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Recreational nightlife: Risk and protective factors fordrug misuse among young Europeans in recreationalenvironmentsAmador Calafat a; Cesáreo Fernández a; Montse Juan ab; Elisardo Becoña aca IREFREA, Spainb Alicante University, Spainc Santiago de Compostela University, Spain

Online Publication Date: 01 April 2008To cite this Article: Calafat, Amador, Fernández, Cesáreo, Juan, Montse andBecoña, Elisardo (2008) 'Recreational nightlife: Risk and protective factors for drug

misuse among young Europeans in recreational environments', Drugs: education, prevention and policy, 15:2, 189 - 200To link to this article: DOI: 10.1080/09687630701267366URL: http://dx.doi.org/10.1080/09687630701267366

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Drugs: education, prevention and policy,April 2008; 15(2): 189–200

Recreational nightlife: Risk and protectivefactors for drug misuse among youngEuropeans in recreational environments

AMADOR CALAFAT1, CESAREO FERNANDEZ1,MONTSE JUAN1,2, & ELISARDO BECONA1,3

1IREFREA, Rambla, Palma de Mallorca, Spain, 2Alicante University, Spain,

and 3Santiago de Compostela University, Spain

AbstractAim: To assess the predictive relevance of recreational nightlife-related variables for druguse in comparison with other intrapersonal and interpersonal risk and protective factors.Sample: A total of 1777 young people were interviewed in recreational nightlifeenvironments in 10 European cities. The sample was balanced by drug use (users andnon-users), gender and age.Measurements: Participants were interviewed on the basis of a structured questionnairecomprising several risk domain factors (sociodemographics, substance-use history, riskbehaviours and related attitudes, motivations and perceptions relating to substance use,peer and family substance use and opinions, motivation and clubbing habits).Findings: A global multivariate logistic regression analysis correctly classified 92% of theindividuals using drugs. Among the factors studied, the group of variables relating tothe management of recreational activities (opinions, motivation and clubbing habits) werethe best predictors of drug use. But traditional risk factors are also relevant in predictingdrug use among recreational drug users.Conclusions: The results suggests the need to address the management of weekendrecreational habits as an important objective in the prevention of drug use and misuse,including the implication and the meaning given to recreational nightlife.

Introduction

At the end of the 1990s Kunz (1997) made a bibliographical review of the linkbetween alcohol and leisure time and found only 43 references. He believed thatthe number was so low because this association was not a very old one and many

Correspondence: Amador Calafat, IREFREA, Rambla, 15, 2,� 3a 07003 Palma de Mallorca, Spain.Tel: þ34 971 727434. Fax: þ34 971 213306. E-mail: irefrea@irefrea.org

ISSN 0968–7637 print/ISSN 1465–3370 online � 2008 Informa UK Ltd.DOI: 10.1080/09687630701267366

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people were drinking alcohol without any account being taken of the differentsocial occasions (work, home, leisure, etc.). And, indeed, even at the beginning ofthe 1990s, certain studies had not found a very direct relationship betweenalcohol and the manner of employing one’s free time, since drinking was relatedmore to socioeconomic group and gender. In his review, Kuntz looked at the kindof leisure preferred and its relationship with the manner of drinking but heconcluded that there was still little known on the psychosocial factors (such ascoping skills, social networks and stress) that determine the consumption ofalcohol. Kuntz pointed out that there were very few studies that researched themotivations for taking part in recreational activities, and the reasons for drinkingin respect of the kind of leisure chosen.

However, around the middle of the 1980s—somewhat earlier in summer touristareas such as the Balearic Islands—a weekend night-time recreational leisure wasalready coming into being, among the young in certain countries, one that wouldrapidly undergo an enormous expansion and end up by changing theirentertainment habits in a readily visible way (Collin, 1997). This form ofentertainment has been given several names, depending on the country concerned(clubbing, salir de marcha, party machen, andare in giro . . . ) and implies a radicalchange in the way of enjoying oneself. Depending on the city, young Europeansare devoting between 4 and 7 hours every weekend night to leisure pursuits of thiskind (Calafat et al., 1999). There is a well-documented relationship betweenspecific nightlife recreational environments and synthetic substance use, as well asevidence of a high prevalence of recreational substance use (Bellis, Hale, Bennet,Chaves, & Kilfoyle, 2000; Calafat et al., 1999; Forsyth, Barnard, & McKeganey,1997; Tossmann, Bold, & Tensil, 1999), to such an extent that certain kinds ofdrugs are even baptized with a name that emphasizes their relationship with aspecific environment, such as club drugs, dance drugs, recreational drugs, etc.,in addition, one speaks of the ecstasy generation or the ecstasy culture (Fountain& Griffiths, 1997). Referring precisely to this relationship, and in reference to theyoung English, it can be said that ‘by the age of 17, young people’s drug use hasbecome increasingly sophisticated in terms of the range of drugs on offer, drugschosen, others rejected and the social context for such use . . . choosing individualdrugs in certain social contexts for specific anticipated effects’ (Measham, Parker,& Aldridge, 1998).

