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Underage Drinking

 | 
Philippe De Witte
, 
Mack C. Mitchell Jr.

Chapter 2. Risk and Protective Factors for Underage Drinking

Reinout W. Wiers, Kim Fromme, Antti Latvala et Sherry Stewart

Texte intégral

1A wide range of factors is known to influence adolescent alcohol use behaviours as reviewed by Hawkins, Catalano, and Miller (1992). Although somewhat outdated as a review, the categorization of the risk factors is still useful. The authors distinguish between on the one hand individual and interpersonal factors and on the other hand contextual factors. Like almost all human behaviour, alcohol use – though fundamentally the behaviour of individuals – occurs in the context of societies with their legal and cultural norms and other factors restricting or enabling behaviour. We start with individual risk factors (genetics, cognitive processes, personality), followed by interpersonal risk factors (e.g., influences of family and peers), and end with some environmental factors (e.g., neighbourhood influences). Factors at different levels of description can influence each other; for example, a stressful family environment has an impact on the development of the stress-reactivity of an individual and this is moderated by genetic factors, which can lead to “developmental cascades” (Masten & Cicchetti, 2010). We acknowledge that this is not a full systematic review in all of these wide domains, which was beyond the scope of this project. We illustrate current thinking about risk and protective factors across different levels of description and their interplay. We also note that many risk and protective factors have not been studied across many different cultures, and in research on some risk factors there is a gender bias (e.g., acute alcohol effects, which has been primarily studied in men, mostly for pragmatic reasons such as risk of pregnancy, lower tolerance in women, etc.).

KEY FINDINGS

2• Risk and protective factors can be described at many different levels of description, ranging from genes and (sub-) cellular processes to societal characteristics. It is important to distinguish risk- and protective factors with respect to their causal status and with respect to their malleability. We focused on risk factors with some evidence of causality and/or which may be malleable through interventions.

3• Peers and parents are important factors across cultures in influencing underage drinking and related problems, with many indirect pathways (e.g., parental SES, neighbourhood-effects, etc.). Recent evidence has demonstrated a causal role for alcohol-specific rule setting on delaying age of onset both in North Europe and in the U.S.

4• Personality is an important risk factor, with different facets of personality influencing risk for underage drinking and related problems in different ways. Externalizing characteristics and related traits (impulsivity, sensation seeking, weak self-control) have been related to early onset and escalation. Internalizing problems appear to be less strongly related to age of onset, but do appear to play an important role in the escalation of teen drinking, with an important role for motivations to drink in order to cope with problems.

5• Alcohol-related cognitive processes are important predictors of alcohol use and problems, with some operating more on explicit reasoning processes (e.g., motives to drink) and others operating more automatically (e.g., attention captured by alcohol-related stimuli).

6• Some risk factors (parenting, personality, cognitive processes) can be targeted in interventions, as are discussed in Chapter 3.

7• Two important issues regarding risk and protective factors are their causal status, and whether or not they are amenable to intervention. Regarding causal status, there are two ways to investigate this: first, longitudinal studies can be done where the risk factor is assessed and mediation of the risk factor regarding the outcome is tested (Baron & Kenny, 1986; MacKinnon & Fairchild, 2009; MacKinnon & Lockwood, 2003; Maric, Wiers, & Prins, 2012). The most convincing way to demonstrate causality, however, is to conduct an experiment and to manipulate the variable of interest in an experiment with random assignment and to demonstrate the effect on the outcome. In this context, that strategy is often a form of an intervention, although most prevention programmes are broad and rarely target a specific variable. As an example from underage drinking, it has been demonstrated that strict rule setting regarding alcohol use by parents is longitudinally related to a delayed age of onset of drinking in children (van der Vorst, Engels, Dekovic, Meeus, & Vermulst, 2007). From this observation it seems likely that lack of strict alcohol rules (no drinking allowed before the legal drinking age) is a causal factor in the prediction of underage drinking. However, there are other potential explanations: so called third-variables that could explain this relationship. For example, parents scoring high on intelligence or low on impulsivity could set more strict alcohol-specific rules than parents scoring low on intelligence or high on impulsivity. Given that these characteristics are influenced by heritability, offspring of highly intelligent (low impulsive) parents will score relatively high on intelligence (low on impulsivity), which could predict late age of onset. In that case the correlation between parental rule-setting and late age of onset would be a spurious one. The only way to rule out the possibility of third variables is to conduct an experiment, and that has been done for this example (Koning et al., 2009). Adolescents were randomly assigned to conditions combining universal prevention aimed at the adolescents themselves, with prevention aimed at the parents or to universal prevention alone. Only adolescents receiving the universal prevention, and whose parents had also received the parent intervention, delayed their onset of drinking. In this case, third variables can be ruled out, and the interpretation of this effect was strengthened by the fact that changes in parental attitudes and perceived rules mediated the intervention effect (Koning, van den Eijnden, Engels, Verdurmen, & Vollebergh, 2011).

8The second important feature of risk and protective factors is the extent to which they are malleable. Genes or low SES are not easily changed, but it is possible that some of the processes through which they exert their effects may be malleable. For that reason, psychological variables are particularly interesting, because there is evidence that some of the psychological risk factors (e.g., ideas adolescents have about the level of drinking of others, expected outcomes, coping strategies, and automatically triggered associative processes) can be changed by interventions. As was shown above so can parental rule-setting. Other important societal factors related to levels of alcohol use and problems in the population include policies and laws regulating the availability of alcohol, cultural norms (including religion), and various factors related to social cohesion and control, most of which are discussed in detail in this chapter (see, Babor et al., 2010; Galea, Nandi, & Vlahov, 2004; Mäkelä & Österberg, 2009; Sampson, Morenoff, & Gannon-Rowley, 2002 for greater details). Where possible, direct comparison studies between European and American research are highlighted.

GENETIC LIABILITY

9The relative contributions of genetic and environmental influences to variation in a trait can be estimated in studies of monozygotic (MZ) and dizygotic (DZ) twins. This is based on the fact that members of a MZ twin pair are genetically identical, whereas DZ co-twins share, on average, 50% of their segregating genes (Boomsma, Busjahn, & Peltonen, 2002). A central concept of twin studies is heritability, meaning the proportion of total variance in a trait attributable to genetic variance. Alcohol use and disorders have been extensively studied by the twin study methodology. A robust finding of twin studies has been that genetic factors have a notable influence on the risk to develop alcohol use disorders. A review of community based twin studies of alcohol-related phenotypes from many different countries and more than 18,000 twin pairs found that the average heritability (weighted by sample size of the study) of alcohol dependence in adult populations was 55% (Dick, Prescott, & McGue, 2009).

10The contribution of genetic and environmental variation to initiation and development of drinking has been investigated in studies of adolescent twins. In contrast to alcohol use disorders, drinking onset has been found to be strongly influenced by environmental factors, including those shared by members of a twin pair, such as factors related to growing up in the same family and sharing peers. Regarding initiation of drinking, the weighted average proportions of variation explained by genetic, shared environmental and non-shared environmental factors were 37%, 36% and 27%, respectively (Dick et al., 2009).

11Environments shared by adolescent co-twins thus have an important influence on the early stages of alcohol use. However, based on both prospective and retrospective data, these factors seem to become less important in subsequent stages of alcohol use, whereas the relative contributions of genes and individual-specific environmental factors become more important (Fowler et al., 2007; Kendler, Schmitt, Aggen, & Prescott, 2008; Pagan et al., 2006; Rhee et al., 2003; Rose, Dick, Viken, Pulkkinen, & Kaprio, 2001). Importantly, the classic twin study methodology estimates proportions of variation which does not have a straight-forward relation to the mean level of the trait under study. Thus, the role of genetic factors underlying variation in adolescent drinking behaviours has been found to be independent of trends and cohort effects in adolescent drinking (Geels et al., 2012).

12A recent study modeled genetic influences on a multitude of alcohol-related traits, ranging from use of alcohol to dependence. Based on two different data sets of twins, from the U.S. and Finland, Dick, Mayers, Rose, Kaprio and Kendler (2011) identified four independent genetic sources of variation. This means that the distribution of genetic and environmental influences on alcohol use, abuse and dependence, is highly phenotype (behaviour) specific. This would imply that intervening on different alcohol-related behaviours might require interventions that are behaviour-specific. While some specific genes acting on alcohol use and dependence have been identified, notably those involved in the metabolism of alcohol, findings relating specific genes to alcohol use have mostly been inconsistent and the findings have indicated, at most, weak associations. Thus, the genetic liability to alcohol use is probably composed of multiple genes, each with, at most, minor effects on the liability to use. This hypothesis is exemplified by the recent genome-wide analysis of alcohol consumption in 20,000 subjects with genome-wide array data, from which only one finding of interest emerged (Schumann et al., 2011). Larger population studies of common genetic variants may reveal some more genes of relevance, but these are unlikely to account for a major fraction of the variance underlying alcohol use. For adolescent alcohol use, it is even less likely that specific genes play any major role.

13Though traditional genetic models assume that genetic and environmental factors act independently of each other, accumulating evidence suggests that this is not the case. A recent review indicated that studies of inferred genotype, such as twin studies, provide fairly consistent evidence that specific environmental factors, such as parental and peer influences, region of residence, religious involvement and marital status modify the importance of genetic factors (Young-Wolff, Enoch, & Prescott, 2011). The same review indicated that studies of specific candidate genes, however, provide a more varied picture with less consistent findings. Partly, these are due to the weaker associations of individual genes with alcohol-related phenotypes, as well as lack of power, in mostly small to medium-sized samples. Overall, such studies indicate that variation in environmental conditions can minimize the impact of genetic liability. That is, genetic effects on alcohol use are very context-dependent.

PERSONALITY AND UNDERAGE DRINKING

14Individual differences in temperamental and personality traits in childhood and adolescence have been found to be robust predictors of the development of alcohol use behaviours. For example, children whose behaviour was classified as under-controlled (i.e. impulsive, restless, or distractible) at age 3 were significantly more likely to be diagnosed with alcohol dependence at age 21 than children not exhibiting these behavioural tendencies (Caspi, Moffitt, Newman, & Silva, 1996). Similarly, the personality dimensions of high novelty-seeking and low harm-avoidance, assessed at age 11, were found to distinguish boys with an increased risk for alcohol abuse at age 27 (Cloninger, Sigvardsson, & Bohman, 1988).

15Externalizing characteristics. A large research literature has replicated and extended these findings (Barman, Pulkkinen, Kaprio, & Rose, 2004; de Wit, 2009; Dick et al., 2010; Iacono, Carlson, Taylor, Elkins, & McGue, 1999; Vanyukov et al., 2003; Verdejo-Garcia, Lawrence, & Clark, 2008; Weinberg & Glantz, 1999). It is thus currently generally accepted that a tendency for disinhibited, easily distractible, impulsive, or aggressive behaviour in childhood and adolescence significantly increases the risk to engage in alcohol use behaviours, ranging from initiation of drinking to alcohol dependence. Related to these behaviours are the psychiatric disorders: antisocial personality disorder, conduct disorder and attention-deficit/hyperactivity disorder (ADHD), which are strongly related to the risk of alcohol use disorders, in part due to shared genetic risk (Edwards & Kendler, 2012).

16During the past decade, a hot topic of research has become the interplay between personality, brain development and substance use during adolescence (Casey & Jones, 2010; Gladwin, Figner, Crone, & Wiers, 2011; Steinberg, 2010; Steinberg et al., 2008; White et al., 2011; Wiers, Ames, Hofmann, Krank, & Stacy, 2010). For example, there is increasing evidence that two often confounded concepts, impulsivity and sensation seeking have a different developmental pathway, with sensation seeking peeking during adolescence, while impulsivity gradually decreases with age, which has been attributed to different developmental pathways of motivational brain circuits (fast development during adolescence) and brain systems underlying executive control (Casey & Jones, 2010; Gladwin et al., 2011; Steinberg, 2010; Steinberg et al., 2008; Wiers, Ames et al., 2010). Recent reviews have indicated that there is abundant evidence reporting correlations between impulsivity and abuse of alcohol and other substances, but that the causal pathways are less clear. The strongest evidence in humans points to impulsivity as a risk factor for the development of later problems with alcohol and other substances, and suggestive evidence for increased impulsivity due to early alcohol or substance abuse (de Wit, 2009; Verdejo-Garcia et al., 2008). Note that when impulsivity is defined as a lack of (executive) control over impulses, there is overlap with the concept of self-regulation.

17Self-regulation capacity has a strong genetic component (Friedman, Miyake, Robinson, & Hewitt, 2011; Friedman et al., 2008); children who find it difficult to restrain their impulses (e.g., to not eat a cookie after an experimenter has left the room, which will yield two cookies upon the return of the experimenter), also show relatively weak executive control functions during adolescence (Friedman et al., 2011) and sub-optimal academic success and health outcomes in the long run (Mischel et al., 2011; Mischel, Shoda, & Peake, 1988). Lower self-control in childhood also leads to adolescent substance use, problems and dependence (Moffitt et al., 2011; Neal & Carey, 2007). Hence, sub-optimal development of control over impulses and self-regulation are risk factors for the development of addiction and other externalizing problem behaviours.

18On the other hand, good self-control can be a buffering factor against adolescent problem behaviours (Wills, Ainette, Stoolmiller, Gibbons, & Shinar, 2008; Wills & Stoolmiller, 2002). Buffering factors reduce the effect of risk factors on behavioural outcomes, with good self control buffering the effects of negative life events and peer substance use. In a 4-year prospective study, adolescents (ages 14 to 15 years) who had higher self-control showed lower increases in substance use in response to life events and peers who used substances (Wills et al., 2008). Research also shows that the capacity for self-control could be stimulated successfully in children (Diamond, Barnett, Thomas, & Munro, 2007), and that this delayed the onset of substance use later as adolescents (van Lier, Huizink, & Crijnen, 2009).

19In addition to impulsivity and related characteristics (suboptimal executive control or self-regulation) predicting later problems with alcohol and drugs, as discussed above, animal research increasingly suggests a detrimental role of abuse of alcohol and other substances on the normal developmental pathways during adolescence (Crews, He, & Hodge, 2007). The scarce prospective human research suggests that this may also be the case in human adolescents, with perhaps more possibilities for recovery to more normative developmental pathways with early cessation of alcohol abuse (White et al., 2011). This clearly constitutes an area for future research.

20Internalizing characteristics. Internalizing characteristics such as neuroticism and negative affectivity have also been studied in adolescents in relation to risk for alcohol misuse. For example, neurotic personality traits have been shown to predict the progression from drinking in adolescence to alcohol problems in young adulthood (e.g., Jackson & Sher, 2003). Interestingly, both externalizing and internalizing personality characteristics appear to be linked to risk for problematic drinking through different mechanisms. Specifically, externalizing traits, like sensation seeking, appear to be linked to drinking to enhance positive affect, which in turn increases risk for alcohol problems via heavy drinking. In contrast, internalizing traits and symptoms, like neuroticism and negative affectivity, are linked to risk for alcohol problems through increased coping-motivated drinking, which is directly associated with drinking problems over and above drinking levels (Cooper, 1994; Cooper, Frone, Russel, & Mudar, 1995). In a longitudinal study, Marmorstein, White, Loeber, & Stouthamer-Loeber (2010) found that higher levels of both social anxiety and generalized anxiety predicted earlier age of onset among adolescent males. Generalized anxiety remained significant when delinquency was included in the model, but social anxiety did not.

21In addition to the role of broad internalizing traits like neuroticism and anxiety disorders, researchers have explored the role of more specific internalizing personality characteristics such as anxiety sensitivity and introversion-hopelessness by examining the extent to which these more specific factors are associated with heavier drinking behaviour, alcohol-related problems, and/or risky drinking motives in adolescents and emerging adults. Anxiety sensitivity involves a fear of anxiety-related sensations, such as rapid heart beat, shaking or dizziness. Young people with high levels of anxiety sensitivity are theoretically at-risk of misusing alcohol because they are highly motivated to engage in behaviours that may reduce their unpleasant anxiety sensations, at least in the short term (Stewart & Kushner, 2001). Introversion-hopelessness is a personality profile characterized by introversion, neuroticism, and pessimism (Conrod, Pihl, Stewart, & Dongier, 2000). Studies have shown that anxiety sensitivity and introversion-hopelessness can both be reliably measured in young people, can be discriminated from one another both in factor analysis and in specific correlates, and can be well discriminated from other personality risk factors for alcohol abuse, such as the externalizing factors of impulsivity and sensation seeking discussed above (Woicik, Conrod, Stewart, & Pihl, 2009). We first discuss the evidence for a role of anxiety sensitivity in risk for excessive drinking and/or alcohol problems in young drinkers, and then move on to a consideration of the role of introversion-hopelessness in this group.

22Anxiety sensitivity appears to be reliably associated with elevated alcohol-related problems in young adulthood, although it is not reliably associated with increased alcohol use (Krank, Stewart, O’Connor, Woicik, Wall, & Conrod, 2011; Mackie, Castellanos-Ryan, & Conrod, 2011; Woicik et al., 2009). Moreover, anxiety sensitivity has been shown to moderate the association between anxiety symptoms and escalations in alcohol use over time (Mackie et al., 2011). Adolescents were tested at four separate times over an 18-month period. Adolescents with higher levels of both anxiety symptoms and anxiety sensitivity showed a faster rate of increase in alcohol use over time. Additionally, anxiety sensitivity has been uniquely associated with self-report reasons for alcohol use that reflected a desire to reduce negative emotional states and to reduce peer pressure (i.e., coping and conformity drinking motives, respectively; Woicik et al., 2009). Finally, targeting anxiety sensitivity in youth at-risk concurrently prevents onset of alcohol misuse, panic symptoms, and school avoidance in young adolescents (Castellanos & Conrod, 2006; O’Leary-Barrett, Mackie, Castellanos-Ryan, Al-Khudhairy, & Conrod, 2010), and reduces conformity drinking, relief alcohol outcome expectancies, and alcohol problems in emerging adults (Watt, Stewart, Birch, & Bernier, 2006). These prevention findings are consistent with the notion of anxiety sensitivity as a direct risk factor for alcohol problems or with the possibility that anxiety sensitivity predisposes to anxiety psychopathology which in turn increases risk for self-medication with alcohol (Stewart, Grant, Mackie, & Conrod, in press). Introversion-hopelessness is associated with elevated alcohol use and more problematic use in adolescents and emerging adults (Krank et al., 2011; Mackie et al., 2011; Woicik et al., 2009). Relative to other personality risk factors for alcohol misuse, introversion-hopelessness is uniquely associated with self-report motives for alcohol use that reflect a desire to reduce depressive symptoms and “numb pain” (Woicik et al., 2009), at least when using motives scales that allow for assessment of the extent to which an individual uses alcohol to cope with depressive symptoms in particular (Grant, Stewart, O’Connor, Blackwell, & Conrod, 2007). Finally, targeting introversion-hopelessness in young adolescents at-risk concurrently prevents onset of both alcohol misuse and depression symptoms (Castellanos & Conrod, 2006; O’Leary-Barrett et al., 2010). Again, these prevention findings are consistent with the idea of introversion-hopelessness as a direct risk factor for alcohol misuse, or with the possibility that introversion-hopelessness increases the risk for depressive disorders, which in turn increases risk for self-medication with alcohol leading to eventual heavy drinking and alcohol problems (Stewart et al., in press). These prevention findings are discussed in more detail in the prevention chapter (see Chapter 3).

