Do Drinking Practices at University Differ among Students Coming from Urban and Rural Centers? A Preliminary Examination of Knowledge, Attitudes and Beliefs.
Bibliographic record
Abstract
This exploratory study examined the influence of residential background and gender on university student drinking patterns. A questionnaire was distributed to 255 kinesiology and physical education students. Rural students (n=104) were more likely than urban students (n=151) to drink at outdoor parties or in vehicles during their first experience with alcohol. No significant differences were found between residential background and drinking motives, knowledge, or negative consequences concerning alcohol. Males, however, experienced significantly more negative ramifications, such as driving while under the influence, damaging property, breaking the law, injuring another party, and getting into a physical or verbal confrontation. This study supports the gender differences concerning the negative consequences of alcohol consumption, and adds to the information concerning rural-urban differences and alcohol use. Introduction The university years are a period of transition for young adults involving a myriad of changes, such as new living arrangements, increased academic pressures and changes in social norms and expectations. In recent literature, alcohol consumption among university-aged students has received considerable attention, primarily due to the negative consequences of its misuse/abuse. Statistics Canada (2003) reports that 76% of men and 61% of women between the ages of 20 and 24 are regular drinkers (consume one or more drinks per month). In a United States national survey of 14,000 college students, 19% were found to be abstainers, 44% binge drinkers (5{4} drinks in a row for males {females} during past 2 weeks), and 23% frequent binge drinkers (binged 3+ times in past 2 weeks) (Wechsler, Lee, Kuo & Lee, 2000). High rates of alcohol consumption have the potential to compromise the well-being of university students, resulting in negative consequences such as illness, unplanned or unsafe sex, injury, memory loss, trouble with the law, and academic repercussions (Wechsler, Dowdall, Davenport & Rimm, 1995; Haemmerlie, Montgomery & Saling, 1994). For example, in a sample of 1919 university students, alcohol consumption was significantly linked to number of sexual partners and to the frequency of sexual activity (Prince & Bernard, 1998). In addition, 70% of 210 college students admitted inconsistent condom use after the consumption of alcohol (Poulson, Eppler, Satterwhite, Wuensch & Bass, 1998). Further, Barr and MacKinnon (1998) found that a mere 6% of 544 university students consistently used a non-drinking designated driver. Additionally, Caldwell (2002) found that heavier drinkers (eight or more drinks per episode) suffered significantly more negative consequences than those who drank lesser amounts. Influence of Gender and Residential Background A. Consumption Rates In a study of 130 male and 130 female potential problem drinkers (15+ drinks/week), 59% of males were found to drink at least 5 or 6 drinks on nearly every occasion, while only 36% of females drank this amount. Males consumed almost twice as much as females on a weekly basis (Corbin, McNair & Carter, 1996). Further a survey of Ontario university students showed males to be 3 times more likely to consume 15 drinks weekly (Gliksman, Newton-Taylor, Adlaf & Giesbrecht, 1997) (see also, Robinson, Gloria, Roth & Schuetter, 1993; Humphrey & Friedman, 1986). When comparing urban and rural residents, inconsistent findings exist. Mitic (1989) found that rural female adolescents (aged 13-19) reported more alcohol abstinence than their urban counterparts, while Booth, Ross, and Rost (1999) found that 61% of randomly selected rural residents abstained from alcohol compared to 49% of urban residents. Cronk and Sarvela (1997) revealed that consumption varied by regions at different times, with alcohol use being more prevalent among rural youth and the age of consumption being younger among rural youth; however, it was noted that the gap appears to be decreasing as time progresses. …
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".