Descriptive and injunctive norms in college drinking: a meta-analytic integration.
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 usually are lower than comparable judgments of others. These SODs 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 SODs. This research was conducted to address these issues.


METHODS
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 SODs 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 and nonspecific questions, as well as on smaller campuses.


CONCLUSIONS
More systematic attention should be given to how norms are assessed. In particular, SODs can be maximized or minimized, depending on the specificity of the behaviors/attitudes evaluated and the reference groups chosen for comparison.
Borsari
Brian
B
Center for Health and Behavior, 430 Huntington Hall, Syracuse University, Syracuse, New York 13244-2340, USA.
Carey
Kate B
KB
D000428:Alcohol Drinking / Q000453:epidemiology*; D005260:Female; D006801:Humans; D008297:Male; D012737:Sex Factors; D013334:Students / Q000706:statistics & numerical data*; D011795:Surveys and Questionnaires; D014495:Universities / Q000706:statistics & numerical data*