Multiple domain-general assessments of cognitive functions in elite athletes: Contrasting evidence for the influence of expertise, sport type and sex
Bibliographic record
Abstract
Converging evidence has shown that domain-general cognitive abilities, especially executive functions (EF), tend to be superior in sport experts. However, recent studies have questioned this cognitive advantage and found inconsistent findings when comparing sport type and sex. This study aimed to compare the impact of sport expertise, sport type, and sex on various domains of cognitive functions. Two hundred and thirty elite athletes (nFemale = 124, nMale = 106) representing three sport categories (Team [n = 91], Precision-skill dependent [n = 63], and Speed-strength [n = 76] sports) were assessed using a computerized neuropsychological test battery including tests of EF (working memory, inhibition, cognitive flexibility and planning), as well as tests of selective and sustained attention. T-scores and raw values were used to analyze performance through t-tests and ANCOVA with age as covariate. Athletes demonstrated better performance than the normative mean on 5 out of 11 cognitive test variables (p < 0.005). However, their performance fell within the average range when considering the results along a normative scale, except for sustained attention and working memory where they performed just above average (<1 SD). There was a significant main effect of sport category on only one EF variable (p = 0.003). Males performed significantly faster than females on motor reaction time measures of attention and inhibition (all p < 0.001). In this study, the ‘expert advantage’ on domain-general cognitive tests was less prominent when utilizing a normative scale and controlling for age or speed-accuracy trade-offs, except for sustained attention and working-memory. Cognitive functions did not appear to differ meaningfully based on athletes’ sport type or sex.
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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 | 0.001 | 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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".