 criteria, doses and duration of SROM, psychiatric disease, psychiatric medication) as shown in table 1.

Substance consumption habits and values are presented in the table 2. A t-test with FDR correction showed that the MHR cocaine group used more different substances (t = –2.71, p = 0.012) and also had more so-called risky consumptions as evaluated by the ASSIST score (t = –2.86, p <0.01). This significant proportion of substance abuse in the MHR cocaine group was also observed in the ASSIST total score (t = –2.0995, p = 0.045). However, when cocaine use was left out of the analysis, this effect was lost, showing that apart from cocaine, this group does not use more substances than the LR group. Fisher’s test showed a significantly higher proportion of hallucinogen use (p = 0.04) and a tendency to use psychostimulants (p = 0.09) for the MHR cocaine group. A t-test with a Bonferroni correction on the ASSIST score of each substance showed a significantly higher proportion of hallucinogen use (t = –2.1926, p = 0.032) and a higher tendency to use psychostimulants, without being significant (t = –1.9365, p = 0.056).

Table 2:

Substances used and abused in the low-risk (LR) cocaine use and medium–high-risk (MHR) cocaine use groups, and comparison of ASSIST scores between the two groups.

 UsesAbusesASSIST score 
 LR cocaine MHR cocaineLR cocaine MHR cocaineLR cocaineMHR cocainet-test
Total substances, mean ±SD3.25 ± 1.064.64 ± 1.361.92 ± 0.793 ± 136.2 ± 14.852.5 ± 21.60.045
Cocaine33.3%100%0%100%0.92 ± 1.3813.50 ± 8.54<0.001
Tobacco100.0%100%91.7%100%17.60 ±7.2817.70 ± 4.410.96
Alcohol75.0%81.8%16.7%27.3%5.92 ± 5.359.36 ± 10.800.34
Cannabis75.0%72.7%58.3%54.5%8.33 ± 8.077.64 ± 7.570.83
Psychostimulant0.0%27.3%0%0%0.000.82 ± 1.400.056
Hallucinogen0.0%36.4%0%9.1%0.001.36 ± 2.060.032
Tranquiliser41.7%45.5%25%9.1%3.42 ± 6.602.18 ± 3.840.59

ASSIST: alcohol, smoking and substance involvement screening test; SD: standard deviation

Table 3 shows mean and standard deviation for all task performances (delay discounting, BART and SSRT) and for the UPPS-P subscale scores, comparing the groups. The LR cocaine group showed a significantly prolonged SSRT (t = 2.29, p = 0.033) compared with the MHR cocaine group, but did not differ in other outcomes. For the UPPS scores, we found no statistical differences between both groups.

Table 3:

Mean scores and standard deviation for both groups on all task performances and UPPS-P and independent sample t-test with false discovery rate (FDR) correction.

MeasurementsLR cocaine useMHR cocaine usep-value
 Mean (SD)Mean (SD) 
BART115.9 ± 6.616.7 (6.9)0.80
Stop signal2342.0 (41.6304.0 (38.20.033
Delay siscounting373.3 (16.862.7 (16.10.14
UPPS-P   
Urgency (Ur20.0 (2.821.5 (6.40.48
– Positive Urgency (PU)10.1 (1.610.8 (2.80.44
– Negative Urgency (NU)9.9 (1.610.6 (2.80.60
Lack of consciousness (LC)25.5 (3.823.2 (5.00.22
– Lack of premeditation (LPr)12.0 (2.210.9 (2.80.31
– Lack of perseverance (LPe)13.5 (212.3 (2.50.21
Sensation seeking (SS)10.0 (3.48.4 (3.80.29

AUC: area under the curve; BART: balloon analogue risk task; LR: low risk; MHR: medium–high risk

1 Mean adjusted pumps; 2 mean reaction time in ms; 3 AUC

Discussion and conclusion

This study aimed to explore several dimensions of impulsivity in patients receiving OMT, distinguishing between those with and without concomitant cocaine abuse. We expected the former to show higher levels of impulsivity. Drug use, and in particular cocaine use, had previously been identified as a factor that can induce, both through its acute and long-term effects, an increase in impulsivity and, consequently, an increase in risky behaviours such as unprotected and unsafe sex [39, 40]. Surprisingly, in the present study, whereas both groups showed a similar impulsivity profile, one impulsivity component, motor impulsivity, was significantly higher in the group without cocaine use. Although this result may appear counterintuitive at first sight, we found much evidences in literature that could explained it.

