Coaches’ Full Range Leadership Behaviors and University Athletes’ Personal Development and Negative Experiences: Is It All About Relationship Building?
Bibliographic record
Abstract
Sport coaches can facilitate positive youth development in athletes. However, little is known about how coach behaviors that span the full range leadership model (i.e. FRLM) impact development. In this study, we asked whether FRLM coaching behaviors promote positive development outcomes and mitigate negative experiences in the university sport context and whether these effects are mediated by perceptions of a quality coach-athlete relationship. In total, 605 Canadian university athletes (Mage = 20.09 SD = 1.74) completed the Multifactor Leadership Questionnaire, the University Sport Experience Survey, and the Coach-Athlete Relationship Questionnaire. Mediation analyses assessed the explanatory role of athletes’ perceived coach-athlete relationship in associations between coaches’ leadership behaviors and athletes’ reports of personal developmental outcomes and negative experiences. The coach-athlete relationship was positively associated with positive development outcomes in university athletes (i.e. initiative, basic skills, interpersonal relationships, teamwork and social skills, and adult network and social capital) and inversely associated with negative experiences (i.e. stress, negative peer interactions, social exclusion, and negative leadership). Findings only partially supported the assertion that transformational leadership promotes positive development and reduces negative experiences by enhancing the coach-athlete relationship. The results support benefits of transformational coaching when targeting positive development, similar to youth sport, but suggest the coach-athlete relationship has little explanatory value when examining associations between coach leadership and positive development outcomes in university sport. Instead, the coach-athlete relationship does help account for the mitigation of negative experiences in the university sport context.
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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 | 0.005 |
| 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 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".