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Questionnaires were completed by 80 women (38.8%) and 126 men (61.2%),
with 4 participants not indicating their sex. Statistical analyses
were based on 11 of the drugs surveyed; we omitted heroin because
only 8 respondents had used it. Participant ages ranged from 16
to 32 years (mean 21.4 years, SD 3.18). In all analyses, we considered
sex and event attended; however, no significant interaction effects
were found. Drug histories are summarized in Table
Progression of Drug Use
Average age of first use for alcohol was 14.05 years (SD 2.18,
n = 188), for cannabis 15.13 years (SD 2.59, n = 192,)
and for nicotine 14.21 years (SD 2.34, n = 63), which identified
these drugs as potentially the first 3 steps in drug experimentation
(see Table 1).
To accommodate the data that fit a block design with missing values,
we used a univariate analysis of variance to calculate significant
differences between the means of age of first use. We treated subjects
independently to account for variability in the number of different
drugs used by each participant. We found an overall significant
difference between mean age of first use and the particular drug
used (F = 60.125, P < 0.001). We than applied Bonferroni
and Tukey honestly significant difference (HSD) contrasts to identify
specific significant mean differences. We found significant mean
differences with the following subsets, defined using harmonic mean
sample sizes and an alpha level of 0.05: 1) alcohol, nicotine, and
cannabis; 2) cannabis, LSD, and psilocybin; 3) amphetamine, cocaine,
MDMA, GHB, ephedrine, and ketamine. Based on overall significance,
a rank order for progression can be inferred, which indicates the
following linear trend in progression of first use: 1) alcohol,
2) nicotine, 3) cannabis, 4) LSD, 5) psilocybin, 6) amphetamine,
7) cocaine, 8) MDMA, 9) GHB, 10) ephedrine, and 11) ketamine.
To test for linear and quadratic trends, we also applied a repeated-measures
analysis of variance (ANOVA) to the data on drugs used by more than
25% of the sample. While this analysis yields results only for those
subjects who used all the listed substances (n = 44), we
found a similarly significant linear trend for the experimentation
order: 1) alcohol, 2) cannabis, 3) LSD, 4) psilocybin, 5) amphetamine,
6) cocaine, 7) MDMA (F = 304.8, P < 0.001).
To further delineate these trends, we employed a correlational analysis
using the nonparametric Spearmans rho to account for monotonic
relations between variables. We found significant positive correlations
at the 0.01 level between the age of first use of alcohol and cannabis,
cocaine, amphetamines, ephedrine, GHB, psilocybin, MDMA, nicotine,
and LSD. As well, we found significant positive correlations between
age of first use of cannabis and age of first use of all drugs except
ketamine. After we applied a Bonferroni correction, significant
relations were maintained for all except the alcohol-to-amphetamine,
-ephedrine and -GHB correlations and the cannabis-to-GHB and -ephedrine
Total Number of Lifetime Uses
Table 1 indicates
the percentage of the subjects who had used each drug.
Although mean computations suggest the highest use for cannabis
(mean 1088.4) and alcohol (mean 361.2), it is important to note
that we did not collect lifetime estimates of tobacco consumption.
When median scores are calculated to account for outliers in the
data, alcohol (median 100) and cannabis (median 150) remain the
most frequently used substances.
We conducted bivariate correlations using the nonparametric Spearmans
rho to determine relations among the number of lifetime uses for
different drug types. After we applied a Bonferroni statistical
correction, we found significant relations (P < 0.01)
for the following groupings: alcohol lifetime use correlated with
cannabis lifetime use; amphetamine lifetime use with MDMA lifetime
use; cannabis lifetime use with psilocybin lifetime use; and LSD
lifetime use with psilocybin lifetime use.
Number of Uses in Preceding 30 Days
Table 1 reports
what percentage of subjects who had reported at least 1 use of a
particular drug had used that drug in the preceding 30 days, as
well as the mean number of uses for each drug during this time period.
Listed in descending order according to percentage of recent recurrent
users, the drugs rank as follows: alcohol, cannabis, amphetamine,
MDMA, ketamine, ephedrine, GHB, psilocybin, and LSD.
Median scores were also considered, to account for extreme users.
With these scores, cannabis is notable as the most frequently consumed
drug during the preceding 30 days (median 15), followed by alcohol
Our study sought to clarify the drug-consumption patterns of Montreal
youth who attend raves. Research on this population suggests that
rave attendees represent a significant proportion of illicit drug
users. Our findings confirm that members of this group take greater
quantities and experiment with a greater variety of substances than
do their peers who do not attend raves (2127).
