Structuring competitive youth sport programs: Understanding the relationships between program quality, psychological needs satisfaction, and mental health
Bibliographic record
Abstract
Sport program structures have been shown to directly influence outcomes associated with youth sport participation (Baldwin & Wilder, 2014), including mental health (Durlak et al., 2010). However, there is limited research on the specific mechanisms that facilitate or hinder mental health in this context. The purpose of this study was to examine the relationships between perceived program quality, basic needs satisfaction, and mental health within youth sport. Youth participating in sport programs (N = 160; Mage = 15.36, SD = 2.50) completed validated paper questionnaires at mid-point in their sport program, with questions related to the quality of their sport program, and at end-point in their sport program, with questions pertaining to basic needs satisfaction and mental health. Structural equation modeling was used to test the direct relationships between program quality and mental health and between basic needs satisfaction and mental health. Using a variety of fit indices, results revealed an adequate fit of both models to the data, suggesting that program quality significantly and positively predicted basic needs satisfaction and basic needs satisfaction significantly and positively predicted mental health. Bootstrapping analysis was used to test if basic needs satisfaction mediated the relationship between program quality and mental health. Results supported mediation, with a large effect (k2 = 0.28). These findings emphasize the value of structuring youth sport programs to satisfy basic needs, which can have positive implications on mental health. This is important because mental health in childhood may translate into mental health in adulthood.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".