In effect, the link between the recreational context and the kind of drug used issignificant. For instance, if we look at the subject of musical preferences, we findthat many bars, discos and other entertainment events for the young are identifiedwith a specific type of music—a number of studies have shown how thepreference for less mainstream musical styles is related to greater antisocialconduct and risk behaviours (Fouce, 2003; Mulder, ter Bogt, & Raaijmakers,2006). In this sense, in the USA, heavy metal fans have been linked to the use ofalcohol and drugs, drugs and driving and other antisocial behaviours (Amett,1991; Miranda & Claes, 2004). In a sample of 2700 clubbers from nine differentEuropean cities, 39% preferred house music, 18% heavy metal, 12% pop, etc.Significantly, the house and the heavy metal fans used to get drunk more often

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than the other groups; and concerning a very frequent use of cannabis (from oncea week to daily) the highest users were the house, the jungle/drum&bass/funkybeat group, and reggae fans, and, in relation to the use of ecstasy, they were thehouse and jungle/drum&bass/funky beat fans (Calafat et al., 1999). Membershipof a group with common musical tastes explains variance in both internalizing andexternalizing problem behaviour in young people (Mulder et al., 2006).

It would seem elementary, then, if a significant amount of drinking alcohol andillegal drug use among young Europeans occurs in relation to night-timerecreational activity (Fountain & Griffiths, 1997), that it would be worthwhileknowing how that close interrelationship being established between recreationalcontexts and drug use could be used in prevention. Nevertheless, this relationshipwith the context, understood as a risk or protective factor, has not normally beentaken into account as a key element in preventive programmes in these contexts,which have concentrated their focus almost exclusively on the basis of harmminimization. On the other hand, the majority of the studies on risk factors stillcontinue to be centred on what are traditionally considered to be vulnerablegroups for drugs, such as the young homeless, children whose parents misusedrugs, young offenders, etc. (Arthur, Pollard, Hawkins, Catalano, & Baglioni,2002; Lloyd, 1998), without it being taken into consideration that this model ofrecreational drug use is becoming increasingly prevalent and that it affects mostlymiddle-class young people with a good level of social integration.

The study of risk and protective factors for drug use is well established in NorthAmerica (Brown, 2002; Kendler, 2003; Arthur et al., 2002). Very often, thesestudies are based on traditionally linear correlation; this implies that if there is asignificant correlation between one or a few risk factors and the use of drugs, andwe are able to eliminate these risk factors, this is prevention. This has been auseful approach until now, but it has serious limitations because, in individualfunctioning, there is a continuous interaction between factors. It is necessary tosee how all these risk factors interact and evolve according to the circumstances,the developmental age, etc. In the case of Europe, the study of risk factors hasserious limitations according to a recent review (Rhodes et al., 2003):(a) insufficient studies including samples from different European countries;(b) a lack of studies integrating relevant environmental factors and analysingrelative weights in predicting substance use/misuse; and (c) a lack of studiesfocused on substance misuse, and not only on prevalence rates for substance use.

But what is interesting to point out here, especially, is that there has been littleresearch on how environmental and cultural factors relate to recreational nightlifeand on the influence of the recent generalization of recreational activities amongyouth on the use and misuse of drugs. And, in addition, we are finding ourselvesfacing a new situation, with a distinctive type of user and with differentexpectations when using substances. With respect to these big differences fromother forms of known drug uses, more closely linked to marginality or socialdelinquency, we could think that traditional risk and protective factors wouldhave a distinct role and, at the same time, that other relevant factors more closelylinked to these new contexts have not been explored yet. On this line of thought,

