Boosting effect of regular sport practice in young adults: Preliminary results on cognitive and emotional abilities
Bibliographic record
Abstract
Several studies have shown that physical exercise (PE) improves behavior and cognitive functioning, reducing the risk of various neurological diseases, protecting the brain from the detrimental effects of aging, facilitating body recovery after injuries, and enhancing self-efficacy and self-esteem. Emotion processing and regulation abilities are also widely acknowledged to be key to success in sports. In this study, we aim to prove that regular participation in sports enhances cognitive and emotional functioning in healthy individuals. A sample of 60 students (mean age = 22.12; SD = 2.40; M = 30), divided into sportive and sedentary, were subjected to a neuropsychological tests battery to assess their overall cognitive abilities (Raven's Advanced Progressive Matrices, APM), verbal and graphic fluency (Word Fluency Task and modified Five Point Test, m-FPT), as well as their emotional awareness skills (Toronto Alexithymia Scale, TAS-20). Our results showed that sportive students performed better than sedentary ones in all cognitive tasks. Regarding emotional processing abilities, significant differences were found in the TAS-20 total score as well as in the Difficulty Describing Feelings (DDF) subscale and the Difficulty Identifying Feeling (DIF) subscale. Lastly, gender differences were found in the External-Oriented Thinking (EOT) subscale. Overall, our findings evidence that PE has positive effects on cognitive functioning and emotion regulation, suggesting how sports practice can promote mental health and wellbeing.
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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".