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Official websites use. Share sensitive information only on official, secure websites. This article is distributed under the terms of the Creative Commons Attribution Noncommercial License which permits any noncommercial use, distribution, and reproduction in any medium, provided the original author s and source are credited. An increasing number of fatal road-accidents have been reported in which ecstasy was found in the blood of drivers. Although, ecstasy is frequently found to have been used in combination with alcohol, studies on the acute effects of ecstasy co-administered with alcohol on driving performance are relatively rare. The present study was designed to establish the extent of driver impairment as a consequence of ecstasy or combined ecstasy and alcohol use as compared to driving under the influence of 0. Furthermore, subjective performance was also assessed. Alcohol and ecstasy mainly influenced automated driving performance such as lateral and speed control. However, small to no effects of the substances were found on more complex driving behaviour. Overall, variance within the different driving measures was high especially when participants were treated with 3. Furthermore, equivalence testing showed that combined use may lead to impaired driving for some, but not all, drivers. Participants rated their own performance to be slightly worse than normal in both studies. Since driving was actually seriously deteriorated, this was a falsely positive assessment of their condition. For example, an intoxicated individual might decide to drive because the feelings of alertness caused by MDMA cloud the impairing effects of other drugs such as alcohol, thereby creating a potentially serious risk for traffic safety. Driving under the influence of drugs is an important public health and road traffic safety related problem Christophersen and Morland ; Drummer et al. Several fatal and non-fatal injurious road accidents have been reported in which ecstasy was found in the blood of drivers Henry ; Verschraagen et al. In fact, the EMCDDA estimates that the life time prevalence ever used of ecstasy use for adults 16—64 years in Europe ranges between 0. Ecstasy refers to a synthetic substance that is chemically related to amphetamines but differs to some extent in its effects. Whereas amphetamines are mainly known for their energising effects, ecstasy is commonly appreciated for its entactogenic properties. Concretely this means that besides increased feelings of energy after the ingestion of ecstasy, there is also a feeling of euphoria and an intensification of impressions in contact with other people, music and light Baylen and Rosenberg The best-known member of the ecstasy group of drugs is 3. The drug is commonly used in social scenes such as dance events and is frequently combined with other drugs such as cannabis and amphetamines and most frequently alcohol Brookhuis et al. Only, a small number of experimental studies have assessed the acute effects of MDMA on skills related to driving. These studies generally showed that MDMA acted as a psychomotor stimulant that increases arousal and psychomotor function. However, MDMA has also been shown to have a negative effect on skills that are important for driving, for example the impairment of spatial memory performance Kuypers and Ramaekers ; Kuypers et al. Reports on the acute effects of MDMA co-administered with alcohol on driving performance are also relatively rare Brookhuis et al. Kuypers et al. Furthermore, there was no effect of co-administration on SDSP. The responses of drivers to speed changes of a lead vehicle as measured by the car following test Brookhuis et al. However, because of the obvious reason that high-risk situations in an experiment on the road cannot be ethically acceptable, other more complex interactions with traffic participants and risk taking in traffic could not be investigated in this study. Brookhuis et al. In this latter study, recreational ecstasy users who were going to a dance party drove in the simulator before going to the party, 1 hour after the use of their own, self-bought and self-administered ecstasy average MDMA, 59 mg. The participants were also tested in a sober condition on a different day at a comparable time. As found in the on-road study, performance on the car following test was unaffected in both drug conditions. However, measures of risk taking and situation awareness in complex traffic situations were affected by multidrug use increased gap time and an increased number of crashes. Because of the quasi-experimental design, i. Therefore, the aim of the present study was to investigate the risks involved in driving under the influence of MDMA mg alone and when co-administered with alcohol 0. What is more to determine the implications of the results for traffic safety? In this study study 1 the influence of three levels of alcohol 0. According to Dumont et al. This is an important notion for traffic safety and therefore subjective effects are also assessed. Nineteen participants started the study; however, two dropped out during the experiment due to physical problems not related