A school-based program to prevent adolescent dating violence: a cluster randomized trial.
Bibliographic record
Abstract
OBJECTIVE: To determine whether an interactive curriculum that integrates dating violence prevention with lessons on healthy relationships, sexual health, and substance use reduces physical dating violence (PDV). DESIGN: Cluster randomized trial with 2.5-year follow-up; prespecified subgroup analyses by sex. SETTING: Grade 9 health classes. PARTICIPANTS: A total of 1722 students aged 14-15 from 20 public schools (52.8% girls). Intervention A 21-lesson curriculum delivered during 28 hours by teachers with additional training in the dynamics of dating violence and healthy relationships. Dating violence prevention was integrated with core lessons about healthy relationships, sexual health, and substance use prevention using interactive exercises. Relationship skills to promote safer decision making with peers and dating partners were emphasized. Control schools targeted similar objectives without training or materials. MAIN OUTCOME MEASURES: The primary outcome at 2.5 years was self-reported PDV during the previous year. Secondary outcomes were physical peer violence, substance use, and condom use. Analysis was by intention-to-treat. RESULTS: The PDV was greater in control vs intervention students (9.8% vs 7.4%; adjusted odds ratio, 2.42; 95% confidence interval, 1.00-6.02; P = .05). A significant group x sex interaction effect indicated that the intervention effect was greater in boys (PDV: 7.1% in controls vs 2.7% in intervention students) than in girls (12.1% vs 11.9%). Main effects for secondary outcomes were not statistically significant; however, sex x group analyses showed a significant difference in condom use in sexually active boys who received the intervention (114 of 168; 67.9%) vs controls (65 of 111 [58.6%]) (P < .01). The cost of training and materials averaged CA$16 per student. CONCLUSION: The teaching of youths about healthy relationships as part of their required health curriculum reduced PDV and increased condom use 2.5 years later at a low per-student cost.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.005 | 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 | 0.002 | 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".