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Parker (2003) and Parker, Williams, and Aldridge (2002) maintain the theorythat the individual risk factors that have been considered up to now—underachievement at school, social exclusion, sensation seeking, lack of familycontrol, etc.—and which have been employed to explain the use of substancessuch as heroin or crack, can scarcely serve to explain the use of recreational drugs,since said uses have gone on to become ‘normalized’. Parker is even of theopinion that this kind of recreational user may make a better transition to adultlife than his/her abstemious peers. Shedler and Block (1990) have already offeredthe similarly provocative proposal that individuals who experiment with drugs arepsychologically healthier than abstainers, on the basis of a longitudinal study witha sample of 85 individuals. Nevertheless, this proposal could not be corroboratedin a longitudinal replication study made with a sample of 2071 adolescents(Milich et al., 2000).

The aim of this study is precisely that of assessing the relative weight oftraditional validated risk and protective factors in predicting drug use incomparison with the management of recreational nightlife by young peoplerecruited in recreational contexts from different European cities. The hypothesesof this study are twofold:

1. The risk or protective factors linked to the management of recreationalactivities must be good predictors of drug use since the young people establisha special and important relationship with these contexts.

2. If substance use/misuse is ‘normalized’ among youth when going out, thentraditional risk and protective factors would fail in predicting these drug-usepatterns.

Materials and methods

Sample

The population that was the focus of this study comprised young peopleparticipating in the nightlife of ten European cities (Athens, Berlin, Bologna,Lisbon, Liverpool, Nice, Palma de Mallorca, Turku, Utrecht and Vienna).Around two hundred participants were interviewed from each of these cities, witha total sample of 1777 young people being interviewed. Participants wererecruited from the most representative recreational areas in these ten Europeancities. These areas were selected after previous qualitative research developed ineach city as a part of this study (further information of this qualitative section ofthe study can be found in Calafat et al., 2003).

In order to compare the relevance of the risk factors, we divided the sample intotwo groups, according to the large groups that actually exist among people goingclubbing at the weekend, based on previous studies (Calafat et al., 1999, 2003).

Consumers (C). People using legal and illegal drugs. In this study, individualswho, in addition to using alcohol and/or tobacco, also used some illegal drugduring the last year.

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Non-consumers (NC). Abstainers and those who only occasionally and moder-ately used legal substances. A non-drug consumer is a person who does not useillegal drugs and has not been drunk during the last year, has not smokedcigarettes on more than three occasions in the last month, has not smoked morethan three cigarettes in one day on those occasions, has not drunk alcohol onmore than four days in the last month and has not had more than two alcoholicdrinks on any one of those occasions.

Individuals were selected at random, but stratified according to the level ofdrug consumption (C or NC), age and gender; and they were interviewedbetween March and July 2001. The interviewer was instructed to place him/herself close to the entrance to the selected establishment and to interview everyfifth person who entered there, starting with a ‘zero individual’ selected atrandom. Against expectations, the percentage of refusals was quite low, but therewere difficulties in finding non-consumers to complete the sample in Liverpooland Palma de Mallorca, and in finding consumers in Turku (Finland).Sometimes the selected person was recruited as mentioned, but the interviewtook place in a quieter setting (because of weather conditions, noise, etc.).

As a consequence of the stratification of the sample, a similar percentage ofmales (861; 48.5%) and females (916; 51.5%) was interviewed, and around a halfof the sample was below 19 years (878; 49.4%) or 19 and above (899; 50.6%).The average age was 20.3 years (SD¼ 3.8 years); 28% were in employment and65% were students; the majority still lived with their family of origin (59.5%),and half of them (50%) believed that their families belonged to the middle class,and 35% above middle class. Therefore, these young people are not marginalindividuals, and not remotely similar to the usual stereotype of drug users.

In relation to the use of drugs—and as a consequence again of stratification—943 (53%) were consumers (C) and 834 (47%) were non-consumers (NC).During the last year, almost all C drank alcohol (95%), smoked (94%) and usedcannabis (93%), and a substantial percentage used ecstasy (44%), cocaine (35%),LSD (22%) or speed (21%). In addition, the large majority of these drug-consumers (73.3%) admit that they have been drunk at least once in thepreceding month, and more than one half (52.9%) on two or more occasions.According to these percentages, a consumer (C) in our sample is an individualwho has drunk alcohol, smoked and used cannabis during the last year, and alsoused other illegal drugs in percentages that range between 21% and 44%.In addition, the majority of them get drunk frequently.

