Prevalence and Misreporting of Illicit Drug Use among Electronic Dance Music Festivals Attendees: A Comparative Study between Sweden and Belgium
Abstract
Illicit drug use is common among attendees of electronic dance music (EDM) festivals, but is often significantly underreported by participants. The current study aimed to compare the prevalence and over- and under-reporting of illicit drug use among attendees at EDM festivals in two European countries with distinct drug laws and cultures. Self-reported data regarding recent drug use were collected through interviews. Participants’ blood alcohol concentrations were measured using a breathalyzer. Recent illicit drug use was assessed through sampling microparticles in the breath and consequent off-site analysis through liquid chromatography and tandem mass spectroscopy. Illicit drug use was higher in Belgium than in Sweden as indicated by self-reports (56.8 vs. 4.3%) and drug testing (37.2 vs. 12.5%). Underreporting was higher in Sweden than in Belgium; in Sweden, only 2.6% reported taking an illicit drug other than cannabis, whereas 11.6% tested positive, while the corresponding figures in Belgium were 36.5% and 36.9%. In both countries, results from self-reporting and drug testing for specific drugs matched poorly at the individual level, indicating unwitting consumption of substances. This study indicates that the drug use prevalence and the likelihood of disclosure may differ between countries or cultures, which should be considered when choosing methods to investigate drug use prevalence.
Article type: Research Article
Keywords: drug testing, drug consumption, breath sampling device, drinking, intoxication, biological sampling
Affiliations: STAD, (Stockholm Prevents Alcohol and Drug Problems), 11364 Region Stockholm, Sweden; tobias.elgan@ki.se (T.H.E.); johanna.gripenberg@ki.se (J.G.); Centre for Psychiatry Research, Department of Clinical Neuroscience, Karolinska Institute & Stockholm Health Care Services, 11364 Region Stockholm, Sweden; olof.beck@ki.se; Belgium Substance Use and Psychosocial Risk Behaviours (SUPRB), HOGENT University of Applied Sciences and Arts, 9000 Ghent, Belgium; bert.hauspie@hogent.be (B.H.); nicky.dirkx@hogent.be (N.D.); tina.vanhavere@vandenbroucke.fed.be (T.V.H.)
License: © 2024 by the authors. CC BY 4.0 Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
Article links: DOI: 10.3390/toxics12090635 | PubMed: 39330563 | PMC: PMC11436008
Relevance: Moderate: mentioned 3+ times in text
Full text: PDF (295 KB)
1. Introduction
Music festivals constitute a setting in which young people meet and socialize. The great majority of attendees also consume alcohol during or prior to entering the festival area [ref. 1,ref. 2,ref. 3,ref. 4]. High levels of alcohol intoxication increase the risk of injuries, sexual risk-taking and various forms of violence, including sexual violence [ref. 5,ref. 6,ref. 7,ref. 8,ref. 9,ref. 10,ref. 11,ref. 12]. Furthermore, the use of illicit drugs is prevalent in nightlife settings [ref. 13,ref. 14,ref. 15,ref. 16,ref. 17,ref. 18,ref. 19], including music festivals [ref. 2,ref. 3,ref. 20,ref. 21,ref. 22].
Illicit drugs are potent psychoactive compounds, such as cannabis (THC: delta-9-tetrahydrocannabinol), cocaine, ecstasy (MDMA: 3,4-methylenedioxymethamphetamine), amphetamine, and hallucinogens. Each substance is associated with its own acute risk, including psychosis, hallucinations, panic attacks, myocardial infarctions, overheating, and violence [ref. 23,ref. 24,ref. 25,ref. 26,ref. 27,ref. 28]. Moreover, when these substances are taken together with alcohol or when various illicit drugs are taken within a given time window (polydrug use), the risk of negative consequences increases [ref. 3,ref. 9,ref. 10,ref. 13,ref. 14,ref. 17,ref. 21,ref. 29,ref. 30,ref. 31]. Attendees at nightlife events consume these substances to a higher degree than the general population, although prevalences varied between studies conducted in different countries [ref. 13,ref. 14,ref. 15,ref. 16,ref. 32,ref. 33,ref. 34,ref. 35,ref. 36,ref. 37]. However, little is known about the extent to which attendees of electronic dance music (EDM) festivals consume illicit drugs and whether the levels of consumption differ between countries.
Although drug use among nightlife attendees has been widely studied, few have measured the use of these substances at EDM festivals using bioanalytical tests [ref. 3,ref. 20,ref. 21]. For example, a study of a large 40 h EDM event on a cruise ship departing from Sweden demonstrated that 4% of attendees self-reported recent drug use, but 10% tested positive for an illicit drug, indicating underreporting of drug use [ref. 3]. Similarly, a study of six festivals in Norway showed that 6% self-reported drug use, but 11% tested positive for drug use [ref. 21]. Thus, these two studies indicate that biological testing is needed to estimate the prevalence of drug use among festival attendees, a notion which was previously derived from studies conducted in clubs in Norway and the US [ref. 15,ref. 17,ref. 33]. The underreporting of EDM events in clubs and festivals in Sweden was confirmed in our recent study [ref. 38].
Potential reasons for underreporting drug use may be recall or social desirability biases [ref. 39,ref. 40,ref. 41]. While recall bias concerns difficulties among respondents in recalling previous events and experiences, social desirability bias refers to respondents’ tendency to modify their answers to conform to social norms [ref. 39,ref. 40]. For instance, the respondent may overreport what is considered good behavior to maintain a good self-image or underreport what is considered bad behavior to avoid shame and embarrassment in front of the interviewer or bystander [ref. 40]. Moreover, if confidentiality is uncertain, respondents may fear legal sanctions or risk to their employment or reputation [ref. 39].
