Mood and anxiety symptoms following pediatric mild traumatic brain injury: a scoping review.
Bibliographic record
Abstract
Background: Thousands of children sustain mild traumatic brain injuries (mTBI) worldwide each year. Multiple physical and somatic symptoms can occur following pediatric mTBI, including new-onset mood symptoms, headaches, and pain. Objective: This scoping review examined the existing literature pertaining to mood and anxiety symptoms following pediatric mTBI, in order to summarize the current evidence and identify areas for future research. Methods: The Pubmed, EMBase, and APA PsycINFO databases were searched to identify articles that examined mood and anxiety symptoms in children and adolescents following mTBI. Results: A total of 20 published articles were included in the review. The existing research suggests that mood and anxiety symptoms are more common in children and adolescents with mTBI, when compared to orthopedically injured or healthy controls. Several factors may contribute to the development of these symptoms: injury characteristics, older age at injury, female sex, and psychosocial variables including lower socioeconomic status and family history of psychiatric disorders. Conclusion: The findings of this review highlight the need for additional research on the relationship between pediatric mTBI and subsequent mood and anxiety symptoms. We particularly recommend long-term prospective cohort studies which include appropriate control groups as well as a neuroimaging component to distinguish complicated from uncomplicated mTBI.
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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 | 0.003 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 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".