Instrument and variables

The individuals in the sample were interviewed using a structured questionnairecomprising the following domains:

Sociodemographics and personal history.

. Gender, age, age of onset for tobacco and alcohol, education, self-assessmentas a student, living arrangements, family socioeconomic status, occupation,political preferences and religiosity.

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Interpersonal factors (family and peers).

. Drug use by relatives (any parent/brother/sister): Alcohol, tobacco, cannabis,other illegal substance.

. Percentage of friends frequently using: Alcohol, getting drunk, tobacco,cannabis, cocaine, ecstasy, any other illegal drug.

. Attitudes towards a friend/partner using illegal drugs.

. Family and social integration: Ten questions.

Motivation, going out habits and opinion on the recreational contexts. This sectionof the questionnaire was validated through different studies made by us(Calafat et al., 1999, 2003).

. Implication in going out: Number of weekends per month and nights perweekend, hours of a typical session, and percentage of money spent on goingout.

. Motivations for going out: Dancing, getting to know people, meeting friends,music, looking for a partner, looking for sex, breaking daily routine, drinkingalcohol, taking drugs.

. Opinion on the physical context where they go clubbing: Their opinion on tencharacteristics of places where they go/would like to go.

Risk behaviour and related attitudes.

. Risk perception of 8 drug-use patterns.

. Participation in drug and driving behaviours (four items).

. Socially-deviated behaviours (four items).

. Sensation-seeking behaviours (three items)

Mediating variables (motivations for drug use, attitudes to drug use). This section ofthe questionnaire was validated through different studies made by us (Calafatet al., 1999, 2003).

. Reasons why some people neither take illegal drugs nor abuse legal drugs(alcohol and tobacco): A list of ten items.

. Reasons why some people use drugs: A list of seven items.

. Social image of non-users, as perceived by drug-users (six items).

. Attitudes regarding social control on drug use.

Statistical analysis

With the aim of considering the relative predictive ability of different risk andprotective factors, multivariate analysis was used, based on multinomial logisticregression, using a drug-use dichotomy. In a first step (Analysis 1), a logisticregression analysis was made for each domain of variables, introducing allvariables significantly related with drug use from each domain. In a second step(Analysis 2) a logistic regression analysis was made introducing all the variablesselected as significant predictors for each domain in the previous step (p < 0.05).

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The statistical analyses were made using the statistical programme SPSS forWindows (v. 10.1.3).

Results

In order to identify and compare the best predictors regarding people attendingrecreational contexts, results are presented (first step: Analysis 1) to show themost relevant risk and protective factors (see Table I) across each domain of thequestionnaire, selected through logistic regression analysis. In a second step(Analysis 2), we show the best predictors found in the analysis when weintroduced only those factors previously selected during the first step; that is,when we use only the risk or protective factors that were significant in Analysis 1.

Best predictors of drug use in recreational settings, domain by domain (Analysis 1)

Accordingly, we proceeded first to identify the best predictors and their relativeweight as predictors corresponding to each domain of variables (see Analysis 1 inTable I). On the basis of this procedure, in the sociodemographic and personal drug-use history domain, we obtained five significant variables that were capable ofcorrectly identifying 74% of the individuals with a good fit (Chi square p < 0.001).The capability to identify the consumers (97%) was higher than for NC (48%).

The domain relating to interpersonal factors resulted in eight variables thatcorrectly classified 80% of participants in their drug use status and showed a goodfit (Chi square p < 0.001).

Nightlife recreational related variables resulted in an equation that correctlyclassified a large majority of C (85%) and NC (86%) and showed a good fit(Chi square p < 0.001). This domain comprised ten significant predictors.

The domains relating to risk perception and risk behaviours were able to classifyclose to or more than three out of four individuals (75%) regarding their drug-usestatus, and showed a good fit (Chi square p < 0.001), and nine variables wereselected as significant.

Finally, in the mediating variables domain, ten variables had sufficientsignificance and, using logistic regression analysis, were capable of classifying77% of the sample (80% of the C and 74% of the NC) and showed a good fit(Chi square p < 0.001).

