https://orcid.org/0000-0003-1775-1882
Abstract
Electronic dance music (EDM) festivals have become a popular venue for recreational drug use, including the use of traditional stimulants like 3,4-methylenendioxymethamphetamine (MDMA) and novel psychoactive substances (NPS). Using this cohort of people who use drugs recreationally, this study sought to collect biological specimens and self-reported drug use data from EDM festival attendees in the United States to monitor regional and temporal trends related to NPS use and turnover between 2014 and 2017. Oral fluid samples were collected at three United States EDM festival locations, including Miami, Florida (2014 to 2017); Tampa, Florida (2017) and Atlanta, Georgia (2017). Samples were screened by liquid chromatography–quadrupole time-of-flight mass spectrometry and confirmed by liquid chromatography–tandem mass spectrometry. Over the 4 years, 1,233 oral fluid samples were collected. With respect to self-reported drug use, 63% of respondents reported medicinal and/or recreational drug use within the last week. When comparing 4 years of data from Miami (2014 to 2017), NPS trends showed the disappearance of alpha-PVP after 2014 followed by a significant increase in ethylone positivity in 2015 and rapid decrease in 2016. Dibutylone was identified for the first time in Miami 2016, and N-ethyl pentylone was identified for the first time in Miami 2017. Additionally, 3,4-methylenendioxymethamphetamine positivity steadily increased from 2014 to 2017. A comparison across study sites (Miami, Tampa and Atlanta) and specific trends with respect to novel simulant use are described within. Using this opportunistic approach of monitoring drug trends, we have found that peak positivity of novel stimulants usually is within a year of their first detection. Understanding the dynamics of NPS drug markets will allow laboratories to plan for resource allocation and scope updates within a timely fashion to assist with the detection and confirmation of these emerging substances in samples submitted for forensic analysis.
Introduction
The rapid rate at which novel psychoactive substances (NPS) emerge on the market is well reflected in reports produced by the National Forensic Laboratory Information Systems, the Drug Enforcement Administration and European Monitoring Centre for Drugs and Drug Addiction (1–3). Information related to consumption of NPS within the general population is heavily reliant on the detection of these substances within the clinical and forensic communities or based on self-reported use, which rarely includes analytical testing, thus limiting the utility of the data. The use of novel stimulants, also referred to as synthetic stimulants or NPS stimulants, is well documented within the peer-reviewed literature and has resulted in several adverse events, including intoxication and fatalities (4–11). According to the 2019 World Drug Report, novel stimulants continue to emerge and since 2009 account for the majority of NPS reported to the United Nations Office on Drugs and Crime early warning advisory (12). Of the 79 new substances identified and reported for the first time in 2017, 26 were novel stimulants. For purposes of this discussion, 3,4-methylenendioxymethamphetamine (MDMA) and 3,4-methylenedioxyamphetamine (MDA) are not considered to be novel stimulants.
Ingested for their euphoric effects, increased alertness and heightened sense of awareness, novel stimulants have become widely used at electronic dance music (EDM) festivals. The use of novel stimulants has been well documented based on self-reported survey data and reports of NPS use at several EDM festivals in the United States and worldwide (13–20). We previously reported that 72% of participants reported using a recreational or medicinal substance within the prior week based on surveys (n = 342) received from festival attendees in 2014 and 2015 (19). Of the 396 individuals that provided a biological sample for analytical testing, 75% were positive for a drug and/or alcohol, with 36% of the positive samples containing one or more NPS (18%) and/or MDMA (18%). In a recent study evaluating toxicology data from intoxicated individuals as well as seized drug material from an EDM festival, approximately 54% of 121 patients confirmed positive for MDMA, 4% were positive for an NPS and the majority of the patients were positive for multiple substances (9).
Within the context of EDM festivals, adverse events, toxicity and death attributed to the use of drugs, including NPS, have been reported at one of the festivals attended as part of this study, among others (9, 21–26). Studies have identified recreational drug use necessitating onsite medical treatment and/or hospital transportation but also found increased polydrug use, particularly among people who use MDMA, which increases the likelihood of an adverse event (21, 27, 28). Due to the high incidence of recreational drug use, particularly with novel stimulants, the EDM community represents an important study population. Further, this cohort of individuals is often viewed as trendsetters with respect to emerging drug use. By collecting biological specimens from people who use drugs recreationally that can be analytically confirmed, this study sought to obtain information related to the emerging substances in circulation, as well as the overall prevalence of novel stimulants and other common drugs of abuse within this cohort, including trend information related to turnover and proliferation.
Methods
Biological samples and survey information were collected from participants over 4 years (2014–2017) at 7 EDM festival events in the United States, including 4 repeat visits to one festival site. This was an Institutional Review Board (IRB) approved study (Arcadia University, Glenside, PA). Festival locations included Miami, Florida (Spring 2014–2017); Tampa, Florida (Summer 2017) and Atlanta, Georgia (Fall 2017). The festivals varied in duration, with the longest festivals occurring over 3 days (Friday, Saturday and Sunday; Miami 2014–2017 and Atlanta 2017) and the shortest festival occurring over 2 days (Saturday and Sunday; Tampa 2017). Participants were peer-recruited to participate in the study. Prior to signing a statement of informed consent agreeing to participate in the research, participants were allowed the opportunity to ask questions related to the study and asked if they had taken any recreational substances on that day. Any individual who answered “yes” to that question was excluded from the study. Additional exclusion criteria included individuals under the age of 18, individuals deemed unable to donate the required blood, urine and oral fluid specimens and individuals who appeared too visibly intoxicated to give consent or could not understand the study as described. Following consent, participants were asked a series of open-ended questions related to prescription and recreational drug use within the prior week and provided blood, urine and/or oral fluid sample. Because of logistical challenges related to collection of blood and urine, the ease of collection of oral fluid and our previous assessment of the level of agreement between drug test results in blood and oral fluid (19), oral fluid was the matrix of choice for this study.
