Parent and Youth Athlete Perceptions of Concussion Injury: Establishing a Factor Structure
Bibliographic record
Abstract
OBJECTIVE: The first objective was to establish the respective factor structures of a concussion perceptions inventory that was adapted for youth athletes (ages 8-14 years) and their parents from the Perceptions of Concussion Inventory for Athletes. The second objective was to understand the associations between the concussion perceptions of youth athlete-parent dyads. METHOD: In this cross-sectional study, 329 parent-youth athlete dyads completed a respective concussion perception inventory. Mean age of youth respondents was 10.9 ± 1.8 years (70.1% male) and mean age of parent respondents was 40.5 ± 13.6 years (60.9% female). RESULTS: Exploratory factor analyses revealed unique 7-factor structures for both the youth athlete and parent inventories (youth athlete: anxiety, clarity, treatment, permanent injury, symptom variability, long-term outcomes, and personal control; parent: anxiety, clarity, treatment, permanent injury, symptom variability, and long-term outcomes, and affect others). Weak associations were found between dyads on the 5 factors that were composed of identical items (anxiety, clarity, treatment, permanent injury, and symptom variability). CONCLUSIONS: Findings suggest that this adapted inventory has adequate psychometric properties to be used in the study of the concussion perceptions of youth athletes and their parents. Weak correlations across the concussion perceptions in the dyads suggest that parents and children hold different concussion perceptions and this should be considered in instrument selection of future studies.
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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 | 0.005 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".