Furthermore, studies among American homes and veterans conducted in 2001–2002 and 1996, respectively, found that cannabis use was overreported, whereas cocaine use was underreported, indicating that social acceptance of the substance also influenced the likelihood of self-reporting [ref. 42,ref. 43]. Nevertheless, in a Swedish cruise ship study conducted in 2011, somewhat higher prevalence rates for cannabis and cocaine were obtained through self-reporting compared to drug testing, whereas amphetamine and ecstasy were clearly underreported. This could also indicate that participants were unaware of the actual substance they had consumed; for example, they had received amphetamine instead of cocaine. Furthermore, in a Norwegian festival study conducted in 2016, cannabis, ecstasy, and cocaine use was underreported. Hence, it is not fully understood whether underreporting is country- or substance-specific.
Sweden and Belgium have distinct drug laws. While drug use is a criminal offence in Sweden, leading to fines or imprisonment (Act on Penal Law on Narcotics (1968:64)), Belgium has no laws against drug use. However, possession of drugs, including cannabis, is illegal in both countries (Belgium: Narcotic Drug Act of 24 February 1921, Sweden: Act on Penal Law on Narcotics (1968:64)). In Belgium, cannabis possession for personal use can lead to fines or up to one year of imprisonment depending on the frequency of offenses within a certain period as well as the level of public disorder, but prosecution of cannabis possession for personal use should be given the lowest priority according to ministerial directives [ref. 44]. Differences in laws, policies, or norms may influence the extent of drug use as well as the over- or under-reporting of drug use.
Therefore, the present study’s aim was to compare the prevalence, as well as over- and under-reporting of illicit drug use among attendees at music festivals in Belgium and Sweden.
2. Materials and Methods
2.1. Settings
This study was conducted at three EDM festivals: a large two-day festival in Sweden, and two smaller festivals in Belgium. Data were collected during the summer of 2018 (June to September). Festival organizers were contacted ahead of time, informed about the study, and approved the data collection.
2.2. Procedure
The procedure was similar to that described previously [ref. 1,ref. 3,ref. 17,ref. 45]. Briefly, cross-sectional data were collected by a team of four to seven trained research assistants. Two teams were collecting data simultaneously at different locations at the larger Swedish festival. Each team consisted of several interviewers and one recruiter who invited festival attendees to participate in the study. Prior training of research assistants included how to approach participants, informed consent (voluntary and anonymous participation), the interview process, mouth rinsing before breath measurements, and how to correctly handle the breathalyzer and drug breath sampling device. Recruiters invited every third person to pass through an imaginary line to participate in the study [ref. 3,ref. 32,ref. 45]. To minimize refusal, individuals accompanying the person approached were also invited to participate [ref. 46]. Upon refusal, the estimated age and gender of the approached person were recorded.
First, the participant was given a cup of water for mouth rinsing (necessary for correctly measuring alcohol and drugs in the exhaled breath). Participants were then asked questions on demographic information (age, gender and employment status) as well as smoking and alcohol drinking habits using the AUDIT-C (Alcohol Use Disorder Identification Test-C) [ref. 47,ref. 48]. Blood alcohol concentration (BAC) was assessed using an alcohol breathalyzer (Dräger Alcotest 6820). Participants were asked to complete a questionnaire on their own use of different types of illicit drugs. At the end of the interview, the participant was asked to exhale ten times—breathing normally—through a device containing a filter collecting aerosol microparticles (BreathExplor®, Munkplast, Uppsala, Sweden) [ref. 49]. The interview and breath sampling were completed in about ten to fifteen minutes. Stickers containing identical barcodes were attached to the questionnaire and device. Devices were stored in cooler boxes (+4 °C) during data collection and then transferred to freezers (−20 °C) and stored until analysis. Finally, a small incentive was offered to the participants (chips, chocolate, and chewing gum). When invited to the study, participants were informed that it focused on alcohol and drugs, and were made aware of the offered incentive, but were not told about the drug testing to avoid influencing the accuracy of their self-reporting.
2.3. Chemical Analysis
The filter was removed from the device, and microparticles were extracted using a methanol solution. Samples were analyzed as previously described [ref. 49,ref. 50] using a combination of liquid chromatography and tandem mass spectroscopy, including electrospray ionization and selective reaction monitoring. This method has high sensitivity and specificity, with a detection limit of one picogram. Each sample was analyzed for 47 different substances (Table 1), including illicit drugs and their metabolites.
Table 1: List of substances analyzed in the breath samples.
| Cannabis (THC) | Central stimulants |
| Ketamine | Cocaine |
| Opioids | Benzoylecgonine (Cocaine metabolite) |
| heroin metabolites | Amphetamine |
| 6-Acetylmorphine | Methamphetamine |
| Morphine | Ecstasy (MDMA) |
| 6-Acetylcodeine | Mephedrone (4-MMC) |
| Codeine | MDA |
| pain medications | MDPV |
| Dihydrocodeine | 4-Methylcathinone |
| Hydromorphone | Methylone (MDMC) |
| Tramadol | Butylone |
| O-Desmethyltramadol | PMMA |
| Oxycodone | ADHD medications |
| opioid use disorder medications | Ritalinic acid (Methylphenidate metabolite) |
| Methadone | |
| EDDP (methadone metabolite) | New Psychoactive Substances (NPS) |
| Buprenorphine | Alpha-PVP |
| Norbuprenorphine (Buprenorphine metabolite) | Pentedrone MDEA |
| Benzodiazepines | MBDB |
| Diazepam | BDB (MBDB metabolite) |
| Nordazepam | Other medications (classed as narcotics) |
| Oxazepam | Zopiclone |
| Temazepam | Zolpidem |
| Flunitrazepam | Pregabalin |
| Alprazolam | Gabapentin |
| Bromazepam | |
| Midazolam | |
| Lorazepam |
Alpha-PVP: alpha-pyrrolidinovalerophenone, BDB: 1,3-benzodioxolylbutanamine, EDDP: 2-ethylidene-1,5-dimethyl-3,3-diphenylpyrrolidine, MBDB: 1,3-benzodioxolyl-N-methylbutanamine, MDA: 3,4-methylenedioxyamphetamine, MDEA: 3,4-methylenedioxy-N-ethylamphetamine, MDMA: 3,4-methylenedioxymeth-amphetamine, MDMC: 3,4-methylenedioxy-N-methylcathinone, MDPV: methylenedioxypyrovalerone, 4-MMC: 4-methyl methcathinone, PMMA: para-methoxyamphetamine, THC: delta-9-tetrahydrocannabinol.