Oral fluid samples were collected with the Immunalysis Quantisal® oral fluid collection device (Pomona, CA). All oral fluid samples were initially screened using nontargeted liquid chromatography–quadrupole time-of-flight mass spectrometry (LC–QTOF-MS). Data were processed against a regularly updated library that at the time of testing included over 500 compounds. Identifications were made by comparing acquire MS-MS data to the accurate mass library database. Additional criteria for identifying positive cases included mass error (<5 ppm), retention time (<0.25), library score (>70), signal-to-noise ratio (>10) and peak intensity (>800). Data not meeting the abovementioned criteria was subject to further review by the analyst. Drug positive results were subsequently confirmed using liquid chromatography–tandem mass spectrometry for quantitative confirmation or a secondary LC-QTOF-MS analysis for qualitative confirmation. The limit of detection from all novel stimulants and MDMA was 1 ng/mL. Details regarding these analytical methods have been previously reported (17–19).
Several analyses were undertaken, including the investigation of temporal trends, geographic trends and drug positivity by day of the event, as well as evaluations related to drug use versus gender and drug use versus age. The goal of these analyses was to provide comprehensive insight into the patterns and trends of novel stimulant use within this population. Statistical analyses were conducted using a chi-squared test followed by a Fisher’s exact test; statistical significance was determined by a P value less than 0.05.
Results and Discussion
Over the 4-year study (2014–2017), a total of 1,233 oral fluid samples were collected from participants. A breakdown of the number of participants who provided an oral fluid sample by festival location is provided in Table I. We have previously reported data from the 2014 and 2015 festival events (19), including rates of self-reported admitted medicinal or recreational drug use of 72%. For the four festivals attended in 2016 and 2017, a total of 691 subjects completed the drug use questionnaire, and 63% (n = 436) reported using a medicinal substance or recreational drug within the prior week. Self-reported drug use by festival for 2016 and 2017 is shown in Figure 1. The demographics of participants providing survey response data included 431 males (62%) and 255 females (35%), with 5 participants not indicating gender. The average age of the participants was 23.7 (±5.2) years old.
Qualitative Oral Fluid Results by Festival and Year
| Substance detected | Miami | Tampa | Atlanta | Total (n = 1,233) | % Positivity | |||
|---|---|---|---|---|---|---|---|---|
| 2014 (n = 136) | 2015 (n = 248) | 2016 (n = 244) | 2017 (n = 308) | 2017 (n = 131) | 2017 (n = 166) | |||
| Novel stimulants | ||||||||
| MDMA | 9 (6.6%) | 19 (7.6%) | 43 (17%) | 76 (24%) | 24 (18%) | 79 (47%) | 250 | 20.3 |
| MDA | 6 (4.4%) | 11 (4.4%) | 36 (14%) | 70 (22%) | 26 (19%) | 71 (42%) | 220 | 17.8 |
| Ethylone | 15 (11%) | 41 (16%) | 18 (7.3%) | 3 (0.9%) | 2 (1.5%) | 2 (1.2%) | 81 | 6.6 |
| Methylone | 24 (17%) | 1 (0.4%) | 3 (1.2%) | 4 (1.2%) | 2 (1.5%) | 2 (1.2%) | 36 | 2.9 |
| Dibutylone | – | – | 12 (4.9%) | 11 (3.5%) | 1 (0.7%) | 3 (1.8%) | 27 | 2.2 |
| Butylone | 4 (2.9%) | – | 12 (4.9%) | 6 (1.9%) | – | 3 (1.8%) | 25 | 2 |
| N-ethyl pentylone | – | – | – | 3 (0.9%) | 11 (8.3%) | 8 (4.8%) | 22 | 1.8 |