ALCOHOL-RELATED COGNITIONS

23One of the most investigated and strongest correlates of alcohol use is alcohol-related cognitions. Traditionally, these include alcohol-related expectations or expectancies, drinking motives, and related social-cognitive constructs such as attitudes, beliefs and intentions. In the broader field of psychological science, researchers have begun to distinguish between implicit and explicit cognitive processes (Evans, 2003; Gawronski & Bodenhausen, 2006; Greenwald & Banaji, 1995; Kahneman, 2003; Smith & DeCoster, 2000; Strack & Deutsch, 2004). Implicit or impulsive cognitive processes are relatively automatic, associative processes that can lead to behaviour without conscious reflection, while explicit or reflective cognitive processes require (limited) cognitive resources and have unique properties related to propositional reasoning (Gawronski & Bodenhausen, 2006; Smith & DeCoster, 2000; Strack & Deutsch, 2004). According to dual process models, these two systems jointly predict behaviour, with boundary conditions determining the relative weight of the processes in the decision making process (Hofmann, Friese, & Wiers, 2008; Strack & Deutsch, 2004). For example, there are individual differences in the relative influence of reflective vs. impulsive processes on behaviour, related to individual differences in executive control functions. In people with relatively well-developed cognitive control functions, explicit cognitions better predict behaviour than implicit cognitions, and the reverse is found in individuals with relatively poorly developed cognitive control functions (Hofmann, Friese et al., 2008; Hofmann, Gschwendner, Friese, Wiers, & Schmitt, 2008). In addition, there are important factors within an individual that influence the relative influence of both processes; after exhaustion, fatigue, stress and alcohol and drug use, implicit cognitive processes gain in relative influence (for reviews see to: Hofmann, Friese et al., 2008; Wiers, Houben, Roefs, Hofmann, & Stacy, 2010).

24These general models have been applied to the field of alcohol and drug use (Deutsch, Gawronski, & Strack, 2006; Gladwin et al., 2011; Stacy, Ames, & Knowlton, 2004; Wiers, Bartholow et al., 2007; Wiers & Stacy, 2006), with conceptually similar models in the neurocognitive literature, in which specific brain systems are associated with the impulsive versus reflective system (Bechara, 2005). The general notion is that in the course of the development of addiction, implicit cognitive processes gain relative weight over explicit cognitive processes, through two types of feedback loops (or neuro-adaptations); with repeated use, implicit cognitive processes become stronger (once triggered by the relevant alcohol-related stimulus), and explicit cognitive processes become weaker (Wiers et al., 2007). There is increasing evidence that both effects are stronger when alcohol and drugs are taken at a younger age (Casey & Jones, 2010; Gladwin et al., 2011).

Explicit Alcohol Cognitions

25Two cognition constructs have received the most attention in the alcohol field: alcohol-related expectancies (from now on “expectancies”) and drinking motives (“motives”). Hundreds of studies have demonstrated that expectancies are strongly related to alcohol use and problems in cross-sectional research, with most studies in young adults but some in underage drinkers (e.g., Christiansen & Goldman, 1983; Christiansen, Smith, Roehling, & Goldman, 1989; for reviews see: Goldman, Del Boca, & Darkes, 1999; Jones, Corbin, & Fromme, 2001; Wiers, Hoogeveen, Sergeant, & Boudewijn Gunning, 1997). Fewer studies have investigated prospective prediction, and there prediction is weaker (especially after controlling for earlier drinking levels), but still significant (Jones et al., 2001; Sher, Wood, Wood, & Raskin, 1996). While early research only investigated positive expectancies (Brown, Goldman, & Christiansen, 1985), later research also assessed negative expectancies (Fromme, Stroot, & Kaplan, 1993) and demonstrated that negative expectancies account for unique variance in use (Jones et al., 2001). It appears that negative expectancies can serve as a protective factor for underage drinking, with beliefs about the potential negative consequences of drinking being inversely associated with both the frequency of drinking and amount consumed per drinking occasion for underage drinkers (Fromme et al., 1993; Fromme & D’Amico, 2000). Negative expectancies might also contribute to efforts to limit one’s drinking (Lee, Greely, & Oei, 1999) as well as motivate problem drinkers and alcoholics to reduce or stop their alcohol use (Jones & McMahon, 1994). In the latter context, negative expectancies are related to motivation to change (Jones & McMahon, 1998), which is an important concept in the treatment literature (Miller, 1998). Finally, there are also some studies indicating that expectancies differ by dose and that in older adolescents and young adults, high-dose positive expectancies may be particularly relevant, both in Europe (Wiers et al., 1997) and in the U.S. (Read & O’Conner, 2006; Read, Lau-Barraco, Dunn & Borsani, 2009). Specifically, young binge-drinkers score especially highly on positive and arousal expectancies after many drinks.

Drinking Motives

26Motives to drink have been studied extensively by Cooper (1994) and colleagues (1995). These investigators developed a widely used scale: the Drinking Motives Questionnaire – Revised (DMQ-R), which has also been used often in studies of underage drinkers, both in North America and in Europe (Kuntsche, Stewart, & Cooper, 2008; Kuntsche, Wiers, Janssen, & Gmel, 2010). The scale combines two types of reinforcement (positive/negative) with an internal or external drive leading to four motives to drink: Enhancement (internal, positive reinforcement, for example drink for the kick); Social (external, positive reinforcement; drinking to affiliate); Coping (internal, negative reinforcement; drinking to manage negative emotional states); and Conformity (external, negative reinforcement; drinking to reduce or avoid social censure). The scales have been replicated across countries, and enhancement and coping drinking motives have been found to be primary predictors of excessive underage drinking and alcohol-related problems. For example, one study by Kuntsche et al. (2008) compared motives across two North American (Canada and the U.S.) and one European country (Switzerland) among teenage drinkers. The structure of the scale was consistent across countries, meaning that the four types of motives are held by North American and European adolescents. Moreover, the same motives generally predicted heavy alcohol use and alcohol-related problems across the North American and European adolescents. Specifically, across countries, enhancement and coping motives were positively related to heavier alcohol use, and coping motives were additionally related to alcohol problems. Among all three countries, social motives were the most normative (in terms of being most strongly endorsed) and they were not strong predictors of either heavy drinking or alcohol problems. Interestingly, conformity motives were higher among the North American adolescents than the Swiss adolescents, and conformity motives only predicted alcohol-related problems in the two North American samples but not in the Swiss sample. This suggests that peer pressure to drink may be higher among North American than European adolescents (at least those in Switzerland), and that North American youth’s conformity motivated drinking is associated with greater negative consequences from drinking.

27A study of motives among adolescents across multiple North American and European countries is needed to expand this work and to determine, for example, how motives and their correlates might vary across adolescents from different drinking cultures within Europe (e.g., Northern vs. Southern European). For example, a recent study of Dutch adolescents showed that it was social, rather than coping or enhancement motives, that predicted heavier alcohol involvement one year later (Schelleman-Offermans, Kuntsche, & Knibbe, 2011). The authors suggested that in a wet drinking culture, such as the Dutch drinking culture, social motives might prove risky rather than protective given that the norms modeled for affiliative alcohol use would involve heavier drinking.

28Studies of cultural differences within countries are also needed in the drinking motives area. One such study examined drinking motives in a sample of Canadian First Nations adolescents using both quantitative (administration of the DMQ-R) and qualitative (interview) methods. Across both methods, an absence of social motives was observed in this cultural group. More specifically, a unique social motives factor did not emerge in factor analysis of DMQ-R items and a social motive also did not emerge in thematic analysis of responses to a qualitative interview on reasons for drinking. In contrast, the riskier drinking motives of enhancement, coping, and conformity were found to be present among adolescents in this cultural group. The authors suggested that the absence of a protective social motive for drinking may help explain the high prevalence of excessive and problematic alcohol use among Canadian First Nations adolescents (Mushquash, Stewart, Comeau, & McGrath, 2008).

29An important question is the relationship between expectancies and motives (Patel & Fromme, 2010). First, it is noticeable that usually motives to abstain are not assessed (equivalent to negative expectancies). However, a recent study found that motives to not drink do indeed predict unique variance in an American sample of adolescents (Anderson, Grunwald, Bekman, Brown, & Grant, 2011). Second, according to motivational theory, motives are a more proximal predictor of drinking than expectancies. According to Cooper and colleagues (1995), drinking to cope is predicted by expectancies to reduce tension after drinking, combined with negative emotion, and drinking to enhance is predicted by expectancies of enhancement, combined with sensation seeking. In a recent study Kuntsche and colleagues (2010) tested whether the prediction of alcohol use by expectancies was indeed mediated by motives, while using the exact same wordings for both (e.g., Expectancy: How likely is it that you get high after drinking?; Motive: How often do you drink to get high?). It was largely confirmed that the prediction of drinking from expectancies was mediated by motives to drink. Motives may provide the drive for obtaining expected effects that are believed to result from alcohol. Importantly, the sources of inter-individual variation in drinking motives among adolescents are not very well understood. However, a recent study of more than 1,400 twins and siblings from the U.K. suggested that heritable genetic influences play an important role especially in predisposing adolescents to drink to cope with negative affects (Mackie, Conrod, Rijsdijk, & Eley, 2011).

Implicit Alcohol Cognitions

30Implicit alcohol cognitions are assessed with tests that do not rely on introspection or explicit recall. Instead, different, largely behavioural techniques are used. For example, many studies have used varieties of a reaction time test, the Implicit Association Test (IAT) (Greenwald, McGhee, & Schwartz, 1998; first application to alcohol/addiction: Wiers, van Woerden, Smulders, & de Jong, 2002). This test assesses associations by comparing reaction times in two sorting conditions (e.g., alcohol/positive press left; soft-drink/negative press right vs. soft-drink/positive press left; alcohol/negative press right). Many studies have now found that varieties of this test predict unique variance in drinking, after controlling for explicit cognitions, both in adolescents and in young adults (Houben & Wiers, 2006; Thush & Wiers, 2007; Wiers et al., 2002; for meta-analyses Reich, Below, & Goldman, 2010; Rooke, Hine, & Thorsteinsson, 2008). In addition to reaction-time based tests, there are also paper and pencil tests assessing spontaneous first associations, for example with homographs (e.g., first thing that comes to mind for “draft”), and these tests also predict unique variance after controlling for explicit cognitions, in young adults (Stacy, 1997) and adolescents (Ames, Grenard, Thush, Sussman, & Wiers, 2007; Thush et al., 2007). Other tests used to assess implicit cognitive processes are tests of attentional bias for alcohol (review: Field & Cox, 2008; not much used in adolescents yet) and tests of automatic action tendencies for alcohol (Field, Kiernan, Eastwood, & Child, 2008; Wiers, Rinck, Dictus, & van den Wildenberg, 2009).

Individual Differences, Implicit Associations, and Expectancies

31As noted above, there are important boundary conditions, regarding which type of cognitive processes predict better in whom and under what circumstances. A number of recent studies have demonstrated that in adolescents with relatively weakly-developed executive functions (i.e., a weak reflective system), implicit cognitive processes are a stronger predictor of alcohol use than in individuals with relatively well-developed executive functions (Grenard et al., 2008; Houben & Wiers, 2009; Thush et al., 2008). There is also some evidence that in the latter group explicit cognitive processes are the stronger predictor (Thush et al., 2008).

32While the studies above focused on individual differences between people (strength of executive control processes), other studies have investigated individual differences within the same people. After exhaustion (or “ego-depletion”), the influence of impulsive processes becomes stronger and the influence of reflective processes becomes weaker (Hofmann, Friese et al., 2008; Hofmann, Rauch, & Gawronski, 2007; Wiers, Houben et al., 2010). After alcohol, implicit appetitive processes leading to further alcohol use become stronger (Schoenmakers, Wiers, & Field, 2008), and reflective and executive processes become weaker (for reviews see: Field, Wiers, Christiansen, Fillmore, & Verster, 2010; Fillmore & Vogel-Sprott, 2006). When people are exhausted or after some alcohol, implicit cognitive processes become better predictors, not only of further alcohol use, but also of other behaviours such as (unhealthy) eating (Hofmann & Friese, 2008), and aggression after alcohol (Wiers, Beckers, Houben, & Hofmann, 2009; for a review see: Wiers, Houben et al., 2010).

Interactions with Other Predictors and Implications

33It has been argued that cognitive processes could constitute a “final common pathway” for other risk factors, including biological factors (e.g., temperament, genetics), as well as psychosocial factors (e.g., peer-and parental influences: Goldman & Darkes, 2004; Goldman et al., 1999). Although this claim is probably too strong (it would imply that all other factors would be mediated through cognitions), there is evidence that cognitive processes interact with many other risk factors, such as genetics (explicit cognitions: Hendershot et al., 2009; McCarthy, Brown, Carr, & Wall, 2001; van der Zwaluw, Kuntsche, & Engels, 2011; and implicit cognitions: Hendershot, Lindgren, Liang, & Hutchison, 2012; Wiers, Rinck et al., 2009). Other factors that interact with cognitions are personality (Littlefield et al., 2011) and the effects of peers (partially mediated through expectancies). In addition, there is some evidence that effects of advertising on youth drinking is mediated by effects on cognitions (Stacy, Zogg, Unger, & Dent, 2004). A recent study also found that automatic approach tendencies predicted alcohol use in adolescents with relatively weak working memory and weak parental control, suggesting that control over drinking should come either from inside (working memory) or from outside (parental rules) in adolescents at-risk to escalate their drinking (Pieters, Burk, van der Vorst, Wiers, & Engels, 2012). Because alcohol-related cognitions are a central construct in the predicting of underage drinking, they have become a prime target for prevention approaches, with promising findings both regarding modification of explicit cognitions (Darkes & Goldman, 1993; Darkes, Greenbaum, & Goldman, 1998; Marlatt et al., 1998; Wiers, van de Luitgaarden, van den Wildenberg, & Smulders, 2005) and regarding modification of implicit cognitive processes (e.g., Houben, Havermans, & Wiers, 2010; Houben, Nederkoorn, Wiers, & Jansen, 2011; Schoenmakers et al., 2010; Wiers, Eberl, Rinck, Becker, & Lindenmeyer, 2011), although it should be noted that most of this work has been done in adults (see Chapter 3).

FAMILY INFLUENCES ON UNDERAGE DRINKING

34Socio-demographic factors related to the family, such as low parental education and socio-economic status, are related to an increased risk for heavy drinking in adolescence (Caldwell et al., 2008; Hawkins et al., 1992), as are economic adversity of the family, and parental divorce or death (Clark, Lesnick, & Hegedus, 1997; Green et al., 2010; Huurre et al., 2010; Kestilä et al., 2008; van der Vegt et al., 2009). In contrast to alcohol problems, however, adolescent alcohol use as such does not seem to have a simple relationship with parental education and socioeconomic status. Longitudinal studies of representative samples from different countries have yielded inconsistent results, with some studies finding a positive association, some studies a negative association, and most studies no association between parental socio-economic status and drinking among adolescents (Hanson & Chen, 2007; Melotti et al., 2011; Wiles et al., 2007).

35It has been firmly established that children of parents with alcohol and other substance use disorders are at increased risk for substance-related disorders (Alati et al., 2005; Biederman, Faraone, Monuteaux, & Feighner, 2000; Bucholz, Heath, & Madden, 2000; Lieb et al., 2002; Macleod et al., 2008; Walden, Iacono, & McGue, 2007). Consistent with a number of previous studies, Lieb et al. (2002) found that parental alcohol use disorders increased the risk of alcohol abuse and dependence in their children. In this community-based sample, both maternal and paternal alcoholism increased the risk for heavier alcohol consumption in their offspring. Parental substance use disorders have also been associated with increased use of alcohol and other substances during adolescence (Walden et al., 2007).

36In addition to the genetic influences described earlier, parental alcohol use influences adolescent drinking through a variety of direct and indirect mechanisms (Andrews, Hops, Ary, & Tildesley, 1993; Chassin, Pillow, Curran, Molina, & Barrera, 1993). Perhaps the most direct effect of parental drinking is through the role modelling of drinking behaviour. Adolescents observe the drinking practices of their parents and may match their own drinking behaviour accordingly (White, Johnson, & Buyske, 2000). In a prospective study of 432 adolescents from ages 15 to 28, parental drinking behaviour was the most significant predictor of drinking in their offspring. In addition, living in a home with a heavy drinking parent may increase access to alcohol for adolescents (Johnson, Sher, & Rolf, 1991).

37A uniquely powerful method to differentiate these possible direct influences of parental drinking from underlying genetic risk is to study families of children who have been adopted. Such studies have suggested that exposure to parental alcohol misuse is associated with increased likelihood of alcohol use in biologically unrelated adopted adolescents, indicating influences of the family environment, but that the risk related to parental alcohol dependence is mostly attributable to inherited genetic risk (King et al., 2009; McGue, Sharma & Benson, 1996).

