Acculturation domains, drinking motives, and alcohol use and consequences among Asian American university students
Bibliographic record
Abstract
Although Asian American (AA) college students tend to exhibit lower prevalence of heavy alcohol use compared to other racial/ethnic groups, excessive alcohol consumption within this population occurs. It has been suggested that U.S. acculturation may be associated with both alcohol use and negative alcohol consequences. Theory and research with other ethnic groups point to the importance of drinking motives in influencing alcohol consumption and consequences. However, the extent to which acculturation is associated with drinking behaviors, particularly when examined simultaneously with drinking motives in a multivariate context has not been delineated among AA college students. Using multivariate modeling techniques with a multisite sample of AA college student drinkers ( n = 243), we tested how specific acculturation domains (cultural practices/identity) and drinking motives were associated with alcohol use and negative drinking consequences. Results indicated that higher endorsement of heritage cultural practices was related to less alcohol use but more negative alcohol consequences. These associations remained significant after accounting for drinking motives and known demographic predictors of alcohol use. Higher endorsement of enhancement motives was associated with elevated alcohol use while higher coping-depression motives were related to negative alcohol consequences. Overall, our findings suggest that heritage cultural practice aspects of acculturation are a protective factor against increased alcohol use that may also be a risk factor for negative alcohol consequences among AA students. Further work within AA college student samples and various racial/ethnic groups is recommended to examine the extent to which certain acculturation domains may exert contradictory effects on alcohol consumption and associated consequences.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 teacher head, 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".