Understanding the relationships between programme quality, psychological needs satisfaction, and mental well-being in competitive youth sport
Bibliographic record
Abstract
Youth sport programme structures and processes can directly influence participation outcomes, including mental health and well-being. Researchers have found that programme quality and basic needs satisfaction foster psychosocial outcomes; however, limited research has examined the mechanisms that facilitate mental health. The purpose of this study was to examine relationships between programme quality, basic needs satisfaction, and mental well-being in competitive youth sport. Youth (N = 160, 89 males, 71 females; Mage = 15.36, SD = 2.50) completed questionnaires at mid-season, with questions related to quality of their sport programming, and at programme end, with questions pertaining to basic needs satisfaction and mental well-being. Structural equation modelling was used to test the direct relationships between programme quality and mental well-being (r = .46, p < .001; model 1) and between basic needs satisfaction and mental well-being (r = .63, p < .001; model 2). Using several fit indices, results showed an adequate fit of both models to the data, suggesting that programme quality significantly predicted basic needs satisfaction and basic needs satisfaction significantly predicted mental well-being. Bootstrapping analysis was used to test if basic needs satisfaction mediated the relationship between programme quality and mental well-being. Results supported mediation, with a large effect (k2 = 0.28). The study findings help to emphasise the value of structuring youth sport programmes to satisfy basic needs, which may have positive implications on youth mental health. This is important because supporting mental well-being at an earlier age may facilitate mental health and well-being 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 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 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".