The Sport & Concussion Research on Executive Systems (SCoRES) study: a quantitative and qualitative examination of executive function, sport and physical activity in young adults
Bibliographic record
Abstract
Introduction: The cognitive benefits of physical activity and sport on executive function are of interest to researchers, especially considering the subsequent interventions that could be implemented. However, researchers frequently use different approaches to conceptualize and measure executive function, often using only a few computerized tasks. My Master’s thesis, therefore, aims to investigate the associations between executive function and physical activity and sport through two different studies to obtain a robust evaluation of executive function: 1) A quantitative study examining physical activity, sport and concussion history in university students and their effect on executive function, and 2) A qualitative study exploring the executive functions engaged during a game from elite university athletes’ experiences. Methods: Quantitative Study. Canadian university students (n=247) completed an online study with nine computerized executive function tasks and a behavioural self-report of executive function, as well as questions assessing weekly physical activity, athletic status, and concussion history. Structural equation modelling and linear regression were conducted to predict executive function based on age, sex, physical activity, athletic status and concussion history. Qualitative study. Canadian university athletes (n=19) participated in semi-structured interviews via Zoom to determine the executive functions engaged during a game. Thematic analysis was used to analyze the interview transcripts. Results: Quantitative Study. The three-factor model of executive function had an overall good fit: χ2 = 66.38, df = 51, p = 0.07, CFI = 0.95, TLI = 0.93, RMSEA = 0.04 [90% CI: 0.00–0.06], SRMR = 0.05. No direct relationship was found between the factors and age, physical activity, concussion history, or athletic status. Sex was significantly related to inhibition, b = 0.52, p = 0.02, such that males had greater inhibition. Physical activity (b = 0.09, p < .01), concussion history (b = 3.29, p < .05) and athletic status (b = -4.01, p < .05) were found to be significant predictors in the regression predicting self-reported executive functioning. Qualitative study. Three themes were generated: 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: The quantitative study found that physical activity, athletic status and concussion history were predictive of subjective but not objective executive function. The qualitative study determined that athletes engage many executive functions that are dependent on the timing of both the play and the game (pre-, mid- or post-). Real-life behavioural manifestations of executive functioning are more challenging to assess and measure but may be better predicted by and relate to life factors such as physical activity and sport participation. The results of my thesis provide support for future research to utilize and develop more unique and ecologically valid methods of measuring EF in the field of physical activity and sport.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".