The maximum time window of detection for the analyzed compounds was between 24–48 h after consumption, except for delta-9-tetrahydrocannabinol (THC), for which the detection window was up to six hours [ref. 51]. Positive test results for metabolites were treated as an indication for illicit drugs (see Table 1): ritalinic acid for methylphenidate; EDDP for methadone; norbuprenorphine for buprenorphine; benzolyecgonine for cocaine; and morphine, codeine, 6-acteylmorphine and 6-acetylcodeine for heroin [ref. 52].
2.4. Statistical Analysis
Data were analyzed using SPSS (version 27). Chi2-analysis was conducted to compare demographic factors, as well as smoking, BAC levels, AUDIT-C score category, and self-reported and measured drug use prevalence between countries. A t-test was used to compare BAC levels between countries. Binomial regressions were conducted to investigate if country-specific differences in self-reported and tested drug use remained after controlling for age, gender, education status and frequency of going out to clubs.
The level of agreement between self-reported data and biological test results were measured with Cohen’s kappa (k) and defined as follows: no agreement < 0.20, minimal 0.21–0.39, weak 0.40–0.59, moderate 0.60–0.79, strong 0.80–0.90 and almost perfect > 0.90 [ref. 53]. The significance level was set at 0.05.
2.5. Ethical Considerations
This study was conducted in accordance with the Declaration of Helsinki and approved by the Regional Ethical Review Board in Stockholm (2017/1207-32) and the Ethics Committee of the Faculty of Psychology and Educational Sciences, Ghent University, Belgium (2017/14/Bert Hauspie, 14 April 2017). Informed consent was obtained from all participants involved in the study.
3. Results
3.1. Participants
In Sweden, 77% (n = 669) of the 864 individuals invited agreed to participate. Participants’ median (IQR) age was 21 (20–24) years, and 55% were men. Among those who did not participate, the median (IQR) age was 22 (20–25) years, and 71% were men. In Belgium, 88% (n = 329) of the 376 people invited agreed to participate. Participants’ median (IQR) age was 21 (19–25) years, and 71% (n = 235) were men. Among those who did not participate, the median (IQR) age was 23 (20–28), and 62% were men.
A comparison of demographic data revealed that in Belgium, compared to Sweden, a larger proportion were men, more participants were students, fewer were working full-time, and fewer were going out to clubs at least six times a year (Table 2). Comparing substance use between countries demonstrated that, in Belgium compared to Sweden, a larger proportion of the participants were daily smokers, hazardous drinkers, and had taken illicit drugs during their lifetime (Table 2). However, the measured BAC level was higher in Sweden than Belgium (mean ± SD: 0.079 ± 0.056% vs. 0.051 ± 0.054%, t(996) = 7.74, p < 0.001).
Table 2: Demographic data and substance use during lifetime.
| Sweden% (n) | Belgium% (n) | Chi-Square (df),p-Value | |
|---|---|---|---|
| Gender Men Women Other | 55.0 (366)44.6 (297)0.5 (3) | 71.4 (235)28.6 (94)0.0 (0) | 25.76 (2),<0.001 |
| Employment status Full-time Part-time University student High-school student Unemployed Other | 61.1 (409)13.2 (88)16.6 (111)5.1 (34)1.8 (12)2.2 (15) | 44.3 (143)3.4 (11)31.6 (102)17.0 (55)3.1 (10)0.6 (2) | 94.32 (5), <0.001 |
| Number of club visitsper year <6 times ≥6 times | 15.0 (98)85.0 (554) | 22.5 (72)77.5 (248) | 8.30 (1), 0.004 |
| Smoking Non-smoker Non-daily Daily smoker | 53.6 (358)32.8 (219)13.6 (91) | 32.1 (104)16.4 (53)51.5 (324) | 163.74 (2), <0.001 |
| Drinking habits last year Abstainers Non-hazardous Hazardous drinkers | 3.4 (23)40.7 (272)55.8 (668) | 2.7 (9)29.2 (96)68.1 (224) | 13.82 (2), <0.001 |
| Last use of illicit drug Never Several years ago During the last year | 54.0 (361)16.3 (109)29.6 (198) | 9.5 (31)8.5 (28)82.0 (269) | 249.50, <0.001 |
| Ever-use of substances Cannabis Cocaine Ecstasy Amphetamine Mushrooms LSD NPS Ketamine Heroin Benzodiazepines Opioid medication ADHD medication Anabolic androgenic steroids | 42.6 (284)20.3 (135)18.2 (121)9.2 (61)7.2 (48)5.3 (35)3.5 (23)2.1 (14)0.3 (2)11.4 (75)9.1 (60)9.9 (65)1.5 (10) | 84.6 (270)53.7 (175)63.9 (209)34.4 (111)34.8 (114)28.0 (92)17.2 (56)45.1 (147)10.4 (34)20.2 (66)19.9 (65)19.8 (64)1.2 (4) |
Participants: n = 669 (Sweden), n = 329 (Belgium). Data are missing for gender (n = 3), employment status (n = 6), club visits (n = 26), smoking (n = 6), drinking habits (n = 1), illicit drug use (n = 2), cannabis (n = 12), cocaine (n = 7), ecstasy (n = 5), amphetamine (n = 10), mushrooms (n = 5), LSD (n = 6), NPS (n = 8), ketamine (n = 8), heroin (n = 5), benzodiazepines (n = 16), opioid medication (n = 11), ADHD medication (n = 16), anabolic androgenic steroids (n = 13).