38An additional way in which parental heavy drinking may negatively impact the child is through an effect on parenting practices (Windle, 1996). A parent’s alcohol abuse may contribute to inconsistent and unpredictable parental monitoring, including ineffective rule-setting or enforcement. Lower parental warmth or nurturance, combined with the potential for harsh punishment, can contribute to a generally less positive family environment which increases the risk for adolescent drinking (Donovan & Molina, 2011; Windle, 1996).

The Influence of Parenting Practices on Underage Drinking

39Whereas poor parenting practices can serve as a risk factor for underage drinking (Guo, Hawkins, Hill, & Abbott, 2001; Latendresse et al., 2008; Ryan, Jorm, & Lubman, 2010), good parenting can serve as a buffer against other risks for alcohol use. Four domains of parenting practice have been identified as potentially buffering the onset and level of adolescent drinking (Windle et al., 2009). Specifically, parental nurturance, parental monitoring, time spent together, and parent-adolescent communication, which reflect the degree of parental involvement with the adolescent and may affect the influence parents have on their children. High parental nurturance, as indicated by the parents’ emotional warmth and support, is associated with delay in the initiation of alcohol use and lower consumption by adolescents who drink. Parental monitoring, which is reflected by setting and enforcing reasonable rules, is inversely associated with adolescent drinking. Consistent parental enforcement of clear rules, such as setting and maintaining curfews, is associated with later onset of drinking (van der Vorst, Engels, Meeus, & Dekovic, 2006), as well as lower levels of adolescent alcohol use (Windle et al., 2009). Prospective studies further indicate that parents’ involvement in their adolescents’ lives is significantly associated with later age of drinking initiation (Ryan et al., 2010). Further, students’ perceptions of their parents’ awareness and caring of their behaviour during high school predicted adolescents’ alcohol use during their first year in college (Wetherill & Fromme, 2007). Some evidence suggests that the effects of parental monitoring may be mediated through encouragement of adolescent involvement in more conventional and pro-social activities, such as church and community (Kim & Neff, 2010). Overall, findings suggest that good parenting contributes to a later onset of drinking, and possibly lowers overall underage drinking, and that these effects may continue even after the child has left home.

40There is also growing evidence that the time that parents and adolescents spend together is associated with lower levels of adolescent alcohol use (Windle et al., 2009). Data from the National Survey of American Attitudes on Substance Abuse: Teens and Parents (2001) indicated that adolescents who participated in frequent family dinners were less likely to use alcohol, less likely to have friends who drank regularly, and less able to obtain alcohol. Lastly, good parent-adolescent communication has been associated with lower levels of adolescent drinking (Windle et al., 2009). A recent review of prospective studies of parenting practices, and adolescent alcohol use, supported the positive effects of general communication, although not alcohol-specific communication, between parent and child on the age of drinking onset and levels of adolescent alcohol use (Ryan et al., 2010). Both delayed onset of drinking and reduced levels of underage drinking were also predicted by parental disapproval of adolescent drinking, general discipline, parental monitoring, and good parent-child relationship quality. Parental support was associated with delayed onset of drinking, but not with lower levels of later alcohol use, whereas parental involvement in the child’s life predicted delayed onset of drinking but not later levels of alcohol use. It seems clear that parents exert a powerful effect on their adolescents’ decisions to drink and levels of consumption once they have begun drinking alcohol.

41Earlier drinking onset has clearly been related to the later development of alcohol-related problems (e.g., Warner & White, 2003). Yet, an important question relates to the possible effect of parental provision of alcohol on underage drinking. Studies from southern European countries have shown that parental provision of alcohol to adolescents and parentally supervised drinking may reduce the risk for adolescent drinking and alcohol-related problems (Bellis et al., 2007; Bonino, Cattelino, & Ciairano, 2005; Foley, Altman, Durant, & Wolfson, 2004; Strunin et al., 2010; Warner & White, 2003). Parental socialization of their children into appropriate use of alcohol is particularly evident when adolescents are allowed to drink alcohol with meals in a family setting (Strunin et al., 2010). Other studies in North America and Northern Europe, however, find that providing alcohol to adolescents and/or allowing them to drink in their parents’ home predicts both earlier onset of alcohol use and higher levels of later drinking (Ryan et al., 2010; van der Vorst et al., 2007). These differences could relate to whether parents provide alcohol for adolescents’ parties, which is associated with increased risk of binge drinking, or whether adolescents are drinking with their parents, which has been found to be protective against binge drinking (Foley et al., 2004). Clearly the influence of parents should be considered from a broader cultural context. In cultures with a relatively high-risk of underage binge drinking strict parenting appears to be a protective factor, but this may not be the case in cultures with a relatively low risk of underage binge drinking (Southern Europe).

42Perceived parental attitudes about drinking may be one mechanism through which provision of alcohol can serve as both a risk and protective factor in underage drinking. Provision of alcohol by parents in the home setting may convey the notion that alcohol is to be used moderately and only under certain situations. On the other hand, parental provision of alcohol for adolescent parties may convey the message that the parents condone or approve of adolescent binge drinking. Indeed parental disapproval of binge drinking can serve as a protective and buffering factor against heavy underage drinking. In a prospective study of 5,591 adolescents, annual surveys from ages 14 to 19 indicated that adolescents, of parents who consistently disapproved of substance use, were more likely to abstain from heavy drinking, even when they affiliated with peers who drank (Martino, Ellickson, & McCaffrey, 2009).

PEER INFLUENCES ON UNDERAGE DRINKING

43Peers exert one of the strongest influences on adolescents’ decisions to drink, and peer influence is among the most widely studied factors in underage drinking (Pandina, Johnson, & White, 2010). Adolescents who drink alcohol have consistently been found to also have alcohol-using peers, highlighting the social nature of adolescent drinking behaviours (Ary, Tidesley, Hops, & Andrews, 1993; Guo et al., 2001; Hawkins et al., 1992; Nation & Heflinger, 2006; Zhang, Welte, & Wieczorek, 1997). The number of heavy drinking peers in an individual’s social network is strongly and positively associated with the individual’s alcohol consumption. Likewise, membership in groups of abstainers or light drinkers is associated with lower levels of alcohol use and problems (Wechsler & Nelson, 2008). Some research suggests that, even after controlling for social, family and individual factors, the strongest influence on adolescent drinking is having friends who drink (Fergusson, Horwood, & Lynskey, 1995; Reboussin, Song, Shrestha, Lohman, & Wolfson, 2006). Others, however, suggest that the influence of peers may be overestimated (Jaccard, Blanton, & Dodge, 2005), pointing to unexplained correlated events (e.g., changing schools) and shared method variance. In addition, the influence of peers’ alcohol use seems to decrease over time and may not add much to the prediction of adolescents’ later regular drinking patterns (Poelen, Scholte, Willemsen, Boomsma, & Engels, 2007; Poelen, Engels, Scholte, Boomsma, & Willemsen, 2009).

44It is well known that the formation of peer groups is not random but an active process involving psychological and behavioural characteristics of the adolescents, which are also partly influenced by genetic predispositions (Kendler & Baker, 2007; Loehlin, 2010). Two processes that have been extensively examined in an effort to explain similarity in peer drinking are selection into heavy drinking peer groups; and socialization to drinking within the peer group (Curran, Stice, & Chassin, 1997). The process of selection indicates that adolescents choose environments or people that have certain patterns of drinking. For example, heavy drinkers may seek out peers who also drink heavily, which leads them to join more deviant peer groups. Socialization, on the other hand, suggests that adolescents adapt to their environment and friends. In other words, adolescents alter their drinking to meet expectations of their peers and they match the drinking rates of their friends. There is general agreement that both processes occur and that there are reciprocal relations between selection and socialization processes in the development of adolescents’ alcohol use patterns (Curran et al., 1997; Read, Wood, & Capone, 2005; White, Fleming, Kim, Catalano, & McMorris, 2008).

45There is also some evidence that the relative importance of these processes may shift across adolescence. Developmental trends in selection and socialization were studied in three cohorts of adolescents in Sweden, who represented early adolescence (ages 9-11), middle adolescence (ages12-14) and late adolescence (ages 15-18) (Burk, van der Vorst, Kerr, & Stattin, 2012). Peer selection was found to be more important than socialization among early adolescents, whereas both processes contributed to similarity in peer drinking in middle and late adolescence. Peer socialization was not evident until middle adolescence and remained an important influence on alcohol use through late adolescence. Nevertheless, the overwhelming evidence supports the importance of both selection and socialization in the observed similarity of adolescent peer drinking.

46A special factor related to peer influence that has received considerable attention is the relationship between adolescent sports participation and alcohol use. Participation in team sports has especially been found to be associated with elevated levels of alcohol use and problems in several studies (e.g., Lorente, Souville, Griffet, & Grélot, 2004; Mays & Thompson, 2009; Wichstrom & Wichstrom, 2009). A recent review of 29 studies examining the relationship between sports participation and alcohol use in high school and college students found that in 22 of those studies individuals who participated in sports reported higher levels of drinking than those who did not participate, while seven studies did not find this relationship (Lisha & Sussman, 2010). However, another review, focusing on the methodology of the studies looking at this association, concluded that various definitions and measures of sports participation have been used, and that the failure to differentiate between relevant contextual factors may have confounded the relationship (Mays, Gatti, & Thompson, 2011). Indeed, several studies have reported mixed results and complex relationships between sports and alcohol use, depending on, for example, age, sex, type of sport, and participation in other activities than sports (Mays & Thompson, 2009; Mays et al., 2010a; Moore & Werch, 2005; Peck, Vida, & Eccles, 2008; Peretti-Watel, Beck, & Legleye, 2002). However, some studies finding a positive association have indicated that differences in perceptions of peer drinking and drinking-related risks may moderate the relationship between sports participation and alcohol use (Mays et al., 2010b; Wetherill & Fromme, 2007; Yusko, Buckman, White, & Pandina, 2008).

Direct and Indirect Peer Influences on Underage Drinking

47There are a number of possible direct and indirect mechanisms through which peers exert their effects on adolescent drinking. Direct peer influences include buying and providing alcohol to one’s friends, offering drinks, and encouragement to drink or to get drunk (Borsari & Carey, 2001). When alcohol is widely accepted and drinking is expected, there may be overt peer pressure to drink and, possibly, to drink faster and more than one anticipated. Drinking games, for example, have become a popular means by which peers encourage the rapid consumption of alcohol, often to high levels of intoxication (Nagoshi, Wood, Cote, & Abbit, 1994). Although the research literature on direct peer influences is modest, offers of drink have been associated with alcohol use and problems (Wood, Read, Palfai, & Stevenson, 2001). Personality factors and group context are likely to influence the ability of adolescents to refuse offers to drink. For example, those adolescents who are more socially confident, and those within an established peer group, are better able to refuse drinks, whereas those who are less secure may accept offers of drinks in an attempt to fit in with a new peer group (Borsari & Carey, 2001). Resistance to direct peer influence may, therefore, be influenced by individual differences in personality, motivations, and social skills.

48Indirect peer influences on adolescent drinking include the role modelling of alcohol use by peers (Borsari & Carey, 2001). As with the observation of parental drinking, adolescents, who see their friends or peers drink, may learn to imitate that behaviour (White, Bates, & Johnson, 1991). Experimental studies, using confederates to model drinking behaviour, have shown that individuals will match or model the drinking rate and amount of the confederate (Borsari & Carey, 2001; Quigley & Collins, 1999). Individuals who are paired with heavy-drinking models consume more than those with a light-drinking model, and this effect is especially strong when the confederate behaves in a warm and friendly manner (Collins, Parks, & Marlatt, 1985). It is easy to see an extension of these laboratory findings to the actual peer drinking context, when being in the presence of friendly, heavy-drinking peers is likely to encourage drinking by the adolescent.

49A second, and more recently studied, indirect influence of peers on underage drinking is perceived peer norms (e.g., Pandina et al., 2010; Perkins & Craig, 2003). Perceived drinking norms of peers are strongly associated with both adolescent and young adult drinking (e.g., Pandina et al., 2010; Perkins & Wechsler, 1996; Song, Smiler, Wagoner, & Wolfson, 2012). Alcohol-related norms have been differentiated into descriptive and injunctive drinking norms (Borsari & Carey, 2001). Descriptive norms are the person’s beliefs about how much and how often their peers drink alcohol, whereas injunctive norms reflect the individuals’ beliefs about their peers’ approval of drinking.

50An increasingly large body of research, primarily on U.S. college students, provides evidence that both descriptive (Baer, Stacy, & Larimer, 1991; Stappenbeck, Quinn, Wetherill, & Fromme, 2010) and injunctive norms (Neighbours, Lindgren, Knee, Fossos, & DiBello, 2011) are associated with underage drinking patterns (Borsari & Carey, 2003). In fact, social norms are among the best predictors of underage drinking (Neighbors, Lee, Lewis, Fossos, & Larimer, 2007; Patel & Fromme, 2010) and may even influence the individuals’ alcohol use when they are portrayed on Facebook (Litt & Stock, 2011). In fact teens ages 12-17 who see pictures of other teens getting drunk or having passed out on social networking sites are twice as likely to drink (National Center on Addiction and Substance Use, 2011). Adolescents’ increased involvement with mass media has led some to suggest that social media may serve as a “super peer” (Windle et al., 2009, p. 33) by conveying alcohol-related messages.

51Again, focusing primarily on college students, the influence of perceived norms appears to vary by the reference group (Neighbors et al., 2008; Larimer et al., 2011). Injunctive norms, or perceived approval of drinking, are positively associated with one’s own drinking when they are about one’s friends, but are negatively associated when they are about more distal referents, such as the “typical student” (Neighbors et al., 2008). Injunctive norms are also associated with the experience of drinking-related consequences, especially when close friends or parents are the source of the perceived norm (LaBrie, Hummer, Neighbors, & Larimer, 2010).

52Descriptive norms, which are beliefs about how often and how much others drink, are consistently and positively associated with an individual’s own drinking (e.g., Borsari & Carey, 2001; Neighbors et al., 2007). Yet there is compelling evidence to suggest that individuals tend to over-estimate the amount that their peers drink, perhaps leading to an increase in drinking in an effort to match the misperceived norms (Baer et al., 1991; Perkins, Meilman, Leichliter, Cashin, & Presley, 1999). Social norms-based interventions are designed to correct these misperceived norms in an effort to reduce underage drinking among both high school (e.g., Haines, Barker, & Rice, 2003) and college students (e.g., Agostinelli, Brown, & Miller, 1995; Perkins, Haines, & Rice, 2005; see Chapter 3 for details on prevention strategies targeting social norms).

53The influence of peers increases during early adolescence when children are given more autonomy from parents (Windle et al., 2009). Peer influence peaks around ages 11 to 13 (Windle et al., 2008), and then appears to decline as the adolescent matures. For example, in a prospective study, same and opposite gender peer dyads were assessed from ages 19 to 27 years (Andrews, Tildesley, Hops, & Fuzhong, 2002). At the earlier ages, both same- and opposite-gender peer use predicted the target participant’s binge drinking. However, at later years there was a concurrent, but not a prospective, association between both same and, opposite gender friend’s alcohol use and that of the participant. Thus, the strong effect of peers on adolescent drinking had subsided by young adulthood. The authors further suggested that the findings support the selection and maintenance of friends with similar drinking patterns, and that peers might serve as either a risk or protective factor as the individual moves into young adulthood. Because selection of peers in adolescence is such an important and potentially long-lasting influence, prevention programmes might consider the inclusion of the friends and partners of adolescents.

CULTURAL, CONTEXTUAL, RELIGIOUS AND ACADEMIC INFLUENCES ON UNDERAGE DRINKING

Cultural Attitudes about Drinking and Drunkenness

54Since the classic examination of alcohol intoxication as “time out” by MacAndrew and Edgerton (1969), it has been clear that different cultures’ and subgroups within cultures’ have distinct views about drinking and drunkenness. What is perfectly acceptable, and even expected, in one culture, for example, may be completely unacceptable in others. Cultural attitudes about drunkenness by underage youth include the view that it is a warning sign or symptom of problem drinking or alcoholism (Finn, 1979). Yet, adolescent intoxication is also viewed as a motivated behaviour that includes the desires to celebrate an occasion, escape responsibilities, relieve negative feelings, or justify sexual misconduct (Critchlow, 1983; Finn, 1979; Maggs, 1997).

55The Healthy People 2010 report identified attitudes about alcohol as a strong contributing factor to underage drinking (USDHHS, 2010). The report indicated that the perception that alcohol use is socially acceptable is associated with the fact that 80% of American youth drink alcohol before their 21st birthday, whereas the lack of social acceptance was associated with lower rates of use. Consequently one of the objectives of the Healthy People 2010 report is to increase the proportion of youth who disapprove of people having one or two drinks a day (USDHHS, 2010). A generally permissive societal attitude toward drinking, through the media, parents, and peers, is partly attributable for the current substance use problems among adolescents (National Center on Addiction and Substance Use, June 2011). Whereas the report suggests that most parents do not explicitly condone substance use among adolescents, the messages they convey through their own use of alcohol can be interpreted as ambivalent, tolerant, or providing implied approval. In their report on American attitudes towards substance use, teens of parents who disagree about the messages they convey to their teens about the use of alcohol are twice as likely to drink (31% versus 14%) (National Center on Addiction and Substance Use, August 2011).

56In a recent cross-sectional survey-study involving five states in the U.S., perceived support for drinking, regardless of the source, was associated with greater alcohol involvement and alcohol-related behaviour (Song et al., 2012). Among both drinkers and non-drinkers, the belief that they would be punished for drinking (either by school officials or police) was associated with lower odds of all alcohol-related behaviours. However, community consequences were less important among adolescent drinkers, who believed that school officials and police were unlikely to punish them for drinking, than among non-drinkers. It seems clear that consistent messages about the unacceptability of drinking by youth, whether from parents, schools, or the media, is a necessary step toward reducing the prevalence of underage drinking.