| Dimethylone | 5 (3.6) | 1 (0.4%) | 3 (1.2%) | 1 (0.3%) | – | 1 (0.6%) | 11 | 0.9 |
| Alpha-PVP | 11 (8.0%) | – | – | – | – | – | 11 | 0.9 |
| Pentylone | – | – | 1 (0.4%) | 1 (0.3%) | – | – | 2 | 0.2 |
| Eutylone | – | – | – | – | 2 (1.5%) | 1 (0.6%) | 3 | 0.2 |
| 4-Fluoroamphetamine (4-FA) | 2 (1.4%) | – | 1 (0.4%) | – | – | – | 3 | 0.2 |
| Methyldiethanolamine (MDEA) | – | – | – | – | – | 2 (1.2%) | 2 | 0.2 |
| 2,5-Dimethoxy-4-bromophenethylamine | – | – | – | 2 (0.6%) | – | – | 2 | 0.2 |
| (2C-B) | ||||||||
| 2,5-Dimethoxy-4-bromoamphetamine (DOB) | – | – | – | 2 (0.6%) | – | – | 2 | 0.2 |
| 3-Trifluoromethylphenylpiperazine (TFMPP) | – | – | – | 1 (0.3%) | – | – | 1 | 0.1 |
| Benzylpiperazine (BZP) | – | – | – | 1 (0.3%) | – | – | 1 | 0.1 |
| Common drugs of abuse | ||||||||
| Tetrahydrocannabinol (THC) | 56 (41%) | 90 (36%) | 79 (32%) | 93 (30%) | 55 (41%) | 105 (63%) | 478 | 38.8 |
| Cocaine | 17 (12%) | 22 (8.8%) | 20 (8.1%) | 24 (7.7%) | 11 (8.3%) | 53 (31%) | 147 | 11.9 |
| Benzoylecgonine | 17 (12%) | 24 (9.6%) | 18 (7.3%) | 20 (6.4%) | 7 (5.3%) | 43 (25%) | 129 | 10.5 |
| Amphetamine | 3 (2.2%) | 4 (1.6%) | 16 (6.5%) | 17 (5.5%) | 5 (3.8%) | 16 (9.6%) | 61 | 4.9 |
| Cocaethylene | 6 (4.4%) | 6 (2.4%) | 1 (0.4%) | 5 (1.6%) | 2 (1.5%) | 19 (11%) | 39 | 3.2 |
| Lysergic acid diethylamide (LSD) | – | – | 3 (1.2%) | 2 (0.6%) | 3 (2.2%) | 14 (8.4%) | 22 | 1.8 |
| Methamphetamine | 4 (2.9% | 2 (0.8%) | 2 (0.8%) | 6 (1.9%) | – | 8 (4.8%) | 22 | 1.8 |
| Ketamine | – | 1 (0.4%) | 2 (0.8%) | 3 (0.9%) | 2 (1.5%) | 8 (4.8%) | 16 | 1.3 |
| Norketamine | – | 1 (0.4%) | – | 3 (0.9%) | 1 (0.7%) | 3 (1.8%) | 8 | 0.6 |
| Alprazolam | 1 (0.7%) | 1 (0.4%) | 2 (0.8%) | – | 3 (2.2%) | – | 7 | 0.6 |
| Oxycodone | 2 (1.4%) | 1 (0.4%) | 2 (0.8%) | – | – | 1 (0.6%) | 6 | 0.5 |
| Morphine | 1 (0.7%) | 1 (0.4%) | 2 (0.8%) | – | – | – | 4 | 0.3 |
| Lorazepam | 2 (1.4%) | – | – | – | – | – | 2 | 0.2 |
| Hydrocodone | – | 1 (0.4%) | – | – | – | 1 (0.6%) | 2 | 0.2 |
| 6-Monoacetylmorphine | 1 (0.7%) | – | 2 (0.8%) | – | – | – | 3 | 0.2 |
| Codeine | – | – | 2 (0.8%) | – | – | – | 2 | 0.2 |
| Buprenorphine | – | – | 1 (0.4%) | – | – | 1 (0.6%) | 2 | 0.2 |
| Naloxone | – | – | 1 (0.4%) | – | – | 1 (0.6%) | 2 | 0.2 |
| Dextromethorphan | – | 1 (0.4%) | – | 1 (0.3%) | – | – | 2 | 0.2 |
| Methylphenidate | – | – | – | 2 (0.6%) | – | 1 (0.6%) | 3 | 0.2 |
| Psilocin | – | – | – | – | 1 (0.7%) | – | 1 | 0.1 |
| Etizolam | – | – | – | 1 (0.3%) | – | – | 1 | 0.1 |
| Clonazepam | 1 (0.7%) | – | – | – | – | – | 1 | 0.1 |
| Dihydrocodeine | – | – | – | – | – | 1 (0.6%) | 1 | 0.1 |
| Fentanyl | – | – | 1 (0.4%) | – | – | – | 1 | 0.1 |
| Diacetylmorphine | – | – | 1 (0.4%) | – | – | – | 1 | 0.1 |
| Tramadol | – | – | – | – | 1 (0.7%) | – | 1 | 0.1 |
| Desmethyltramadol | – | – | – | – | 1 (0.7%) | – | 1 | 0.1 |
| Ortho/meta-Chlorophenylpiperazine (o/m-CPP) | – | – | – | 1 (0.3%) | – | – | 1 | 0.1 |
| Mitragynine | – | – | – | 1 (0.3%) | – | – | 1 | 0.1 |
| None detected | 56 (41%) | 122 (49%) | 114 (46%) | 165 (53%) | 58 (44%) | 34 (20%) | 549 | 44.5 |
| Substance detected | Miami | Tampa | Atlanta | Total (n = 1,233) | % Positivity | |||
|---|---|---|---|---|---|---|---|---|
| 2014 (n = 136) | 2015 (n = 248) | 2016 (n = 244) | 2017 (n = 308) | 2017 (n = 131) | 2017 (n = 166) | |||
| Novel stimulants | ||||||||
| MDMA | 9 (6.6%) | 19 (7.6%) | 43 (17%) | 76 (24%) | 24 (18%) | 79 (47%) | 250 | 20.3 |
| MDA | 6 (4.4%) | 11 (4.4%) | 36 (14%) | 70 (22%) | 26 (19%) | 71 (42%) | 220 | 17.8 |