3.2. Recent Use of Illicit Drugs: Self-Reporting and Biological Testing
In Sweden, drug testing revealed a higher prevalence of illicit drug use (any substance) as well as cocaine, ecstasy, and amphetamine use than self-reporting (Table 3). In Belgium, self-reporting resulted in a higher prevalence than drug testing, mainly regarding cannabis and ecstasy but not amphetamine use. In both countries, cannabis was detected in only a few samples, likely because of the short detection window of up to 6 h. With the exception of hallucinogens and heroin, self-reported recent drug use was significantly higher in the Belgian sample than in the Swedish sample (Table 3). Furthermore, a significantly larger proportion of participants in Belgium than in Sweden tested positive for cocaine, amphetamine, ketamine, and heroin.
Table 3: Prevalence of recent illicit drug use obtained by drug tests using exhaled breath samples and self-reports during the past 48 h.
| Sweden | Belgium | |||
|---|---|---|---|---|
| Self-Reported Use Last 48 h% (n) | PositiveBreath Test% (n) | Self-Reported UseLast 48 h% (n), p-Value 5 | Positive Breath Test% (n), p-Value 5 | |
| Any illicit drug 1 | 4.3 (29) | 12.5 (83) | 56.8 (187), <0.001 | 37.2 (122), <0.001 |
| Illicit drug other than cannabis | 2.6 (17) | 11.6 (77) | 36.5 (120), <0.001 | 36.9 (121), <0.001 |
| Cannabis/THC 2 | 2.4 (16) | 1.1 (7) | 46.3 (150), <0.001 | 0.3 (1), 0.215 |
| Cocaine | 1.7 (11) | 5.1 (34) | 15.0 (48), <0.001 | 11.9 (39), <0.001 |
| Ecstasy | 1.1 (7) | 3.2 (21) | 25.8 (82), <0.001 | 0.6 (2), 0.012 |
| Amphetamine | 0.2 (1) | 3.2 (21) | 5.9 (19), <0.001 | 16.2 (53), <0.001 |
| Mushrooms 3 | 0.2 (1) | – | 0.6 (2), 0.211 | – |
| LSD 3 | 0.3 (2) | – | 0.9 (3), 0.195 | – |
| NPS 4 | 0.3 (2) | 0.0 (0) | 1.9 (6), 0.010 | 0.0 (0) |
| Ketamine | 0.2 (1) | 0.3 (2) | 12.2 (39), <0.001 | 13.7 (45), <0.001 |
| Heroin | 0.2 (1) | 0.3 (2) | 0.0 (0), 0.486 | 10.4 (34), <0.001 |
Participants completed a self-reported questionnaire regarding their drug use during the last 48 h (self-reported). Breath samples were then analyzed for the presence of the same illicit drugs. A total of 669 people were interviewed in Sweden and 329 in Belgium, of whom 665 and 328 were tested for drugs in Sweden and Belgium, respectively. 1 self-reported drug use of at least one substance listed in the table. Positive test results for at least one of the 47 substances tested. 2 Analyses of breath samples can only detect cannabis within the last 6 h. 3 Magic mushrooms and LSD were not tested in breath samples. 4 Of the four NPS tested, none were found in the breath samples. Self-reported data for cannabis (n = 20), cocaine (n = 27), ecstasy (n = 26), amphetamine (n = 15), mushrooms (n = 10), LSD (n = 8), NPS (n = 13), ketamine (n = 13), and heroin (n = 11) are missing. 5 Chi-square test of corresponding values between countries.
Regarding self-reported recent drug use, the binomial regression model was statistically significant overall (χ2(9) = 385.84, p < 0.001, Nagelkerke R2 = 0.511). The likelihood of reporting recent drug use was significantly higher among participants from Belgium compared to Sweden (OR = 35.79, p < 0.001), males compared to females (OR = 2.28, p < 0.001), and those who regularly go to clubs (OR = 1.83, p = 0.022). Conversely, this probability was significantly lower among high school students compared to full-time employees (OR = 0.281, p = 0.001) and was not significantly influenced by age (p = 0.065).
Similarly, the binomial regression model for testing positive for at least one illicit drug was also statistically significant overall (χ2(9) = 94.93, p < 0.001, Nagelkerke R2 = 0.149). The probability of a positive drug test result was significantly higher in Belgium compared to Sweden (OR = 4.76, p < 0.001) and among those who regularly go to clubs (OR = 1.62, p = 0.040). However, it was not significantly affected by age (p = 0.119), gender (p = 0.400), or employment status (p = 0.099).
Out of 34 individuals who tested positive for heroin, 33 tested positive for 6-acetylmorphine (of which eight were also positive for 6-acetylcodeine) and one tested positive for codeine but not for other heroin metabolites or dihydrocodeine.
Apart from the drugs listed in Table 3, the following substances were also found in the samples: tramadol (n = 2 in Belgium, n = 1 in Sweden), oxycodone (n = 1, Sweden), oxazepam (n = 1, Sweden), temazepam (n = 2, Sweden), methamphetamine (n = 2 in Belgium, n = 1 in Sweden), MDA (n = 1 in Sweden), mephedrone (n = 1, Belgium), pregabalin (n = 2, Sweden), gabapentin (n = 1 in Belgium, n = 1 in Sweden), and methylphenidate or metabolite (n = 6, Sweden).
In Belgium, no differences existed between genders, as 37% of both men and women tested positive for an illicit drug (χ2(1) = 0.00, p = 0.993). In Sweden, however, there was a difference, as 14% of men and 11% of women tested positive (χ2(1) = 1.91, p = 0.166).
To further investigate over- and under-reporting, the results of drug testing and self-reports were matched at the individual level. Among participants who had not self-reported the recent use of any illicit drug, approximately 11% in Sweden and 28% in Belgium tested positive for at least one illicit drug (Table 4), indicating underreporting. In both countries, there was no agreement between self-reported and measured use of cannabis and only minimal agreement regarding cocaine use. In Belgium, there was no agreement between ecstasy and minimal agreement for amphetamines. In Sweden, there was minimal agreement on ecstasy and no agreement on amphetamines. Almost none of the participants who had reported cannabis use tested positive, potentially due to the shorter detection window of up to six hours.