Contextual Factors and Underage Drinking

57Neighbourhood influences in the U.S. The role of neighbourhood effects on adolescent alcohol use is part of an area of burgeoning research, exploring the differential effects of area-level socio-economic factors on adolescent health and behavioural outcomes. Predicated on social disorganization theory (Shaw & McKay, 1969), research on neighbourhoods and crime in the U.S. has found that neighbourhood-level characteristics, such as low socio-economic status (SES), ethnic heterogeneity, and residential mobility, negatively affect social organization and result in an increased rate of crime and delinquency (Sampson, Morenoff, & Gannon-Rowley, 2002). As well, a substantial body of work seems to suggest that substance use patterns vary across neighbourhoods, although the findings are mixed as to whether neighbourhood social disadvantage is related to increased substance use, including alcohol use (Karriker-Jaffe, 2011; Sampson et al., 2002). The mixed findings are due, in part, to differences in the definition of a neighbourhood, the measurement of SES, study designs, and outcome measures. Whereas some studies have shown a positive association between neighbourhood disadvantage and adolescent alcohol use, others show that higher SES neighbourhoods can also lead to increased alcohol use. Additionally, some studies have either found no effects of SES on alcohol, or revealed mixed results based on the measure of SES (Karriker-Jaffe, 2011). Taken together, the research suggests that both low and high SES neighbourhoods may be associated with risk factors for increased adolescent alcohol use. While lower SES neighbourhoods suffer from lack of proper infrastructure, various levels of economic disadvantage, and opportunities for youth, higher SES neighbourhoods are characterized by greater adolescent disposable income, lax parental monitoring, intense competitive pressure, and social norms that condone frequent alcohol use (Gardner, Barajas, & Brooks-Gunn, 2010). All these factors may potentially contribute to higher prevalence of alcohol use among adolescents.

58Leventhal and Brooks-Gunn (2000) provide a framework for understanding how neighbourhood structure influences individual-level outcomes. They propose that structural factors, such as institutional resources, relationships, and collective efficacy, may mediate the relation between neighbourhood SES and adolescent substance use. The differential nature of these components in advantaged and disadvantaged neighbourhoods provides a way to understand the particular structural factors that drive alcohol use. For instance, whereas schools in low SES neighbourhoods might lead to alcohol use as a result of poor quality and risk of failure, high SES schools are characterized by intense scholastic and achievement pressure (Gardner et al., 2010). The literature, taken primarily from the U.S., clearly suggests that the school environment has a definite impact on adolescent alcohol use. Risk for alcohol use among students is lower in schools where less students drink and norms are less favourable to use and where the school climate promotes bonding and consistent enforcement of substance use policies (Ennett & Haws, 2010). Similarly, the quality and availability of neighbourhood group activities, such as youth groups, can be instrumental in providing adolescents with pro-social activities and keeping them away from substances. Generally there is a difference between the low and high SES neighbourhoods in terms of the quality and quantity of such organizations, where the former, compared to the latter, tend to have fewer organized youth activities.

59Differences in family functioning across neighbourhoods might also account for neighbourhood effects on adolescent drinking (Gardner et al., 2010). For example, parents in high SES neighbourhoods have been shown to practice lax monitoring because the environment is relatively safe. Lax parental monitoring in turn can increase the risk for adolescent drinking. Alternatively, higher rates of family stress and conflict that occur more often in disadvantaged than non-disadvantaged neighbourhoods tend to be positively related to alcohol and substance use.

60Another key mechanism accounting for the association between neighbourhoods and adolescent deviant behaviours is collective efficacy, which is characterized by social ties and support among neighbours (Sampson et al., 2002). Higher collective efficacy has generally been found to be protective against deviant behaviours, including adolescent substance use. Nonetheless, studies have found low collective efficacy in both high and low SES neighbourhoods. Whereas neighbourhood disadvantage in low SES neighbourhood predicts lower collective efficacy, studies have also found low collective efficacy in some high SES neighbourhoods due to the high premium placed on privacy, which precludes social cohesion (Gardner et al., 2010).

61Overall, the findings are equivocal on whether adolescent alcohol use is more prevalent and frequent in lower or higher SES neighbourhoods. Neighbourhood racial segregation patterns in the U.S. and racial differences in substance use (see Chapter 1) further complicate this picture (Cronley et al., 2012).

62European and cross-cultural neighbourhood influences. The relationship between characteristics of the neighbourhood and adolescent alcohol use may well vary across countries and cultures. The recent systematic review of associations between area-level socioeconomic status and substance use outcomes, by Karriker-Jaffe (2011), included studies from North America (U.S. and Canada), Europe (U.K., Finland, and the Netherlands), and New Zealand. As summarized above, the findings related to adolescent alcohol use outcomes were inconsistent. A formal analysis of study characteristics indicated that although fewer associations with SES were observed in non-U.S. studies, these differences among the total of 180 studied effects could have arisen by chance.

63Two recent European studies, not included in the review by Karriker-Jaffe (2011), further illustrate the inconsistencies related to neighbourhood SES. Caria and colleagues (Caria, Faggiano, Bellocco, & Galanti, 2011) reported findings from the EU-Dap prevention programme (see Chapter 3). The study sample included 5,541 students 12-14 years of age from 143 schools in 7 European countries (Austria, Belgium, Germany, Greece, Italy, Spain and Sweden). Schools within each regional study center were classified as being of high, medium or low SES, based on indicators such as unemployment rate and average income in the school district. An analysis across these European countries found that at study baseline students from high SES schools were more likely than students from other schools to drink at least monthly, while students from low SES schools were more likely to report recent episodes of drunkenness and alcohol-related problem behaviours (Caria et al., 2011). However, the practical significance of these small differences (absolute differences were less than three percentage points) is questionable.

64Contrasting these findings related to neighbourhood SES, another European study conducted longitudinal analyses in a representative sample of 863 Dutch adolescents and found no association between average neighbourhood income (based on official data from Statistics Netherlands) at an average age of 14.9 years and frequency or quantity of alcohol use four years later (Ayer et al., 2011). Further, neighbourhood characteristics had no moderating effect on the predictive associations between adolescent personality profiles and drinking outcomes, leading the authors to suggest that proximal risk factors such as personality may be more strongly related to drinking behaviour than variation among neighbourhoods (within cultures).

65However, information on neighbourhood characteristics may still be useful when studying individual-level risk factors for alcohol outcomes. As an example, Lemstra and colleagues (2009) studied the association between Aboriginal cultural status and lifetime drunkenness in a school survey of 4,093 children and adolescents aged 9 to 15 years in the city of Saskatoon, Saskatchewan in Canada. The authors found that the increased risk for drunkenness among Aboriginal youth (crude odds ratio = 3.52) diminished to non-significance (adjusted OR = 0.80) when individual-level and neighbourhood variables were included in the analysis. Low neighbourhood income was among the risk factors significantly associated with drunkenness in the final, fully adjusted model, as were age, skipping school, being bullied, low self-esteem, and having substance-using friends (Lemstra et al., 2009).

66Urban vs. rural residence and adolescent alcohol use. In addition to socio-economic factors related to neighbourhoods, studies have compared adolescents’ alcohol use in urbanized and rural areas of residence. Theoretically, both urban and rural residence could be related to increased risk for adolescent alcohol use, albeit for different reasons. In more urban areas, it may be easier for adolescents to access alcohol and other substances, and societal control over drinking may be weaker. On the other hand, the variety of leisure activities available for youth may be more restricted in rural areas, and the more homogenizing cultural influences may lead to drinking being more normative. Correspondingly, recent representative surveys in European countries have found both urban (Iceland: Heimisdottir, Vilhjalmsson, Kristjansdottir, & Meyrowitsch, 2010; Finland: Winter, Karvonen, & Rose, 2002) and rural (Germany: Donath et al., 2011; Denmark: Stock et al., 2011) residence to be associated with higher frequency of drinking and drunkenness among adolescents. Existing evidence also suggests that urban vs. rural residence is not associated with the prevalence of alcohol use disorders among European adult population (Rehm, Room, van den Brink, & Jacobi, 2005). Studies from North America have indicated that although prevalence of heavy and binge drinking in the adult population is somewhat higher in urban areas, the increase in prevalence between 1995 and 2003 was steeper in more rural areas (Jackson, Doescher, & Hart, 2006). Recent studies conducted in the U.S. and Canada have suggested that adolescents living in more rural areas tend to drink more frequently and increase their drinking more rapidly than do adolescents of urban residence (Jiang, Li, Boyce, & Pickett, 2008; Martino, Ellickson, & McCaffery, 2008). However, the dichotomy between urban and rural is often ambiguous, and Martino and colleagues, in fact, found that youth residing in the most rural areas had lower risk than youth from “micropolitan” areas (medium and large towns).

67Taken together, the evidence regarding the role of urban vs. rural residence in relation to adolescent alcohol use behaviours is inconsistent. There may be genuine associations with adolescent drinking, and these associations may differ across countries, but it is crucial to differentiate the effects of place of residence from population characteristics that could explain the association. For example, the higher levels of abstinence and lower frequency of drinking among drinkers in rural as compared to urban Finnish adolescents were found to be partly explained by differences in religiosity between rural and urban families (Winter et al., 2002).

Religiosity and Adolescent Drinking

68Children who are more religious and who attend religious services are less likely to begin drinking at an early age (e.g., Donovan & Molina, 2011). However, the mechanisms that explain this association are poorly understood. Religiosity is often thought to be comprised of two components, the importance or value placed on religion, and participation in religious practices, such as attending religious services (Walker, Ainette, Wills, & Mendoza, 2007). Whereas some studies find that both aspects of religiosity are inversely associated with adolescent drinking (e.g., Nonnemaker, McNeely, & Blum, 2003), others indicate that only personal values about religion makes a unique contribution to substance use (Walker et al., 2007). The extent to which religiosity affects adolescent alcohol use appears to depend upon the outcome measures (e.g., onset, frequency, or quantity consumed) and whether other influences (e.g., peer, family, school) are simultaneously considered (Mason & Windle, 2002). For example, the effects of religious importance and religious practices were examined in a one-year longitudinal study of 1,175 middle-adolescent boys and girls in the U.S.. Controlling for age and gender, religious salience was a prospective predictor of the prevalence of drinking, whereas religious attendance predicted the amount consumed per drinking occasion. When peer, family and school variables were added to the model, however, the effect of religious salience on frequency of drinking became non-significant, whereas the effect of religious attendance on quantity consumed remained significant.

69These findings are consistent with the possibility that the association between religiosity and lower risk for underage drinking may be explained by environmental or genetic factors (Harden, 2010). In a study of twin and sibling pairs from the National Longitudinal Study of Adolescent Health, analyses indicated that environmental differences between families completely accounted for the association between religiosity and later age of first drink. Thus, religiosity may serve as a proxy for other important family, personal, or social influences on drinking (Harden, 2010). For example, religiosity is associated with more conventional values (Mason & Windle, 2002) and may reduce the effects of life stress (Chawla, Neighbors, Lewis, Lee, & Larimer, 2007; Wills, Yaeger, & Sandy, 2003), thereby decreasing adolescent drinking.

Academic Achievement and Motivations

70School misbehaviour, such a skipping class, is widely recognized as a correlate of problematic drinking among underage youth (Wechsler, Dowdall, Davenport, & Castilo, 1995). Conversely, placing a high value on academic achievement can serve as a protective factor for alcohol use and related behaviours (Bryant, Schulenberg, O’Malley, Bachman, & Johnston, 2003). For example, college-bound high school seniors who had stronger academic motivations did not intend to drink heavily in college (Rhoades & Maggs, 2006). Indeed, in a longitudinal study of 1,447 first-time college students, those who had higher academic motivations drank less across five years of surveys (Vaughan, Corbin, & Fromme, 2009). Nevertheless, social motivations had the strongest influence on alcohol use during the transition from high school to college, with academic motivations having a relatively weaker effect on drinking.

CROSS-NATIONAL AND CROSS-CULTURAL COMPARISONS OF RISK AND PROTECTIVE FACTORS

Comparisons within Europe

71Risk and protective factors for underage drinking have been extensively investigated in separate studies in different parts of Europe. However, differences among European countries in the factors that modify an individual’s likelihood of engaging in alcohol use behaviours have only rarely been formally assessed. As the previous chapter indicated, there is considerable variation between adolescents in different European countries in drinking frequency, quantity, and levels of intoxication. Against this background, it would be important to also compare risk and protective factors and their association with drinking outcomes across European countries.

72Potential sources of cross-national information on risk factors are the ESPAD and HBSC surveys, described in the previous chapter. Using the 1999 ESPAD survey data from six countries (Bulgaria, Croatia, Greece, Romania, Slovenia and U.K.), Kokkevi, Richardson, Florescu, Kuzman and Stergar (2007) investigated the role of individual-level factors such as antisocial behaviour and depression as well as factors related to friends, siblings and parents. The authors found that adjusting for country most of the studied factors were associated with using alcohol more than ten times during the last thirty days. Relatively strong associations were observed for older siblings’, as well as friends’, smoking, alcohol and cannabis use, low parental monitoring, and school truancy, with antisocial behaviour, anomie (lack of social norms), and depressive mood also associated with frequent drinking in both boys and girls. In a separate analysis, few statistically significant interactions between the risk factors and country of study were observed, suggesting a similar role for these factors in these six European countries (Kokkevi et al., 2007).

73A special topic of the 2007 HBSC survey was inequalities in adolescent health and health-related behaviours, including socio-economic differences (Currie et al., 2008). Thus, the HBSC study report also included information on associations between family affluence and alcohol use behaviours in different European countries. The associations of family affluence with weekly drinking, having been drunk on two or more occasions, and age at first drunkenness were varied: for each of the outcomes, an association with family affluence was observed in less than half of the countries, and there was no easily discernible pattern of differences between countries. In the countries where an association was found, higher family affluence was generally associated with higher rates of weekly drinking and drunkenness. A similar pattern of mixed findings emerged from analyses of the 2001/2002 HBSC survey data with regard to family affluence, parental occupation and SES (Richter, Leppin, & Nic Gabhainn, 2006; Richter et al., 2009).

74In addition to directly analyzing comparable cross-national data, information on risk factors in different European countries can be gauged from meta-analytic and systematic reviews of risk factors for adolescent alcohol use. Such reviews attempt to identify and create a synthesis of all available studies that are relevant to the topic, and they can also assess between-study heterogeneity. A systematic review of longitudinal studies on parenting-related factors and adolescent alcohol use identified 77 studies, of which 16 were European (Ryan et al., 2010). The authors classified the parenting factors into 12 different variables. Most European studies included data on parents’ alcohol use, and there was some inconsistency in the European findings; altogether seven European studies found a positive association between parental alcohol use and later adolescent drinking (three studies were conducted in the Netherlands, two in Finland, one in the U.K., and one in Germany), whereas two studies found the opposite result, a negative association (one study from the Netherlands, one from Iceland). In addition, two Dutch studies included in the systematic review found contradictory results concerning the association between quality of parent-child relationship and adolescent alcohol use (Ryan et al., 2010). This heterogeneity of findings even within a single country suggests that comparing risk factors between different countries is not an easy task, and the differences found may be due to chance or be related to methodological differences in, for example, sampling and instruments used in data collection. A similar conclusion can be reached based on the findings of a systematic review of longitudinal studies on SES in childhood and later alcohol use (Wiles et al., 2007). This analysis identified nineteen relevant articles, of which eight were based on European samples. As was the case in HBSC data, there was little consistent evidence of an association between childhood SES and later alcohol use, and also the included European studies (three studies from Finland, three from Sweden, and two from the U.K.) reported both positive and negative as well as no associations.

Comparisons between Europe and North America

75The influence of parents and peers has been compared in only a few North American and European studies. The general consensus is that peers exert similar influences on adolescent drinking in both continents (e.g., Adler & Kandel, 1982; Agostinelli & Grube, 2003; Link, 2008), and that deviant peers and perceived peer drinking are significantly and positively associated with adolescent alcohol use (Bank et al, 1985; Link, 2008). Among adolescents (ages 12-18 years) in Australia, France, Norway, and the U.S., peer modelling and peer norms had significant effects on adolescent drinking in all four countries (Bank, 1985).

76Data from the 2005/2006 HBSC survey of 11,277 adolescents (ages 11.5 to 13.5 years) in Greece, Scotland, Switzerland, and the U.S. also found that perceived peer and adolescent alcohol use were positively associated in all countries (Farhat et al., 2012). Interestingly, an interaction effect was found, such that the association between perceived peer drinking and own monthly alcohol use was weaker in Greece than in other countries. The authors hypothesized that this interaction reflected a difference in the drinking culture, specifically the more tolerant attitudes toward adolescent wine-drinking in Greece compared to the other countries. When the analysis was repeated excluding wine from the alcohol use outcome, no differences among the countries in the association between own and peer drinking were observed. The authors concluded that the association between peer and adolescent drinking may depend on country-level variation in contextual factors of alcohol use (Farhat et al., 2012).

77Another cross-cultural study surveyed adolescents from three unique cultural contexts (Caldwell, Weichold, & Smith, 2006); specifically post-apartheid South Africa (n=2,342), post-communist Germany (n=278), and a rural U.S. setting (N=629). Across these very diverse cultural and socio-economic samples, peer influence was positively associated with alcohol use for these adolescents, leading the authors to conclude that “peer influence is a universal influence on substance use” (p. 264).

78Likewise, parental influence on adolescent drinking is found in both Europe and the U.S. In a comparison of adolescents in France, Israel, and the U.S, parents’ drinking (along with peer use) was a more powerful predictor of alcohol use than the adolescents’ personal attitudes or demographics (Adler & Kandel, 1982). Across these countries, which have quite different patterns of alcohol use, parental tolerance of drinking as well as the parents’ own drinking were associated with increased adolescent alcohol use in all three samples. The effects of parents were stronger, however, among Israeli adolescents than among the French, and were much stronger in Israel and France than in the U.S..

79In another study of adolescents in Australia, France, the U.S. and Norway, parental modelling had significant effects on the alcohol use of adolescents in Australia and France, but not in Norway or the U.S. (Bank et al., 1985). Further, parental norms were significantly associated with adolescent drinking in Australia and the U.S. but not in France or Norway. Thus, for French adolescents, parents’ drinking behaviour has greater influence than the messages their parents provide. The authors also suggested that Norwegian parents may be less likely to provide strong messages about drinking than parents in Australia or the U.S.. Further, a comparison of American and Finnish parents indicated almost unanimous agreement that parents should not drink in the presence of small children (Raitasalo, Holmila, & Mäkelä, 2011), yet 38% of Finnish parents indicated that drunkenness in the presence of small children was acceptable as long as someone remained sober to take care of the children. These apparently contradictory views arise when norms are in conflict (Room, 2011). Moreover, in the absence of strong and consistent messages and modelling by parents, adolescents look to their peers for decisions about drinking.