| Ethylone | 15 (11%) | 41 (16%) | 18 (7.3%) | 3 (0.9%) | 2 (1.5%) | 2 (1.2%) | 81 | 6.6 |
| Methylone | 24 (17%) | 1 (0.4%) | 3 (1.2%) | 4 (1.2%) | 2 (1.5%) | 2 (1.2%) | 36 | 2.9 |
| Dibutylone | – | – | 12 (4.9%) | 11 (3.5%) | 1 (0.7%) | 3 (1.8%) | 27 | 2.2 |
| Butylone | 4 (2.9%) | – | 12 (4.9%) | 6 (1.9%) | – | 3 (1.8%) | 25 | 2 |
| N-ethyl pentylone | – | – | – | 3 (0.9%) | 11 (8.3%) | 8 (4.8%) | 22 | 1.8 |
| Dimethylone | 5 (3.6) | 1 (0.4%) | 3 (1.2%) | 1 (0.3%) | – | 1 (0.6%) | 11 | 0.9 |
| Alpha-PVP | 11 (8.0%) | – | – | – | – | – | 11 | 0.9 |
| Pentylone | – | – | 1 (0.4%) | 1 (0.3%) | – | – | 2 | 0.2 |
| Eutylone | – | – | – | – | 2 (1.5%) | 1 (0.6%) | 3 | 0.2 |
| 4-Fluoroamphetamine (4-FA) | 2 (1.4%) | – | 1 (0.4%) | – | – | – | 3 | 0.2 |
| Methyldiethanolamine (MDEA) | – | – | – | – | – | 2 (1.2%) | 2 | 0.2 |
| 2,5-Dimethoxy-4-bromophenethylamine | – | – | – | 2 (0.6%) | – | – | 2 | 0.2 |
| (2C-B) | ||||||||
| 2,5-Dimethoxy-4-bromoamphetamine (DOB) | – | – | – | 2 (0.6%) | – | – | 2 | 0.2 |
| 3-Trifluoromethylphenylpiperazine (TFMPP) | – | – | – | 1 (0.3%) | – | – | 1 | 0.1 |
| Benzylpiperazine (BZP) | – | – | – | 1 (0.3%) | – | – | 1 | 0.1 |
| Common drugs of abuse | ||||||||
| Tetrahydrocannabinol (THC) | 56 (41%) | 90 (36%) | 79 (32%) | 93 (30%) | 55 (41%) | 105 (63%) | 478 | 38.8 |
| Cocaine | 17 (12%) | 22 (8.8%) | 20 (8.1%) | 24 (7.7%) | 11 (8.3%) | 53 (31%) | 147 | 11.9 |
| Benzoylecgonine | 17 (12%) | 24 (9.6%) | 18 (7.3%) | 20 (6.4%) | 7 (5.3%) | 43 (25%) | 129 | 10.5 |
| Amphetamine | 3 (2.2%) | 4 (1.6%) | 16 (6.5%) | 17 (5.5%) | 5 (3.8%) | 16 (9.6%) | 61 | 4.9 |
| Cocaethylene | 6 (4.4%) | 6 (2.4%) | 1 (0.4%) | 5 (1.6%) | 2 (1.5%) | 19 (11%) | 39 | 3.2 |
| Lysergic acid diethylamide (LSD) | – | – | 3 (1.2%) | 2 (0.6%) | 3 (2.2%) | 14 (8.4%) | 22 | 1.8 |
| Methamphetamine | 4 (2.9% | 2 (0.8%) | 2 (0.8%) | 6 (1.9%) | – | 8 (4.8%) | 22 | 1.8 |
| Ketamine | – | 1 (0.4%) | 2 (0.8%) | 3 (0.9%) | 2 (1.5%) | 8 (4.8%) | 16 | 1.3 |
| Norketamine | – | 1 (0.4%) | – | 3 (0.9%) | 1 (0.7%) | 3 (1.8%) | 8 | 0.6 |
| Alprazolam | 1 (0.7%) | 1 (0.4%) | 2 (0.8%) | – | 3 (2.2%) | – | 7 | 0.6 |
| Oxycodone | 2 (1.4%) | 1 (0.4%) | 2 (0.8%) | – | – | 1 (0.6%) | 6 | 0.5 |
| Morphine | 1 (0.7%) | 1 (0.4%) | 2 (0.8%) | – | – | – | 4 | 0.3 |
| Lorazepam | 2 (1.4%) | – | – | – | – | – | 2 | 0.2 |
| Hydrocodone | – | 1 (0.4%) | – | – | – | 1 (0.6%) | 2 | 0.2 |
| 6-Monoacetylmorphine | 1 (0.7%) | – | 2 (0.8%) | – | – | – | 3 | 0.2 |
| Codeine | – | – | 2 (0.8%) | – | – | – | 2 | 0.2 |
| Buprenorphine | – | – | 1 (0.4%) | – | – | 1 (0.6%) | 2 | 0.2 |
| Naloxone | – | – | 1 (0.4%) | – | – | 1 (0.6%) | 2 | 0.2 |
| Dextromethorphan | – | 1 (0.4%) | – | 1 (0.3%) | – | – | 2 | 0.2 |
| Methylphenidate | – | – | – | 2 (0.6%) | – | 1 (0.6%) | 3 | 0.2 |
| Psilocin | – | – | – | – | 1 (0.7%) | – | 1 | 0.1 |
| Etizolam | – | – | – | 1 (0.3%) | – | – | 1 | 0.1 |
| Clonazepam | 1 (0.7%) | – | – | – | – | – | 1 | 0.1 |
| Dihydrocodeine | – | – | – | – | – | 1 (0.6%) | 1 | 0.1 |
| Fentanyl | – | – | 1 (0.4%) | – | – | – | 1 | 0.1 |
| Diacetylmorphine | – | – | 1 (0.4%) | – | – | – | 1 | 0.1 |
| Tramadol | – | – | – | – | 1 (0.7%) | – | 1 | 0.1 |
| Desmethyltramadol | – | – | – | – | 1 (0.7%) | – | 1 | 0.1 |
| Ortho/meta-Chlorophenylpiperazine (o/m-CPP) | – | – | – | 1 (0.3%) | – | – | 1 | 0.1 |
| Mitragynine | – | – | – | 1 (0.3%) | – | – | 1 | 0.1 |