to the experiment. Therefore, data of 17 participants nine males, eight females with an average age of The participants were all experienced drivers who had held their driving licence for at least 3 years mean SD , 4. All participants were in good health and reported no prior problems with drug or alcohol abuse. Participation was voluntary and participants received a monetary bonus. The study was conducted according to a double-blind, placebo-controlled, four-way cross-over design with treatment orders counterbalanced. Participants were presented with alcoholic drinks leading up to a BAC of 0. The participants were instructed to abstain from alcohol in the 24 h prior to the experiment and to refrain from caffeinated beverages on the morning of the experiment. They were then tested during five separate testing days. Each test day started between 1 p. The first testing day started with a screening of the participants by questioning them about their lifestyle in relation to alcohol and drugs using the Drug Abuse Screening Test Skinner After this screening the participants were trained in the simulator for 30 min. In this training the participants practised all of the driving scenarios in a full dress rehearsal and were screened for simulator sickness. The amount of administered alcohol was dependent on the weight, height and gender of the participant and was calculated using the Widmark formula Widmark The driving test was then conducted 20 min post-alcohol intake and took approximately 50 min. In order to keep the participant at a constant alcohol level, the test was paused every 20 min to do a breath analysis and administer extra alcohol when necessary. The tests differed in the order of occurrence in different sessions to prevent the participants from anticipating the critical moments during the scenarios. After the driving task, the participants were asked to fill in questionnaires and had to wait in waiting room until they were able to return home safely. The participants were only allowed to leave when their BAC was below 0. The study was approved by the ethical committee of the Department of Psychology at the University of Groningen. Other vehicles in the simulated world interact with each other and the simulator car autonomously, and behave according to hierarchically structured decision rules that are based on human driving behaviour Van Wolffelaar and Van Winsum A virtual world, including relevant scenarios for testing, the effects of alcohol and drugs was developed for these studies; see Veldstra et al. The virtual environment consisted of several road types: urban 6. Average traffic densities were used on all of these road types. Speed was assessed on all road types. Participants under the influence of alcohol might lower their speed to compensate for sedating effects. On the other hand, stimulating drugs such as MDMA might make the participant want to speed up because hazard perception is decreased see also Brookhuis et al. Another compensating mechanism in speed management is deliberately varying speed. In the case of severe sedation, a participant might temporarily increase speed to increase feelings of arousal, indicated by an increase in the standard deviation of speed Brookhuis Therefore, besides average speed, the SDSP was assessed as well. Response to other traffic participants was assessed using a car following test on a rural road Brookhuis et al. In this scenario the participant was instructed to follow a lead car at a short but safe distance. The coherence is the extent to which the patterns of speed changes of the lead- and following car correspond. So, if the participant is not following speed changes of the lead car properly, the coherence would be low. However, if the participant is following as instructed coherence would be high. After coherence is established, the style of following can also be analysed. This is done by assessing the gain and the delay. The gain is a measurement of the type of speed reaction the participants had to the speed changes of the lead car and is returned as an amplification factor between the speed signals of the lead- and follow car. When there is an overreaction, the gain is larger than one, while at an underreaction, the gain is smaller than one. The delay technically, phase shift between the two speed signals is the response time of the participant to the speed changes of the lead car see Brookhuis et al. The gap acceptance task was used to asses risk taking in traffic Adams The time between each of the cars in this stream increased every 1 s, ranging from 1 to 12 s. In this task the driver had to weigh the waiting time versus the risk of causing an accident and come to a decision to either choose a small risky gap, with a short waiting time or a larger, safer gap with a longer waiting time. The parameters included to assess the drivers risk taking were: the size of the chosen gap in seconds and the distance to the car approaching the driver while traversing the crossing. Accordingly, lower gap time in seconds and a smaller distance to the approaching car entails riskier behaviour. Analyses of driver records of patients that admitted substance abuse showed that drug