Does an evidence-based healthy relationships program for 9th graders show similar effects for 7th and 8th graders? Results from 57 schools randomized to intervention
Bibliographic record
Abstract
Integrating social and emotional learning (SEL) programming throughout curricula to support the development of healthy behaviors and prevent violence is critical for a comprehensive approach to school health. This study used a post-test comparison design to evaluate a healthy relationships program for eighth grade students that applies a SEL approach. The program was adapted from the Fourth R, an evidence-based program for ninth graders, but matches the curriculum and developmental context for eighth graders. Surveys were collected post-intervention from 1012 students within 57 schools randomized to intervention or control conditions. Multivariate multilevel analysis accounted for the nested nature of students within schools. There were significant group differences on three of four outcomes following intervention, including improved knowledge about violence, critical thinking around the impact of violence, and identification of more successful coping strategies. There was no group difference on general acceptance of violence. Overall, students learned relevant information and strategies and were able to apply that knowledge to demonstrate critical thinking, suggesting that adapting an evidence-based approach for use with younger students provided similar benefits. These findings build a case for 2 years of consecutive evidence-based healthy relationships programming in grades 8 and 9, consistent with best practice guidelines.
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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 | 0.007 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".