Symptom Trajectories and Their Biopsychosocial Correlates in Pediatric Concussion: An A-CAP Study
Bibliographic record
Abstract
This study sought to identify trajectories of symptom status in children and adolescents with concussion across the first 6 months post-injury and to examine their biopsychosocial correlates. The study used data collected as part of a prospective, longitudinal cohort study, Advancing Concussion Assessment in Pediatrics (A-CAP), conducted from 2016 to 2019, which recruited 967 English- or French-speaking children 8.0 to <17 years old with either a concussion ( N = 633) or mild orthopedic injury (OI; N = 334) from five pediatric emergency departments (EDs) in Canada. Participants rated post-injury symptoms weekly from 1 week to 3 months and biweekly from 3 to 6 months post-injury. The ratings of children with concussion were classified as symptomatic/asymptomatic relative to retrospective pre-injury symptom ratings using reliable change equations derived from the OI group. A set of 26 biopsychosocial variables, assessed in the ED or at a 1-week visit, was derived from core measures collected in the A-CAP study. They were grouped a priori into clusters of five to seven variables representing four domains (i.e., social determinants of health [SDoH], neurobiological, child psychosocial, and parent/family psychosocial). Symptom trajectories were examined using latent class growth analysis (LCGA). Multinomial logistic regression tested the independent and joint ability of the variables in the four domains to discriminate trajectories. Multiple imputation with chained equations was completed prior to multivariable analyses. Analyses included children with concussion with ≥1 post-injury symptom rating ( N = 553; age m = 12.4 years, standard deviation = 2.5; 40.3% female). Based on multiple statistical criteria, as well as parsimony and interpretability, LCGA identified four distinct symptom trajectories: rapid recovery ( n = 301, 54%); typical recovery ( n = 106, 19%); slow recovery ( n = 73, 13%); and chronically symptomatic ( n = 73, 13%). Variables in the SDoH, neurobiological, and child psychosocial domains independently discriminated the trajectories (polytomous discrimination index [PDI] = 0.39–0.44). When combined, significant variables from those three domains showed the best overall discrimination (PDI = 0.49). The findings indicate that children with concussion display distinct symptom trajectories that differ on SDoH, neurobiological, and psychosocial variables, confirming that a biopsychosocial model is critical to understanding pediatric concussion recovery and guiding its management. The findings may inform clinical prognosis and suggest potential targets for clinical trials, including post-acute pain and loneliness, to reduce persisting symptoms after 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 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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".