users had significantly more traffic violations than a non-drug control group MacDonald et al. Therefore, the violation of traffic regulations was assessed by a traffic light scenario developed by De Waard et al. If participants kept the same speed they would drive through red, if they sped up they would most likely drive through amber and if they wanted to stop they had to brake firmly. The choice of the participant was determined by assessing the colour of the traffic light at the moment of crossing. Alcohol intoxication and sedation by medicinal drugs has been associated with significant deterioration in attention and reaction time Kelly et al. The dependent measure was the minimal time to collision. Even though crashes tend to occur more frequently in a driving simulator than in real traffic, it is still an important indicator of driving safely. Having a crash is the ultimate outcome of an unsafe act Brookhuis et al. Therefore, the total number of crashes during the entire ride was assessed. The Rating Scale Mental Effort RSME; Zijlstra was used to assess whether there was a difference in the mental effort participants had to invest during the driving session for the different alcohol conditions. Using the Driving Quality Scale developed by Brookhuis et al. Normally distributed data were subjected to a general linear model univariate repeated measures analysis with alcohol level four levels as main within-subjects factor. Missing values were corrected by replacing them with the mean of the participant over all conditions i. This technique was chosen to preserve the data. Replacement of missing values with individual means was chosen over replacement with overall mean values to prevent the downward attenuation of variance. The average alcohol levels in the three alcohol administration conditions as measured by breath analyses were: 0. A main within-subjects effect of alcohol level on speed was revealed in the urban driving setting F 2. The average speed was not above the posted speed but participants tended to drive faster when their alcohol level was above 0. There was no effect of alcohol level on speed when driving on the rural road and motorway. Also, there was no effect of alcohol on SDSP for any of the road types. As compared to the placebo, SDLP was decreased for 0. When comparing the different alcohol levels to each other, contrast analyses revealed that the difference between the SDLP with alcohol levels 0. However, the SDLP difference between a 0. There was no within-subjects effect of alcohol level on running red lights, reaction to the car pulling out of a car park or the number of crashes see Table 1. Overall the coherence was high average, 0. There was no significant main effect of alcohol level on gap times. When looking at the participants distance to the approaching car, at the moment of crossing the junction, it seems that participants generally accepted a smaller distance when alcohol level was higher; however, this effect was non-significant F 2. There was an overall effect for time on task on the KSS pre vs. There was, however, no alcohol effect. Although the time on task effect appeared to increased with alcohol level, the interaction effect of alcohol and time was not significant F 2. There was an overall effect of alcohol on ratings of mental effort F 2. Participants rated their invested effort as higher in the alcohol conditions as compared to the placebo condition. Contrast tests revealed that this difference was significant for the 0. There was no effect of alcohol on the subjective assessment of driving performance. Participants rated their performance to be slightly worse than normal in all conditions. The highest rate of correct guesses was in the 0. However, tests revealed no significant difference for any of the alcohol conditions. The results of the alcohol study indicate that alcohol mainly influenced automated driving performance such as speed control and weaving SDLP. Speed on urban roads increased when BAC was above 0. However, this increase was small and did not exceed the posted speed. SDLP increased as a function of BAC, indicating that participants were weaving increasingly more as they were under the influence of higher alcohol levels, comparable to the well-known Borkenstein curve Borkenstein et al. Car following was performed adequately as reflected in a high coherence values; however, we found no effects of alcohol on any of the car following measures. Previous research on the influence of alcohol on car following measures has been ambiguous. The aim of study 1 was to serve as a reference for driving under the influence of MDMA and combined MDMA and alcohol in automated but also in more complex driving tasks. However, the majority of the scenarios in which more complex driving performance was assessed showed no significant differences from the placebo and could therefore not be used as references for the second study. For only one scenario, an effect of alcohol on performance was found, namely the gap acceptance scenario. Since drug-affected drivers have demonstrated reduced perceptions of risk Brookhuis et al. However, participants selected approximately the same gap irrespective