Concurrent Psychosocial Concerns and Post-Concussive Symptoms Following Pediatric mTBI: An A-CAP Study
Bibliographic record
Abstract
OBJECTIVES: To measure the association between psychosocial problems and persistent post-concussive symptoms (PCS) in youth who were seen in the emergency department with mild traumatic brain injury (mTBI) or orthopedic injury (OI). METHODS: From a larger prospective cohort study, Advancing Concussion Assessment in Pediatrics (A-CAP), 122 child-guardian pairs who presented to the emergency department with mTBI (N = 70) or OI (N = 52) were recruited for this cross-sectional sub-study. Each pair completed 2 measures assessing PCS burden at 2 weeks, 3 months, and 6 months post-injury. At one visit, pairs concurrently completed MyHEARTSMAP, a comprehensive, psychosocial self-assessment tool to evaluate 4 domains of mental wellness. RESULTS: When measured at the same visit, children who self-reported moderate or severe Psychiatry domain concerns concurrently experienced a greater burden of cognitive symptoms (β = 5.49; 0.93-10.05) and higher overall PCS count (β = 2.59; 0.70-4.48) after adjusting for covariables, including retrospective pre-injury symptoms and injury group. Additionally, reports indicating mild Function domain severity were associated with increased cognitive (β = 3.34; 95% CI: 0.69-5.99) and somatic symptoms (β = 6.79; 2.15-11.42) and total symptom count (β = 1.29; 0.18-2.39). CONCLUSION: Increasing severity in multiple domains of mental health is associated with more PCS in youth. While the differences in PCS between the mTBI and OI groups appeared somewhat larger for children with more mental health concerns, the interaction was not statistically significant; larger sample sizes are needed to evaluate the moderating effect of psychosocial difficulties on post-concussion symptoms.
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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 | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".