Mediation effects of a culturally generic substance use prevention program for Asian American adolescents.
Bibliographic record
Abstract
In this paper, we examined the mediation effects of a family-based substance use prevention program on a sample of Asian American families. These families were randomized into an intervention arm or a non-intervention control arm. Using path models, we assessed the effect of the intervention on adolescent girls' substance use outcomes at 2-year follow-up through family relationships and adolescent self-efficacy pathways. Bias-corrected bootstrapping strategy was employed to assess the significance of the mediation effect by evaluating the 95% confidence interval of the standardized coefficient. The results show that receiving the intervention exerted a positive effect on girls' family relationships at 1-year follow-up. Such an improvement was associated with girls' increased self-efficacy, which in turn led to girls' decreased alcohol use, marijuana use, and future intention to use substances at 2-year follow-up. Considering the diverse cultural backgrounds, as well as languages, nationalities, and acculturation levels under the umbrella term "Asian Americans", we demonstrate that a universal web-based intervention that tackles the theoretical- and empirical-based risk and protective factors can be effective for Asian Americans. Despite its generic nature, our program may provide relevant tools for Asian American parents in assisting their adolescent children to navigate through the developmental stage and ultimately, resist 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".