A randomized controlled trial of guided self-change with minority adolescents.
Bibliographic record
Abstract
OBJECTIVE: Adolescent substance use and abuse is a pressing public health problem and is strongly related to interpersonal aggression. Such problems disproportionately impact minority youth, who have limited access to evidence-based interventions such as ecological family therapies, brief motivational interventions (BMIs), and cognitive behavioral therapies (CBTs). With a predominantly minority sample, our objective was to rigorously evaluate the efficacy of a school-based BMI/CBT, Guided Self-Change (GSC), for addressing substance use and aggressive behavior. METHOD: We conducted a school-based randomized, controlled trial with 514 high school students (mean age 16.24 years, 41% female, 80% minority) reporting using substances and perpetrating aggression. We used structural equation modeling to compare participants randomly assigned to receive GSC or standard care (SC; education/assessment/referral-only) at posttreatment and at 3 and 6 months posttreatment on alcohol use, drug use, and interpersonal aggression outcomes as assessed by the Timeline Follow-Back. RESULTS: Compared with SC participants, GSC participants showed significant reductions (p < .05) in total number of alcohol use days (Cohen's d = 0.45 at posttreatment and 0.20 at 3 months posttreatment), drug use days (Cohen's d = 0.22 at posttreatment and 0.20 at 3 months posttreatment), and aggressive behavior incidents (Cohen's d = 0.23 at posttreatment). Moreover, treatment effects did not vary by gender or ethnicity. CONCLUSIONS: With minority youth experiencing mild to moderate problems with substance use and aggressive behavior, GSC holds promise as an early intervention approach that can be implemented with success in schools.
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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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.012 | 0.001 |
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".