| None detected | 56 (41%) | 122 (49%) | 114 (46%) | 165 (53%) | 58 (44%) | 34 (20%) | 549 | 44.5 |
Qualitative Oral Fluid Results by Festival and Year
| Substance detected | Miami | Tampa | Atlanta | Total (n = 1,233) | % Positivity | |||
|---|---|---|---|---|---|---|---|---|
| 2014 (n = 136) | 2015 (n = 248) | 2016 (n = 244) | 2017 (n = 308) | 2017 (n = 131) | 2017 (n = 166) | |||
| Novel stimulants | ||||||||
| MDMA | 9 (6.6%) | 19 (7.6%) | 43 (17%) | 76 (24%) | 24 (18%) | 79 (47%) | 250 | 20.3 |
| MDA | 6 (4.4%) | 11 (4.4%) | 36 (14%) | 70 (22%) | 26 (19%) | 71 (42%) | 220 | 17.8 |
| Ethylone | 15 (11%) | 41 (16%) | 18 (7.3%) | 3 (0.9%) | 2 (1.5%) | 2 (1.2%) | 81 | 6.6 |
| Methylone | 24 (17%) | 1 (0.4%) | 3 (1.2%) | 4 (1.2%) | 2 (1.5%) | 2 (1.2%) | 36 | 2.9 |
| Dibutylone | – | – | 12 (4.9%) | 11 (3.5%) | 1 (0.7%) | 3 (1.8%) | 27 | 2.2 |
| Butylone | 4 (2.9%) | – | 12 (4.9%) | 6 (1.9%) | – | 3 (1.8%) | 25 | 2 |
| N-ethyl pentylone | – | – | – | 3 (0.9%) | 11 (8.3%) | 8 (4.8%) | 22 | 1.8 |
| Dimethylone | 5 (3.6) | 1 (0.4%) | 3 (1.2%) | 1 (0.3%) | – | 1 (0.6%) | 11 | 0.9 |
| Alpha-PVP | 11 (8.0%) | – | – | – | – | – | 11 | 0.9 |
| Pentylone | – | – | 1 (0.4%) | 1 (0.3%) | – | – | 2 | 0.2 |
| Eutylone | – | – | – | – | 2 (1.5%) | 1 (0.6%) | 3 | 0.2 |
| 4-Fluoroamphetamine (4-FA) | 2 (1.4%) | – | 1 (0.4%) | – | – | – | 3 | 0.2 |
| Methyldiethanolamine (MDEA) | – | – | – | – | – | 2 (1.2%) | 2 | 0.2 |
| 2,5-Dimethoxy-4-bromophenethylamine | – | – | – | 2 (0.6%) | – | – | 2 | 0.2 |
| (2C-B) | ||||||||
| 2,5-Dimethoxy-4-bromoamphetamine (DOB) | – | – | – | 2 (0.6%) | – | – | 2 | 0.2 |
| 3-Trifluoromethylphenylpiperazine (TFMPP) | – | – | – | 1 (0.3%) | – | – | 1 | 0.1 |
| Benzylpiperazine (BZP) | – | – | – | 1 (0.3%) | – | – | 1 | 0.1 |
| Common drugs of abuse | ||||||||
| Tetrahydrocannabinol (THC) | 56 (41%) | 90 (36%) | 79 (32%) | 93 (30%) | 55 (41%) | 105 (63%) | 478 | 38.8 |
| Cocaine | 17 (12%) | 22 (8.8%) | 20 (8.1%) | 24 (7.7%) | 11 (8.3%) | 53 (31%) | 147 | 11.9 |
| Benzoylecgonine | 17 (12%) | 24 (9.6%) | 18 (7.3%) | 20 (6.4%) | 7 (5.3%) | 43 (25%) | 129 | 10.5 |
| Amphetamine | 3 (2.2%) | 4 (1.6%) | 16 (6.5%) | 17 (5.5%) | 5 (3.8%) | 16 (9.6%) | 61 | 4.9 |
| Cocaethylene | 6 (4.4%) | 6 (2.4%) | 1 (0.4%) | 5 (1.6%) | 2 (1.5%) | 19 (11%) | 39 | 3.2 |
| Lysergic acid diethylamide (LSD) | – | – | 3 (1.2%) | 2 (0.6%) | 3 (2.2%) | 14 (8.4%) | 22 | 1.8 |
| Methamphetamine | 4 (2.9% | 2 (0.8%) | 2 (0.8%) | 6 (1.9%) | – | 8 (4.8%) | 22 | 1.8 |
| Ketamine | – | 1 (0.4%) | 2 (0.8%) | 3 (0.9%) | 2 (1.5%) | 8 (4.8%) | 16 | 1.3 |
| Norketamine | – | 1 (0.4%) | – | 3 (0.9%) | 1 (0.7%) | 3 (1.8%) | 8 | 0.6 |
| Alprazolam | 1 (0.7%) | 1 (0.4%) | 2 (0.8%) | – | 3 (2.2%) | – | 7 | 0.6 |
| Oxycodone | 2 (1.4%) | 1 (0.4%) | 2 (0.8%) | – | – | 1 (0.6%) | 6 | 0.5 |
| Morphine | 1 (0.7%) | 1 (0.4%) | 2 (0.8%) | – | – | – | 4 | 0.3 |
| Lorazepam | 2 (1.4%) | – | – | – | – | – | 2 | 0.2 |
| Hydrocodone | – | 1 (0.4%) | – | – | – | 1 (0.6%) | 2 | 0.2 |
| 6-Monoacetylmorphine | 1 (0.7%) | – | 2 (0.8%) | – | – | – | 3 | 0.2 |
| Codeine | – | – | 2 (0.8%) | – | – | – | 2 | 0.2 |
| Buprenorphine | – | – | 1 (0.4%) | – | – | 1 (0.6%) | 2 | 0.2 |
| Naloxone | – | – | 1 (0.4%) | – | – | 1 (0.6%) | 2 | 0.2 |
| Dextromethorphan | – | 1 (0.4%) | – | 1 (0.3%) | – | – | 2 | 0.2 |
| Methylphenidate | – | – | – | 2 (0.6%) | – | 1 (0.6%) | 3 | 0.2 |
| Psilocin | – | – | – | – | 1 (0.7%) | – | 1 | 0.1 |
| Etizolam | – | – | – | 1 (0.3%) | – | – | 1 | 0.1 |
