National-level drug policy and young people's illicit drug use: A multilevel analysis of the European Union
Introduction
Despite recent evidence of cross-national differences in substance use rates and calls to exploit cross-national differences to uncover the cultural and structural factors influencing drug use (Teesson et al., 2006, Degenhardt et al., 2008), most examinations of predictors of use are confined within a single national context, neglecting a critical source of variation that may explain differences in use (Ghandour et al., 2012). National-level drug policy, however, provides a specific context for substance use (Vuolo, 2012). Fields such as sociology have a long tradition of examining contextual effects. According to organizational institutionalism, across- and within-nation variation in policy and behavior is a product of institutionalized cultural frames (Meyer et al., 1997). Institutional structure, such as cultural models and discourse, diffusely influence national and regional actors. Resultant loosely coupled changes in law, policies, attitudes, and values engender an uneven drift towards improvement on a particular outcome (Schofer and Hironaka, 2005). These cultural frames provide a lens through which individual actors understand the world and act within it, shaping the social behaviors and practices that are deemed legitimate, or even thinkable (Bourdieu, 1972, Swidler, 1986). This line of research has shown that national-level context drives individual-level behaviors such as civic engagement (Schofer and Fourcade-Gourinchas, 2001), blood-giving (Healy, 2000), environmentalism (Schofer and Hironaka, 2005), and religiosity (Kelley and De Graaf, 1997). Though connecting national context to related behaviors, this literature has rarely examined policies that were explicitly created to affect behavior. For such policies, the role of cultural diffusion is even more salient, as was recently shown for tobacco policy and youth cigarette use (Vuolo, 2012). Following this approach, this study examines whether national-level drug policies diffuse in a way that is associated with behavior, or whether such policies are too distal.
Both legal (Ewick and Silbey, 1998) and health (Bird and Rieker, 2008) policy create institutionalized cultural frames that influence behavior. The drug policy literature provides reasons to believe such policies may provide frames for behavior. The dominant strategy at all levels of government towards illegal drugs has been antidrug legislation and law enforcement (MacCoun and Reuter, 2001). In the limited locations adopting decriminalization, drug use does not increase, unless a substance becomes commercialized (MacCoun and Reuter, 2001, Reinarman et al., 2004). Nonetheless, for decades, common rhetoric has implied that removing penalties will result in increased use and harm to society and send an improper message of tolerance of drug use (Goldstein and Kalant, 1990, Hall, 2001). For health-related policy, while evidence shows reductions in use and harm for current users in the presence of methadone maintenance (Kleber, 2008), syringe exchanges (Des Jarlais et al., 2009), and treatment more generally, little is known about how the presence of such programs are related to young people's drug use in the general population, which is an important effect to explore if one assumes policy provides cultural frames.
Even with evidence of cross-national variation, most research on adolescent substance use has examined the individual-level of variation, producing a well-established, high quality body of research. According to Bachman et al. (2002), the social bonds of school and work are important predictors of substance use for adolescents. Illicit drug use is higher for non-college bound students and remains high following high school (Bachman et al., 1997). During high school, excessive work can lead to increased substance use (Resnick et al., 1997, McMorris and Uggen, 2000). Following high school, those who are neither students nor employed have higher consumption (Schulenberg et al., 2000). Beyond bonds, perceiving a substance as risky results in lower use (Bachman et al., 1998, Bachman et al., 1990). The consumption of peers and parents is also central, with such use increasing the likelihood of one's own use (Bauman and Ennett, 1996, Li et al., 2002, Ennett et al., 2006). Finally, demographics also distinguish users, with males (European Monitoring Center for Drugs and Drug Addiction, 2006), older adolescents (Bachman et al., 2002), and residents of particular neighborhoods (Sampson et al., 2002) more likely to use drugs.
It remains important to consider contextual influences on adolescent drug use (Teesson et al., 2006, Degenhardt et al., 2008, Ghandour et al., 2012), particularly the influence of drug policy. While drug policy is often the focus of research, such research has rarely accounted for cross-national policy variation in examinations of the predictors of individual-level use. Thus, the goal of this article is twofold. First, the article examines the extent to which individual-level drug use is better predicted taking into account policy context. In other words, if significant variation exists cross-nationally, do policy differences explain this variation? Second, the article explores to what extent certain policies are associated with individual-level use, using the above studies as a guide for potentially important predictors. The variation across nations in both the qualitative presence of certain policies and their utilization provide the opportunity to examine these often overlooked contextual influences at the individual-level among adolescents.
