Enhancing Youth Athletes' Self-Efficacy, Mental Skills, Emotional Management, and Rugby-Specific Skills through the SUPER Rugby Program
Bibliographic record
Abstract
This study aimed to evaluate the effectiveness and acceptability of the SUPER Rugby Program in enhancing youth athletes' self-efficacy, mental skills, emotional management, and rugby-specific skills. The program implemented as an eight-week intervention, integrated rugby-specific training with mental and emotional skill development. The study objectives included examining participant engagement, learning outcomes, and program applicability, as well as analysing pre- and post-test results for both experimental and control groups. Utilizing a randomized experimental design, the research involved 30 male youth rugby players aged 13-15, evenly assigned to experimental and control groups. Assessment tools comprised the Physical Self-Efficacy Scale (PSES), Ottawa Mental Skills Assessment Tool-3 (OMSAT-3), Life Skills Transfer Survey (LSTS), and rugby skill evaluations. Results demonstrated that participants in the experimental group experienced statistically significant improvements in self-efficacy (t = -33.23, p < 0.001), mental skills (t = -58.92, p = 0.001), emotional management (t = -8.08, p < 0.001), and rugby-specific skills (t = -20.03, p < 0.001) compared to the control group. While some participants noted variability in enjoyment and the quality of program presentation, high levels of learning and practical application of acquired skills were reported. In conclusion, the SUPER Rugby Program effectively enhanced both the physical and psychological competencies of youth athletes. Future studies should investigate the program's long-term impact and consider refining its visual and instructional components to further improve participant engagement and overall enjoyment.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".