A Qualitative Investigation of Executive Function in Externally Paced Sports within “the Structure and Chaos of the Game”
Bibliographic record
Abstract
Introduction: While previous quantitative research has determined that executive function is malleable to sport participation, executive functioning in sport has not yet been investigated qualitatively in elite university athletes' sport experiences. Understanding the executive processes used in sports from an athletes ' perspective is vital to create more pertinent assessments as well as to provide accessible, athlete-focused language to describe executive function in sport. Therefore, our study had the following research question: 'What is the role of executive function in elite EP sports athletes' sport experiences?'. Methods: 19 Canadian U-Sports athletes (ages 18 – 25; 37% female) were recruited through emailing coaches and social media. The participants completed semi-structured interviews via Zoom with a focus on identifying their executive function processes in sport. Thematic analysis was used to analyze the interview transcripts. Results: We generated three themes: 1) Engaging in pre-play or pre-game planning, organization and decision making, 2) Engaging in mid-play problem solving and purposive action and 3) Engaging in post-play or post-game information processing, emotional control and effective performance. Conclusions: Our study determined that the executive functions athletes use are dependent on their involvement in the play and the point of the game (pre-, mid- or post-). The three themes demonstrate that throughout different moments of the game, the athletes engage in several executive functions such as planning (pre-), problem-solving (mid-), and self-monitoring (post-). These findings offer a unique contribution to our understanding of athletes’ executive function in sport and have important implications for sports psychologists and related professionals assessing and explaining executive function to athletes in the future.
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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 | 0.007 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.010 | 0.013 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".