of their BAC. Only the average distance of the participants to the approaching car at the moment of crossing was affected by alcohol, in that the average distance was smaller when BAC was higher. Since the perceptual motor capacities necessary for crossing the junction tend to be affected by alcohol, both in speed and coordination Tarter et al. One could argue that the participants were taking a greater risk by accepting the same gap while ignoring initiation capabilities. It would have been safer to wait for a larger gap, since it would take more time to cross. As stated, the effects of alcohol were mainly found on automated driving performance and were not found in the scenarios where more complex driving behaviour was measured. This might be due to the dynamic nature of these kinds of tasks. Since the scenarios measuring complex driving performance are so dynamic, they allow for different strategies to compensate for intoxicating effects. For example, where one participant might have reduced speed to have an increased reaction time to unexpected events, another might have adopted an alternative strategy in which altering speed was not necessary. For automated driving tasks, these compensatory strategies are limited and may therefore be more sensitive to drug-induced effects. Fairclough and Graham hypothesised that compensatory responses are triggered by the awareness and subjective discomfort of reduced performance efficacy. Although the current study was double blind, the majority of the participants still guessed the alcohol condition they were in correctly and may perhaps have responded by compensating for the impairing effects. One way in which they did this was by investing more mental effort, since scores on the RSME increased for the higher alcohol levels. This might also explain why participants felt they had not driven any worse under the influence of any of the alcohol conditions as compared to the placebo when asked to rate their own driving performance. In conclusion, the effects of alcohol were mainly found on automated driving performance such as weaving and speed control. Therefore, these are the main parameters that will serve as references for the second study on the influence of MDMA and alcohol on driving performance. Participants were recruited by flyers distributed at the University of Groningen. In the beginning 20 volunteers participated in this study. However, one participant did not comply with the rules of participation and was therefore discarded from further analyses. This participant tested positive for MDMA in the placebo condition even though he had tested negative in the urine drug screen as was conducted at the start of every testing day. This became apparent during the post hoc pharmacological analyses. Therefore, 19 healthy volunteers ten males, nine females aged between 21 and 40 years mean SD , They were all experienced drivers who had held their driving licence between 3 to 20 years mean SD , 8. Moreover, they had experience with alcohol use but were not abusers participants on average drank 7. Participants were medically examined by a medical supervisor. Vital signs were checked and standard blood chemistry was examined. This study was conducted according to the code of ethics on human experimentation established by the declaration of Helsinki latest revision, Seoul and in accordance with the Medical Research Involving Human Subjects Act WMO. A permit for obtaining, storing and administering MDMA was obtained from the Dutch drug enforcement administration. The study design was a double-blind, placebo-controlled, four-way crossover design with treatment orders counterbalanced according to a Latin square. On the testing days, the participants randomly received a single dose of mg MDMA, or placebo, and a single dose of alcohol aiming at BAC 0. The placebos, alcohol and MDMA where administered orally. Alcohol was administered according to the same procedure as in the alcohol reference study study 1 and MDMA and placebo—MDMA were administered in a capsule. After there was no medical objection for participation, participants were invited to come in for a training day to check for simulator sickness and to practise all of the driving scenarios in a full dress rehearsal. After the training day, participants visited the facilities four additional times 1 day for each condition , with a washout period of 1 week in between. Participants were asked to refrain from any drugs starting 1 week before the screening and during the whole study period. Drug screens in urine and alcohol screened in breath were conducted before the start of every testing day. Female participants were also screened for pregnancy. Participants were allowed to take part on the testing day only if they had passed these screenings. Furthermore, participants were asked to refrain from alcohol and on the day prior to the testing day and from caffeinated beverages on the testing day itself. Participants were compensated for their participation by means of a monetary reward. Two blood samples 10 ml were taken 1. One sample was centrifuged after collection for 15 min at ca. Furthermore, dried bloodspots were collected by finger