Extreme Binge Drinking During Adolescence: Associations With Subsequent Substance Use Disorders in American Indian and Mexican American Young Adults
Bibliographic record
Abstract
OBJECTIVE: This study collected retrospective data on adolescent binge drinking (ABD) (5 drinks for boys, 4 for girls per occasion at least once per month) and/or extreme adolescent binge drinking (EABD) (10 or more drinks per occasion at least once per month) and tested for associations with demographic and diagnostics variables including alcohol and other substance use disorders (AUD/SUD). METHODS: Cross-sectional data were collected from young adult (age 18-30 yrs) American Indians (AI) (n = 534) and Mexican Americans (MA) (n = 704) using a semi-structured diagnostic instrument. RESULTS: Thirty percent (30%) of the sample reported ABD and 21% reported EABD. Those having had monthly ABD were more likely to be AI and have less education; those having had EABD were more likely to be AI, male, younger, have less education and lower economic status compared to participants without ABD. ABD/EABD was associated with higher impulsivity, a family history of AUD, and lower level of response to alcohol (ORs = 1.0-2.0), as well as with adult AUD (ORs = 3.7-48), other substance use disorders (ORs = 3.5-9), and conduct disorder/ antisocial personality disorder (ORs = 2.0-2.6), but not with anxiety/depression. Monthly EABD further increased the odds of AUD/SUD. CONCLUSIONS: Although binge drinking was more common in AI compared to MA, there were little effects of race in individual risk factor analyses. Monthly ABD and EABD were common among these AI/MA as adolescents, and, as with other ethnic groups, these drinking patterns resulted in highly significant increases in the odds of developing alcohol and other substance use disorders in young adulthood.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| 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".