It is commonly accepted that all addictions, substance used disorders (SUDs) and behavioural addictions, are associated with motor inhibitory deficits. Often, these observations are made by comparing populations without distinguishing causal factors, or chronic/acute effects of substances [41]. Studies that focused on the acute effect of substance on motor impulsivity showed different impacts depending on the substance. For example, alcohol [42] or cannabis [41] impair inhibitory control, whereas psychostimulants improve it [42]. This improvement of the inhibitory control induced by psychostimulants is observed on subjects whose initial SSRT were slow, and/ or subjects with attention deficit hyperactivity disorder (ADHD) [40, 43]. Also, in a study on patients with cocaine use disorder (CUD) where the SSRT was administered during a period of abstinence from cocaine, an alteration in performance was found [44]. These impaired performances in motor inhibition have been commonly observed in users of stimulants such as amphetamine [12]. On the other hand, injection of methylphenidate compared to saline improves the performance of SSRT in CUD compared with saline, showing a better inhibitory control induced by the psychostimulant [45]. These studies provide information on the acute effect of drugs and not on the chronic effect. In the light of these data, the significantly lower motor impulsivity in the MHR cocaine group and their tendency to have a greater appetite for psychostimulants led us to hypothesise that the participants in this group were attempting to self-medicate their deficit. Nevertheless, this hypothesis cannot be verified because of our methodological limitations. Indeed, we ignored participants’ last cocaine use, although due to their difficulty in controlling their cocaine use, it can be assumed that their consumption was closer in time than for the LR cocaine use group. In order to conclude on the self-therapeutic dimension of cocaine use and its acute effect on neurocognitive performance, it would be necessary at least to know if participants were under the influence of cocaine during the tasks, and at best to know the performance without cocaine and just after cocaine use, a manoeuvre which may be difficult to realise for ethical reasons. The higher tendency to consume psychostimulants in the MHR cocaine use group could be another argument in favour of the self-medication hypothesis. But this aspect must be balanced by the observation of a significantly higher tendency of the MHR cocaine group to use hallucinogens. In line with this hypothesis, there are many arguments in the literature around the self-medication hypothesis in CUD, with the notion that ADHD is a risk factor for cocaine use and CUD [46]. Moreover, if the acute administration of psychostimulants is associated with behavioural inhibition, it is important to highlight that chronic exposure may have long-term sequelae that result in a defect of motor inhibition [47]. Furthermore, this hypothesis is put forward without  a hypothesis on the origin of this deficit, i.e., to answer the question of whether the deficit is prior to cocaine intake, as is the case in ADHD, or consecutive to chronic cocaine intake. Despite this, it is well-known that patients with ADHD and comorbid CUD have higher motor impulsivity than those with ADHD only [48], which implies that the two causes could be intertwined. Nevertheless, this only partially explains why the LR cocaine group showed higher impulsivity. Another reason that could explain why the LR cocaine group showed higher impulsivity is the influence of several substances they use, which we have seen could negatively affect impulsivity, such as alcohol or cannabis [41, 42]. However, the LR cocaine group did not consume more alcohol, cannabis or others substances than the MHR cocaine group. Another explaination could be an undiagnosed comorbid ADHD. Thus, presence of ADHD in a proportion of our sample could explain our results, since ADHD has been associated with altered motor inhibition [49]. It is important to remember that the check of psychiatric disease identified only one participant with a diagnosis of ADHD in the MHR cocaine group. But this information does not mean that other participants could not have ADHD, it only means that one participant had already been diagnosed with ADHD. Indeed, if ADHD is particularly associated in the literature with CUD, this disease is also too associated to other substance use disorders [50, 51]. Specifically, it has been reported that in the OUD population the proportion with ADHD could be estimated to be between 11% and 33%, but this disease remains underestimated with currently a low proportion of patients having received medication for ADHD [52].

Both heroin and cocaine users are known to show poorer performance in decision-making and higher risk taking than controls [6, 53]. In our study, risk taking as assessed by the BART was similar in both groups, with and without cocaine use. This result is in agreement with a previous study that found no difference in risk-taking propensity between subjects receiving OMT with cocaine use and abstainers [7]. Yet it has previously been suggested that different risk profiles may mediate the orientation of substance choice, with higher risk taking in the BART for cocaine rather than for heroin users [17, 54]. Thus, heroin-dependent individuals have been characterised in a study published by Ahn et al. [12] to be lesser risk taking individuals than stimulant users. However, in contrast to our study, the subjects included in the Ahn et al. study were abstinent, and described as having only a problematic use whereas our participants were mainly polydrug users [12, 17, 54]. Risky decisions and behaviours could be explained by the inability to differentiate rewards. Delayed discounting was used to assess a behavioural economic index of impulsivity, that is, the extent to which a reward is devalued by its delayed receipt. The use of stimulants such as cocaine is associated in the literature with delay aversion, leading authors to identify it as a stimulant use endophenotype [12, 55, 56]. Primary cocaine users were previously found to have a higher preference for small, immediate rewards compared with primary heroin users [17]. In the present study, we did not find differences in delay discounting between our both groups. Cocaine use did not seem to affect delay discounting here. Most studies that found cocaine users to exhibit greater impulsivity than heroin users examined single-use situations. In addition to being associated with substance choice, delay discounting may also be associated with polysubstance use. Thus, individuals using two or more substances use exhibited higher impulsive decision-making than individuals with single substance use, but there was no further cumulative effect with the number of substances used beyond two drugs [57]. In addition, recent meta-analyses have shown that the delay discounting appears to be affected by SUDs and severity of their addiction its, but is not affected by substance type [58, 59]. The presence of comorbid psychiatric illness could also affect the discounting of delays [58]. However, our two groups are equivalent for the severity of addiction assessed by the number of DSM-5 criteria, or for psychiatric diseases. One could thus tentatively conclude, based on the results of our present study, that the impulsivity components measured by the BART and the delay discounting task are more related to polysubstance use than the substance choice. In the present sample of polysubstance users receiving OMT a general high level of impulsivity may have masked possible differences between cocaine users and non-users.

