Document Type
Article
Publication Date
1-2017
Publication Title
Statistical and Data Sciences: Faculty Publications
Volume
64
Abstract
Personalized normative feedback is a recommended component of alcohol interventions targeting college students. However, normative data are commonly collected through campus-based surveys, not through actual participant-referent relationships. In the present investigation, we examined how misperceptions of residence hall peers, both overall using a global question and those designated as important peers using person-specific questions, were related to students’ personal drinking behaviors. Participants were 108 students (88% freshman, 54% White, 51% female) residing in a single campus residence hall. Participants completed an online baseline survey in which they reported their own alcohol use and perceptions of peer alcohol use using both an individual peer network measure and a global peer perception measure of their residential peers. We employed network autocorrelation models, which account for the inherent correlation between observations, to test hypotheses. Overall, participants accurately perceived the drinking of nominated friends but overestimated the drinking of residential peers. Consistent with hypotheses, overestimating nominated friend and global residential peer drinking predicted higher personal drinking, although perception of nominated peers was a stronger predictor. Interaction analyses showed that the relationship between global misperception and participant self-reported drinking was significant for heavy drinkers, but not non-heavy drinkers. The current findings explicate how student perceptions of peer drinking within an established social network influence drinking behaviors, which may be used to enhance the effectiveness of normative feedback interventions.
First Page
143
Last Page
147
Recommended Citation
Kenney, Shannon R.; Ott, Miles Q.; Meisel, Matthew; and Barnett, Nancy P., "Alcohol Perceptions and Behavior in a Residential Peer Social Network" (2017). Statistical and Data Sciences: Faculty Publications, Smith College, Northampton, MA.
https://scholarworks.smith.edu/sds_facpubs/5
Digital Object Identifier (DOI)
doi:10.1016/j.addbeh.2016.08.047
Rights
© the authors
Comments
Peer reviewed accepted manuscript.
HHS Public Access