Table 4: Agreement between self-reported and measured drug use.
| Tested Positive Sweden % (n Positive /n Total) | Cohen’s Kappa | Tested Positive Belgium% (n Positive /n Total) | Cohen’s Kappa | |
|---|---|---|---|---|
| Any illicit drug did not self-report use self-reported use | 10.6 (67/635)55.2 (16/29) | 0.236 | 28.4 (40/141)43.9 (82/187) | 0.147 |
| Illicit drug other than cannabis did not self-report use self-reported use | 9.9 (64/646)76.5 (13/17) | 0.245 | 27.9 (58/208)52.5 (63/120) | 0.246 |
| Cannabis did not self-report use self-reported use | 1.1 (7/635)0 (0/16) | -0.015 | 0 (0/173)0.7 (1/150) | 0.007 |
| Cocaine did not self-report use self-reported use | 3.8 (24/638)72.7 (8/11) | 0.356 | 7.7 (21/271)35.4 (17/48) | 0.303 |
| Ecstasy did not self-report use self-reported use | 2.2 (14/644)71.4 (5/7) | 0.375 | 0.4 (1/235)1.2 (1/82) | 0.012 |
| Amphetamine did not self-report use self-reported use | 3.2 (21/659)0 (0/1) | −0.003 | 13.7 (41/300)63.2 (12/19) | 0.269 |
Participants (n = 669). Data are missing for any illicit drug (n = 6), illicit drug other than cannabis (n = 7), cannabis (n = 24), cocaine (n = 30), ecstasy (n = 30), amphetamine (n = 19).
4. Discussion
Drug testing revealed that recent drug use prevalence was higher among attendees at the EDM festivals investigated in Belgium than among those in Sweden. Furthermore, participants in Sweden, but not in Belgium, underreported their recent drug use. Nevertheless, participants in Belgium often reported having taken substances other than those that tested positive. Drug testing seems to measure recent drug use prevalence more accurately in Sweden, in contrast to Belgium, where recent drug use was more honestly reported.
4.1. Drug Use Prevalence Differences
In Sweden, the prevalence of illicit drug use as discovered by drug testing was similar to that reported in studies on EDM events and festivals in Northern Europe [ref. 3,ref. 21]. In Belgium, the prevalence of drug use was higher than that in Sweden for both illicit drugs overall and for several illicit drugs separately. The higher prevalence of drug use in Belgium aligns with the broader European trends. A report by the European Union Drug Agency (EUDA, formerly known as EMCDDA) positioned Belgium as a significant hub for substances such as cocaine, amphetamine, and MDMA [ref. 54]. This central role in the drug trade, and thereby high availability, could contribute to the higher drug use prevalence observed at the Belgian festival scene. In contrast, Sweden’s lower prevalence and higher under-reporting rates may reflect its stricter drug policies and the social stigma associated with drug use. The wastewater analysis results from 2018 and 2019 presented on the EUDA webpage supported these findings, showing varying levels of drug use across different cities and substances [ref. 55]. Whereas cocaine and MDMA were found at higher levels in Belgian cities than in Stockholm, amphetamine was found at higher levels in Stockholm than in Belgian cities such as Antwerp or Oostende, but at much lower levels than in Brussels. Nevertheless, differences in the type of festival, gender, and employment status (see Section 4.4), as well as the fact that drug use is illegal in Sweden but not in Belgium, could also contribute to differences in drug use prevalence.
4.2. Self-Reports vs. Drug Testing
In Sweden, the drug use prevalence was higher when using drug testing than when using self-reporting, while in Belgium, levels were similar once cannabis was excluded (owing to the shorter detection window). In the current study, drug use was underreported in Sweden by a factor of four, which is similar to studies that reported factors of two to three [ref. 3,ref. 21]. Using either self-reporting or drug testing, the prevalence of drug use for most drugs was higher in Belgium than in Sweden, with the exception of heroin, which was not self-reported. Heroin use could have been unknown to the participants or potentially associated with higher stigma and therefore, less likely to be declared in self-reporting. However, when matching drug testing and self-reports at the individual level, agreement was minimal for most drugs, and both under- and over-reporting were found. These results indicate that people are not aware of the substance they consume, signaling unwitting drug consumption; therefore, drug testing is superior to self-reporting in identifying substance use and determining its prevalence. Furthermore, drug checking services could be a relevant harm reduction initiative at EDM events or festivals [ref. 56,ref. 57,ref. 58] but are also characterized by challenges regarding resources, logistics, and scientific evidence of efficiency [ref. 59]. Unwitting drug consumption can result from adulteration, mislabeling, or the sale of counterfeit drugs in illegal, unregulated markets.
4.3. Potential Reasons for Over- and Underreporting
There could be a variety of reasons for over- and under-reporting, both common and different, across countries. Owing to stricter laws and their increased enforcement in Sweden compared to Belgium, underreporting could be related to fear of legal consequences, as well as social stigma. Studies on drug use [ref. 15,ref. 45] found similar trends in underreporting due to social desirability bias, and legal concerns have been reported. In Belgium, a more permissive attitude toward drug use and less stringent policies may contribute to more honest reporting. Similar to questions regarding drug use, other surveys on sensitive topics have demonstrated social desirability bias (see review [ref. 40]). Furthermore, the settings and procedures can influence the likelihood of reporting drug use. To ensure comparability, researchers from both countries assisted in data collection and ensured that recruitment, interviews, sampling, and sample handling were similarly conducted. The fact that the survey was anonymous, no identifying information was recorded, and the test results could not be seen on-site may have limited the extent of underreporting and dropping out of the study.
