Do Children Who Sustain Traumatic Brain Injury in Early Childhood Need and Receive Academic Services 7 Years After Injury?
Bibliographic record
Abstract
OBJECTIVE: To examine the prevalence of academic need, academic service utilization, and unmet need as well as factors associated with academic service utilization 6.8 years after traumatic brain injury (TBI) in early childhood. METHODS: Fifty-eight (16 severe, 14 moderate, 28 complicated mild) children with TBI and 72 children with orthopedic injury (OI) completed the long-term follow-up 6.8 years after injury in early childhood (ages 3-7 years). Injury group differences in rates of need for academic services, academic service utilization, and unmet need as well as factors associated with service utilization and unmet need were examined. RESULTS: Students with moderate and severe TBI had significantly greater rates of need than those with OI. A greater proportion of the severe TBI sample was receiving academic services at long-term follow-up than the OI and complicated mild groups however, among those with an identified need, injury group did not affect academic service utilization. Below average IQ/achievement scores was the only area of need predictive of academic service utilization. Rates of unmet need were high and similar across injury groups (46.2%-63.6%). CONCLUSION: The need for academic services among patients who sustained a TBI during early childhood remains high 6.8 years post injury. Findings underscore the importance of continued monitoring of behaviors and academic performance in students with a history of early childhood TBI. This may be especially true among children with less severe injuries who are at risk for being underserved.
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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 | 0.005 |
| 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 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".