Should Young Children with Traumatic Brain Injury Be Compared with Community or Orthopedic Control Participants?
Bibliographic record
Abstract
Pediatric traumatic brain injury (TBI) research depends on comparisons of profiles and outcomes between brain-injured individuals and groups consisting either of injured controls (e.g., orthopedic injuries, OI) or uninjured, typically developing children recruited from the community (community controls, CC). Children with OI are thought to provide optimal comparisons for individuals with TBI because they share injury-related experiences and pre-morbid characteristics; however, a study by Mathias and colleagues (2013)1 in adults has called into question the added value of injury control groups in TBI research. The comparability of these control groups has not been established in young children. Seventy-two children with OI and 84 CC aged between 18 and 60 months were compared on a range of demographic variables, developmental and medical history, pre-injury behavioral and adaptive profiles, as well as on measures of adaptive functioning, behavior, family functioning, post-concussive symptoms, and cognition (intellectual functioning, verbal abilities, executive functioning, social cognition) 6 months after the OI. There were no statistically significant differences between the OI and CC groups on any of the variables tested, whether they related to pre-injury or post-injury characteristics. The findings are applicable to studies seeking to identify appropriate control groups in the context of preschool TBI research, and suggest no clear advantage in recruiting OI controls based on the variables studied and the methodology used. However, further work is necessary to verify additional factors and outcomes relevant to pediatric TBI research, as well as to compare outcomes between these two groups at more acute stages (i.e., prior to 6 months post-injury).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.049 | 0.132 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.005 |
| Open science | 0.005 | 0.002 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".