80In a more general comparison of risk and protective factors in the U.S. and Netherlands, similar factors were found in both countries (Oesterle et al., 2011). One difference, however, was that Dutch youth perceived their parents as having more favourable attitudes toward alcohol use, and these attitudes were more strongly associated with adolescents’ regular drinking in the Netherlands than in the U.S. As was described in the section comparing different European countries, there appears to be nuanced differences in the effects of parents on adolescent drinking in Europe and the U.S..

81Studies of alcohol expectancies between the U.S. and European countries have often focused on Ireland, possibly because Ireland has a high proportion of both abstainers and alcohol dependent individuals, in contrast to the U.S. and Canada where the distribution of consumption is less extreme (Young & Oei, 1993). In comparison to adolescents in the U.S., Irish adolescents expected less social benefit, less improvement of cognitive and motor functioning and less sexual enhancement, but greater aggression from drinking (Christiansen & Teahan, 1987). In a study of Irish and American college students, Irish, compared to American, men expected more camaraderie and cheerfulness from drinking. Irish women indicated that they used alcohol to relieve sexual inhibitions (Teahan, 1987), whereas American women endorsed more tension reduction and disinhibition expectancies (Teahan, 1987).

82In a more recent study of college drinking and consequences among American and Swedish first year students, expectancies were similar among the men, but American women scored higher than Swedish women, especially on aggression expectancies (Stahlbrandt et al., 2008). In both countries, positive alcohol expectancies were significantly associated with harmful drinking, but the association was stronger among Swedish men than American men. In a study of college students from Cyprus and the U.S., positive and negative alcohol expectancies were predictive of alcohol use in both cultures (Strahan, Panayiotou, Clements, & Scott, 2011). Students from Cyprus, however, endorsed fewer positive and more negative expectancies than students in the U.S.. Lastly, using data from the Gender, Alcohol and Culture International Study (GENACIS) three indicators of positive expectancies for social, relational, and intimate dimensions were studied in 11 countries (Nigeria, Uganda, India, Japan, the Czech Republic, Spain, Sweden, the United Kingdom, the U.S., Argentina, and Costa Rica). Despite these quite varied cultures and continents, the three expectancy dimensions formed generally similar patterns of endorsement (Bergmark & Kuendig, 2008). The most striking findings from this study were not by country, but by gender. As with peer influences, it appears that the effects of alcohol expectancies on underage drinking is generally, similar in the U.S. and in Europe (and other countries). Generally both men and women who expected alcohol to make it easier to be open with others (especially their partners) drank more than those who did not hold those beliefs. In addition, women who believed alcohol made social life easier and sexual activity more pleasurable drank more than those women who did not hold those beliefs.

CONCLUSIONS

83Risk and protective factors range from the biological (genetic) level to the cultural level, with relevant influences, at many different levels of description (genetics and personality, cognitions, family and peer influences and socio-cultural influences). Two important characteristics of risk and protective factors are their causal status and whether they can be changed (malleability). It is important to consider whether they are mere correlates, or whether there is evidence that the risk or protective factor is involved in the causal pathway towards drinking. In terms of malleability, whereas genes and SES are difficult to change, some psychological characteristics can successfully be changed leading to positive outcomes. This will be explored further in the next chapter on prevention. While the more distal factors such as genetic factors have been briefly summarized, we have focused here on the psychological and social factors that are amenable to change.

84Personality. Both externalizing and internalizing personality characteristics confer risk for underage drinking. Externalizing traits, or the tendency towards impulsive, disinhibited behaviours and sensation seeking, are associated with earlier onset of drinking and a greater likelihood of later alcohol-related problems. Self-regulation, or the ability toward self-control, can serve as a protective factor. Whereas poor self-control in childhood has been associated with adolescent substance use and problems, good self-control is associated with delayed onset of substance use and can buffer against increases in substance use in the face of peer use. Internalizing personality characteristics, such as introversion-hopelessness and anxiety sensitivity, are risk factors for heavy drinking and alcohol-related problems, respectively, among underage drinkers. Both types of internalizing characteristics may exert their influence primarily through drinking motives or reasons for drinking. For example, introversion-hopelessness may manifest itself through drinking to cope with feelings of depression, and anxiety sensitivity may operate through drinking to decrease negative emotions and peer pressure. The interface between personality characteristics and reasons for drinking illustrates the association between more distal risk factors, such a genetically-based personality traits, and more proximal risk factors, such as drinking motives, outcome expectancies, and implicit associations.

85Alcohol-related cognitions have been argued to constitute a “final common pathway”, mediating (some of) the effects of other influences. It has also been demonstrated that it is important to distinguish between more automatic or implicit cognitive processes and more explicit processes, and that both ot them uniquely contribute to adolescent drinking. In fact, they are moderated by executive control and self-regulation capacities (i.e., there is a stronger influence of implicit cognitions in adolescents with weak control capacities and a stronger influence of explicit cognitions in adolescents with good control capacities). Explicit cognitions, such as alcohol expectancies, drinking motives, and perceived norms may all be malleable by a variety of interventions, making them particularly interesting candidates for preventive interventions. In addition, novel interventions have targeted implicit cognitive processes, with encouraging results (see Chapter 3).

86Parenting. Parental alcoholism and other parental characteristics, such as low education and SES, are related to an increased risk for heavy drinking in adolescence, yet the non-genetic influences are complex and interact with environmental factors. For example, neighbourhood characteristics are confounded with low SES and ethnic heterogeneity that contribute to increased rates of crime and delinquency. Yet, both economic disadvantage and affluence have been found to contribute to underage drinking. Both may operate through social norms, school climate, and differing values on achievement. High value on academic achievement can serve as a protective factor for alcohol use and related behaviours, but excessive pressures to succeed in academics or sports can lead to stress that exacerbates underage drinking. A good balance in economic resources, social opportunities, and achievement values are most likely to help prevent underage drinking and related problems.

87Parental alcohol use has both direct effects, via modelling of drinking behaviour and availability of alcohol in the home, and indirect effects on the drinking behaviour of their children. The indirect effects of parental drinking can manifest in poor parenting practices, such as failure to effectively monitor or set rules for the adolescent, which can result in earlier onset and heavier alcohol use. Conversely, good parenting practices, including monitoring, nurturance, and consistent rule enforcement, can serve as protective factors against underage drinking. Perhaps the most powerful effect of parents on the alcohol use of their adolescents operates through the messages parents convey. Consistent and uniform parental disapproval of underage drinking has been found to be one of the strongest deterrents to underage drinking across both North America and Northern Europe. Yet, it should also be noted that the influence of parents’ behaviours and attitudes appears to vary across different cultures, with evidence for strict rule-setting regarding alcohol coming from North America and Northern Europe, while the scarce evidence from Southern Europe appears to indicate a positive role for alcohol-related socialization in the family.

88Peers. Peer influence is one of the most consistent correlates of underage drinking. Even after controlling for individual and family influences, having heavy drinking peers is the strongest predictor of heavy drinking among adolescents. Peers can have both direct and indirect influences on adolescent drinking. Peers can provide alcohol and model drinking behaviour, but more importantly, they can encourage heavy drinking. Peers exert their influence on adolescent drinking through the processes of both selection and socialization, with the importance of these social processes changing across development. Younger adolescents appear to select peers based on a peer’s alcohol use. Once adolescents have joined a peer group that drinks alcohol, they are further socialized into heavier drinking. Because peer selection is especially important for younger adolescents, parents should be active in monitoring and influencing their adolescent’s selection of friends during the early adolescent years. Once older adolescents are established in a peer group, it is important that parents remain involved in their adolescent’s activities, meeting their friends and monitoring their adolescent’s social activities. Because parental involvement is not a panacea, adolescents must also learn to cope with peer pressure, which is an important challenge.

89Summary. Evidence supports the strong effects of personality traits, peer influence, and the early and continued influence of parents on their offspring’s alcohol use. In all of these cases, evidence suggests that the associations are not fully causal but also reflect effects of genetic risk and environmental factors. Furthermore, the influence of parents’ behaviours and attitudes seems to vary across different cultures, with some countries being more permissive than others. Although the idea of a “final common pathway” may not be fully explanatory, alcohol-related cognitive processes are important in predicting underage drinking, and appear to be more easily changeable than a number of more distal risk factors at different levels of description (e.g., genetics, neighbourhood, etc.). Lastly, with a few exceptions, there was considerable similarity in the risk and protective factors between North America and Europe and within Europe. Peers are the most consistently identified potential risk factor across the different geographic locations. The most notable cross-national inconsistencies relate to the potential influence of SES, neighbourhood, and family affluence (within Europe). Differences also emerge in terms of parental attitudes toward drinking, with some European countries having more permissive attitudes about adolescent drinking. Because of the importance of parental disapproval of underage drinking, this is one area that warrants greater attention.

Bibliographie

References

Adler, I. & Kandel, D. B. (1982). A cross-cultural comparison of sociopsychological factors in alcohol use among adolescents in Israel, France, and the United States. Journal of Youth and Adolescence, 11, 89-113.

Adolescent Substance Use: America’s #1 Public Health Problem (June 2011). National Center on Addiction and Substance Use.

Agostinelli, G., Brown, J. M., & Miller, W. R. (1995). Effects of normative feedback on consumption among heavy drinking college students. Journal of Drug Education, 25, 31-40.

Agostinelli, G., & Grube, J. W. (2003). Social distancing in adolescents’ perceptions of alcoho use and social disapproval: The moderating roles of culture and gender. Journal of Applied Social Psychology, 33, 2354-2372.

Alati, R., Najman, J. M., Kinner, S. A., Mamun, A. A., Williams, G. M., O’Callaghan, M., et al. (2005). Early predictors of adult drinking: A birth cohort study. American Journal of Epidemiology, 162, 1098-1107.

Ames, S. L., Grenard, J. L., Thush, C., Sussman, S., & Wiers, R. W. (2007). Comparison of indirect assessments of association as predictors of marijuana use among at-risk adolescents. Experimental and Clinical Psychopharmacology, 15, 204-218.

Anderson, K. G., Grunwald, I., Bekman, N., Brown, S. A., & Grant, A. (2011). To drink or not to drink: motives and expectancies for use and nonuse in adolescence. Addictive Behavior, 36, 972-979.

Andrews, J. A., Hops, H., Ary, D., & Tildesley, E. (1993) Parental influence on early adolescent substanse use: Specific and nonspecific effects. The Journal of Early Adolescence, 13, 285-310.

Andrews, J. A., Tildesley, E., Hops, H., & Fuzhong, L. (2002). The influence of peers on young adult substance use. Health Psychology, 21, 349-357.

Ary, D. V., Tildesley, E., Hops, H., & Andrews, J. (1993). The influence of parent, sibling, and peer modeling and attitudes on adolescent use of alcohol. International Journal of the Addictions, 28, 853-880.

Ayer, L., Rettew, D., Althoff, R. R., Willemsen, G., Ligthart, L., Hudziak, J. J. & Boomsma, D. I. (2011). Adolescent personality profiles, neighborhood income, and young adult alcohol use: A longitudinal study. Addictive Behaviors, 36, 1301-1304.

Babor, T., Caetano, R., Casswell, S., Edwards, G., Giesbrecht, N., Graham, K., et al. (2010). Alcohol: No Ordinary Commodity. Research and Public Policy. Oxford: Oxford University Press.

Baer, J. S., Stacy, A., & Larimer, M. (1991). Biases in the perception of drinking norms among college students. Journal of Studies on Alcohol, 52, 580-586.

Bank, B. J., Biddle, B. J., Anderson, D. S., Hauge, R., Keats, D. M., Keats, J. A., Marlin, M. M., & Valantin, S. (1985). Comparative research on the social determinants of adolescent drinking. Social Psychology Quarterly, 48, 164-177.

Barman, S. K., Pulkkinen, L., Kaprio, J., & Rose, R. J. (2004). Inattentiveness, parental smoking and adolescent smoking initiation. Addiction, 99, 1049-1061.

Baron, R. M., & Kenny, D. A. (1986). The moderator-mediator variable distinction in social psychological research: conceptual, strategic, and statistical considerations. Journal of Personality and Social Psychology, 51, 1173-1182.

Bechara, A. (2005). Decision making, impulse control and loss of willpower to resist drugs: a neurocognitive perspective. Nature Neuroscience, 8, 1458-1463.

Bellis, M. A., Hughes, K., Morleo, M., Tocque, K., Hughes, S., Allen, T., et al. (2007). Predictors of risky alcohol consumption in schoolchildren and their implications for preventing alcohol-related harm. Substance Abuse Treatment, Prevention, and Policy, 2, 15.

Bergmark, K. H., & Kuendig, H. (2008). Pleasures of drinking: A cross-cultural perspective. Journal of Ethnicity in Substance Abuse, 7, 131-153.

Biederman, J., Faraone, S. V., Monuteaux, M. C., & Feighner, J. A. (2000). Patterns of alcohol and drug use in adolescents can be predicted by parental substance use disorders. Pediatrics, 106, 792-797.

Bonino, S., Cattelino, E., & Ciairano, S. (2005). Adolescents and Risk. Behaviors, Functions and Protective Factors. New York: Springer-Verlag.

Boomsma, D., Busjahn, A., & Peltonen, L. (2002). Classical twin studies and beyond. Nature Reviews Genetics, 3, 872-882.

Borsari, B. & Carey, K. B. (2001). Peer influences on college drinking: A review of the research. Journal of Substancee Abuse, 13, 391-424.

Borsari, B., & Carey, K. B. (2003). Descriptive and innunctive norms in college drinking: A meta-analytic integration. Journal of Studies on Alcohol, 24, 331-341.

Brown, S. A., Goldman, M. S., & Christiansen, B. A. (1985). Do alcohol expectancies mediate drinking patterns of adults? Journal of Consulting and Clinical Psychology, 53, 512-519.

Bryant, A. L., Schulenberg, J. E., O’Malley, P. M., Bachman, J. G., & Johnston, L. D. (2003).How academic achievement, attitudes, and behaviors relate to the course of substance use during adolescence: A 6-year, multiwave national longitudinal study. Journal of Research on Adolescence, 13, 361-397.

Bucholz, K. K., Heath, A. C., & Madden, P. A. (2000). Transitions in drinking in adolescent females: Evidence from the Missouri Adolescent Female Twin Study. Alcoholism: Clinical and Experimental Research, 24, 914-923.

Burk, W. J., van der Vorst, H., Kerr, M., & Stattin, H. (2012). Alcool use and friendship dynamics: Selection and socialization in early-, middle-, and late-adolescent peer networks. Journal of Studies on Alcohol and Drugs, 73, 89-98.

Caldwell, L. K., Weichold, K., & Smith, E. A. (2006). Peer influence, substance use and leisure: A cross-cultural comparison. SUCHT: Zeitschrift fur Wissenschaft und Praxis, 52, 261-267.

Caldwell, T. M., Rodgers, B., Clark, C., Jefferis, B. J., Stansfeld, S. A., & Power, C. (2008). Lifecourse socioeconomic predictors of midlife drinking patterns, problems and abstention: Findings from the 1958 British Birth Cohort Study. Drug and Alcohol Dependence, 95, 269-278.

Caria, M. P., Faggiano, F., Bellocco, R. & Galanti, M. R. (2011). The influence of socioeconomic environment on the effectiveness of alcohol prevention among European students: A cluster randomized controlled trial. BMC Public Health, 11:312.

Casey, B. J., & Jones, R. M. (2010). Neurobiology of the adolescent brain and behavior: implications for substance use disorders. Journal of the American Academy of Child and Adolescent Psychiatry, 49, 1189-1201.

Caspi, A., Moffitt, T. E., Newman, D. L., & Silva, P. A. (1996). Behavioral observations at age 3 years predict adult psychiatric disorders – longitudinal evidence from a birth cohort. Archives of General Psychiatry, 53, 1033-1039.

Castellanos, N., & Conrod, P. J. (2006). Efficacy of brief personality-targeted cognitive behavioral interventions in reducing and preventing adolescent emotional and behavioral problems. Journal of Mental Health, 15, 1-14.

Chassin, L., Pillow, D. R., Curran, P. J., Molina, B. S. G, & Barrera, M. Jr. (1993). Relation of parental alcoholism to early adolescent substance use: A test of three mediating mechanisms. Journal of Abnormal Psychology, 102, 3-19.

Chawla, N., Neighbors, C., Lewis, M. A., Lee, C. M. & Lariimer, M. E. (2007). Attitudes and perceived approval of drinking as mediators of the relationship between the importance of religion and alcohol use. Journal of Studies on Alcohol and Drugs, 68, 410-418.

Christiansen, B. A., & Goldman, M. S. (1983). Alcohol-related expectancies versus demographic/background variables in the prediction of adolescent drinking. Journal of Consulting and Clinical Psychology, 51, 249-257.

Christiansen, B. A., Smith, G. T., Roehling, P. V., & Goldman, M. S. (1989). Using alcohol expectancies to predict adolescent drinking behavior after one year. Journal of Consulting and Clinical Psychology, 57, 93-99.

Christiansen, B. A., & Teahan, J. E. (1987). Cross-cultural comparisons of Irish and American adolescent drinking practices and beliefs. Journal of Studies on Alcohol, 48, 558-562.

Clark, D. B., Lesnick, L., & Hegedus, A. M. (1997). Traumas and other adverse life events in adolescents with alcohol abuse and dependence. Journal of the American Academy of Child and Adolescent Psychiatry, 36, 1744-1751.

Cloninger, C. R., Sigvardsson, S., & Bohman, M. (1988). Childhood personality predicts alcohol abuse in young adults. Alcoholism: Clinical and Experimental Research, 12, 494-505.

Collins, R. L., Parks, G. A. & Marlatt, G. A. (1985). Social determinants of alcohol consumption: the effects of social interaction and model status on the self administration of alcohol. Journal of Consulting and Clinical Psychology, 53, 189-200.

Conrod, P. J., Pihl, R. O., Stewart, S. H., & Dongier, M. (2000). Validation of a system of classifying female substance abusers based on personality and motivational risk factors for substance abuse. Psychology of Addictive Behaviors, 14, 243-256.

