Accessing mental health walk-in clinics and other services for children and families
Bibliographic record
Abstract
Background: Mental health walk-in clinics (MHWCs) are a model of service delivery that has gained increasing interest and traction. The aim of the study was to better understand how MHWC use is related to use of other services provided by agencies. Objectives: (1) Explore if and how MHWCs are used alongside other services, including the different time points (e.g. MHWCs used exclusively, MHWCs used before other agency services); (2) identify correlates of MHWC use alongside other agency services. Design: Administrative data from two child and youth mental health agencies in Ontario were extracted, including demographics, visit data, and presenting concerns. Methods: In this exploratory, descriptive study, analyses of administrative data were conducted to identify patterns and correlates of MHWC use before other agency services, compared with MHWC use exclusively. Results: More than half of families used MHWCs and other agency services before or concurrently with other agency services. Child age, guardianship, and disposition at discharge emerged as correlates of MHWC use before other agency services. Conclusions: MHWCs are sufficient for some families, easing the pressure on other agency services. For the remaining families, MHWCs can help support them at the beginning of their service use journey.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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".