Up close and personal: temporal variability in the drinking of individual college students during their first year

Abstract

Surveys have documented excessive drinking among college students and tracked annual changes in consumption over time. This study extended previous work by examining drinking changes during the freshman year, using latent growth curve (LGC) analysis to model individual change, and relating risk factors for heavy drinking to growth factors in the model. Retrospective monthly assessments of daily drinking were used to generate weekly estimates. Drinking varied considerably by week, apparently as a function of academic requirements and holidays. A 4-factor LGC model adequately fit the data. In univariate analyses, gender, race/ethnicity, alcohol expectancies, sensation seeking, residence, and data completeness predicted growth factors (ps <.05); gender, expectancies, residence, and data completeness remained significant when covariates were tested simultaneously. Substantive, methodological, and policy implications are discussed.