Another reason for underreporting or overreporting could be that, with increasing intoxication levels, there may be a negative effect on memory. Although more people in Belgium than Sweden were identified as hazardous drinkers, BACs were higher in Sweden than in Belgium. Nevertheless, illicit drug use is higher in Belgium, which may have led to higher levels of drug intoxication. These findings could possibly be explained by legal differences between the two countries, i.e., the legal drinking age is 16 in Belgium and 18 in Sweden, and that drug use is not criminalized in Belgium. However, studies suggest that while alcohol intoxication decreases the number of details being recalled (completeness), the accuracy and reliability of recall memory are not compromised [ref. 60,ref. 61]. Moreover, alcohol intoxication did not seem to increase honesty or impede people’s ability to conceal information [ref. 61,ref. 62]. Furthermore, the regression model indicated that men are more likely to report recent use of illicit drugs compared to women. This finding is consistent with our previous study, which showed that although fewer women than men tested positive for drugs, those women who did test positive were less likely to report drug use, suggesting a tendency toward underreporting among women [ref. 38].
4.4. Limitations
This study’s limitations include a potential gender imbalance in the participant pool, although even among those refusing there was also a male majority. In addition, our previous studies suggested a similar male majority in frequent EDM event attendees [ref. 37,ref. 63,ref. 64]. Similarly, there were differences in employment statuses between countries, which could influence drug use patterns and reporting, but this could have also been related to the different types of events. The study’s findings are limited to specific festival settings in Belgium and Sweden and may not be generalizable to other contexts or countries. The Belgian festivals visited were smaller than the Swedish festivals and might have represented a more niched subculture in which illicit drug use was more common. During the summer before our study, a small EDM festival planned to be held at an old factory and with already sold tickets was not allowed to be held after a decision from the police three weeks before the event based on safety concerns owing to the building in combination with expected alcohol and drug intoxication. Therefore, we had trouble finding a similar small-niched festival in the year of our study, and although the one we chose was larger, it clearly played EDM. Furthermore, open-ended questions regarding the substances used were not included in the questionnaire, which could have potentially provided further insight into which substances the participants believed they had consumed, especially when slang or street names might have been more familiar to them.
5. Conclusions
This study provides crucial insights into the patterns of illicit drug use and reporting during music festivals in Belgium and Sweden. The observed differences underscore the need for culturally and legally sensitive approaches to address drug use in nighttime settings. These findings emphasize the importance of considering local drug policies, cultural attitudes, and reliable methods for measuring drug use in research and policymaking. In addition, our findings also allow law enforcement and medical personnel to better prepare for and respond to substance use-related incidents. Future research should explore in depth the cultural and legal factors influencing drug use reporting and develop and test strategies tailored to specific environments and cultures. Understanding these factors is crucial for developing effective drug prevention and harm reduction strategies, such as drug-checking services and how to communicate to those under the influence, which are sensitive to the specific cultural and legal contexts of different countries.
References
- K. Feltmann, T.H. Elgán, J. Gripenberg. High levels of alcohol intoxication and strong support for restrictive alcohol policies among music festival visitors. Subst. Abus. Treat. Prev. Policy, 2019. [DOI | PubMed]
- L. Gjersing, A.L. Bretteville-Jensen, H. Furuhaugen, H. Gjerde. Illegal substance use among 1,309 music festival attendees: An investigation using oral fluid sample drug tests, breathalysers and questionnaires. Scand. J. Public. Health, 2019. [DOI | PubMed]
- J. Gripenberg-Abdon, T.H. Elgán, E. Wallin, M. Shaafati, O. Beck, S. Andréasson. Measuring substance use in the club setting: A feasibility study using biochemical markers. Subst. Abus. Treat. Prev. Policy, 2012. [DOI | PubMed]
- T. Martinus, J. McAlaney, L.J. McLaughlin, H. Smith. Outdoor music festivals: Cacophonous consumption or melodious moderation?. Drugs Educ. Prev. Policy, 2010. [DOI]
- M.L. Exum. Alcohol and aggression: An integration of findings from experimental studies. J. Crim. Justice, 2006. [DOI]
- E.K. Bye, I. Rossow. The impact of drinking pattern on alcohol-related violence among adolescents: An international comparative analysis. Drug Alcohol. Rev., 2010. [DOI | PubMed]
- A. Abbey, R. Wegner, J. Woerner, S.E. Pegram, J. Pierce. Review of survey and experimental research that examines the relationship between alcohol consumption and men’s sexual aggression perpetration. Trauma. Violence Abus., 2014. [DOI]
- C.A. Crane, S.A. Godleski, S.M. Przybyla, R.C. Schlauch, M. Testa. The Proximal Effects of Acute Alcohol Consumption on Male-to-Female Aggression: A Meta-Analytic Review of the Experimental Literature. Trauma. Violence Abus., 2016. [DOI]
- D.L. Espelage, J.P. Davis, K.C. Basile, W.L. Rostad, R.W. Leemis. Alcohol, prescription drug misuse, sexual violence, and dating violence among high school youth. J. Adolesc. Health, 2018. [DOI | PubMed]
- K.C. Basile, S.G. Smith, Y. Liu, A. Lowe, A.K. Gilmore, S. Khatiwada, M.-J. Kresnow. Victim and perpetrator characteristics in alcohol/drug-involved sexual violence victimization in the U.S. Drug Alcohol Depend., 2021. [DOI | PubMed]
- N.B. Busch-Armendariz, D.M. DiNitto, H. Bell, T. Bohman. Sexual assault perpetrators’ alcohol and drug use: The likelihood of concurrent violence and post-sexual assault outcomes for women victims. J. Psychoact. Drugs, 2010. [DOI]
