Alcohol use among college students: generating behavior prediction models for social and personal motivational contexts

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Title: Alcohol use among college students: generating behavior prediction models for social and personal motivational contexts
Author: Robinette, Kerstin Lee
Abstract: Alcohol use and abuse are widespread and serious concerns for the college student population (Carnegie Foundation for the Advancement of Teaching , 1990 ) . A multitude of studies have attempted to uncover the factors that influence college students' decisions about alcohol use . However , most preventive intervention programs that draw upon this research have failed to significantly influence college student drinking , suggesting that the complex network of factors involved in these decisions has not yet been uncovered (Meacci , 1990 ) . In the present investigation , behavior prediction models for socially and personally motivated alcohol use among college students were generated through exploratory factor analysis and CALIS structural modeling procedures , instead of forcing the data to fit into a preconceived pattern . Adequate models were constructed for both the social and personal contexts across the model building sample of participants (n=167 ) . Further , a cross -validation test (n=95 ) revealed that the models are likely to generalize to other populations of college students . Supplemental tests of model fit performed on men's (n=101 )and women's (n=161 ) responses separately indicated that the social context model best predicts men's college alcohol use . However , women's responses resulted in a less effident fit to the social context model than did men's responses and a problematic fit to the personal context model . These results suggest that further investigations may be warranted in order to discover optimal models for personal context alcohol use and for women college students' alcohol use .
URI: http : / /hdl .handle .net /2346 /8711
Date: 1997-08

Citation

Robinette, Kerstin Lee Alcohol use among college students: generating behavior prediction models for social and personal motivational contexts. Doctoral dissertation, Texas Tech University. Available electronically from http : / /hdl .handle .net /2346 /8711 .

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