| Clonazepam | 1 (0.7%) | – | – | – | – | – | 1 | 0.1 |
| Dihydrocodeine | – | – | – | – | – | 1 (0.6%) | 1 | 0.1 |
| Fentanyl | – | – | 1 (0.4%) | – | – | – | 1 | 0.1 |
| Diacetylmorphine | – | – | 1 (0.4%) | – | – | – | 1 | 0.1 |
| Tramadol | – | – | – | – | 1 (0.7%) | – | 1 | 0.1 |
| Desmethyltramadol | – | – | – | – | 1 (0.7%) | – | 1 | 0.1 |
| Ortho/meta-Chlorophenylpiperazine (o/m-CPP) | – | – | – | 1 (0.3%) | – | – | 1 | 0.1 |
| Mitragynine | – | – | – | 1 (0.3%) | – | – | 1 | 0.1 |
| None detected | 56 (41%) | 122 (49%) | 114 (46%) | 165 (53%) | 58 (44%) | 34 (20%) | 549 | 44.5 |
| Substance detected | Miami | Tampa | Atlanta | Total (n = 1,233) | % Positivity | |||
|---|---|---|---|---|---|---|---|---|
| 2014 (n = 136) | 2015 (n = 248) | 2016 (n = 244) | 2017 (n = 308) | 2017 (n = 131) | 2017 (n = 166) | |||
| Novel stimulants | ||||||||
| MDMA | 9 (6.6%) | 19 (7.6%) | 43 (17%) | 76 (24%) | 24 (18%) | 79 (47%) | 250 | 20.3 |
| MDA | 6 (4.4%) | 11 (4.4%) | 36 (14%) | 70 (22%) | 26 (19%) | 71 (42%) | 220 | 17.8 |
| Ethylone | 15 (11%) | 41 (16%) | 18 (7.3%) | 3 (0.9%) | 2 (1.5%) | 2 (1.2%) | 81 | 6.6 |
| Methylone | 24 (17%) | 1 (0.4%) | 3 (1.2%) | 4 (1.2%) | 2 (1.5%) | 2 (1.2%) | 36 | 2.9 |
| Dibutylone | – | – | 12 (4.9%) | 11 (3.5%) | 1 (0.7%) | 3 (1.8%) | 27 | 2.2 |
| Butylone | 4 (2.9%) | – | 12 (4.9%) | 6 (1.9%) | – | 3 (1.8%) | 25 | 2 |
| N-ethyl pentylone | – | – | – | 3 (0.9%) | 11 (8.3%) | 8 (4.8%) | 22 | 1.8 |
| Dimethylone | 5 (3.6) | 1 (0.4%) | 3 (1.2%) | 1 (0.3%) | – | 1 (0.6%) | 11 | 0.9 |
| Alpha-PVP | 11 (8.0%) | – | – | – | – | – | 11 | 0.9 |
| Pentylone | – | – | 1 (0.4%) | 1 (0.3%) | – | – | 2 | 0.2 |
| Eutylone | – | – | – | – | 2 (1.5%) | 1 (0.6%) | 3 | 0.2 |
| 4-Fluoroamphetamine (4-FA) | 2 (1.4%) | – | 1 (0.4%) | – | – | – | 3 | 0.2 |
| Methyldiethanolamine (MDEA) | – | – | – | – | – | 2 (1.2%) | 2 | 0.2 |
| 2,5-Dimethoxy-4-bromophenethylamine | – | – | – | 2 (0.6%) | – | – | 2 | 0.2 |
| (2C-B) | ||||||||
| 2,5-Dimethoxy-4-bromoamphetamine (DOB) | – | – | – | 2 (0.6%) | – | – | 2 | 0.2 |
| 3-Trifluoromethylphenylpiperazine (TFMPP) | – | – | – | 1 (0.3%) | – | – | 1 | 0.1 |
| Benzylpiperazine (BZP) | – | – | – | 1 (0.3%) | – | – | 1 | 0.1 |
| Common drugs of abuse | ||||||||
| Tetrahydrocannabinol (THC) | 56 (41%) | 90 (36%) | 79 (32%) | 93 (30%) | 55 (41%) | 105 (63%) | 478 | 38.8 |
| Cocaine | 17 (12%) | 22 (8.8%) | 20 (8.1%) | 24 (7.7%) | 11 (8.3%) | 53 (31%) | 147 | 11.9 |
| Benzoylecgonine | 17 (12%) | 24 (9.6%) | 18 (7.3%) | 20 (6.4%) | 7 (5.3%) | 43 (25%) | 129 | 10.5 |
| Amphetamine | 3 (2.2%) | 4 (1.6%) | 16 (6.5%) | 17 (5.5%) | 5 (3.8%) | 16 (9.6%) | 61 | 4.9 |
| Cocaethylene | 6 (4.4%) | 6 (2.4%) | 1 (0.4%) | 5 (1.6%) | 2 (1.5%) | 19 (11%) | 39 | 3.2 |
| Lysergic acid diethylamide (LSD) | – | – | 3 (1.2%) | 2 (0.6%) | 3 (2.2%) | 14 (8.4%) | 22 | 1.8 |
| Methamphetamine | 4 (2.9% | 2 (0.8%) | 2 (0.8%) | 6 (1.9%) | – | 8 (4.8%) | 22 | 1.8 |
| Ketamine | – | 1 (0.4%) | 2 (0.8%) | 3 (0.9%) | 2 (1.5%) | 8 (4.8%) | 16 | 1.3 |
| Norketamine | – | 1 (0.4%) | – | 3 (0.9%) | 1 (0.7%) | 3 (1.8%) | 8 | 0.6 |
| Alprazolam | 1 (0.7%) | 1 (0.4%) | 2 (0.8%) | – | 3 (2.2%) | – | 7 | 0.6 |
| Oxycodone | 2 (1.4%) | 1 (0.4%) | 2 (0.8%) | – | – | 1 (0.6%) | 6 | 0.5 |
| Morphine | 1 (0.7%) | 1 (0.4%) | 2 (0.8%) | – | – | – | 4 | 0.3 |
| Lorazepam | 2 (1.4%) | – | – | – | – | – | 2 | 0.2 |
| Hydrocodone | – | 1 (0.4%) | – | – | – | 1 (0.6%) | 2 | 0.2 |
| 6-Monoacetylmorphine | 1 (0.7%) | – | 2 (0.8%) | – | – | – | 3 | 0.2 |
