Coach-athlete relationship, basic psychological needs satisfaction, and life skills development in Canadian high school sport
Bibliographic record
Abstract
For students, high school sport represents a meaningful activity to develop relationships (CamirA©, 2015), increase connection to school (CamirA©, 2014), foster health-conscious decision-making (Van Boekel et al., 2016), develop athletic talents (Gould & Carson, 2008), and learn life skills (CamirA© & Kendellen, 2016). To better apprehend the outcomes of participation, the associations between the coach-athlete relationship, athletes' basic psychological needs satisfaction, and life skills development were examined. A total of 1238 high school coaches (males = 728, 59%) from Alberta (n = 672), British Columbia (n = 474), and Newfoundland and Labrador (n = 92) were recruited. Coaches (Mage = 55.91; SD = 11.76) completed an online questionnaire in February-March 2018, which included demographic questions, the Coach-Athlete Relationship Questionnaire (CART-Q; Jowett & Ntoumanis, 2004), the Interpersonal Behaviors Questionnaire (IBQ; Rocchi et al., 2016), and the Life Skills Scale for Sport (LSSS; Cronin & Allen, 2017). Confirmatory factor analyses indicated good model fit for all scales (Hair et al., 2010; CFI 0.08, RMSEA > 0.05, and X²/df > 5). A mediation analysis using structural equation modeling tested (a) whether an association existed between CART-Q and LSSS outcomes and (b) whether the association between CART-Q and LSSS outcomes was dependent on the satisfaction of athletes' basic psychological needs. Results indicated the coach-athlete relationship was directly related to athletes' emotional and social skills and indirectly related to teamwork, goal setting, problem solving, leadership, time management, and communication through the satisfaction of athletes' basic psychological needs.Acknowledgments: SHHRC
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".