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KMID : 0858820120290020083
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Journal of Korean Society for Health Education and Promotion
2012 Volume.29 No. 2 p.83 ~ p.91
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Effects of Policy and Environmental Characteristics of University on Drinking Problems among University Students
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Kim Kwang-Gi
Jekarl Jung
Lee Ki-Il
Park Jung-Eun
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Abstract
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Objectives: This study is to examine that drinking problems among university students were accounted for not only by student’s individual characteristics but alcohol policy and environmental characteristics of the university in which students were enrolled.
Method: Secondary data analysis was employed in which variables under study were derived from a raw data of a nationwide representative sample in 2009. Raw data under analysis included 3,665 students from 63 universities across Korea. Organizational and environmental characteristics of the university were collected from university administrators while individual characteristics and drinking behavior from the students in using self-administrated questionnaire. Multilevel regression analyses were employed to describe alcohol policy effects on students’s drinking problems measured by AUDIT by using HLM7.0.
Results: ICCs indicate that variation in drinking problem depends on alcohol policy of university. Multilevel regression models identified statistically significant factors in explaining variance of drinking problems. Group means on drinking problem are affected by indicators representing alcohol policy with level of drinking problem of student being decreased in accordance to level of availability of alcohol on campus.
Conclusions: It is concluded that drinking problems among university students were associated with both individual characteristics and alcohol policy of the university they enrolled. This study supports policy belief that interventions at environmental as well as individual level are required to prevent drinking problem among university students.
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KEYWORD
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Alcohol related problem, College student, Individual characteristics, Alcohol policy of the university, Multi-level regression analysis
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