Excessive alcohol consumption represents a significant concern on U.S. college campuses, and there is a need to identify students who may be at risk for engaging in risky alcohol use. The current study examined how variables measured prior to college matriculation, specifically alcohol-related decision-making variables drawn from the Theory of Reasoned Action (i.e., alcohol expectancies, attitudes, and normative beliefs), were associated with patterns of alcohol use prior to and throughout the first semesters of college. Participants were 392 undergraduate students (56 % female) from a large Northeastern U.S. university. Decision-making variables were assessed prior to college matriculation, and alcohol use was measured with five assessments before and throughout freshman and sophomore semesters. Latent profile analysis was used to identify types of students with distinct patterns of decision-making variables. These decision-making profiles were subsequently linked to distinct patterns of alcohol use using latent transition analysis. Four distinct decision-making profiles were found and were labeled “Anti-Drinking,” “Unfavorable,” “Mixed,” and “Risky.” Five drinking patterns were observed and included participants who reported consistently low, moderate, or high rates of alcohol use. Two patterns described low or non-drinking at the pre-college baseline with drinking escalation during the measurement period. Students’ likelihood of following the various drinking patterns varied according to their decision-making. Findings suggest the early identification of at-risk students may be improved by assessing decision-making variables in addition to alcohol use. The findings also have implications for the design of early identification assessments to identify at-risk college students and for the targeting of alcohol prevention efforts to students based on their alcohol-related attitudes and beliefs.
All Science Journal Classification (ASJC) codes
- Public Health, Environmental and Occupational Health
- College students
- Early identification