| Codeine | – | – | 2 (0.8%) | – | – | – | 2 | 0.2 |
| Buprenorphine | – | – | 1 (0.4%) | – | – | 1 (0.6%) | 2 | 0.2 |
| Naloxone | – | – | 1 (0.4%) | – | – | 1 (0.6%) | 2 | 0.2 |
| Dextromethorphan | – | 1 (0.4%) | – | 1 (0.3%) | – | – | 2 | 0.2 |
| Methylphenidate | – | – | – | 2 (0.6%) | – | 1 (0.6%) | 3 | 0.2 |
| Psilocin | – | – | – | – | 1 (0.7%) | – | 1 | 0.1 |
| Etizolam | – | – | – | 1 (0.3%) | – | – | 1 | 0.1 |
| Clonazepam | 1 (0.7%) | – | – | – | – | – | 1 | 0.1 |
| Dihydrocodeine | – | – | – | – | – | 1 (0.6%) | 1 | 0.1 |
| Fentanyl | – | – | 1 (0.4%) | – | – | – | 1 | 0.1 |
| Diacetylmorphine | – | – | 1 (0.4%) | – | – | – | 1 | 0.1 |
| Tramadol | – | – | – | – | 1 (0.7%) | – | 1 | 0.1 |
| Desmethyltramadol | – | – | – | – | 1 (0.7%) | – | 1 | 0.1 |
| Ortho/meta-Chlorophenylpiperazine (o/m-CPP) | – | – | – | 1 (0.3%) | – | – | 1 | 0.1 |
| Mitragynine | – | – | – | 1 (0.3%) | – | – | 1 | 0.1 |
| None detected | 56 (41%) | 122 (49%) | 114 (46%) | 165 (53%) | 58 (44%) | 34 (20%) | 549 | 44.5 |
Select self-reported recreational drug use comparison among the four sample collection sites (2016–2017).
Oral fluid confirmatory results by festival and year are shown in Table I for all seven events from 2014 to 2017. No recreational or therapeutic substances were present in 549 (44.5%) of the oral fluid samples. Delta-9-tetrahydrocannabinol (THC) had the highest positivity across all festivals (38%), followed by MDMA (20%) and MDA (17%). With respect to novel stimulants, ethylone had the greatest positivity across all years (6.5%), despite a sharp decline in the number of confirmed cases after 2016. Methylone was the second most frequently encountered novel stimulant (2.9%), with the majority of identifications occurring in 2014.
Trend data
Repeated sample collection at one festival location (Miami) allowed for the investigation of novel stimulant use trends with respect to percent positivity by year (Figure 2). In 2014, the first year of the study, the highest positivity rate was for methylone (32%), followed by ethylone (20%). Alpha-PVP was detected in 2014 but subsequently not detected any year thereafter. Ethylone spiked in positivity (56%) in 2015 but rapidly declined in positivity (14%) in 2016. The rapid decline in ethylone in 2016 and 2017 was replaced by increasing MDMA and MDA positivity. The novel stimulants, dibutylone and butylone, were detected less frequently but had their highest positivity in 2016, both at 9%. Dibutylone was detected for the first time in 2016 and N-ethyl pentylone was detected for the first time in 2017. By 2019, N-ethyl pentylone was the second most commonly identified cathinone in seized drug evidence (29). For the first time in 2016, MDMA and MDA positivity was greater than any of the NPS stimulants detected. The overall positivity for novel stimulants was the lowest in 2017 with no substance having greater than 6% positivity. The data show a steady increase in positivity for MDMA and MDA, rising from 12% and 8% positivity in 2014 to 43% and 40% positivity in 2017, respectively. Temporal trends (i.e., the rise and fall) in Miami for MDMA, MDA, methylone, dimethylone, ethylone, butylone and dibutylone were found to be statistically significant with respect to positivity and year (at least P < 0.02); N-ethyl pentylone was detected too infrequently for statistical analysis.
Novel stimulant percent positivity over 4 years (Miami only).
