Alcohol outcome expectancies, attitudes toward drinking and the theory of planned behavior |
Author(s):
,Journal/Book: J Stud Alcohol. 1998; 59: C/O Deirdre English, 607 Allison Rd, Piscataway, NJ 08854-8001. Alcohol Res Documentation Inc Cent Alcohol Stud Rutgers Univ. 409-419.
Abstract: Objective: The present study investigated whether alcohol outcome expectancies are empirically distinguishable from attitudes toward drinking. Specifically, the contribution of expectancies and attitudes to the Theory of Planned Behavior was assessed. Method: Undergraduates (N = 316; 170 male), of legal drinking age, who drank at least once a month participated. Intentions to drink ''too much'' and self-report excessive consumption episodes served as criterion measures, and attitudes, subjective norm, perceived behavioral control and alcohol outcome expectancies were employed as predictor variables. Stepwise regression analyses were performed separately for men and women. Results: The Theory of Planned Behavior appeared to be a valid framework for predicting excessive alcohol consumption among undergraduates. The predictive power of the model, however, was enhanced through the inclusion of gender-specific alcohol outcome expectancies. Specifically, in addition to attitudes and perceived behavioral control, women's expectancies for sociability enhanced the prediction of intentions to drink ''too much.'' Expectancies for sexual functioning (male) and assertiveness (female) improved the prediction of excessive consumption, over and above intentions and perceived behavioral control. Conclusions: Alcohol outcome expectancies, unlike attitudes, are proximal predictors of excessive alcohol consumption among undergraduates.
Note: Article Wall AM, York Univ, Dept Psychol, 4700 Keele St, Behav Sci Bldg, N York, ON M3J 1P3, CANADA
Keyword(s): ADOLESCENT DRINKING; GENDER DIFFERENCES; COLLEGE-STUDENTS; HEALTH BEHAVIOR; REASONED ACTION; DRUG-USE; PATTERNS; PREDICTION; MODEL; SELF
© Top Fit Gesund, 1992-2024. Alle Rechte vorbehalten – Impressum – Datenschutzerklärung