Acute Effects of Concussion in Adolescent Athletes With High Preseason Anxiety
Bibliographic record
Abstract
OBJECTIVE: To examine associations between pre-existing anxiety symptoms, and symptoms and cognitive functioning acutely following a suspected concussion. DESIGN: Nested case-control study. SETTING: High schools in Maine, USA. PARTICIPANTS: Participants were identified from a dataset of 46 920 student athletes ages 13 to 18 who received baseline preseason testing. A subset of 4732 underwent testing following a suspected concussion. Of those, 517 were assessed within 72 hours after their suspected concussion and met other inclusion criteria. Nineteen injured athletes endorsed anxiety-like symptoms on the Post-Concussion Symptom Scale (PCSS) during baseline testing and were placed in the high anxiety group. Each athlete was matched to 2 injured athletes who did not endorse high levels of anxiety-like symptoms (N = 57). MAIN OUTCOME MEASURES: Immediate Post-Concussion Assessment and Cognitive Testing cognitive composite scores, PCSS total score, and symptom endorsement. RESULTS: Cognitive composite scores were similar between groups across testing times ( = 0.004-0.032). The high anxiety group endorsed a greater number of symptoms than the low anxiety group ( = 0.452) and rated symptoms as more severe ( = 0.555) across testing times. Using a modified symptom score that excluded anxiety-like symptoms, a mixed analysis of variance indicated a group by injury interaction ( = 0.079); the high anxiety group reported greater increases in overall symptom severity following injury. CONCLUSIONS: Adolescent athletes who have an anxious profile at baseline are likely to experience greater symptom burden following injury. Consideration of pre-injury anxiety may inform clinical concussion management by tailoring intervention strategies (eg, incorporating mental health treatments) to facilitate concussion recovery.
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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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 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 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".