Two-year outcomes of a randomized, family-based substance use prevention trial for Asian American adolescent girls.
Bibliographic record
Abstract
Asian Americans have been largely ignored in the prevention outcome literature. In this study, we tested a parent-child program with a sample of Asian American adolescent girls and their mothers, and evaluated the program's efficacy on decreasing girls' substance use and modifying risk and protective factors at individual, family, and peer levels. A total of 108 Asian American mother-daughter dyads recruited through online advertisements and from community service agencies were randomly assigned to an intervention arm (n = 56) or to a test-only control arm (n = 52). The intervention consisted of a nine-session substance abuse prevention program, delivered entirely online. Guided by family interaction theory, the prevention program aimed to strengthen the quality of girls' relationships with their mothers while increasing girls' resilience to resist substance use. Intent-to-treat analyses showed that at 2-year follow-up, intervention-arm dyads had significantly higher levels of mother-daughter closeness, mother-daughter communication, maternal monitoring, and family rules against substance use compared with the control-arm dyads. Intervention-arm girls also showed sustained improvement in self-efficacy and refusal skills and had lower intentions to use substances in the future. Most important, intervention-arm girls reported fewer instances of alcohol and marijuana use and prescription drug misuse relative to the control-arm girls. The study suggests that a culturally generic, family-based prevention program was efficacious in enhancing parent-child relationships, improving girls' resiliency, and preventing substance use behaviors among Asian American girls.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".