prick for a special drug assessment kit provided by the University of Heidelberg in order to investigate a new less invasive way of testing for drugs in blood Jantos et al. Driving tests were conducted between 1. Alcohol level was kept constant during all parts of the drive. The same measures employed in study 1 were also used in study 2. The same subjective measures employed in study 1 were also used in study 2. In addition, we asked participants in the introduction session how they thought the different drug conditions would influence their driving performance on a scale ranging from 0 worse to 12 better. We then asked them again after every driving session, to see whether they thought that the drug they had had may have influenced their driving performance. Treatment effects were handled in the same way as in study 1. After the assessment of treatment effects, a so called equivalence test was conducted on measures in which the treatment effect in the alcohol reference study was significant. In this test the equivalence of drug effects based on the difference to the placebo were compared to the criterion levels as established in the alcohol reference study. If this was so, then the drug effect was considered to be clinically relevant Mascha and Sessler BAC levels were 0. MDMA and MDA concentrations in blood serum, whole blood and dry bloodspots and oral fluid were comparable between treatments see Table 2 and for further analyses see also Jantos et al. As can be seen in Fig. Hereafter, the level was relatively stable for the remaining hours that were measured. There was no correlation between serum and oral fluid MDMA concentrations. This is in line with Samyn et al. Mean SE performance scores for all driving tasks and p values for main treatment effects are displayed in Table 3. Participants kept to the posted speed on all road types. The SDSP was higher when participants were driving under the influence of alcohol 0. Furthermore, there was an interaction effect of alcohol 0. As expected, there was a main within-subjects effect of treatment on weaving, measured as the SDLP F 2. Moreover, SDLP increased 2. Therefore, equivalence could be tested. Equivalence testing demonstrated that increments in SDLP when treated with combined alcohol 0. However, the lower bound of the confidence interval spreads over the null line as well; indicating that a subset of individuals may show no impairment or even an average improvement i. There was no within-subjects effect of alcohol level on gap acceptance, running red lights, the car pulling out of a car park scenario or the number of crashes. Overall the coherence was lower than in study 1 average SE , 0. At the end of every session, participants were asked in which condition they thought they were in. For all conditions except the MDMA co-administered with alcohol condition, this was the case. When asking participants in the introduction session how they thought the different drug treatments would influence their driving performance, participants predicted their performance to be worse than normal. After testing the participants were asked if the treatment they thought that they had had may have influenced their driving performance. Overall, participants thought that the drug treatment that they had received would still make them drive a little worse than normal. However, this time they expected that the influence on their driving performance did not differ between treatments. Furthermore, we compared the pre-driving test subjective ratings with post-driving test ratings of participants who had guessed the treatment they had received correctly. Participants rated the influence of the treatment on their performance worse in the pre- as compared to the post-driving test. The average ratings of alertness as measured by the KSS pre-driving test were equal over all conditions. The effect of 0. Moreover, an increase in SDLP of about 2. As reported before in other studies Ramaekers and Kuypers ; Ramaekers et al. Equivalence testing demonstrated, though, that combined use could lead to impairment that is equivalent to BAC 0. However, the lower bound of the confidence interval spreads over the null line as well, indicating that a subset of participants may not be impaired or even slightly improved with respect to SDLP performance as compared to the placebo condition. Furthermore, this illustrates the large variance found in performance. Apparently, participants were differentially influenced by the different drug conditions. The lack of association between drug concentrations and performance confirms this assertion. This indicates that participants might keep up their vigilance for a longer period of time because of the stimulating effects of MDMA. However, this stimulation did not appear to be not large enough to uphold when MDMA was co-administered with alcohol since the pattern of weaving increase observed was the same in the co-administration condition as in the placebo and alcohol condition. This is in line with the alertness ratings of participants before and after driving, in that the participants indicated they felt less alert after driving as compared with before driving in all treatment