Performance on a domain-general and a domain-specific cognitive task during exercise: what are the effects of exercise intensity, exercise modality, and time of cognitive assessment among highly-trained athletes?
Bibliographic record
Abstract
This study examined cognitive performance during exercise and the effects of exercise intensity, exercise modality, cognitive task type, and time of assessment, as well as assessed the accompanying self-reported measures. Eighteen highly-trained and elite water polo players (21.04 ± 3.27 years of age; 12 male, 6 female) completed a dual-task protocol on two occasions: once performing a domain-general task (Stroop test with three cognitive trial types) and once performing a domain-specific task (water polo video-based test) during cycling exercise. The exercise involved three work-matched bouts of cycling: continuous moderate intensity, continuous high intensity, and interval high intensity. Self-reported measures (rating of perceived exertion, affect, mental effort, mental and physical demands) were recorded after each exercise condition. There were exercise intensity-related effects on Stroop performance only, including faster reaction time during moderate-intensity exercise for naming trials (p < 0.001), and interactions with cognitive trial type (p = 0.037). There were no differences between continuous and interval high-intensity exercise conditions for either performance or self-reported responses. Notably, mental effort and demand, in addition to physical effort and demand, were perceived to be significantly higher for the Stroop task than for the video-based test despite identical exercise conditions. Furthermore, Stroop accuracy was associated with more positive affect (r = 0.47) and lower ratings of physical demand (r = −0.37). These findings imply possible task-specificity of athletes’ dual-task performance. They also support the importance of further exploring how task duration and participants' perceptions relate to executive function performance during exercise.
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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 | 0.003 |
| 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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".