Multicentre evaluation of anxiety and mood among collegiate student athletes with concussion
Bibliographic record
Abstract
Objectives: Mental health problems are a premorbid and postinjury concern among college student athletes. Clinical phenotypes of anxiety and mood disruption are prevalent following mild traumatic brain injury, including concussion, a common sports injury. This work examined whether concussed student athletes with a history of mental health problems and higher symptoms of anxiety and mood disruption at baseline were more likely to have higher postinjury reports of mood and anxiety as well as prolonged resolution of postconcussive symptoms to near-baseline measures. Methods: This was a retrospective cohort study of a multi-institutional database of standardised baseline and postinjury assessments among college student athletes. Anxiety/mood evaluation data among varsity college athletes from four institutions over 1 year were measured and compared at baseline and postconcussion recovery using descriptive statistics and multilevel/mixed-effects analysis. Results: Data from 2248 student athletes were analysed, with 40.6% reporting at least one symptom of anxiety and/or mood disruption at baseline. Of the 150 distinct concussions, 94.7% reported symptoms of anxiety/mood disruption during recovery (recovery time=0-96 days). Higher anxiety/mood scores at baseline were significantly associated with higher scores following concussion (p<0.001). Recovery trajectories of anxiety/mood scores showed different patterns by sex and prolonged recovery. Conclusion: among college student athletes. These students are at higher risk for symptomatology following injury, representing a screening cohort that may benefit from early counselling. Almost all student athletes will experience symptoms of anxiety and/or mood disruption following concussion.
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 | 0.006 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.001 | 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".