Examining the Drinking Motives <scp>Questionnaire‐Revised</scp> Short Form among university students in Australia, New Zealand and Argentina
Bibliographic record
Abstract
INTRODUCTION: The Drinking Motives Questionnaire-Revised Short Form (DMQ-R-SF) is widely used among alcohol researchers studying adolescents and young adults. The psychometric properties of the DMQ-R-SF have been examined among university students in many countries, but to our knowledge, not in Australia, New Zealand or Argentina. We sought to examine the reliability and endorsement of the items on the DMQ-R-SF, and test the associations between the DMQ-R-SF subscales and alcohol use, and negative alcohol consequences between university students from Australia, New Zealand and Argentina. METHOD: University students (N = 820) in Australia (n = 315), New Zealand (n = 265) and Argentina (n = 240) completed a confidential online alcohol survey which included the DMQ-R-SF, the Daily Drinking Questionnaire and the Brief Young Adult Alcohol Consequences Questionnaire. RESULTS: Using the alignment method, support for the four-factor model on the DMQ-R-SF emerged and the factor loadings for 11 of the 12 items were invariant across sites. Most items (8 out of 12) on the DMQ-R-SF were fully invariant across all sites, but some small differences in item reliability for one item, and endorsement for three items emerged between the sites. Across the three countries, coping motives were positively correlated with negative alcohol consequences. Enhancement motives were positively associated with both alcohol use and negative alcohol consequences among students from Australia and New Zealand. DISCUSSION AND CONCLUSIONS: Most items on the DMQ-R-SF were comparably reliable among the university students sampled from Australia, New Zealand and Argentina. Our preliminary findings suggest that the DMQ-R-SF can be reliably used with university students from these countries.
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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 | 0.002 |
| 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 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 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".