Emergency Department Use for Mental Health Problems by Youth in Child Welfare Services.
Bibliographic record
Abstract
Objectives: In Canada, little research has focused on emergency department (ED) use by youth involved with child welfare services, a vulnerable population. Our aims were therefore (1) to examine the characteristics of ED users among child welfare-involved youth, 2) to identify predictors of ED use and 3) to identify youth trajectories to EDs. Methods: Data were collected from child welfare charts from two agencies in Montreal, Canada. Logistic regression was conducted to determine the predictors of ED use. Latent class analysis was used to identify trajectories to the ED. Results: The sample included 226 youth aged 11-18 years. 33% of youth visited the ED at least once for mental health problems during child welfare involvement. ED users were more likely to be youth with a history of 1) sexual abuse, 2) parental mental illness, and 3) placements outside of the home, compared to youth with no ED visits. Mental health treatment was initiated in the 30 days following an ED presentation in 24% of cases. Three trajectories were found: 1) ED contact initiated by child welfare workers for suicidal ideation/attempts, 2) ED contact initiated by police for substance use and externalized behaviours and 3) ED contact initiated by parents for suicidal ideation/attempts. Discussion: Despite all youth being followed by child welfare and many already receiving mental health services, youth had high, often recurrent ED use. This highlights the need for stronger coordination between child welfare, youth mental health services and EDs.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".