A - 35 Subjective and Objective Cognitive Functioning Differences among University Athletes
Bibliographic record
Abstract
Abstract Purpose To investigate the differences between objective cognitive scores and self-reported cognitive symptoms among university athletes. Method A prospective, quasi-experimental design was used for the study. Participants included athletes from a Canadian university over consecutive seasons who were diagnosed with a Sports Related Concussion (SRC) and underwent a post-injury assessment within 24–48 hours. Nineteen male and female athletes (ages M = 25.11, SD = 3.63) with complete data from the Sideline Concussion Assessment Tool (SCAT-5) were included. An independent T-test and correlational analysis were used to evaluate the relationship between subjective symptoms (memory and concentration) and objective cognitive functioning. Results There were no significant differences between baseline and post-injury testing on SCAT-5’s learning, concentration and delayed recall tests (p > 0.05) but significant differences between baseline and post-injury symptom report of concentration t(36) = −3.4, p < 0.001 and memory t(36) = −3.0, p < 0.001. At baseline, there was a significant negative correlation between memory total score and the reported cognitive symptoms, (r = −0.61, p < 0.05) and between total cognitive score and self-reported symptom report (r = −61, p < 0.05). In contrast, at post-injury, there were no significant correlations between the memory total score or total cognitive scores and the reported symptoms (r = 0.7, p = 0.79; r = 0.11, p = 0.67). Conclusions Participants endorse a significant increase in symptoms at post injury in spite of no significant changes in their cognitive performance. Psychological distress at injury may impact perceptions of cognitive difficulties.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".