A Prospective Study of Childhood Predictors of Traumatic Brain Injuries Sustained in Adolescence and Adulthood
Bibliographic record
Abstract
Objective:Traumatic brain injuries (TBIs) are sustained by approximately 17% of males in the general population, many of whom subsequently present mental disorders, cognitive, and physical problems. Little is known about predictors of TBIs and how to prevent them. The present study aimed to determine whether inattention–hyperactivity and/or all externalizing problems presented by boys at age 10 predict subsequent TBIs to age 34 after taking account of previous TBIs and family social status (FSS).Method:742 Canadian males were followed, prospectively, from age 6 to 34. Diagnoses of TBIs were extracted from health files, parents-reported sociodemographic and family characteristics at participants’ age 6, and teachers-rated participants’ behaviors at age 10. Separate logistic regression models predicted TBIs sustained from age 11 to 17 and from age 18 to 34. For each age period, two models were computed, one included previous TBIs, inattention–hyperactivity, FSS, and interaction terms, the second included previous TBIs, externalizing problems, FSS, and interaction terms.Results:In models that included inattention–hyperactivity, TBIs sustained from age 11 to 17 were predicted by age 10 inattention–hyperactivity (odds ratio [OR] = 1.46, 1.05 to 2.05) and by TBIs prior to age 11 (OR = 3.50, 1.48 to 8.24); TBIs sustained from age 18 to 34 were predicted by age 10 inattention–hyperactivity (OR = 1.31, 1.01 to 170). In models that included all externalizing problems, TBIs from age 11 to 17 were predicted by prior TBIs (OR = 3.66, 1.51 to 8.39); TBIs sustained from age 18 to 34 were predicted by age 10 externalizing problems (OR = 1.45, 1.12 to 1.86). Neither FSS nor interaction terms predicted TBIs in any of the models.Conclusions:Among males, using evidence-based treatments to reduce inattention–hyperactivity and externalizing problems among boys could, potentially, decrease the risk of TBIs to age 34. Further, boys who sustain TBIs in childhood require monitoring to prevent recurrence in adolescence.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| 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".