Transformational coaching in action: An exploration of coaches' real-time leadership behaviours in youth sport
Bibliographic record
Abstract
Coaches' leadership behaviours are an integral component of the youth sport environment (Vella, Oades, & Crowe, 2013). However, research examining coaches' real-time leadership behaviours in youth sport is limited. The aim of the present study was to explore the leadership behaviours that coaches exhibit and to investigate the association between these behaviours and athletes' motivational outcomes. Twenty-one male youth competitive ice hockey coaches were observed over multiple practice. 291 athletes (Mage = 14.15 years; SD = 1.27, 73% male) completed measures of self-determined motivation (Pelletier et al., 1995), psychological need satisfaction (LaGuardia, Ryan, Couchman, & Deci, 2000), and motivational climate (Smith, Cumming, & Smoll, 2008). Coaches' behaviours were assessed using the Coach Leadership Assessment System (Turnnidge & CA´tA©, 2016). Results revealed that coaches used a range of behaviours, with a predominant use of neutral coaching behaviours (M = 68.30%, SD = 13.19), followed by transformational (M = 25.12%, SD = 11.54), and transactional (M = 4.25%, SD = 2.82) coaching behaviours. Coaches exhibited low levels of laissez-faire (M = 1.74%, SD = 4.50) and toxic (M = 0.4%, SD = 0.85) coaching behaviours. Multilevel analyses demonstrated that at the team level, coaches' observed leadership behaviours were not linked to athletes' self-determined motivation, but accounted for between 2-16% of the variance of athletes other motivational outcomes. The findings extend past research by examining coaches' moment-to-moment leadership behaviours and the hierarchical effects of leadership behaviours on youth's motivational outcomes in sport. Practical recommendations as well as avenues for future research are discussed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| 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".