Health-Related Quality of Life in Non-Concussed Children: A Normative Study to Inform Concussion Management
Bibliographic record
Abstract
Purpose: There has been a shift to consider pediatric concussion recovery beyond symptom management by considering how health-related quality of life (HRQoL) affects recovery. This study investigated normative ranges of HRQoL in children and explored its relationship with common pediatric concussion variables.Methods: A cross-sectional study of 1,722 non-concussed children 8–12 years old (M = 10.52 ± 1.23 years; 1,335 males, 387 females) was conducted by secondary analysis of clinical baseline concussion data. Demographic information, concussion-like symptoms (PCSI-C), and HRQoL (KIDSCREEN-10 Index) were self-reported.Results: The most reported concussion-like symptoms were common stress symptoms and were significantly negatively correlated with HRQoL. Premorbid histories of attention deficit hyperactivity disorder, mental health challenges, headaches/migraines, and concussion significantly lowered HRQoL. The number of diagnosed concussions and PCSI-C scores were significantly negatively correlated with HRQoL.Conclusions: The normative ranges and model can indicate HRQoL levels to inform clinicians how children may respond to concussion and streamline care beyond traditional assessment models.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| 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".