Novel stimulant positivity rates were compared based on festival location [Miami (March), Tampa (May) and Atlanta (September)] during 2017. It was initially hypothesized that novel stimulant positivity may vary based on the geographic location of the festival due to drug trafficking patterns and regional variability. Figure 3 illustrates novel stimulant and MDMA/MDA positivity based on location for the three events attended in 2017. Novel stimulants detected only at a single festival location were excluded from the data (i.e., 4-fluoroamphetamine, alpha-PVP and pentylone). The data showed no statistically significant differences, with the exception of the high positivity for N-ethyl pentylone (15%) in Tampa, which was also the location with the lowest MDMA positivity. The decrease in positivity for N-ethyl pentylone could reflect regional differences in drug distribution channels but is also consistent with the temporal shift back MDMA, a phenomenon that was observed over this 4-year study. With respect to festival location, the difference in positivity for N-ethyl pentylone was determined to be statistically significant (P < 0.001).
Novel stimulant percent positivity across three locations (2017 only).
Self-reported drug use, as well the oral fluid analytical data (Figure 1, Table I), demonstrate increased use of traditional hallucinogenic substances (i.e., lysergic acid diethylamide) and dissociative anesthetics (i.e., ketamine). This increase was more pronounced in Atlanta, which was the only festival that provided onsite camping. No other differences in positivity between the three locations could be readily attributed to geographic location or festival logistics. A limitation of the geographical comparison is that all festival locations were located in the southeastern part of the country, and additional regional differences in other parts of the United States could be significant.
No meaningful difference in terms of positivity for MDMA, novel stimulants or combination of the two was observed between males and females (P > 0.05). MDMA positivity was 60% for males compared to 59% for females. A slightly larger percent of females tested positive for a novel stimulant than males (28% compared to 22%, respectively). Conversely, the positivity for males who confirmed positive for both a novel stimulant and MDMA was slightly larger than females (18% compared to 13%, respectively). With respect to age, comparisons were evaluated based on 4 age groups: 18–20, 21–23, 24–26 and >27 years old. These age ranges were arbitrary set in accordance with festival attendee demographics. No significant differences were seen related to positivity among the various age groups (P > 0.05). Comparable positivity for MDMA was seen in all age groups (54–65%), with the highest percent positive among those >27 years old. The highest percent positivity for novel stimulants was found in the youngest age group (18–20, 33%) and lowest in the oldest age group (>27, 13%).
Novel stimulant positivity rates were compared across the days of the festival, and the results are shown in Figure 4. The data provided show correlation and significance (P < 0.05) between novel stimulant positivity and day, with the exceptions of Miami 2015 and Atlanta 2017. In almost all cases, the highest percentage positivity was on the last day of the festival (Sunday in each case). This reflects increasing rates of drug use across the festival with more subjects using stimulants on each successive day and was consistent over all festival events.
Novel stimulant percent positivity across collection days.
Positivity rates for the drugs detected in this study population are significantly higher than those detected in other studies of EDM festivals in European counties, which could reflect international differences in drug use, or could be attributed to the more extensive scope of testing used for this study (20, 30).
The results demonstrate widespread use of psychostimulant drugs (e.g., MDMA, MDA, novel stimulants, etc.) along with marijuana (THC) within the EDM community. The majority of the oral fluid samples collected contained more than one drug or NPS, suggesting high rates of polydrug use, which may increase the potential for an adverse event. Based on the data compiled over the course of 4 years, it appears the prevalence life cycle of a novel stimulant frequently runs the course of a year or less, and that new drugs appear and disappear over the course of 2 years or less. Understanding the duration of this life cycle helps laboratories plan for allocation of resources, including the acquisition of new drug standards, and updating and validating analytical methods on a regular basis, as well as creating an incentive to conduct studies on drug disposition and metabolic fate for the identification of novel drug use biomarkers.
Conclusion
The community of EDM festival attendees represents an important and unique sentinel population as they have repeatedly been demonstrated to be an at-risk population with high incidence of NPS use. We demonstrated the utility of drug testing in this population to monitor and track changes in the NPS market using the voluntary collection of biological samples. We have previously demonstrated that self-reported drug use is an inadequate method of tracking drug trends in these populations because of the imprecise use of drug names (e.g., Ecstasy vs. Molly vs. MDMA, etc.), the users’ lack of knowledge about what substances they are purchasing and consuming, and information related to the variation of drug preparations from the users’ perspective (e.g., pills, powders, capsules, etc.).
High rates of recreational drug use, particularly related to novel stimulants, were found during this study, which has important public health and harm-reduction consequences. Using this opportunistic sample collection model in a known at-risk population provided very useful information about the appearance and prevalence of novel stimulants and the rate of turnover in drug use. Additional consideration should be given to continued vigilance within this population to provide a longitudinal record of the changing drug market and use patterns.
Acknowledgements
The authors of this manuscript would like to acknowledge the following individuals and organizations for their contributions to this project: Jill Yeakel (Harrisburg University of Science and Technology), Tiffany Chan (CFSRE) Donna Papsun (NMS Labs), Francis Diamond (NMS Labs), the Armed Forces Medical Examiner’s Office: Division of Forensic Toxicology, Waters Corporation, SCIEX, staff at the Fredric Rieders Family Foundation and graduate students from Florida International University, Arcadia University and the University of South Florida.
Funding
Funding for this study was awarded by the National Institute of Justice, Office of Justice Programs, U.S. Department of Justice (Award Numbers 2013-DN-BX-K018 and 2015-IJ-CX-K012). The opinions, findings, and conclusions or recommendations expressed in this publication are those of the authors and do not necessarily reflect those of the Department of Justice.