Section snippets
Individual-level sample
The individual-level data come from Eurostat, the European Commission's statistics branch, collected by their Eurobarometer survey. Two near identical in-person surveys, conducted in the appropriate national language, were administered with new cross-sections of 15–24-year olds in 2002 (T. Christensen, 2003) and 2004 (European Communities, 2004). Applying an identical sampling technique across nations, households were drawn in multistage, random probability samples proportional to population
Descriptive findings
As shown in Table 2, the rate of last month drug use among those aged 15–24 across all countries and both years is 2.8%. Fig. 1, however, shows considerable variation across country and year. Ireland had the highest rate of use in both years, while seeing an increase from 2002 (5.0%) to 2004 (7.6%). In both years, Greece exhibits the lowest use. Although most countries saw a change, the direction is inconsistent. The Netherlands and Austria remained fairly stable. Despite its overall rarity,
Discussion
This paper sought to answer recent calls to exploit cross-national differences to uncover the cultural and structural factors influencing drug use (Teesson et al., 2006). Organizational institutionalism (Meyer et al., 1997) justifies an examination of the national-level cultural scripts that guide behavior. The cross-national variation in drug policy provides an area ripe for such an examination. Among young people in the European Union, this analysis demonstrates that drug policy is associated
Role of funding source
This work was supported by a University of Minnesota Graduate School Doctoral Dissertation Fellowship and the University of Minnesota Department of Sociology Director of Graduate Studies Discretionary Award. The University of Minnesota Graduate School and the University of Minnesota Department of Sociology Director of Graduate Studies had no further role in study design; in the collection, analysis and interpretation of data; in the writing of the report; or in the decision to submit the paper
Contributor
Mike Vuolo conducted all aspects of the manuscript.
Conflict of interest
No conflict declared.
Acknowledgements
The author gratefully acknowledges Brian Kelly, Chris Uggen, Joachim Savelsberg, Liz Boyle, and Sandy Weisberg, as well as Associate Editor Jan Copeland and the anonymous reviewers, for their time and feedback on the various versions of this and related papers, and also thanks Ty Miller and Sierra Lange for invaluable research assistance.
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2018, International Journal of Drug PolicyCitation Excerpt :In the studies surveyed, the sights of researchers have largely been trained on one question: whether liberalisation results in increases in rates of adolescent use. Some research findings suggesting a link have been doubted (Shi, Lenzi, & An, 2015; Rogeberg and Stevens, 2016; Vuolo, 2013), and no studies have yet found that prohibition-orientated policies reduce levels of drug use (Home Office, 2014; Stevens, 2011), including among adolescents (Simons-Morton et al., 2010). There is also a debate about whether medical cannabis laws increase rates of juvenile cannabis use (Hasin et al., 2014; Stolzenberg et al., 2016; Wall et al., 2016).
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2017, International Journal of Drug PolicyCitation Excerpt :“Data driven policy coding” is described as using non-legal data, either inputs (like enforcement staffing) or outputs (like tickets) as the policy measure, rather than relying on the policy “as written” to classify and compare policy. For example, rather than use a jurisdiction’s marijuana law, a study might use the possession arrest rate as its measure of “decriminalization policy” (Vuolo, 2013). The “descriptive policy” approach involves collecting, organizing and describing policies in detail.
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2016, International Journal of Drug PolicyCitation Excerpt :In alcohol policy comparisons, examples of multi-level modelling include (Bendtsen et al., 2014; Bosque-Prous et al., 2014; Cherpitel et al., 2012; Cook, Bond, & Greenfield, 2014; Podana & Burianek, 2013). However, this approach is less commonly used in illicit drugs policy analysis; the only readily identifiable example was Vuolo (2013). Multi-level modelling tends to provide greater statistical power because data are based on individuals rather than aggregated state-level data.