Cooper, M. L. (1994). Motivations for alcohol use among adolescents: Development and validation of a four-factor model. Psychological Assessment, 6, 117-128.

Cooper, M. L., Frone, M. R., Russell, M., & Mudar, P. (1995). Drinking to regulate positive and negative emotions: A motivational model of alcohol use. Journal of Personality and Social Psychology, 69, 990-1005.

Crews, F., He, J., & Hodge, C. (2007). Adolescent cortical development: A critical period of vulnerability for addiction. Pharmacology, Biochemistry and Behavior, 86, 189-199.

Critchlow, B. (1983). Blaming the booze: The attribution of responsibility for drunken behavior. Personality and Social Psychology Bulletin, 9, 451-473.

Cronley, C., White, H. R., Mun, E.-Y., Lee, C., Finlay, A., and Loeber, R. (2012). Exploring the interaction effect of neighborhood racial composition and individual race on substance use among male adolescents. Journal of Ethnicity in Substance Abuse (online first at http://dx.doi.org/10.1080/15332640.2012.652526).

Curran, P. J., Stice, R., & Chassin, L. (1997). The relation between adolescent alcohol use and peer alcohol use: A longitudinal random coefficients model. Journal of Consulting and Clinical Psychology, 65, 130-140.

Currie, C., Gabhainn, S. V., Godeau, E., Roberts, C., Smith, R., Currie, D., et al. (2008). Inequalities in young people’s health. Copenhagen: World Health Organization, Regional Office for Europe.

Darkes, J., & Goldman, M. S. (1993). Expectancy challenge and drinking reduction: experimental evidence for a mediational process. Journal of Consulting and Clinical Psychology, 61, 344-353.

Darkes, J., Greenbaum, P. E., & Goldman, M. S. (1998). Sensation seeking– disinhibition and alcohol use: Exploring issues of criterion contamination. Psychological Assessment, 10, 71-76.

de Wit, H. (2009). Impulsivity as a determinant and consequence of drug use: a review of underlying processes. Addiction Biology, 14, 22-31.

Deutsch, R., Gawronski, B., & Strack, F. (2006). At the boundaries of automaticity: negation as reflective operation. Journal of Personality and Social Psychology, 91, 385-405.

Diamond, A., Barnett, W. S., Thomas, J., & Munro, S. (2007). Preschool program improves cognitive control. Science, 318, 1387-1388.

Dick, D. M., Meyers, J. L., Rose, R. J., Kaprio, J., & Kendler, K. S. (2011). Measures of Current Alcohol Consumption and Problems: Two Independent Twin Studies Suggest a Complex Genetic Architecture. Alcoholism: Clinical and Experimental Research, 35, 1-10.

Dick, D. M., Prescott, C., & McGue, M. (2009). The genetics of substance use and substance use disorders. In Y. Kim (Ed.), Handbook of Behavior Genetics (pp.433-454). New York: Springer.

Dick, D. M., Smith, G., Olausson, P., Mitchell, S. H., Leeman, R. F., O’Malley, S. S., et al. (2010). Understanding the construct of impulsivity and its relationship to alcohol use disorders. Addiction Biology, 15, 217-226.

Donath, C., Grässel, E., Baier, D., Pfeiffer, C., Karagülle, D., Bleich, S., & Hillemacher, T. (2011). Alcohol consumption and binge drinking in adolescents: Comparison of different migration backgrounds and rural vs. urban residence – a representative study. BMC Public Health, 11, 84.

Donovan, J. E., & Molina, B. S. G. (2011). Childhood risk factors for early-onset drinking. Journal of Studies on Alcohol and Drugs, 72, 741-751.

Edwards, A. C., & Kendler, K. S. (2012). Twin study of the relationship between adolescent attention-deficit/hyperactivity disorder and adult alcohol dependence. Journal of Studies on Alcohol and Drugs, 73, 185-194.

Ennett, S. T., & Haws, S. (2010). The school context of adolescent substance use. In L. M. Scheier (Ed.), Handbook of drug use etiology: Theory, methods and empirical findings (pp. 443-459). Washington D.C.: American Psychological Association.

Evans, J. S. B. T. (2003). In two minds: Dual-process accounts of reasoning. Trends in Cognitive Sciences, 7, 454-459.

Farhat T., Simons-Morton B. G., Kokkevi A., Van der Sluijs W., Fotiou A., & Kuntsche E. (2012). Early adolescent and peer drinking homogeneity: similarities and differences among European and North American countries. Journal of Early Adolescence, 32, 81-103.

Fergusson, D. M., Horwood, J. & Lynskey, M. T. (1995). The prevalence and risk factors associated with abusive or hazardous alcohol consumption in 16-year-olds. Addiction, 90, 935-946.

Field, M., & Cox, W. M. (2008). Attentional bias in addictive behaviors: a review of its development, causes, and consequences. Drug and Alcohol Dependence, 97, 1-20.

Field, M., Kiernan, A., Eastwood, B., & Child, R. (2008). Rapid approach responses to alcohol cues in heavy drinkers. Journal of Behavior Therapy and Experimental Psychiatry, 39, 209-218.

Field, M., Wiers, R. W., Christiansen, P., Fillmore, M. T., & Verster, J. C. (2010). Acute Alcohol Effects on Inhibitory Control and Implicit Cognition: Implications for Loss of Control Over Drinking. Alcoholism: Clinical and Experimental Research, 34, 1346-1352.

Fillmore, M. T., & Vogel-Sprott, M. (2006). Acute effects of alcohol and other drugs on automatic and intentional control. In R. W. Wiers & A. W. Stacy (Eds.), Handbook on Implicit Cognition and Addiction (pp. 293-306). Thousand Oaks, CA: SAGE Publishers.

Finn, P. (1979). Teenage drunkenness: Warning signal, transient boisterousness, or symptom of social change? Adolescence, 14, 819-834.

Foley, K. L., Altman, D., Durant, R. H., & Wolfson, M. (2004). Adults’ approval and adolescents’ alcohol use. Journal of Adolescent Health, 35, e17-e26.

Fowler, T., Lifford, K., Shelton, K., Rice, F., Thapar, A., Neale, M. C., et al. (2007). Exploring the relationship between genetic and environmental influences on initiation and progression of substance use. Addiction, 102, 413-422.

Friedman, N. P., Miyake, A., Robinson, J. L., & Hewitt, J. K. (2011). Developmental trajectories in toddlers’ self-restraint predict individual differences in executive functions 14 years later: a behavioral genetic analysis. Developmental Psychology, 47, 1410-1430.

Friedman, N. P., Miyake, A., Young, S. E., Defries, J. C., Corley, R. P., & Hewitt, J. K. (2008). Individual differences in executive functions are almost entirely genetic in origin. Journal of Experimental Psychology: General, 137, 201-225.

Fromme, K., & D’Amico, E. J. (2000). Measuring adolescent alcohol outcome expectancies. Psychology of Addictive Behaviors, 14, 206-212.

Fromme, K., Stroot, E. & Kaplan, D. (1993). Comprehensive effects of alcohol: Development and psychometric assessment of a new expectancy questionnaire. Psychological Assessment, 5, 19-16.

Galea, S., Nandi, A., & Vlahov, D. (2004). The social epidemiology of substance use. Epidemiologic Reviews, 26, 36-52.

Gardner, M., Barajas, R. G., & Brooks-Gunn, J. (2010). Neighborhood influences on substance use etiology: Is where you live important? In L. M. Scheier (Ed.), Handbook of drug use etiology: Theory, methods and empirical findings (pp. 423-441). Washington D.C.: American Psychological Association.

Gawronski, B., & Bodenhausen, G. V. (2006). Associative and propositional processes in evaluation: an integrative review of implicit and explicit attitude change. Psychological Bulletin, 132, 692-731.

Geels, L. M., Bartels, M., van Beijsterveldt, T. C., Willemsen, G., van der Aa, N., Boomsma, D. I., & Vink, J. M. (2012). Trends in adolescent alcohol use: Effects of age, sex, and cohort on prevalence and heritability. Addiction, 107, 518-527.

Gladwin, T. E., Figner, B., Crone, E. A., & Wiers, R. W. (2011). Addiction, Adolescence, and the Integration of Control and Motivation. Developmental Cognitive Neuroscience, 1, 364-376.

Goldman, M. S., & Darkes, J. (2004). Alcohol Expectancy Multiaxial Assessment: A Memory Network-Based Approach. Psychological Assessment, 16, 4-15.

Goldman, M. S., Del Boca, F. K., & Darkes, J. (1999). Alcohol expectancy theory: the application of cognitive neuroscience. In K. E. Leonard & H. T. Blane (Eds.), Psychological theories of drinking and alcoholism (2nd ed., pp. 203-246). NY: Guilford.

Grant, V. V., Stewart, S. H., O’Connor, R. M., Blackwell, E., & Conrod, P. J. (2007). Psychometric evaluation of the five-factor Modified Drinking Motives Questionnaire – Revised in undergraduates. Addictive Behaviors, 32, 2611-2632.

Green, J. G., McLaughlin, K. A., Berglund, P. A., Gruber, M. J., Sampson, N. A., Zaslavsky, A. M., et al. (2010). Childhood adversities and adult psychiatric disorders in the National Comorbidity Survey Replication I: Associations with first onset of DSM-IV disorders. Archives of General Psychiatry, 67, 113-123.

Greenwald, A. G., & Banaji, M. R. (1995). Implicit social cognition: attitudes, self-esteem, and stereotypes. Psychological Review, 102, 4-27.

Greenwald, A. G., McGhee, D. E., & Schwartz, J. L. K. (1998). Measuring individual differences in implicit cognition: the implicit association test. Journal of Personality and Social Psychology, 74, 1464-1480.

Grenard, J. L., Ames, S. L., Wiers, R. W., Thush, C., Sussman, S., & Stacy, A. W. (2008). Working memory capacity moderates the predictive effects of drug-related associations on substance use. Psychology of Addictive Behaviors, 22, 426-432.

Guo, J., Hawkins, J. D., Hill, K. G., & Abbott, R. D. (2001). Childhood and adolescent predictors of alcohol abuse and dependence in young adulthood. Journal of Studies on Alcohol, 62, 754-762.

Haines, M. P., Barker, G. P., & Rice, G. P. (2003). using social norms to reduce alcohol and tobacco use in two midwestern high schools. In H. W. Perkins (Ed.), A social norms approach to prevention school and college age substance abuse: A handbook for educators, counselors and clinicians (pp. 235-244). San Francisco: Jossey-Bass.

Hanson, M. D., & Chen, E. (2007). Socioeconomic Status and Health Behaviors in Adolescence: A Review of the Literature. Journal of Behavioral Medicine, 30, 263–285.

Harden, K. P. (2010). Does religious involvement protect against early drinking? A behavior genetic approach. Journal of Child Psychology and Psychiatry, 51, 763-771.

Hawkins, J. D., Catalano, R. F., & Miller, J. Y. (1992). Risk and protective factors for alcohol and other drug problems in adolescence and early adulthood: implications for substance abuse prevention. Psychological Bulletin, 112, 64-105.

Healthy People 2020. United States Department of Health and Human Services. December 2010.

Heimisdottir, J., Vilhjalmsson, R., Kristjansdottir, G. & Meyrowitsch, D. W. (2010). The social context of drunkenness in mid-adolescence. Scandinavian Journal of Public Health, 38, 291-298.

Hendershot, C. S., Lindgren, K. P., Liang, T., & Hutchison, K. E. (2012). COMT and ALDH2 polymorphisms moderate associations of implicit drinking motives with alcohol use. Addiction Biology, 17, 192-201.

Hendershot, C. S., Neighbors, C., George, W. H., McCarthy, D. M., Wall, T. L., Liang, T., et al. (2009). ALDH2, ADH1B and alcohol expectancies: integrating genetic and learning perspectives. Psychology of Addictive Behaviors, 23, 452-463.

Hofmann, W., & Friese, M. (2008). Impulses got the better of me: Alcohol moderates the influence of implicit attitudes toward food cues on eating behavior. Journal of Abnormal Psychology, 117, 420-427.

Hofmann, W., Friese, M., & Wiers, R. W. (2008). Impulsive versus reflective influences on health behavior: a theoretical framework and empirical review. Health Psychology Review, 2, 111-137.

Hofmann, W., Gschwendner, T., Friese, M., Wiers, R. W., & Schmitt, M. (2008). Working memory capacity and self-regulatory behavior: toward an individual differences perspective on behavior determination by automatic versus controlled processes. Journal of Personality and Social Psychology, 95, 962-977.

Hofmann, W., Rauch, W., & Gawronski, B. (2007). And deplete us not into temptation: Automatic attitudes, dietary restraint, and self-regulatory resources as determinants of eating behavior. Journal of Experimental Social Psychology, 43, 497-504.

Houben, K., Havermans, R. C., & Wiers, R. W. (2010). Learning to dislike alcohol: conditioning negative implicit attitudes toward alcohol and its effect on drinking behavior. Psychopharmacology (Berl), 211, 79-86.

Houben, K., Nederkoorn, C., Wiers, R. W., & Jansen, A. (2011). Resisting temptation: Decreasing alcohol-related affect and drinking behavior by training response inhibition. Drug and Alcohol Dependence, 116(1-3), 132-136.

Houben, K., & Wiers, R. W. (2006). Assessing implicit alcohol associations with the Implicit Association Test: fact or artifact? Addictive Behaviors, 31, 1346-1362.

Houben, K., & Wiers, R. W. (2009). Response inhibition moderates the relationship between implicit associations and drinking behavior. Alcoholism: Clinical and Experimental Research, 33, 626-633.

Huurre, T., Lintonen, T., Kaprio, J., Pelkonen, M., Marttunen, M., & Aro, H. (2010). Adolescent risk factors for excessive alcohol use at age 32 years. A 16-year prospective follow-up study. Social Psychiatry and Psychiatric Epidemiology, 45, 125-134.

Iacono, W. G., Carlson, S. R., Taylor, J., Elkins, I. J., & McGue, M. (1999). Behavioral disinhibition and the development of substance-use disorders: Findings from the Minnesota Twin Family Study. Development and Psychopathology, 11, 869-900.

Jaccard, J., Blanton, H., & Dodge, T. (2005). Peer influences on risk behavior: An analysis of the effects of a close friend. Developmental Psychology, 41,135-147.

Jackson, J. E., Doescher, M. P. & Hart, L. G. (2006). Problem drinking: Rural and urban trends in America, 1995/1997 to 2003. Preventive Medicine, 43, 122-124.

Jackson, K. M., & Sher, K. J. (2003). Alcohol use disorders and psychosocial distress: A prospective state-trait analysis. Journal of Abnormal Psychology, 112, 599-613.

Jiang, X., Li, D., Boyce, W. & Pickett, W. (2008). Alcohol consumption and injury among Canadian adolescents: Variations by urban-rural geographic status. The Journal of Rural Health, 24, 143-147.

Johnson, J., Sher, K. J., & Rolf, J. (1991). Models of vulnerability to psychopathology in children of alcoholics. Alcohol Health and Research World, 15 (1), 32-42.

Jones, B. T., Corbin, W., & Fromme, K. (2001). A review of expectancy theory and alcohol consumption. Addiction, 96, 57-72.

Jones, B. T., & McMahon, J. (1994). Negative alcohol expectancy predicts posttreatment abstinence survivorship: the whether, when and why of relapse to a first drink. Addiction, 89, 1653-1665.

Jones, B. T., & McMahon, J. (1998). Alcohol motivations as outcome expectancies. In N. Heather & W. R. Miller (Eds.), Treating addictive behaviors (pp. 75-91). New York, NY, US: Plenum Press.

Kahneman, D. (2003). A perspective on judgment and choice: Mapping bounded rationality. American Psychologist, 58, 697-720.

Karriker-Jaffe, K. (2011). Areas of disadvantage: A systematic review of effects of area level socioeconomic status on substance use ott#omec. Drug and Alc/hol Review, 30, 84-95.

Kendler, K._S., & Baker, J. H. (2007). Genetic influeNces on measures of the environment: A systematic review. Psychological Medicine, 37, 615-626.

Kendler, K. S., Schmitt, E., Aggen, S. _., & Preqcott, C. A. (2008). Genetic and environmental influenc%s on alcohnl, caffeine, bannabis, and nicotine use frmm early adohesbence to middle adulthood. Archives of General Psychiatry, 65, 674-682.

Kestilä, L., Martelin, T., Rahknnen, O., Joutsejniemi, K., Pirkola, S., PoikoLainen, K., et al. (2008). Chiddhood and current determinants of heavy drinking)n early adtlthood. Alcohol and Alcoholism, 43, 460-469.

King, S. M., Keyes, M., Mahone, S. M., Elkhns, I., Legrand, L. N&, Iacono, W. G., & McGue, M. (2009!. Pareotal alcohol $ependence and the transmission of `dolescent behavioral disinhibition: a study of adoptive and non-adoptive familie3. Addiction, 104, 578-586.

Kim, Y. M. & Neff, J. A. (2010). Direct and indiract effects of pareNtal)nfluence upon adolescent alcohol use: A structural equation modeling analysis. Journal of Child and Adolescent Substance Abuse, 19, 244-260.

Kokkevi A., Arapaki A. A., Richardsol C., Florescu S., Kuzman M., & Stergar E. (2007). Further investigation of psychosocial and %nvironmental correlates of substance use in adolescence in six European c/untries. Drug and Alcohol Dependence, 88, 308-312.

Kokkevi A., Richardson C., Florescu S., Kuz-an M., & Stergar E. (2006). Psychosocial correlates of 3ubctance use in adolescence: a cross-national stedy in six European countbids. Drug and Alcohol DepEndence, 86, 67-74.

Koning, I. M,(van den Dijnden, R. J., Engels, R. C., Verdurm%n, J. E., & Vollebergh, W. A. (20!1). Why target earl9 ado,escents and parents in alcohml prerentio.? The mediating effects of seld-cmntrol, rules and attitudes about alcohol use. Addiction, 106, 538-546.

Koning, I. MTM, Vollebergh, W. A., Smit, F*, Verdurmen, J. E., Van Den Eijnden, R. J., Ter Bog4, T. F., et ad. (2009). Preventing heavy alcohol usa in adodesc%nts (PAS): cluster randomized trial of a parent and student intervention offered separately and simultaneously. Addiction, 104, 1669-1678.