Selection of best variables (Analysis 2)

When we performed Analysis 2 with the logistic regression analysis, includingonly the significant factors from each domain identified in Analysis 1, we obtaineda final group of thirteen significant variables, capable of correctly classifying 92%of the participants in their drug-use status (92% correctly classified in eachgroup). The recreational nightlife domain provided five of the thirteen variablescorresponding to this final selection. Moreover, giving any importance to usingdrugs as a main reason for going out was the most relevant risk factor, and givingany importance to drinking alcohol as a main reason for going out was the third

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Table I. Results from two logistic regression analyses on being a drug user. Analysis 1:Multivariate predictors for each domain; Analysis 2: Multivariate predictors with all significantpredictors from Analysis 1. Odds ratio, confidence interval (CI: 95%) and significance for eachsignificant predictor.

Variable Analysis 1a Analysis 2b

Sociodemographic and personal history (74% correct: 97% C and 48% NC )Being an average or good student 0.45 (0.3–0.7)*** –Not living with friends 0.5 (0.3–0.8)** –Non-believer (religiosity) 2.4 (1.9–3.1)*** 1.6 (1.1–2.3)**Never tried alcohol 0.2 (0.1–0.4)*** –Never tried cigarettes 0.01 (0.01–0.02)*** 0.02 (0–0.1)***

Interpersonal factors (80% correct: 82% C and 76% NC )A parent using cannabis 2.3 (0.9–6.3), p < .1 –A sibling using cannabis 2.1 (1.4–3.2)*** –Any friend using cannabis frequently 12.1 (8–18.3)*** 7.64 (4.4–13.4)***Any friend using ecstasy frequently 3.17 (2.4–4.2)*** 2.53 (1.7–3.8)***Majority of friends getting drunk frequently 2.8 (2–3.8)*** 2.38 (1.5–3.8)***Would not start a relationship with a drug user 0.49 (0.4–0.7)*** –Would try to change his/her drug use 0.57 (0.4–0.8)*** –Would end it, if he/she did not change 0.26 (0.4–0.8)*** –

Going out habits and motivations, and opinion on recreational environments(85% correct: 85%C and 86% NC )Goes out� 2 weekends 0.56 (0.4–0.8)*** –Goes out less than 8 hours per typical session 0.57 (0.4–0.9)* –Spends less that 50% of money going out 0.62 (0.4–0.9)** –Meeting friends (importance to going out) 2.16 (1.3–3.6)** 2.15 (1.2–3.9)**Looking for a partner (very important) 0.52 (0.4–0.8)*** –Drinking alcohol (importance to going out) 6.2 (4.6–8.5)*** 5.2 (3.6–7.6)***Taking drugs (importance to going out) 9.6 (6.4–14.5)*** 8.4 (4.9–14.3)***Non-smoking venues preferred when going out 0.19 (0.1–0.3)*** 0.22 (0.2–0.3)***Venues with no illegal drugs

preferred when going out0.26 (0.2–0.3)*** 0.44 (0.3–0.6)***

Slightly seedy places preferred when going out 1.63 (1.2–2.2)*** –

Risk perceptions and behaviour (75% correct: 75% C and 75% NC )Drunkenness monthly/four drinks on a same

occasion (perceived it as dangerous)0.39 (0.30–0.50)*** –

Regular cannabis use is dangerous 0.28 (0.2–0.4)*** –Monthly cocaine use is dangerous 0.72 (0.5–0.97)* –Has driven under the effects of alcohol 3.37 (2.5–4.5)*** 3.16 (2.1–4.8)***Has travelled with a drunken driver 1.98 (1.5–2.5)*** –Would travel with a driver under the effects of drugs 2.22 (1.7–2.9)*** –Has never driven without a driving licence 0.76 (0.6–0.98)* –Thieving from shops/stores 2.3 (1.8–2.9)*** –Rarely did crazy things/what feels good 0.75 (0.6–0.97)* –

Mediating variables (77% correct: 80% C and 74% NC )Agree individuals are non-users because

they haven’t tried it yet2.18 (1.7–2.8)***

Agree drugs are used only by people withoutany purpose on life

0.35 (0.3–0.4)***

Agree drugs can make you feel good 2.16 (1.7–2.8)*** –Agree drugs help in feeling music and dancing 1.7 (1.2–2.3)*** –Agree drugs improve life experience 1.7 (1.4–2.3)*** –

(continued )

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most relevant risk factor. Also, two out of four significant protective factorsreferred to the management of recreational nightlife: Preferring to go out to non-smoking venues and preferring drug-free venues. These findings suggest thatmanagement of recreational nightlife can be a core individual domain inpredicting substance misuse.

