Screening for post-traumatic stress disorder after injury in the pediatric emergency department - a systematic review protocol
Bibliographic record
Abstract
BACKGROUND: Pediatric injury is highly prevalent and has significant impact both physically and emotionally. The majority of pediatric injuries are treated in emergency departments (EDs), where treatment of physical injuries is the main focus. In addition to physical trauma, children often experience significant psychological trauma, and the development of acute stress disorder (ASD) and post-traumatic stress disorder (PTSD) is common. The consequences of failing to recognize and treat children with ASD and PTSD are significant and extend into adulthood. Currently, screening guidelines to identify children at risk for developing these stress disorders are not evident in the pediatric emergency setting. The goal of this systematic review is to summarize evidence on the psychometric properties, diagnostic accuracy, and clinical utility of screening tools that identify or predict PTSD secondary to physical injury in children. Specific research objectives are to: (1) identify, describe, and critically evaluate instruments available to screen for PTSD in children; (2) review and synthesize the test-performance characteristics of these tools; and (3) describe the clinical utility of these tools with focus on ED suitability. METHODS: Computerized databases including MEDLINE, EMBASE, CINAHL, ISI Web of Science and PsycINFO will be searched in addition to conference proceedings, textbooks, and contact with experts. Search terms will include MeSH headings (post-traumatic stress or acute stress), (pediatric or children) and diagnosis. All articles will be screened by title/abstract and articles identified as potentially relevant will be retrieved in full text and assessed by two independent reviewers. Quality assessment will be determined using the QUADAS-2 tool. Screening tool characteristics, including type of instrument, number of items, administration time and training administrators level, will be extracted as well as gold standard diagnostic reference properties and any quantitative diagnostic data (specificity, positive and negative likelihood/odds ratios) where appropriate. DISCUSSION: Identifying screening tools to recognize children at risk of developing stress disorders following trauma is essential in guiding early treatment and minimizing long-term sequelae of childhood stress disorders. This review aims to identify such screening tools in efforts to improve routine stress disorder screening in the pediatric ED setting. TRIALS REGISTRATION: PROSPERO registration: CRD42013004893.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.023 | 0.009 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.017 | 0.004 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".