The effects of coaches' observable emotions on athletes' self-reported enjoyment in a youth recreational basketball league
Bibliographic record
Abstract
Perceived enjoyment has consistently been reported as one of the main determinants of youth sport participation, with coaches playing a salient role in facilitating an enjoyable environment. Observational studies of coaches and their interactions with athletes have traditionally focused on the content of coach behaviours; however there have been recent calls to explore the emotional tones of these behaviours. Given the affective nature of the enjoyment construct and growing interest in the topic of interpersonal emotion regulation, coaches' emotions represent a novel and potentially influential role in athletes' perceptions of enjoyment. Thus, the purpose of this study was to explore the relationship between coaches' observed emotions and youth athletes' perceived enjoyment in a recreational basketball league. Male coaches (n = 6) and their respective youth male athletes (n = 35; Mage = 11.9) were videotaped during games, while athletes also completed a self-report measure of sport enjoyment (SEYSQ; Wiersma, 2001). Coach behaviour was coded using the Assessment of Coaches' Emotions systematic observation instrument (ACE; Allan et al., 2014). A hierarchical cluster analysis of coaches' emotions revealed three distinct clusters: the "tense" coach (n = 1), the "neutral" coaches (n = 3), and the "happy" coaches (n = 2). Separate ANOVAs compared athletes' enjoyment data from six subscales within the SEYSQ. The "happy" coaches' athletes reported significantly higher levels of enjoyment from competition than athletes who were coached by the "tense" coach. The findings of this study provide preliminary evidence to suggest that coaches' emotions influence athletes' enjoyment, specifically competitive excitement.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".