Peer pressure is consistently implicated in the excessive drinking of college students. However, both theory and empirical findings suggest that peer pressure is a combination of three distinct influences: overt offers of alcohol, modeling, and social norms. Overt offers of alcohol can range from polite gestures to intense goading or commands to drink. Modeling occurs when the student's behavior corresponds to another student's concurrent drinking behavior. Perceived social norms can serve to make excessive alcohol use appear common and acceptable to the student. This review critically examines the literature on each form of peer influence and provides suggestions for future research. D

Objective-Many college students overestimate both the drinking behaviors (descriptive norms) and the approval of drinking (injunctive norms) of their peers. As a result, consistent self-other discrepancies (SODs) have been observed, in which self-perceptions of drinking behaviors and approval of drinking are usually lower than comparable judgments of others. These self-other discrepancies form the foundation of the currently popular "social norms approach" to alcohol abuse prevention, which conveys to students the actual campus norms regarding drinking behaviors and approval of alcohol use. However, little attention has been paid to the factors that can influence the magnitude of self-other discrepancies.Method-This meta-analytic integration of 23 studies evaluated the influence of five predictors of SODs: norm type (injunctive or descriptive), gender, reference group, question specificity, and campus size. These studies rendered 102 separate tests of self-other differences in descriptive and injunctive forms, representing the responses of 53,825 participants.Results-All five predictors were significantly related to self-other differences in the perception of norms. Greater SODs were evident for injunctive norms, estimates by women, distal reference groups, non-specific questions, and on smaller campuses.Conclusions-More systematic attention should be given to how norms are assessed; specifically, SODs can be maximized or minimized depending on the specificity of the behaviors/attitudes evaluated and the reference groups chosen for comparison.In the last decade, the "social norms approach" to reducing excessive alcohol use on college campuses has enjoyed a swell of support (DeJong and Linkenbach, 1999;Keeling, 2000). This approach posits that the majority of students overestimate the use and approval of alcohol by campus peers; as a result, these students are less inclined to view their own alcohol use as problematic (see also Perkins, 1997 and 2002 for reviews). The social norms approach, then, proposes that correcting these misperceived norms will result in students gaining a new perspective on the risks associated with their personal alcohol use. This approach is often carried out on a large scale, such as campus-wide media campaigns (e.g., Haines and Spear, 1996). In theory, this new perspective will lead to reductions in alcohol use and the adoption of more conservative attitudes towards drinking. In light of the significance of social norms in alcohol abuse prevention efforts, greater attention to the variability within the drinking norms literature is warranted. Perceived Norms in the College ContextTwo types of norms have been assessed in the college drinking literature: descriptive and injunctive norms. Descriptive norms refer to the perception of other's quantity and frequency Correspondence concerning this article can be directed to the second author at the Center for Health and Behavior, 430 Huntington Hall, Syracuse University, Syracuse, NY 13244-2340. Phone: 1-315-443-2706 FAX: 1-315-443-41...

In light of increasing numbers of controlled studies evaluating alcohol abuse prevention interventions for college drinkers, we conducted a meta-analysis to summarize the current status of the literature. The meta-analysis includes 62 studies, published between 1985 to early 2007, with 13750 participants and 98 intervention conditions. All studies were content coded for study descriptors, participant characteristics, and intervention components. We derived weighted mean effect sizes for alcohol interventions versus comparison conditions for consumption variables and alcohol-related problems, over four measurement intervals. Over follow-up intervals lasting up to 6 months, participants in risk reduction interventions drank significantly less relative to controls. Students receiving interventions also reported fewer alcohol-related problems over longer intervals. Moderator analyses suggest that individual, face-to-face interventions using motivational interviewing and personalized normative feedback predict greater reductions in alcohol-related problems. Implications for future research include attention to maintenance of effects, and developing more efficacious interventions for at-risk college drinkers.

This study adapted and extended M. L. Cooper's (1994) Drinking Motives Measure to examine marijuana motives among 299 college students. An exploratory factor analysis supported the hypothesized 5-factor marijuana motives model, resulting in enhancement, conformity, expansion, coping, and social motives. Analyses supported the internal consistency and concurrent validity of the 5 marijuana motives. Marijuana motives were significant predictors of marijuana use and added to the prediction of use-related problems above and beyond the contribution of lifetime use. Motives and gender interacted in predicting use and use-related problems. Parallel regression analyses revealed that marijuana and alcohol motives predicted comparable amounts of variance in use and use-related problems. However, different patterns of relations emerged across drugs, supporting the discriminant validity of the marijuana and alcohol motives.

This study consisted of a randomized controlled trial of a 1-session motivational intervention for college student binge drinkers. Sixty students who reported binge drinking 2 or more times in the past 30 days were randomly assigned to either a no-treatment control or a brief intervention group. The intervention provided students with feedback regarding personal consumption, perceived drinking norms, alcohol-related problems, situations associated with heavy drinking, and alcohol expectancies. At 6-week follow-up, the brief intervention group exhibited significant reductions on number of drinks consumed per week, number of times drinking alcohol in the past month, and frequency of binge drinking in the past month. Estimates of typical student drinking mediated these reductions. This study replicates earlier research on the efficacy of brief interventions with college students and extends previous work regarding potential mechanisms of change.

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Alcohol misuse occurs commonly on college campuses, necessitating prevention programs to help college drinkers reduce consumption and minimize harmful consequences. Computer-delivered interventions (CDIs) have been widely used due to their low cost and ease of dissemination but whether CDIs are efficacious and whether they produce benefits equivalent to face-to-face interventions (FTFIs) remain unclear. Therefore, we identified controlled trials of both CDIs and FTFIs and used meta-analysis (a) to determine the relative efficacy of these two approaches and (b) to test predictors of intervention efficacy. We included studies examining FTFIs (N = 5,237; 56% female; 87% White) and CDIs (N = 32,243; 51% female; 81% White). Independent raters coded participant characteristics, design and methodological features, intervention content, and calculated weighted mean effect sizes using fixed and random-effects models. Analyses indicated that, compared to controls, FTFI participants drank less, drank less frequently, and reported fewer problems at short-term follow-up (d+s = 0.15 – 0.19); they continued to consume lower quantities at intermediate (d+ = 0.23) and long-term (d+ = 0.14) follow-ups. Compared to controls, CDI participants reported lower quantities, frequency, and peak intoxication at short-term follow-up (d+s = 0.13 – 0.29), but these effects were not maintained. Direct comparisons between FTFI and CDIs were infrequent, but these trials favored the FTFIs on both quantity and problems measures (d+s = 0.12–0.20). Moderator analyses identified participant and intervention characteristics that influence intervention efficacy. Overall, we conclude that FTFIs provide the most effective and enduring effects.

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