Associations between psychological resilience and metrics of white matter microstructure in pediatric concussion
Bibliographic record
Abstract
This study investigated associations between psychological resilience and characteristics of white matter microstructure in pediatric concussion. This is a case control study and a planned substudy of a larger randomized controlled trial. Children with an acute concussion or orthopedic injury were recruited from the emergency department. Participants completed both the Connor-Davidson Resilience Scale 10 and an MRI at 72 h and 4-weeks post-injury. The association between resiliency and fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) at both timepoints were examined. We examined whether these associations were moderated by group. The association between resiliency captured at 72 h and diffusion tensor imaging metrics at 4 weeks was also investigated. Clusters were extracted using a significance threshold of threshold-free cluster enhancement corrected p < .05. A total of 66 children with concussion (median (IQR) age = 12.88 (IQR: 11.80-14.36); 47% female) and 29 children with orthopedic-injury (median (IQR) age = 12.49 (IQR: 11.18-14.01); 41% female) were included. A negative correlation was identified in the concussion group between 72 h resilience and 72 h FA. Meanwhile, positive correlations were identified in the concussion group with concussion between 72 h resilience and both 72 h MD and 72 h RD. These findings suggest that 72 h resilience is associated with white matter microstructure of the forceps minor, superior longitudinal fasciculus, and anterior thalamic radiation at 72 h post-concussion. Resilience seems to be associated with neural integrity only in the acute phase of concussion and thus may be considered when researching concussion recovery.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".