- S. Schnitzer, M.A. Bellis, Z. Anderson, K. Hughes, A. Calafat, M. Juan, A. Kokkevi. Nightlife violence: A gender-specific view on risk factors for violence in nightlife settings: A cross-sectional study in nine European countries. J. Interpers. Violence, 2010. [DOI | PubMed]
- F. Fernández-Calderón, C.M. Cleland, J.J. Palamar. Polysubstance use profiles among electronic dance music party attendees in New York City and their relation to use of new psychoactive substances. Addict. Behav., 2018. [DOI | PubMed]
- A. Sañudo, S. Andreoni, Z.M. Sanchez. Polydrug use among nightclub patrons in a megacity: A latent class analysis. Int. J. Drug Policy, 2015. [DOI | PubMed]
- M.B. Johnson, R.A. Voas, B.A. Miller, H.D. Holder. Predicting drug use at electronic music dance events: Self-reports and biological measurement. Eval. Rev., 2009. [DOI | PubMed]
- B.A. Miller, H.F. Byrnes, A.C. Branner, R. Voas, M.B. Johnson. Assessment of club patrons’ alcohol and drug use: The use of biological markers. Am. J. Prev. Med., 2013. [DOI | PubMed]
- T. Nordfjærn, A.L. Bretteville-Jensen, M. Edland-Gryt, J. Gripenberg. Risky substance use among young adults in the nightlife arena: An underused setting for risk-reducing interventions?. Scand. J. Public. Health, 2016. [DOI | PubMed]
- J.J. Palamar, P. Acosta, S. Sherman, D.C. Ompad, C.M. Cleland. Self-reported use of novel psychoactive substances among attendees of electronic dance music venues. Am. J. Drug Alcohol Abus., 2016. [DOI | PubMed]
- P. Miller, A. Curtis, R. Jenkinson, N. Droste, S.J. Bowe, A. Pennay. Drug use in Australian nightlife settings: Estimation of prevalence and validity of self-report. Addiction, 2015. [DOI | PubMed]
- A.L.A. Mohr, M. Friscia, J.K. Yeakel, B.K. Logan. Use of synthetic stimulants and hallucinogens in a cohort of electronic dance music festival attendees. Forensic Sci. Int., 2018. [DOI | PubMed]
- H. Gjerde, L. Gjersing, H. Furuhaugen, A.L. Bretteville-Jensen. Correspondence between Oral Fluid Drug Test Results and Self-Reported Illicit Drug Use among Music Festival Attendees. Subst. Use Misuse, 2019. [DOI | PubMed]
- L. Bijlsma, A. Celma, S. Castiglioni, N. Salgueiro-González, L. Bou-Iserte, J. Baz-Lomba, M. Reid, M. Dias, A. Lopes, J. Matias. Monitoring psychoactive substance use at six European festivals through wastewater and pooled urine analysis. Sci. Total Environ., 2020. [DOI | PubMed]
- L. Degenhardt, W. Hall. Extent of illicit drug use and dependence, and their contribution to the global burden of disease. Lancet, 2012. [DOI | PubMed]
- M. Di Forti, D. Quattrone, T.P. Freeman, G. Tripoli, C. Gayer-Anderson, H. Quigley, V. Rodriguez, H.E. Jongsma, L. Ferraro, C. La Cascia. The contribution of cannabis use to variation in the incidence of psychotic disorder across Europe (EU-GEI): A multicentre case-control study. Lancet Psychiatry, 2019. [DOI | PubMed]
- A.C. Parrott. Human psychobiology of MDMA or “Ecstasy”: An overview of 25 years of empirical research. Hum. Psychopharmacol., 2013. [DOI | PubMed]
- K.K. Rigg, A. Sharp. Deaths related to MDMA (ecstasy/molly): Prevalence, root causes, and harm reduction interventions. J. Subst. Use, 2018. [DOI]
- G. Vasica, C.C. Tennant. Cocaine use and cardiovascular complications. Med. J. Aust., 2002. [DOI | PubMed]
- J. Mounteney, P. Griffiths, A. Bo, A. Cunningham, J. Matias, A. Pirona. Nine reasons why ecstasy is not quite what it used to be. Int. J. Drug Policy, 2018. [DOI | PubMed]
- R. McKetin, J. Chalmers, M. Sunderland, D.A. Bright. Recreational drug use and binge drinking: Stimulant but not cannabis intoxication is associated with excessive alcohol consumption. Drug Alcohol Rev., 2014. [DOI | PubMed]
- F. Fernández-Calderón, C. Vidal-Giné, A.J. Rojas-Tejada, Ó.M. Lozano-Rojas. Patterns of Simultaneous Polysubstance Use among Partygoers: Correlates and Differences in Adverse Acute Effects Experienced. J. Psychoact. Drugs, 2020. [DOI]
- K.I. Morley, M.T. Lynskey, P. Moran, R. Borschmann, A.R. Winstock. Polysubstance use, mental health and high-risk behaviours: Results from the 2012 Global Drug Survey. Drug Alcohol Rev., 2015. [DOI | PubMed]
- B.A. Miller, D. Furr-Holden, M.B. Johnson, H. Holder, R. Voas, C. Keagy. Biological markers of drug use in the club setting. J. Stud. Alcohol Drugs, 2009. [DOI | PubMed]
- A.L. Bretteville-Jensen, J.B. Andreas, L. Gjersing, E.L. Øiestad, H. Gjerde. Identification and Assessment of Drug-User Groups Among Nightlife Attendees: Self-Reports, Breathalyzer-Tests and Oral Fluid Drug Tests. Eur. Addict. Res., 2019. [DOI | PubMed]
- D.E. Ramo, C. Grov, K. Delucchi, B.C. Kelly, J.T. Parsons. Typology of club drug use among young adults recruited using time-space sampling. Drug Alcohol Depend., 2010. [DOI | PubMed]
- T. Van Havere, W. Vanderplasschen, J. Lammertyn, E. Broekaert, M. Bellis. Drug use and nightlife: More than just dance music. Subst. Abus. Treat. Prev. Policy, 2011. [DOI]
- T. Van Havere, J. Lammertyn, W. Vanderplasschen, M. Bellis, J. Rosiers, E. Broekaert. Illicit drug use in the flemish nightlife scene between 2003 and 2009. Eur. Addict. Res., 2012. [DOI | PubMed]
- E. Van Dyck, K. Ponnet, T. Van Havere, B. Hauspie, N. Dirkx, J. Schrooten, J. Waldron, M. Grabski, T.P. Freeman, H.V. Curran. Substance use and attendance motives of electronic dance music (EDM) event attendees: A survey study. Int. J. Environ. Res. Public Health, 2023. [DOI | PubMed]
- K. Feltmann, T.H. Elgán, M. Böttcher, S. Lierheimer, S. Hermansson, O. Beck, J. Gripenberg. Feasibility of using breath sampling of non-volatiles to estimate the prevalence of illicit drug use among nightlife attendees. Sci. Rep., 2022. [DOI | PubMed]
- T.P. Johnson. Sources of error in substance use prevalence surveys. Int. Sch. Res. Not., 2014. [DOI]
- I. Krumpal. Determinants of social desirability bias in sensitive surveys: A literature review. Qual. Quant., 2013. [DOI]
- L.D. Harrison. The Validity of Self-Reported Data on Drug Use. J. Drug Issues, 1995. [DOI]
- M. Fendrich, T.P. Johnson, J.S. Wislar, A. Hubbell, V. Spiehler. The utility of drug testing in epidemiological research: Results from a general population survey. Addiction, 2004. [DOI | PubMed]
- D.M. Ledgerwood, B.A. Goldberger, N.K. Risk, C.E. Lewis, R.K. Price. Comparison between self-report and hair analysis of illicit drug use in a community sample of middle-aged men. Addict. Behav., 2008. [DOI | PubMed]
- Penalties for Drug Law Offences at a Glance|www.euda.europa.eu, (n.d.)
