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Journal Article

Citation

Layland EK, Calhoun BH, Russell MA, Maggs JL. Prev. Sci. 2019; 20(3): 342-352.

Affiliation

Pennsylvania State University, State College, PA, USA.

Copyright

(Copyright © 2019, Holtzbrinck Springer Nature Publishing Group)

DOI

10.1007/s11121-018-0877-6

PMID

29516357

Abstract

College drinking and its negative consequences remain a major public health concern. Yet, many prevention efforts targeting college drinkers are expensive, are difficult to implement, use indicated approaches targeting only high-risk drinkers, and/or are only marginally effective. An alternative strategy taken explicitly or implicitly by many colleges is campus-led alcohol-free programming which provides students with attractive leisure alternatives to drinking on weekend nights. This study aimed to extend work by Patrick et al. (Prevention Science, 11, 155-162, 2010), who found that students drank less on weekend nights they attended LateNight Penn State (LNPS) activities during their first semester of college. Here, daily diary and longitudinal data on college students' daily lives and risk behaviors were collected from 730 students on 19,506 person-days across seven semesters at a large university in the Northeastern United States. Generalized linear mixed models were used to estimate alcohol and illegal substance use on weekend days as a function of LNPS attendance, gender, legal drinking status (≥ 21 years), and day of the weekend. Across college, students who attended LNPS used alcohol and illegal substances less in general and less on days they participated compared to themselves on days they did not participate. Legal drinking status moderated the association between LNPS attendance and alcohol and illegal substance use such that levels of use were lowest for students under 21 years old on weekend days they attended LNPS. Our findings provide support for campus-led alcohol-free programming as a potential harm reduction strategy on college campuses.


Language: en

Keywords

Alcohol use; College drinking; Multi-level modeling; Prevention; Substance use

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