Frequent substance use (cannabis, ecstasy and drunkenness) among peers wasalso a strong risk factor, as were episodes of driving when drunk. Other significantrisk factors were a lack of religiosity and a permissive attitude towards drug use.The strongest protective factor was never having tried cigarettes.

Discussion

It is clear that there is high prevalence of drug involvement in the weekendrecreational context according to many studies (Calafat et al., 1999, 2001;Measham et al., 1998; Parker, Aldridge, & Measham, 1998), and oursample corroborates this tendency. Several authors claim what they call the‘normalization’ of recreational drug use, based on cultural accommodation ofillegal drug use (Parker et al., 1998, 2002; Shedler & Block, 1990), and thiswould imply that most traditional risk factors would lose their strength. But thisassumption is not supported by our results because traditional risk factors are stillclosely related to the use of drugs.

We fully agree that the young people going out, nowadays, in recreationalsettings in Europe are completely different from the old profile of people comingfrom social exclusion zones. Most of them study or work, belong to a middle-classfamily, etc. Going out for most of them is a part of their social capital and,possibly for the majority of them, the experience of going out often to recreationalsettings will not have a negative influence on their personal careers. Nevertheless,as a result of this study, we found that the use of legal and illegal drugs in oursample is still related to several typical risk factors found in the literature:Sociodemographic (good student, religiosity), deviant behaviour (age of onset ofdrug use, adaptation to school), risky and antisocial behaviours of different kinds

Table I. Continued.

Variable Analysis 1a Analysis 2b

Disagree non-users can’t party as long as others can 0.66 (0.5–0.9)** 0.50 (0.4–0.7)***Disagree non-users enjoy themselves less 0.43 (0.3–0.6)*** –Agree alcohol in streets should be an offence 0.45 (0.4–0.6)*** –Strongly agree illegal drug use in streets

should be an offence0.45 (0.4–0.6)*** 0.47 (0.4–0.6)***

Agree legislation on drugs should be less strict 2.95 (2.3–3.8)*** 1.9 (1.3–2.8)***

Note: aAnalysis 1: Predictors in each domain: Odds ratio (CI, p < 0.05); bAnalysis 2: Predictorsintroducing all significant predictors from each domain: Odds ratio (CI, p < 0.05); *p < 0.05;**p < 0.01; ***p < 0.001. All other variables of the questionnaire are not significant and notincluded in the table.

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(driving having used drugs, thieving, etc.), peer and family drug use, personalitycharacteristics and other mediating variables (motivation, expectancies and riskperception related to drug use) or attitude to social and legal control.

The hypothesis that the factors relating to the management of recreationalactivities were relevant and useful as predictors has been corroborated by thisstudy because the recreational management domain has been the best predictor ofuse or non-use of drugs, and five of the thirteen selections of most relevant factorsbelonged to this domain. The predictors referring to this domain are: Intenseinvolvement in this activity, main motivations for going out (meeting friends,looking for a partner, looking for alcohol or drugs), and certain criteria for theselection of venues (non-smoking, difficulty in using illegal drugs or seedyappearance).

At present, the prevention initiatives in European recreational areas are notevidence based (Calafat & Juan, 2004; Tossmann, Bold, & Tensil, 2001). In themain, they provide information focused on harm-reduction messages, peerinformation and pill-testing practices but have not been adequately assessed, anddo not provide information on their potential impact or iatrogenic effects for non-drug users (Burkhart & Lopez, 2002; Dishion, Poulin, & Burraston, 2001).According to the results of this study, preventive actions in recreational settingsshould integrate the management of recreational activities (control over theinvolvement in recreational activities and an increase in the control on the use ofdrugs as a tool for performing recreational activities), addressing high-risk groupsand promoting another form of leisure during the weekend.

It is necessary to take into account some limitations in the study. This is across-sectional study, not a longitudinal study, and this fact introduces a seriouslimitation with regard to the predictive capability of the variables studied. Wemust understand the study as an exploratory one, in a field where there is still notsufficient information. Also, sampling methods do not guarantee that subsamplesare representative of users of recreational areas from each city, although we canconsider them as good representations of the predominant recreational cultures inthese cities. The goal is not to study a representative sample of European youth,but a sample representative of the people involved in youth subcultures associatedwith recreational substance use during ‘nightlife’-related activities.

Acknowledgement

This study was undertaken with the financial support of the European Union,awarded to IREFREA by the DG SANCO.

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