International Council for Coaching Excellence (ICCE) 14th Global Coach Conference
Bibliographic record
Abstract
Researchers have investigated coaching behaviors as predictors of athlete burnout; however, limited research exists on the relationship between athletes' perceptions of coach communication and their burnout. This study explored (a) the direct effects of athletes' perceptions of each coach communication on their sport and social competence; and (b) the indirect effects of athletes' perceptions of each coach communication construct on their burnout. A total of 291 high school athletes (M age = 15.72 years, 75.3% female, 84.2% White; 63.6% playing varsity) completed selfreport measures assessing four coach communication constructs (social support, useful feedback, prosocial power, conformation), sport competence, social competence, and burnout. Structural equation modelling (SEM) was run in Mplus Version 8.1. Results indicated adequate model fit (X 2 = 951.97; p < .001, TLI = .94; CFI = .95; RMSEA = .04 [CI:.039-.048]; SRMR = .06). Coaches' use of social support ( = 0.24; SE = 0.06; p < .001), useful feedback ( = -0.13; SE=0.08; p<.01), and prosocial power ( = -0.09; SE = 0.04; p < .05) significantly predicted athletes' sport competence, which predicted athlete burnout ( = -0.20; SE = 0.05; p < .001). Interestingly, only coaches' use of useful feedback ( = 0.18; SE = 0.06; p < .01) significantly predicted athletes' social competence, which in turn did not predict athlete burnout ( = -0.01; SE = 0.08; p = .877). The model accounted for 66% of the variance in athlete burnout. The indirect effects of athletes' perceptions on each coach communication construct indicated that coaches' use of social support ( = -0.25; SE = 0.06; p <. 001) and prosocial power ( = -0.13; SE = 0.03; p < .001) were significant predictors of athlete burnout. Our findings reinforce the complexity of coach communication and its critical role on athlete burnout.
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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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".