- T. Nordfjærn, M. Edland-Gryt, A.L. Bretteville-Jensen, K. Buvik, J. Gripenberg. Recreational drug use in the Oslo nightlife setting: Study protocol for a cross-sectional time series using biological markers, self-reported and qualitative data. BMJ Open, 2016. [DOI | PubMed]
- R.B. Voas, D. Furr-Holden, E. Lauer, K. Bright, M.B. Johnson, B. Miller. Portal surveys of time-out drinking locations: A tool for studying binge drinking and AOD use. Eval. Rev., 2006. [DOI | PubMed]
- H. Källmén, A.H. Berman, N. Jayaram-Lindström, A. Hammarberg, T.H. Elgán. Psychometric Properties of the AUDIT, AUDIT-C, CRAFFT and ASSIST-Y among Swedish Adolescents. Eur. Addict. Res., 2019. [DOI | PubMed]
- J.B. Saunders, O.G. Aasland, T.F. Babor, J.R. de la Fuente, M. Grant. Development of the Alcohol Use Disorders Identification Test (AUDIT): WHO Collaborative Project on Early Detection of Persons with Harmful Alcohol Consumption–II. Addiction, 1993. [DOI | PubMed]
- S. Seferaj, S. Ullah, D. Tinglev, S. Carlsson, J. Winberg, P. Stambeck, O. Beck. Evaluation of a new simple collection device for sampling of microparticles in exhaled breath. J. Breath Res., 2018. [DOI | PubMed]
- N. Stephanson, S. Sandqvist, M.S. Lambert, O. Beck. Method validation and application of a liquid chromatography-tandem mass spectrometry method for drugs of abuse testing in exhaled breath. J. Chromatogr. B Analyt. Technol. Biomed. Life Sci., 2015. [DOI]
- O. Beck, S. Ullah, R. Kronstrand. First evaluation of the possibility of testing for drugged driving using exhaled breath sampling. Traffic Inj. Prev., 2019. [DOI | PubMed]
- R.J. Dinis-Oliveira. Metabolism and metabolomics of opiates: A long way of forensic implications to unravel. J. Forensic Leg. Med., 2019. [DOI | PubMed]
- M.L. McHugh. Interrater reliability: The kappa statistic. Biochem. Med., 2012. [DOI]
- 54. EMCDDA European Drug Report 2018: Trends and DevelopmentsEuropean Monitoring Centre for Drugs and Drug Addiction, Publications Office of the European UnionLuxembourg2018
- Wastewater Analysis and Drugs—A European Multi-City Study|www.euda.europa.eu, (n.d.)
- F.C. Measham. Drug safety testing, disposals and dealing in an English field: Exploring the operational and behavioural outcomes of the UK’s first onsite “drug checking” service. Int. J. Drug Policy, 2019. [DOI | PubMed]
- D. Martins, M.J. Barratt, C.V. Pires, H. Carvalho, M.V. Vilamala, I.F. Espinosa, H. Valente. The detection and prevention of unintentional consumption of DOx and 25x-NBOMe at Portugal’s Boom Festival. Hum. Psychopharmacol., 2017. [DOI]
- A. Olsen, G. Wong, D. McDonald. Music festival drug checking: Evaluation of an Australian pilot program. Harm. Reduct. J., 2022. [DOI | PubMed]
- T. Brunt. Drug Checking as a Harm Reduction Tool for Recreational Drug Users: Opportunities and Challenges, 2017
- M.H. Karlén. Interviewing intoxicated witnesses: Memory performance in theory and practice. Scand. J. Psychol., 2018. [DOI | PubMed]
- H.D. Flowe, T. Jores, J. Gawrylowicz, D. Hett, G.M. Davies. Impact of alcohol on memory: A systematic review. Alcohol and Remembering Rape: New Evidence for Practice, 2021. [DOI]
- K. Suchotzki, H. May, M. Gamer. No effect of moderate alcohol intake on the detection of concealed identity information in the laboratory. Sci. Rep., 2020. [DOI | PubMed]
- K. Feltmann, T.H. Elgán, A.K. Strandberg, P. Kvillemo, N. Jayaram-Lindström, M. Grabski, J. Waldron, T. Freeman, H.V. Curran, J. Gripenberg. Illicit drug use and associated problems in the nightlife scene: A potential setting for prevention. Int. J. Environ. Res. Public Health, 2021. [DOI | PubMed]
- J. Waldron, M. Grabski, T.P. Freeman, C. Mokrysz, C. Hindocha, F. Measham, R. van Beek, P. van der Pol, B. Hauspie, N. Dirkx. How do online and offline sampling compare in a multinational study of drug use and nightlife behaviour?. Int. J. Drug Policy, 2020. [DOI | PubMed]
