Optimal functioning after early mild traumatic brain injury: Evolution and predictors
Bibliographic record
Abstract
INTRODUCTION AND OBJECTIVES: Early mild traumatic brain injury (mTBI or concussion sustained between 0 and 5 years old) can lead to post-concussive symptoms, behavioral changes, and cognitive difficulties. Although school-age children (6-17 years old) experience similar consequences, severe neuropsychological deficits are not common, and the majority have no persisting symptoms after one month. Thus, there may be value in focusing on what characterizes optimal functioning (or wellness) after mTBI, but this has not been explored in young children. This study documents the evolution and predictors of optimal functioning after early mTBI. METHOD: = 71). Optimal functioning was defined as: (1) no clinically significant behavioral problems; (2) no cognitive difficulties; (3) no persisting post-concussive symptoms; (4) average quality of life or better. Predictors related to sociodemographic, injury, child, and caregiver characteristics included number of acute symptoms, child sex, age, temperament, maternal education, parent-child attachment and interaction quality, and parenting stress. RESULTS: Fewer children with mTBI had optimal functioning over 6 and 18-months post-injury compared to those with OI and TDC. Higher parent-child interaction quality and lower child negative affectivity temperament independently predicted optimal functioning. CONCLUSION: Children who sustain early mTBI are less likely to exhibit optimal functioning than their peers in the long-term. Parent-child interaction quality could be a potential intervention target for promoting optimal function.
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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 | 0.004 |
| 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 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".