Engagement into treatment: comparing immigrants and non-immigrants in youth mental health services in Montreal
Bibliographic record
Abstract
Access to mental health care is of much concern. In Canada, only 10 to 25% of youth with mental health problems receive treatment and the disparity between need and use of services is even higher for ethnocultural minority groups. Access to care is a wide concept that pertains to be referred to services as well as to receive treatment, which includes being engaged in care. This represents a major public health issue for primary care institutions offering youth mental health (YMH services) because low engagement rates have adverse impacts on clinical outcomes and the cost effectiveness of services. Little is known about factors that specifically influence engagement for immigrant populations accessing primary YMH services. In light of this gap, the primary objective of this research is to explore multi-level factors (youth-, familial-, clinical- and organizational-related) and their influence on the engagement process of youth and their families accessing primary YMH care as well as to address the specific reality of immigrant families. The present research is based on a one-year retrospective file review of requests to two Centre de santé et de services sociaux (CSSS) of two multiethnic neighbourhoods in Montreal. The study had several findings. Firstly, first- and second-generation immigrants, in comparison to non-immigrants, are less likely to attend YMH treatment, and they are less likely to be strongly engaged. Secondly, collaborative care, mixed therapy and referrals involving schools were three significant factors that positively impact strong engagement of youth and families into care. The results suggest a multifactorial and multiphase process of engagement, as well as a complex interplay between these factors and engagement for ethnically diverse populations.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 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".