conditions except in the MDMA condition. A behavioural compensating mechanism to keep up vigilance is deliberately varying speed. In the case of sedation, as would be experienced in the alcohol condition, a participant might temporarily increase speed to increase feelings of arousal as can be seen in an increase in the standard deviation of speed Brookhuis Although this was not a strategy chosen by the group of participants in the first alcohol reference study, in the second, MDMA study participants did tend to vary their speed more when treated with alcohol only as compared to the placebo, but only when driving on the rural road. This is the kind of road type where one would expect such a behavioural compensation, since it is a monotonous road with little other traffic participants to consider. Another compensation mechanism for driving under the influence of sedating drugs such as alcohol is lowering ones speed. Furthermore, Brookhuis et al. In the current study, however, participants kept to the posted speed on all road types and in the MDMA condition even decreased speed a bit more when driving on the rural road. Car following remained unaffected under all treatment conditions. Overall coherence was relatively low, indicating that participants were following the lead car less well, which may have disturbed the measurement of car following. This is in line with Brookhuis et al. As said, the aim of the study was to investigate more complex driving behaviour as well and compare it to driving under the influence of different levels of alcohol. In the alcohol reference study, we found little to no effects of alcohol on any of measures assessing complex driving behaviour. Similarly, in the MDMA study, there were no effects found of any of the treatment conditions on the performance measures in these more complex scenarios. One factor that might have contributed to variance in performance was the variance of the MDMA concentrations, as detected in saliva and, especially, in blood. It has previously been postulated that individuals might genetically differ in their metabolism of the drug e. Individuals may therefore have variable concentrations of the parent compound and metabolites in blood after the same dose was administered De La Torre et al. Although this might explain the high variance of the MDMA in bodily fluids, it does not explain the lack of association with behavioural results. In the alcohol study, it was proposed that this might be due to variance in compensation strategies which make it hard to come to one conclusion about the average effects of treatments on measures in the complex driving scenarios. This idea is supported in this study when looking at the large variances, especially in the multidrug condition. Anecdotally, some participants indicated not to have noticed that they were administered alcohol in addition to MDMA. If drivers are not aware of the intoxicating effects of alcohol when driving under the influence of MDMA, and therefore do not feel the subjective discomfort of reduced performance efficacy, they might not compensate accordingly. Moreover, when comparing self assessment of driving performance with the automated driving results, we could conclude that in case of alcohol consumption the self evaluation led to the wrong conclusions. In this condition participants rated their performance before and after driving under the influence as the same: that is, slightly worse than normal. Since their driving was actually seriously deteriorated, this conclusion was a falsely positive assessment of the situation. In the case of MDMA, the opposite was the case. The driving performance of the MDMA users was better than their self-assessment. Moreover, participants predicted their driving behaviour to deteriorate most when driving under the influenced of combined substances, but after having driven under the influence of the combined treatment condition performance was rated as the same to all other treatment conditions. An intoxicated individual might decide to drive because the feelings of alertness caused by MDMA cloud the impairing effects of other drugs such as alcohol, thereby implying a serious risk for traffic safety. We would like to thank the anonymous reviewers and Ben Lewis Evans for their helpful comments on earlier versions of this paper. As a library, NLM provides access to scientific literature. Psychopharmacology Berl. Effects of alcohol BAC 0. Find articles by Janet L Veldstra. Find articles by Karel A Brookhuis. Find articles by Dick de Waard. Find articles by Barbara H W Molmans. Find articles by Alain G Verstraete. Find articles by Gisela Skopp. Find articles by Ricarda Jantos. Received Jun 6; Accepted Oct 5; Issue date Open in a new tab. Average SE of the driving tasks for all treatment conditions in study 1. Driving task Placebo Alcohol 0. Significance indicated by p value. Average SE of the driving tasks for all treatment conditions in study 2. Gain 5. Delay 0. Gap acceptance Gap time s 4. Distance to car m Car pulling out of parking TTC 1. Similar articles. Add to Collections. Create a new collection. Add to an existing collection. 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