To determine whether there was a general pattern of stepwise drug
experimentation, we applied 2 different statistical analyses to
the data. We identified the following progressive pattern: 1) alcohol,
2) nicotine, 3) cannabis, 4) LSD, 5) psilocybin, 6) amphetamine,
7) cocaine, 8) MDMA, 9) GHB, 10) ephedrine, and 11) ketamine. It
is notable that the substances used by more than 10% but less than
25% of this population appeared as the last 3 in the sequence of
experimentation. A similar study in Norway determined the following
best-fit for the progression pattern: 1) alcohol, 2) cigarettes,
3) cannabis, 4) amphetamines 5) ecstasy, and 6) heroin (28). Despite
the fact that this was a normal population survey, and questions
on hallucinogen use were not incorporated, the overall similarities
with our findings are striking.
The sample used alcohol and cannabis substantially. Overall, 89.5%
of the subjects reported prior intoxication with alcohol, 69.7%
of these in the past 30 days. Similarly, 91.4% of those surveyed
reported having used cannabis, 67.7% of these in the previous 30
days. Interestingly, the early use of either substance was associated
with an early use of cocaine, psilocybin, LSD, and MDMA, suggesting
their potential as possible gateway drugs.
While MDMA was the third most commonly used drug in this sample,
the age of first use appeared later (that is, 8th) in the drug experimentation
sequence than had been anticipated. As well, the lifetime uses and
uses in the preceding 30 days were also lower than had been expected.
MDMA, however, is still among the most prevalent drugs consumed
at raves. Indeed, the high prevalence of MDMA use found in this
study is consistent with research findings in rave samples surveyed
in Australia (76%) (29). Since rave events typically occur on weekends,
however, occasion to take MDMA may be regarded as less frequent
than occasion for consuming substances such as alcohol or cannabis.
The prevalence of amphetamine use, including both recent and overall
consumption, was comparable to that of MDMA. It was the third most
popular drug for use in the preceding 30 days: 47.6% of those surveyed
reported amphetamine use, slightly exceeding the 40% reporting MDMA
use during this period. Further, while 73.3% of the overall sample
reported ever using amphetamine, a comparable 75.2% reported MDMA
lifetime use. These findings suggest that, in addition to MDMA,
amphetamine should be examined as a primary drug used by rave populations.
The use of the hallucinogenic drugs LSD and psilocybin was also
reported by a substantial portion of the sample (56.2% and 70%,
respectively). Although participants reported initially experimenting
with these drugs at a relatively early age, most users did not report
consuming them in the preceding 30 days (22% reported pilocybin
use, and 12.7% reported LSD use). These findings suggest that while
the use of hallucinogenic drugs often precedes the consumption of
drugs like MDMA and amphetamine, these drugs are seldom in active
use by individuals attending raves. It is interesting to note that
while the level of LSD use was positively associated with the level
of psilocybin consumption, using these drugs did not reliably predict
the subsequent level of MDMA or amphetamine use, suggesting a limited
role for hallucinogens as gateway drugs in a rave population.
Several drugs, including ketamine, GHB, and ephedrine, did not
surface as popular substances within this sample, each having been
used by fewer than 25% of those surveyed. Nevertheless, approximately
one-third of those who had experimented with these drugs had done
so recently. It seems plausible that the apparent infrequent use
of these 3 drugs is related to their late introduction into the
typical sequence of drug experimentation.
Although this study identifies the drug-consumption patterns and
histories of individuals who attend Montreal-area raves, it is appropriate
to address some of the investigations possible limitations.
Because this study relied on retrospective recall, the accuracy
of such reports might be questioned. However, it should be noted
that the research question precludes prospective data collection
and that the methods used are in accord with abundant published
reports that use a similar methodology (for example, 2729).
In addition there are several indications that substance use self-report
data can be both reliable and valid (for example, 30,31).
A second issue involves the degree to which this moderate sample
can accurately reflect the drug-taking patterns of Montreal rave
attendees in general. Because the participants were self-selected
for this investigation, it is possible that they do not represent
the group as a whole. Although we attempted to minimize this by
administering questionnaires at 3 separate events and found no significant
differences among these subgroups, only a random sample of rave
attendees would ensure the generalizability of these findings. Nevertheless,
the present results are consistent with findings obtained from other
samples of drug users (for example 28,29). As well, since an entire
generation of ages was surveyed (range 16 to 32 years), this study
potentially captured both long-term and relatively new partygoers.
Funding and Support
SP Barrett was supported by a scholarship from the Canadian Institutes
of Health Research. RO Pihl was supported by Canadian Institutes
of Health Research, grant MT-9980.
The authors acknowledge Jean-Sebastian Fallu and the Groupe
de Recherche et dIntervention Psychosociale for their
assistance in data collection.
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