Physical Load Affects Perceptual-Cognitive Performance of Skilled Athletes: a Systematic Review
Bibliographic record
Abstract
BACKGROUND: Many researchers have considered the impact of physical exercise on perceptual-cognitive performance. There have also been a substantial number of studies that have examined how perceptual-cognitive skills differ between elite athletes and non-athletes. However, the knowledge on how physical exercise interacts with perceptual-cognitive skill is limited. This systematic review aims to provide detailed information on how athletes' perceptual-cognitive performance is influenced by acute physical exercise load and whether these effects differ between elite athletes and lesser skilled groups. METHODS: A systematic review was conducted using different combinations of the keywords physical load, acute, exercise, perception, cognition, perceptual, cognitive, sport, and athlete with the PubMed and SportDiscus databases. Additional articles were found through screening the references of these papers. Articles had to (a) be full journal articles written in English, (b) include an athlete sample, (c) examine acute effects of physical exercise, and (d) measure a perceptual-cognitive task as the dependent variable. RESULTS: Twenty-six articles matched the inclusion criteria. Results suggested the impact of acute physical exercise on perceptual-cognitive performances of athletes depends on the specificity of the induced exercise and perceptual-cognitive task. Additionally, speed and accuracy were influenced differently by physical exercise. Furthermore, skilled athletes seem to be more positively influenced by acute physical exercise than novices. CONCLUSION: Since many factors influence perceptual-cognitive expertise, future research should be highly precise (e.g., regarding the definition of variables, the intensity of the physical exercise) and specific (e.g., regarding the tasks used, the type of the physical 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 | 0.007 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.007 | 0.007 |
| Bibliometrics | 0.007 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| 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".