The different facets of impulsivity, as assessed by the UPPS, have been found to be vulnerability factors for showing risky behaviour and developing substance use disorders [60–62]. If stimulant use were correlated with predominantly sensation-seeking behaviour, and heroin use were more associated with a higher propensity to feel a negative urgency, in our case we found no difference in UPPS between the two groups. But these results are difficult to compare with ours since the subjects were mono-consumers and abstinent without OMT [12]. However, other studies that found a higher impulsivity in subjects receiving OMT than in controls, found no difference regarding their CUD status [18]. Furthermore, it is important to highlight that our LR cocaine use group is not cocaine abstinent and at least 33% of them use cocaine recreationally, . It is important to take this aspect into account because a previous study showed that all cocaine users (recreational and addicted) had the same level of impulsive trait. Moreover, it would seem that impulsivity traits are more associated woth the severity of depressive symptoms or ADHD [63], diseases which do not differ between the two groups or which are not sufficiently controlled.

Several limitations are to be considered when interpreting the results of the present study, mainly the limited sample size and the lack of information about the last use of cocaine. The polysubstance use status of our sample may also have blurred the results. Most previous studies focused on one substance, considering polysubstance use as an exclusion criterion. Selecting a single substance use disorder can limit some bias, but it does not reflect the reality of most heroin users, who are engaged in long-lasting poly-drug use [64]. Duration of the OMT cure/treatment could represent another limitation. Individuals in our sample had been in treatment for more than 3 months (mean 996 days for LR and 790 for MHR). Furthermore, it is known that impulsivity is related to the duration of treatment. On the one hand, the duration of treatment can have a downward influence on the level of impulsivity [65, 66]. On the other hand, higher impulsivity is associated with problems in the effectiveness of psychotherapy, including poorer outcomes and lower retention in treatment [67]. It is possible that our sample, engaged in treatment for more than 3 months, was less impulsive than those not in treatment. However, controlling for dosage and duration of treatment provides a good indicator of stability in treatment and allows comparison between the two groups. Another limitation is the lower proportion of females compared with males included in our sample. However, this underrepresentation of women appears to be consistent with epidemiological data that show a lower proportion of women in the OUD population [68, 69]. A final limitation is represented by the comorbid psychiatric diseases and medication used by participants. If we did not find any differences between our groups, it is important to specify that this information was only declarative. Thus, participants may have omitted data or simply did not know.

In conclusion, if a higher global impulsivity profile in SUD compared to non-users has been established consistently before, the present study led to the hypothesis that cocaine use could be considered as a self-medication attempt. Future studies on impulsivity should not ignore the existence of comorbid ADHD, and should also monitor precisely when cocaine was last used.

Acknowledgement

The authors thank all volunteers for participating in the study.



Financial disclosure

This study was supported by a grant from Mundipharma Medical Company and CARIGEST SA: www.carigest.ch (24, rue de l'Athénée, CH-1206 Genève, +41 (0)22 839 72 90 Fax: +41 (0)22 839 72 99, carigest[at]carigest.ch

Conflict of interestt

Author contributions

GT has received reimbursement for attending congresses from the following company Eli Lilly:
Daniele Zullino (DZ) has received research support from Eli Lilly, Organon, Wyeth, Sanofi-Synthelabo, Aventis and Janssen-Cilag; He is/has been a member of advisory boards for Eli Lilly, Wyeth, Astra Zeneca, Pfizer and Lundbeck; He has received speakers fees from Astra Zeneca, Eli Lilly, Janssen-Cilag, GlaxoSmithKline, Novartis, Pfizer, Organon, Wyeth, Lundbeck. He has received reimbursement for attending congresses from the following companies: Eli Lilly, Wyeth, Astra Zeneca, GlaxoSmithKline, Organon, Janssen-Cilag, GlaxoSmithKline, Lundbeck and Mundipharma. The other authors declare no potential conflict of interest.

The following authors conceived and designed the experiments: DZ, GT, SR, GC. Performed the experiments: GC. Analyzed the data: SR, JG. Contributed reagents/materials/analysis tools: ST, JG. Contributed to the writing of the manuscript: JG, GT, SR, LP, GC, DZ. All authors contributed to and have approved the final manuscript.

Correspondence

Julie Giustiniani, MD, PhD

University Hospital of Geneva CAAP Arve

Route des Acacias 3

CH-1227 Genève

julieleoniechristine.giustiniani[at]hcuge.ch / julie.giustiniani[at]univ-fcomte.fr

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