Acute effects of continuous and high‐intensity interval exercise on executive function
Bibliographic record
Abstract
The purpose of this study was to examine the acute effects of 20‐min of cycling exercise at varying exercise intensities on executive function performance. Participants ( N = 107) completed a baseline measure of executive function (Stroop task [ ST ]) and a graded cardiovascular exercise test during Visit 1. During Visit 2, participants were randomized to groups and completed 20 min of activity involving: high‐intensity interval exercise, high‐, moderate‐ or very‐light intensity continuous exercise, or no‐exercise (control). The ST was performed immediately following the exercise/control manipulation and at 10‐min post‐manipulation. Results showed exercise positively influenced executive function immediately after exercising in all groups with the exception of the very‐light intensity exercise group, while all groups showed significant improvements at 10‐min post‐exercise. Findings also revealed a significant difference between the moderate‐intensity exercise group in comparison to the very‐light intensity exercise group immediately post‐exercise. Among the exercise stimuli investigated, results suggest moderate‐intensity exercise provides the greatest beneficial effects on executive function immediately following exercise. Future research should focus on mechanisms that would account for enhanced executive function performance following acute exercise and dose–response effects.
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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 | 0.001 |
| 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 | 0.000 | 0.000 |
| 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".