Relations between a social emotional learning (SEL) program and changes in resilience, self-esteem, and psychological flourishing in a youth sample
Bibliographic record
Abstract
The HEROES program is a Social Emotional Learning (SEL) initiative designed to foster resilience, self-esteem, and flourishing in youth through strengths-based, experiential learning. This study evaluated the program's impact among Grade 7 and 8 students (N = 87) in rural Alberta, Canada, measuring changes at four time points: pre-intervention, post-intervention, 2 month follow-up, and 5 month follow-up. Resilience was assessed using the Connor-Davidson Resilience Scale (CD-RISC-10), while self-esteem and flourishing were measured with the Rosenberg Self-Esteem Scale (RSES) and the Flourishing Scale (FS), respectively. Repeated-measures ANOVA, using gender as a grouping variable, showed a significant increase in resilience from pre- to post-intervention, which was maintained through 2- and 5 month follow-ups, suggesting sustained program effects. While no significant changes were observed in self-esteem or flourishing scores, minor positive shifts occurred. No gender differences were present across the study variables. These findings indicate that the HEROES program is effective in promoting resilience in youth but may require additional elements to impact self-esteem and psychological flourishing meaningfully. This study contributes to SEL literature by highlighting the potential of school-based interventions to improve youth resilience, with implications for expanding such programs in educational settings. Future research should examine the program's long-term effects and explore how facilitators might optimize outcomes across diverse populations.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".