Characteristics of children and youth who visit the emergency department for a behavioural disorder.
Bibliographic record
Abstract
OBJECTIVE: Relatively little is known about children who present to emergency departments (EDs) to stabilize acute emergencies related to behavioural disorders. This study describes patient and treatment characteristics of such children/youth. METHODS: We conducted a retrospective medical record review of consecutive ED presentations made by children/youth (10 to 17 years) between January 2009 and December 2011 for visits with a main discharge diagnosis of hyperkinetic disorder, mixed disorder of conduct and emotions, or conduct disorder. Socio-demographic and ED visit data were analyzed descriptively. RESULTS: During the study period, 365 consecutive presentations made by 325 children/youth. The most common presenting complaints were related to depression/self-harm (45.8%) and violent behaviours (28.8%). Many children/youth had a previously diagnosed psychiatric disorder (59.4%) and identified being under the care of a child psychiatrist (42.2%). The majority of ED visits were triaged as urgent or emergent (51.5% and 41.1%, respectively) and included mood and suicidality assessments (84.7% and 80.8%, respectively). Follow-up with various services was made for all visits. CONCLUSION: Children and youth presented to the ED for a behavioural disorder had urgent needs related to self-harm, depression and violent behaviours. These findings draw attention to the important role of the ED in managing physical safety and well-being concerns for families and recommending follow-up in the post-crisis period.
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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 | 0.000 | 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 | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".