Neuropsychological Performance: How Mental Health Drives Attentional Function in University-Level Football Athletes
Bibliographic record
Abstract
This preliminary study investigates the potential relationship between electrophysiological profiles measured by quantitative electroencephalography (QEEG) and attentional performance in 34 university American football players. QEEG data revealed patterns associated with burnout, chronic pain, and insomnia among the athletes. Attentional performance was generally average, but players exhibited faster reaction times in the alertness task without warning, fewer errors in the sustained attention task, and lower scores in the divided attention task, favoring visual information over auditory information. Significant negative correlations emerged between QEEG profiles associated with burnout, ADHD, depression, and anxiety and specific attentional subcomponents. These findings suggest a link between mental health-related brain activity and attentional performance. In a clinical context, they emphasize the need for early detection and intervention in mental health problems. This might improve cognitive performance and well-being in athletes. However, due to the small sample size and the lack of a control group, these results are considered preliminary, and further research is required to confirm and expand on these associations.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.000 |
| 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 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".