Krank, M. D., Stewart, S. H., O’Connor, R., Woicik, P. B., Wall, A. M., & Conrod, P. J. (2011). Structural, concurrent, and predictive validity of the Substance Use Risk Profile Scale in early adolescence. Addictive Behaviors, 36, 37-46.

Kuntsche, E., Wiers, R. W., Janssen, T., & Gmel, G. (2010). Same wording, distinct concepts? Testing differences between expectancies and motives in a mediation model of alcohol outcomes. Experimental and Clinical Psychopharmacology, 18, 436-444.

Kuntsche, E., Stewart, S. H., & Cooper, M. L. (2008). How stable is the motive-alcohol use link? A cross national validation of the Drinking Motives Questionnaire Revised among adolescents from Switzerland, Canada, and the United States. Journal of Studies on Alcohol and Drugs, 69, 388-396.

LaBrie, J. W., Hummer, J. F., Neighbors, C., & Larimer, M. E. (2010). Whose opinion matters? The relationship between injunctive norms and alcohol consequences in college students. Addictive Behaviors, 35, 343-349.

Latendresse, S. J., Rose, R. J., Viken, R. J., Pulkkinen, L., Kaprio, J., & Dick, D. M. (2008). Parenting mechanisms in links between parents’ and adolescents’ alcohol use behaviors. Alcoholism: Clinical and Experimental Research, 32, 322-330.

Larimer, M. E., LaBrie, J., Atking, D. C., Lewis, M. A., Lee, C. M., Kilmer, J. R., Daysen, D. L., Pedersen, E. R., Montoya, H., Hodge, K., Desai, S, Hummer, J. F., & Wlater, T. (2011). Descriptive norms: For whom does reference group matter? Journal of Studies on Alcohol and Drugs, 72, 833-843.

Lee, N. K., Greely, J. & Oei, T. P. S. (1999). The relationship of positive and neative alcohol expectancies to patterns of consumptionof alcohol in social drinkers. Addictive Behaviors, 24, 359-369.

Lemstra, M., Neudorf, C., Nannapaneni, U., Bennett, N., Scott, C. & Kershaw, T. (2009). The role of economic and cultural status as risk indicators for alcohol and marijuana use among adolescents. Pediatrics and Child Health, 14, 225-230.

Leventhal, T. & Brooks-Gunn, J. (2000). The neighborhood3 they live in: The effects of neighborhond residence on child and adolescent outcomes. Psychological Bulletin, 126, 309-337.

Lieb, R., Merikangas, K. R., Hofler, M., Pfister, H., Isensee,!B., & Wittchen, H. U. (2002). Parental alcohol use disorders and alcohol use and disorders in offspring: A community study. Psychol/gical Medicine, 32, 63-78.

Link, T. C. (2008). Youthful intoxication: A cross-cultural study of drinking among German and American adolescents. Journal of Studies on Alcohol and Drugs, 69, 362-370.

Lisha, N. E., & Sussman, S. (2010). Relationship of high school and college sports participation with alcohol, tobacco, and illicit drug use: A review. Addictive Behaviors, 35, 399-407.

Litt, D. M. & Ctock, M. L. (2011). Adolescent alcohol-related risk cognitions: The roles of social norms and social networkIng sites. Psychology of Addictive Behaviors, 25, 708-713.

Littlefield, A. K., Agrawal, A., Ellingson, J. M., Kristjansson, S., Madden, P. A., Bucholz, K. K., et al. (2011). Does variance in drinking motives explain the genetic overlap between personality and alcohol use disorder symptoms? A twin study of young women. Alcoholism: Clinical and Experimental Research, 35, 2242-2250.

Loehlin, J. C. (2010). Is there an active gene-environment correlation in adolescent drinking behavior? Behavior Genetics, 40, 447-451.

Lorente, F. O., Souville, M., Griffet, J., & Grélot, L. (2004). Participation in sports and alcohol consumption among French adolescents. Addictive Behaviors, 29, 941-946.

MacAndrew, C., & Edgerton, R. B. (1969). Drunken Comportment: A social explanation. Aldine Press: Oxford, UK.

Mackie, C. J., Conrod, P. J., Rijsdijk, F., & Eley, T. C. (2011). A systematic evaluation and validation of subtypes of adolescent alcohol use motives: genetic and environmental contributions. Alcoholism: Clinical and Experimental Research, 35, 420-430.

Mackie, C. J., Castellanos-Ryan, N., & Conrod, P. J. (2011). Personality moderates the longitudinal relationship between psychological symptoms and alcohol use in adolescents. Alcoholism: Clinical and Experimental Research, 36, 703-716.

MacKinnon, D. P., & Fairchild, A. J. (2009). Current Directions in Mediation Analysis. Current directions in psychological science, 18, 16-20.

MacKinnon, D. P., & Lockwood, C. M. (2003). Advances in statistical methods for substance abuse prevention research. Prevention Science, 4, 155-171.

Macleod, J., Hickman, M., Bowen, E., Alati, R., Tilling, K., & Smith, G.D. (2008). Parental drug use, early adversities, later childhood problems and children’s use of tobacco and alcohol at age 10: Birth cohort study. Addiction, 103, 1731-1743.

Maggs, J. L. (1997). Alcohol use and binge drinking as goal-directed action during the transition to postsecondary education. In J. Schulenberg, J. L. Maggs, & K. Hurrelmann (Eds.), Health risks and developmental transitions during adolescence. pp. 345-371, Cambridge University Press, NY.

Mäkelä, P., & Österberg, E. (2009). Weakening of one more alcohol control pillar: A review of the effects of the alcohol tax cuts in Finland in 2004. Addiction, 104, 554-563.

Maric, M., Wiers, R. W., & Prins, P. J. (2012). Ten Ways to Improve the Use of Statistical Mediation Analysis in the Practice of Child and Adolescent Treatment Research. Clinical Child and Family Psychology Review, 15(3), 177-191.

Marlatt, G. A., Baer, J. S., Kivlahan, D. R., Dimeff, L. A., Larimer, M. E., Quigley, L. A., et al. (1998). Screening and brief intervention for high-risk college student drinkers: results from a 2-year follow-up assessment. Journal of Consulting and Clinical Psychology, 66, 604-615.

Marmorstein, N., White, H. R., Loeber, R., & Stouthamer-Loeber, M. (2010). Anxiety as a predictor of age at first use of substances and progression to substance use problems among boys. Journal of Abnormal Child Psychology, 38, 211-224.

Martino, S. C., Ellickson, P. L. & McCaffery, D. F. (2008). Developmental trajectories of substance use from early to late adolescence: A comparison of rural and urban youth. Journal of Studies on Alcohol and Drugs, 69, 430-440.

Martino, S. C., Ellickson, P. L., & McCaffrey, D. F. (2009). Multiple trajectories of peer and parental influence and their association with the development of adolescent heavy drinking. Addictive Behaviors, 34, 693-700.

Mason, W. A., & Windle, M. (2002). A longitudinal study of the effects of religiosity on adolescent alcohol use and alcohol-related problems. Journal of Adolescent Research, 17, 346-363.

Masten, A. S., & Cicchetti, D. (2010). Developmental cascades. Development and Psychopathology, 22, 491-495.

Mays, D., & Thompson, N. J. (2009). Alcohol-related risk behaviors and sports participation among adolescents: an analysis of 2005 Youth Risk Behavior Survey data. Journal of Adolescent Health, 44, 87-89.

Mays, D., Depadilla, L., Thompson, N. J., Kushner, H. I., & Windle, M. (2010). Sports participation and problem alcohol use: a multi-wave national sample of adolescents. American Journal of Preventive Medicine, 38, 491-498.

Mays, D., Gatti, M. E., & Thompson, N. J. (2011). Sports participation and alcohol use among adolescents: the impact of measurement and other research design elements. Current Drug Abuse Reviews, 4, 98-109.

Mays, D., Thompson, N., Kushner, H. I., Mays, D. F. 2nd, Farmer, D., & Windle, M. (2010). Sports-specific factors, perceived peer drinking, and alcohol-related behaviors among adolescents participating in school-based sports in Southwest Georgia. Addictive Behaviors, 35, 235-241.

McCarthy, D. M., Brown, S. A., Carr, L. G., & Wall, T. L. (2001). ALDH2 status, alcohol expectancies, and alcohol response: preliminary evidence for a mediation model. Alcoholism: Clinical and Experimental Research, 25, 1558-1563.

McGue, M., Sharma, A., & Benson, P. (1996). Parent and sibling influences on adolescent alcohol use and misuse: evidence from a U.S. adoption cohort. Journal of Studies on Alcohol, 57, 8-18.

Melotti, R., Heron, J., Hickman, M., Macleod, J., Araya, R, Lewis, G., et al. (2011). Adolescent alcohol and tobacco use and early socioeconomic position: the ALSPAC birth cohort. Pediatrics, 127, e948-e955.

Miller, W. R. (1998). Why do people change addictive behavior? The 1996 H. David Archibald Lecture. Addiction, 93, 163-172

Mischel, W., Ayduk, O., Berman, M. G., Casey, B. J., Gotlib, I. H., Jonides, J., et al. (2011). ‘Willpower’ over the life span: decomposing self-regulation. Social Cognitive and Affective Neuroscience, 6, 252-256.

Mischel, W., Shoda, Y., & Peake, P. K. (1988). The nature of adolescent competencies predicted by preschool delay of gratification. Journal of Personality and Social Psychology, 54, 687-696.

Moffitt, T. E., Arseneault, L., Belsky, D., Dickson, N., Hancox, R. J., Harrington, H, et al. (2011). A gradient of childhood self-control predicts health, wealth, and public safety. Proceedings of the National Academy of Sciences, 108, 2693-2698.

Moore, M. J., & Werch, C. E. (2005). Sport and physical activity participation and substance use among adolescents. Journal of Adolescent Health, 36, 486-493.

Mushquash, C. J., Stewart, S. H., Comeau, M. N., & McGrath, P. J. (2008). The structure of drinking motives in First Nations adolescents in Nova Scotia. American Indian and Alaska Native Mental Health Research, 15, 33-52.

Nagoshi, C. T., Wood, M. D., Cote, C. C. & Abbit, S. M. (1994). College drinking game participation within the context of other predictors of other alcohol use and problems. Psychology of Addictive Behaviors, 8, 203-213.

Nation, M., & Heflinger, C. A. (2006). Risk factors for serious alcohol and drug use: The role of psychosocial variables in predicting the frequency of substance use among adolescents. American Journal of Drug and Alcohol Abuse, 32, 415-433.

National Survey of American Attitudes on Substance Use XVI: Teens and Parents. (August 2011). National Center on Addiction and Substance Use.

Neal, D.J., & Carey, K.B. (2007). Association between alcohol intoxication and alcohol-related problems: An event-leval analysis. Psychology of Addictive Behaviors, 21, 194-204.

Neighbors, C., Lee, C. M., Lewis, M. A., Fossos, N., & Larimer, M. E. (2007). Are social norms the best predictor of outcomes among heavy-drinking college students? Journal of Studies on Alcohol and Drugs, 68, 556-565.

Neighbors, C., O’Connor, R. M., Lewis, M. A., Chawla, N., Lee, C. M. & Fossoss, N. (2008). the relative impact of injunctive norms on college student drinking: The role of reference group. Psychology of Addictive Behaviors, 22, 576-581.

Nonnemaker, J. M., McNeely, C. A., & Blum, R. W. (2003). Public and privatte domains of religiosity and adolescent health risk behaviors: Evidence from the national longitudinal study of adolescent healther. Social Science and Medicine, 57, 2049-2054.

Oesterle, S., Hawkins, J.D., Steketee, M., Jonkman, H., Brown, E. C., Moll, M. & Haggerty, K. P. (2011, May). A cross-national comparison of risk and protective factors for adoolescent drug use and deliquency in the United States and the Netherlands. Paper presented at the annual meeting of the Society for Prevention Research, Washington, DC.

O’Leary-Barrett, M., Mackie, C. J., Castellanos-Ryan, N., Al-Khudhairy, N., & Conrod, P. J. (2010). Personality-targeted interventions delay uptake of drinking and decrease risk of alcohol-related problems when delivered by teachers. Journal of the American Academy of Child and Adolescent Psychiatry, 49, 954-963.

Pagan, J. L., Rose, R. J., Viken, R. J., Pulkkinen, L., Kaprio, J., & Dick, D. M. (2006). Genetic and environmental influences on stages of alcohol use across adolescence and into young adulthood. Behavior Genetics, 36, 483-497.

Pandina, R. J., Johnson, V. L., & White, H. R. (2010). Peer influences on substance use during adolescence and emerging adulthood. In L. M. Scheier (Ed.), Handbook of Drug Use Etiology (pp. 383-401). Washington, DC: American Psychological Association.

Patel, A. B. & Fromme, K. (2010). Explicit outcome expectancies and substance use: Current research and future directions. In L. M. Schier (Ed.), Handbook of Drug Use Etiology (pp. 147-164). Washington, DC: American Psychological Association.

Peck, S. C., Vida, M., & Eccles, J. S. (2008). Adolescent pathways to adulthood drinking: sport activity involvement is not necessarily risky or protective. Addiction, 103, Suppl 1, 69-83.

Perkins, H. W. & Craig, D. W. (2003). The imaginary lives of peers: Patterns of substance use and mis-pereptions of norms among secondary school students. In H. W. Perkins (Ed.), A social norms approach to preventing school and college age substance abuse: A handbook for educators, counselors, and clinicians (pp. 209-223). San Francisco: Jossey-Bass.

Perkins, H. W., Haines, M. P. & Rice, R. (2005). Misperceiving the college drinking norm and related problems: A nationwide study of exposure to prevention information, perceived norms and student alcohol misuse. Journal of Studies on Alcohol, 66, 470-478.

Perkins, H. W., Meilman, P. W., Leichliter, J. S., Cashin, J. R., & Presley, C. A. (1999). Misperception of the norms for the frequency of alcohol and other drug use on college campuses. Journal of American College Health, 27, 253-258.

Perkins, H. W. & Wechsler, H. (1996). Variation in perceived college drinking norms and its impact on alcohol abuse: A nationwide study. Journal of Drug Issues, 26, 961-974.

Peretti-Watel, P., Beck, F., & Legleye, S. (2002). Beyond the U-curve: the relationship between sport and alcohol, cigarette and cannabis use in adolescents. Addiction, 97, 707-716.

Pieters, S., Burk, W. J., van der Vorst, H., Wiers, R. W., & Engels, R. C. (2012). The Moderating Role of Working Memory Capacity and Alcohol-Specific Rule-Setting on the Relation between Approach Tendencies and Alcohol Use in Young Adolescents. Alcoholism: Clinical and Experimental Research, 36(5), 915-922.

Poelen, E. A. P., Engels, R. C. M. E., Scholte, R. H. J., Boomsma, D. I., & Willemsen, G. (2009). Predictors of problem drinking in adolescence and young adulthood. European Child and Adolescent Psychiatry, 18, 345-352.

Poelen, E. A. P., Scholte, R. H., Willemsen, G., Boomsma, D. I., & Engels R. C. (2007). Drinking by parents, siblings, and friends as predictors of regular alcohol use in adolescents and young adults: A longitudinal twin-family study. Alcohol and Alcoholism, 42, 362-369.

Quigley, B. M. & Collins, R. L. (1999). The modeling of alcohol consumption: A meta-analytic review. Journal of Studies on Alcohol, 60, 90-98.

Raitasalo, K., Holmila, M., & Mäkelä, P. (2011). Drinking in the presence of underage children: Attitudes and behavior. Addiction Research and Theory, 19, 394-401.

Read, J. P., & O’Connor, R. M. (2006). High- and low-dose expectancies as mediators of personality dimensions and alcohol involvement. Journal of Studies on Alcohol and Drugs, 67, 204-214.

Read, J. P., Lau-Barraco, C., Dunn, M. E., & Borsari, B. (2009). Projected alcohol dose influences on the activation of alcohol expectancies in college drinkers. Alcoholism: Clinical and Experimental Research, 33, 1265-1277.

Read, J. P., Wood, M. D., & Capone, C. (2005). A prospective investigation of relations between social influences and alcohol involvement during the transition into college. Journal of Studies on Alcohol and Drugs, 66, 23-34.

Reboussin, B. A., Song, E. Y., Shrestha, A., Lohman, K. K., & Wolfson, M. (2006). A latent class analysis of underage problem drinking: Evidence from a community sample of 16-20 year olds. Drug and Alcohol Dependence, 83, 199-209.

Rehm, J., Room, R., van den Brink, W., & Jacobi, F. (2005). Alcohol use disorders in EU countries and Norway: An overview of the epidemiology. European Neuropsychopharmacology, 15, 377-388.

Reich, R. R., Below, M. C., & Goldman, M. S. (2010). Explicit and implicit measures of expectancy and related alcohol cognitions: a meta-analytic comparison. Psychology of Addictive Behaviors, 24, 13-25.

Rhee, S. H., Hewitt, J. K., Young, S. E., Corley, R. P., Crowley, T. J., & Stallings, M. C. (2003). Genetic and environmental influences on substance initiation, use, and problem use in adolescents. Archives of General Psychiatry, 60, 1256-1264.

Rhoades, B. L., & Maggs, J. L., (2006). Do academic and social goals predict planned alcohol use among college-bound high school graduates? Journal of Youth and Adolescence, 35, 913-923.

Richter, M., Leppin, A., & Nic Gabhainn, S. (2006). The relationship between parental socio-economic status and episodes of drunkenness among adolescents: findings from a cross-national survey. BMC Public Health, 28, 289.

Richter, M., Vereecken, C. A., Boyce, W., Maes, L., Gabhainn, S. N., & Currie, C. E. (2009). Parental occupation, family affluence and adolescent health behaviour in 28 countries. International Journal of Public Health, 54, 203-212.

Rooke, S. E., Hine, D. W., & Thorsteinsson, E. B. (2008). Implicit cognition and substance use: A meta-analysis. Addictive Behaviors, 33, 1314-1328.

Room, R. (2011). Drinking and intoxication when the children are around: Conflicting norms and their resolutions. Addiction Research & Theory, 19, 402-403.

