A - 46 Putting Together “Puzzle Pieces” of the Game: Executive Functions in Athletes with Sports-Related Concussion History
Bibliographic record
Abstract
Abstract Purpose While previous quantitative research has explored the malleability of executive functions in sports, there’s a gap in understanding athletes’ descriptions and utilization of executive functions during gameplay. Understanding these processes from athletes’ perspectives is crucial for developing relevant assessments, particularly following sports-related concussion (SRC), as well as using accessible athlete-driven language to describing executive function in sports neuropsychology. Thus, our study aimed to explore how athletes deploy executive functions during games and identify the most crucial executive function components for success. Method 19 Canadian collegiate athletes (ages 18–25; 37% female) with a history of SRC across various sports (soccer, volleyball, rugby, and basketball) were recruited. Participants completed semi-structured interviews via Zoom with a focus on identifying their executive function processes in their respective sports. Thematic analysis, following Braun and Clarke’s (2006) approach, was used to analyze the interview transcripts. Results We generated three themes: 1) Planning, organizing, and deciding action before actively involved in the play; 2) Problem solving when the contingencies for the pre-planned play changes; 3) Processing and evaluating performance immediately after a play. Conclusions These results provide nuance to our understanding of executive functions in sport by gaining insight into how athletes think while playing, information that neither tasks nor questionnaires offer. Through qualitative interviews, we discovered athletes engage in various executive processes throughout the game, including strategic planning and problem-solving. Overall, this study highlights specific executive processes employed throughout a game, which may become areas of focus for assessment, interventions, and follow-up for athletes following SRC.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".