Individual and Familial Risk and Promotive Factors for Substance Use Among Multiracial American Young Adults
Bibliographic record
Abstract
Background: Multiracial American adults have the highest rates of binge drinking and illicit drug use of all racial groups, yet little is known about the risk and promotive factors that contribute to their substance use. Objectives: This study examines how individual factors (i.e., shifting racial expressions, perceived racial ambiguity, creating third space, self-esteem, depression) and family cohesion relate to substance use among 574 Multiracial young adults in the United States (Mage = 19.87). Results: Findings suggested that Multiracial young adults who reported higher scores on perceived racial ambiguity, self-esteem, and depression had a higher likelihood of drinking to feel drunk and binge drinking, while more family cohesion with their first primary caregiver was associated with a lower likelihood of drinking to feel drunk. Perceived racial ambiguity was also associated with a higher likelihood of illicit drug use, while family cohesion with their second primary caregiver was associated with a lower likelihood of illicit drug use. Multiracial young adults with White ancestry were more likely to drink to feel drunk than Multiple Minority Multiracials, but there were no differences between groups in binge drinking or illicit drug use. Conclusions: In sum, the unique racialized experiences, mental health, and family relationships of Multiracial Americans may play a role in substance use.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.002 | 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".