Rose, R. J., Dick, D. M., Viken, R. J., Pulkkinen, L., & Kaprio, J. (2001). Drinking or abstaining at age 14? A genetic epidemiological study. Alcoholism: Clinical and Experimental Research, 25, 1594-1604.

Ryan, S. M., Jorm, A. F., & Lubman, D. I. (2010). Parenting factors associated with reduced adolescent alcohol use: A systematic review of longitudinal studies. Australian and New Zealand Journal of Psychiatry, 44, 774-783.

Sampson, R. J., Morenoff, J. D., & Gannon-Rowley, T. (2002). Assessing “neighborhood effects": Social processes and new directions in research. Annual Review of Sociology, 28, 443-478.

Schelleman-Offermans, K., Kuntsche, E., & Knibbe, R. A. (2011). Associations between drinking motives and changes in adolescents’ alcohol consumption: A full cross-lagged panel study. Addiction, 106, 1270-1278.

Schoenmakers, T., de Bruin, M., Lux, I. F., Goertz, A. G., Van Kerkhof, D. H., & Wiers, R. W. (2010). Clinical effectiveness of attentional bias modification training in abstinent alcoholic patients. Drug and Alcohol Dependence, 109, 30-36.

Schoenmakers, T., Wiers, R. W., & Field, M. (2008). Effects of a low dose of alcohol on cognitive biases and craving in heavy drinkers. Psychopharmacology (Berl), 197, 169-178.

Schumann, G., Coin, L. J., Lourdusamy, A., Charoen, P., Berger, K. H., Stacey, D., et al. (2011). Genome-wide association and genetic functional studies identify autism susceptibility candidate 2 gene (AUTS2) in the regulation of alcohol consumption. Proceedings of the National Academy of Sciences of the United States of America, 108, 7119-7124.

Shaw, C., & McKay, H. (1969). Juvenile delinquency and urban areas (Rev. ed.). Chicago: University of Chicago Press.

Sher, K. J., Wood, M. D., Wood, P. K., & Raskin, G. (1996). Alcohol outcome expectancies and alcohol use: a latent variable cross-lagged panel study. Journal of Abnormal Psychology, 105, 561-574.

Smith, E. C., & DeCoster, J. (2000). Dual-process models in social and cognitive psychology: Conceptual integration and links to underlying memory systems. Personality and Social Psychology Review, 4, 108-131.

Song, E. Y., Smiler, A. P., Wagoner, K. G., & Wolfson, M. (2012). Everyone says it’s OK: Adolescents’ perceptions of peer, parent, and community alcohol norms, alcohol consumption, and alcohol-related consequences. Substanse Use and Misuse, 47, 86-98.

Stacy, A. W. (1997). Memory activation and expectancy as prospective predictors of alcohol and marijuana use. Journal of Abnormal Psychology, 106, 61-73.

Stacy, A. W., Ames, S. L., & Knowlton, B. (2004). Neurologically plausible distinctions in cognition relevant to drug use etiology and prevention. Substance Use and Misuse,, 39, 1571-1623.

Stacy, A. W., Zogg, J. B., Unger, J. B., & Dent, C. W. (2004). Exposure to televised alcohol ads and subsequent adolescent alcohol use. American Journal of Health Behavior, 28, 498-509.

Stappenbeck, C. A., Quinn, P. D., Wetherill, R. R., & Fromme, K. (2010). Perceived norms for drinking in the transition from high school to college and beyond. Journal of Studies on Alcohol and Drugs, 71, 895-903.

Steinberg, L. (2010). A dual systems model of adolescent risk-taking. Developmental Psychobiology, 52, 216-224.

Steinberg, L., Albert, D., Cauffman, E., Banich, M., Graham, S., & Woolard, J. (2008). Age differences in sensation seeking and impulsivity as indexed by behavior and self-report: evidence for a dual systems model. Developmental Psychology, 44, 1764-1778.

Stewart, S. H., & Kushner, M. G. (2001). Introduction to the special issue on anxiety sensitivity and addictive behaviors. Addictive Behaviors, 26, 775-785.

Stahlbrandt, H., Andersson, C., Johnsson, K. O., Tollison, S. J., Berglund, M., & Larimer, M. E. (2008). Cross-cultural patterns in college student drinking and its consequences: A comparison between the USA and Sweden. Alcohol and Alcoholism, 43, 698-705.

Stewart, S. H., Grant, V. V., Mackie, C. J., & Conrod, P. J. (in press). Comorbidity of anxiety and depression with substance use disorders. To appear in K. J. Sher (Ed.), Oxford Handbook of Substance Use Disorders. New York: Oxford University Press.

Stock, C., Ejstrud, B., Vinther-Larsen, M., Schlattmann, P., Curtis, T., Grøbaek, M. & Bloomfield, K. (2011). Effects of school district factors on alcohol consumption: results of a multi-level analysis among Danish adolescents. European Journal of Public Health, 21, 449-455.

Strack, F., & Deutsch, R. (2004). Reflective and impulsive determinants of social behavior. Personality and Social Psychology Review, 8, 220-247.

Strahan, E. Y., Panayiotou, G., Clements, R., & Scott, J. (2011). Beer, wine, and social anxiety: Testing the “self-medication hypothesis” in the US and Cyprus. Addiction Research and Theory, 19, 302-311.

Strunin, L., Lindeman, K., Tempesta, E., Ascani, P., Anav, S., & Parisi, L. (2010). Familial drinking in Italy: harmful or protective factors? Addiction Research and Theory, 18, 344-358.

Teahan, J. E. (1987). Alcohol expectancies, values, and drinking of Irish and U.S. collegians. International Journal of the Addictions, 22, 621-638.

Thush, C., & Wiers, R. W. (2007). Explicit and implicit alcohol-related cognitions and the prediction of current and future drinking in adolescents. Addictive Behaviors, 32, 1367-1383.

Thush, C., Wiers, R. W., Ames, S. L., Grenard, J., Sussman, S., & Stacy, A. W. (2007). Apples and oranges? Comparing indirect measures of alcohol-related cognition predicting alcohol use in at-risk adolescents. Psychology of Addictive Behaviors, 21, 587-591.

Thush, C., Wiers, R. W., Ames, S. L., Grenard, J. L., Sussman, S., & Stacy, A. W. (2008). Interactions between implicit and explicit cognition and working memory capacity in the prediction of alcohol use in at-risk adolescents. Drug and Alcohol Dependence, 94, 116-124.

Thush, C., Wiers, R. W., Moerbeek, M., Ames, S. L., Grenard, J. L., Sussman, S., et al. (2009). Influence of motivational interviewing on explicit and implicit alcohol-related cognition and alcohol use in at-risk adolescents. Psychology of Addictive Behaviors, 23, 146-151.

USDHHS – U.S. Department of Health and Human Services, 2000. Healthy People 2010: Understanding and Improving Health, Vol. 2. Washington, D.C.: U.S. Government Printing.

van der Vegt, E. J., Tieman, W., van der Ende, J., Ferdinand, R. F., Verhulst, F. C., & Tiemeier, H. (2009). Impact of early childhood adversities on adult psychiatric disorders: A study of international adoptees. Social Psychiatry and Psychiatric Epidemiology, 44, 724-731.

van der Vorst, H., Engels, R. C. M. E, Meeus, W. & Dekovic, M. (2006). The impact of alcohol-specific rules, parental norms about early drinking and parental alcohol use on adolescents’ drinking behavior. Journal of Child Psychology and Psychiatry, 47, 1299-1306.

van der Vorst, H., Engels, R. C., Dekovic, M., Meeus, W., & Vermulst, A. A. (2007). Alcohol-specific rules, personality and adolescents’ alcohol use: a longitudinal person-environment study. Addiction, 102, 1064-1075.

van der Zwaluw, C. S., Kuntsche, E., & Engels, R. C. (2011). Risky alcohol use in adolescence: the role of genetics (DRD2, SLC6A4) and coping motives. Alcoholism: Clinical and Experimental Research, 35, 756-764.

van Lier, P. A., Huizink, A., & Crijnen, A. (2009). Impact of a preventive intervention targeting childhood disruptive behavior problems on tobacco and alcohol initiation from age 10 to 13 years. Drug and Alcohol Dependence, 100, 228-233.

Vanyukov, M. M., Tarter, R. E., Kirisci, L., Kirillova, G. P., Maher, B. S., & Clark, D. B. (2003). Liability to substance use disorders: 1. common mechanisms and manifestations. Neuroscience and Biobehavioral Reviews, 27, 507-515.

Vaughan, E. L., Corbin, W. R., & Fromme, K. (2009). Academic and social motives and drinking behavior. Psychology of Addictive Behaviors, 23, 564-576.

Verdejo-Garcia, A., Lawrence, A. J., & Clark, L. (2008). Impulsivity as a vulnerability marker for substance-use disorders: Review of findings from high-risk research, problem gamblers and genetic association studies. Neuroscience and Biobehavioral Reviews, 32, 777-810.

Walden, B., Iacono, W. G., & McGue, M. (2007). Trajectories of change in adolescent substance use and symptomatology: Impact of paternal and maternal substance use disorders. Psychology of Addictive Behaviors, 21, 35-43.

Walker, C., Ainette, M. G., Wills, T. A., & Mendoza, D. (2007). Religiosity and substance use: Test of an indirect-effect model in early and middle adolescence. Psychology of Addictive Behaviors, 21, 84-96.

Warner, L. A., & White, H. R. (2003). Longitudinal effects of age at onset and first drinking situations on problem drinking. Substance Use and Misuse, 38, 1983-2016.

Watt, M. C., Stewart, S. H., Birch, C. D., & Bernier, D. (2006). Brief CBT for high anxiety sensitivity decreases drinking problems, relief alcohol outcome expectancies, and conformity drinking motives: Evidence from a randomized controlled trial. Journal of Mental Health, 15, 683-695.

Wechsler, H., Dowdall, G. W., Davenport, A., & Castillo, S. (1995). Correlates of college student binge drinking. American Journal of Public Health, 85, 921-926.

Wechsler, H. & Nelson, T. F. (2008). What we have learned from the Harvard School of Public Health college Alcohol Study: Focusing attention on college student alcohol consumption and the environmental conditions that promote it. Journal of Studies on Alcohol and Drugs, 69, 481-490.

Weinberg, N. Z., & Glantz, M. D. (1999). Child psychopathology risk factors for drug abuse: Overview. Journal of Clinical Child Psychology, 28, 290-297.

Wetherill, R. R. & Fromme, K. (2007). Perceived awareness and caring influences alcohol use by high school and college students. Psychology of Addictive Behaviors, 21, 147-154.

White, H. R., Bates, M. E., & Johnson, V. (1991). Learning to drink: Familial, peer and media ainfluences. In D. J. Pittman & H.R. White (Eds), Society, culture, and drinking reexamined, (pp. 177-197). New Brunswick, MJ: Alcohol Research Documentation.

White, H. R., Fleming, C. B., Kim, M. J., Catalano, R. F. & McMorris, B. J. (2008). Identifying two potential mechanisms for changes in alcohol use among college-attending and non-college-attending emerging adults. Developmental Psychology, 44, 1625-1639.

White. H. R., Johnson, V., & Buyske, S. (2000). Parental modeling and parenting behavior effects on offspring alcohol and cigarette use: A growth curve analysis. Journal of Substance Abuse, 12, 287-310.

White, H. R., Marmorstein, N. R., Crews, F. T., Bates, M. E., Mun, E. Y., & Loeber, R. (2011). Associations between heavy drinking and changes in impulsive behavior among adolescent boys. Alcoholism: Clinical and Experimental Research, 35, 295-303.

Wichstrom, T., & Wichstrom, L. (2009). Does sports participation during adolescence prevent later alcohol, tobacco and cannabis use? Addiction, 104, 138–149.

Wiers, R. W., Ames, S. L., Hofmann, W., Krank, M., & Stacy, A. W. (2010). Impulsivity, impulsive and reflective processes and the development of alcohol use and misuse in adolescents and young adults. Frontiers in Psychology, 1(144), 1-12.

Wiers, R. W., Bartholow, B. D., van den Wildenberg, E., Thush, C., Engels, R. C., Sher, K. J., et al. (2007). Automatic and controlled processes and the development of addictive behaviors in adolescents: a review and a model. Pharmacology Biochemistry and Behavior, 86, 263-283.

Wiers, R. W., Beckers, L., Houben, K., & Hofmann, W. (2009). A short fuse after alcohol: Implicit power associations predict aggressiveness after alcohol consumption in young heavy drinkers with limited executive control. Pharmacology Biochemistry and Behavior, 93, 300-305.

Wiers, R. W., Eberl, C., Rinck, M., Becker, E., & Lindenmeyer, J. (2011). Re-training automatic action tendencies changes alcoholic patients’ approach bias for alcohol and improves treatment outcome. Psychological Science. Psychological Science, 22, 490-497.

Wiers, R. W., Hoogeveen, K. J., Sergeant, J. A., & Boudewijn Gunning, W. (1997). High- and low-dose alcohol-related expectancies and the differential associations with drinking in male and female adolescents and young adults. Addiction, 92, 871-888.

Wiers, R. W., Houben, K., Roefs, A., Hofmann, W., & Stacy, A. W. (2010). Implicit Cognition in Health Psychology: Why Common Sense Goes Out of the Window. In B. Gawronski & B. K. Payne (Eds.), Handbook of Implicit Social Cognition. (pp. 463-488). NY: Guilford.

Wiers, R. W., Rinck, M., Dictus, M., & van den Wildenberg, E. (2009). Relatively strong automatic appetitive action-tendencies in male carriers of the OPRM1 G-allele. Genes, Brain and Behavior, 8, 101-106.

Wiers, R. W., Rinck, M., Kordts, R., Houben, K., & Strack, F. (2010). Retraining automatic action-tendencies to approach alcohol in hazardous drinkers. Addiction, 105, 279-287.

Wiers, R. W., & Stacy, A. W. (2006). Implicit cognition and addiction. Current Directions in Psychological Science, 15, 292-296.

Wiers, R. W., van de Luitgaarden, J., van den Wildenberg, E., & Smulders, F. T. Y. (2005). Challenging implicit and explicit alcohol-related cognitions in young heavy drinkers. Addiction, 100, 806-819.

Wiers, R. W., van Woerden, N., Smulders, F. T. Y., & de Jong, P. J. (2002). Implicit and explicit alcohol-related cognitions in heavy and light drinkers. Journal of Abnormal Psychology, 111, 648-658.

Wiles, N. J., Lingford-Hughes, A., Daniel, J., Hickman, M., Farrell, M., Macleod, J., et al. (2007). Socio-economic status in childhood and later alcohol use: a systematic review. Addiction, 102, 1546-1563.

Wills, T. A., Ainette, M. G., Stoolmiller, M., Gibbons, F. X., & Shinar, O. (2008). Good self-control as a buffering agent for adolescent substance use: An investigation in early adolescence with time-varying covariates. Psychology of Addictive Behaviors, 22, 459-471.

Wills, T. A. & Stoolmiller, M. (2002). The role of self-control in early escalation of substance use: A time-varying analysis. Journal of Consulting and Clinical Psychology, 70, 986-997.

Wills, T. A., Yaeger, A. M., & Sandy, J. M. (2003). Buffering effect of religiosity for adolescent substance use. Psychology of Addictive Behaviors, 17, 24-31.

Windle, M. (1996). Effect of parental drinking on adolescents. Alcohol Health and Research World, 20, 181-184.

Windle, M., Spear, L. P., Fuligni, A. J., Angold, A., Brown, J. D., Pine, D., et al. (2008). Transitions into underage and problem drinking: Developmental processes and mechanisms between 10 and 15 years of age. Pediatrics, 121, Supplement 4, S273-S289.

Windle, M., Spear, L. P., Fuligni, A. J., Angold, A., Brown, J. D., Pine, D., et al. (2009). Transitions into underage and problem drinking: Summary of developmental processes and mechanisms, ages 10-15. Alcohol Research and Health, 32, 30-40.

Winter, T., Karvonen, S. & Rose, R. J. (2002). Does religiousness explain regional differences in alcohol use in Finland? Alcohol and Alcoholism, 37, 330-339.

Woicik, P. A., Conrod, P. J., Stewart, S. H., & Pihl, R. O. (2009). The Substance Use Risk Profile Scale: A scale measuring traits linked to reinforcement specific substance use profiles. Addictive Behaviors, 34, 1042-1055.

Wood, M. D., Read, J. P., Palfai, T. P. & Stevenson, J. F. (2001). Social influence proce3sses and college student drinking: The mediational role of alcohol outcome expectancies. Journal of Studies on Alcohol and Drugs, 62, 32-43.

Young, R. & Oei, T. P. S. (1993). Grape expectations: The role of alcohol expectancies in the understanding and treatment of problem drinking. International Journal of Psychology, 28, 337-364.

Young-Wolff, K. C., Enoch, M. A., & Prescott, C. A. (2011). The influence of gene-environment interactions on alcohol consumption and alcohol use disorders: a comprehensive review. Clinical Psychology Review, 31, 800-816.

Yusko, D. A., Buckman, J. F., White, H. R., & Pandina, R. J. (2008). Risk for excessive alcohol use and drinking-related problems in college student athletes. Addictive Behaviors, 33, 1546-1456.

Zhang, L., Welte, J. W., & Wieczorek, W. F. (1997). Peer and parental influences on male adolescent drinking. Substance Use and Misuse, 32, 2121-2136.

Auteurs

Ph.D., Professor
Addiction, Development, and Psychopathology (Adapt)
Department of Psychology
University of Amsterdam
Weesperplein 4
Nl – 1018 XA Amsterdam
r.w.h.j.wiers@uva.nl

Ph.D., Professor
Department of Psychology
The University of Texas at Austin
108 E. Dean Keeton, Mail Stop A8000
USA – Austin TX 78712;
fromme@psy.utexas.edu

Ph.D.
Department of Public Health
Hjelt InstituteUniversity of Helsinki
FI – 00014 Helsinki
and
Department of Mental Health and Substance Abuse Services
National Institute for Health and Welfare
FI – 00271 Helsinki
antti.latvala@helsinki.fi

Ph.D., Professor of Psychiatry and Psychology
Psychology Department
Dalhousie University, 1355 Oxford Street
CA – Halifax, Nova Scotia
sherry.h.stewart@gmail.com

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