Mental health service use of young people in child welfare services in Quebec, Canada.
Bibliographic record
Abstract
Background: Youth involved in child welfare have high rates of mental health problems and are known to receive mental health services from multiple settings. Still, gaps remain in our understanding of service use patterns across settings over the course of youth's involvement with child welfare. Objective: To examine the settings, reasons for contact, persons involved in initiating care, and timing of each mental health service contact for individuals over their involvement with the child welfare system, and to identify factors that predict multi-setting use. Methods: Data on mental health service contacts were collected retrospectively from charts for youth aged 11-18 (n=226) during their involvement with child welfare services in Montreal, Quebec. Logistic regression analysis was conducted to determine predictors of multi-setting mental health services use (defined as ≥3 settings). Results: 83% of youth had at least one mental health service contact over the course of their child welfare services follow-up, with 45% having multi-setting use. Emergency Departments were the top setting for mental health services. Youth with a higher number of placements and from neighborhoods with greater social and material deprivation were significantly likelier to use ≥3 mental health service settings over the course of their follow-up. Conclusion: These findings suggest a need for enhanced collaboration between youth-serving sectors to ensure that continuous and appropriate mental health care is being offered to youth followed by child welfare systems. The relationship between placement instability and multi-setting mental health service use calls for specific policies to ensure that young people do not experience multiple discontinuities of care.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 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) | 0.003 | 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".