A-22 Beyond Sports and Concussions: The Link between Shifting and Higher-Order Executive Functioning in Young Women
Bibliographic record
Abstract
Abstract Purpose Our aim was to investigate the role of lifestyle factors, physical activity, sport, and concussion history, as well as Miyake and colleague’s (2000) three lower-order factors of executive function (shifting, updating, and inhibition) on higher-order decision making and self-reported executive functioning in young women. Methods 180 Canadian female university students (ages 18–25) completed 9 computerized executive function tasks assessing shifting, updating, and inhibition, as well as decision making (Iowa Gambling Task). Participants also completed the Executive Function Index (subjective executive functioning) and reported their age, concussion history, weekly physical activity, and level of sports participation. Linear regression analysis was used to assess the effects of the predictor variables on the Executive Function Index scores and Iowa Gambling Task scores. Results Only shifting significantly predicted both subjective executive functioning scores (b=2.65, p<.05) and Iowa Gambling Task performance (b=269.02, p<.01). Weekly physical activity was significantly associated with subjective executive functioning (b=.10, p<.01), but not Iowa Gambling Task performance. Age, concussion history, sport participation, inhibition, and updating were not significant for either regression. Conclusions These findings suggest that shifting may be a critical component of both higher-order decision making and subjective executive functioning, while physical activity may be important for subjective executive functioning. The lack of predictive value for lifestyle factors such as concussion history and sports participation suggests that there are other factors influencing executive functioning performance in healthy young women. Future studies should explore other factors, such as hormonal variability, that may be impact subjective executive functioning and decision making in young women.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".