Intensive Children and Youth Mental Health Services in Ontario: Applying Gelberg-Andersen's Behavioral Model of Health Service Use for Vulnerable Populations
Bibliographic record
Abstract
Ontario’s child and youth mental health (CYMH) system is undergoing a transformation aimed at improving access to effective services. Evidence-informed policy directions are the new norm however; few dynamic models exist to understand the utilization of CYMH services. This study adapted the Gelberg-Andersen Behavioral Model of Health Service Use for Vulnerable Populations for use in CYMH and tested its utility. The model was tested using a data sample of children and youth (n=642) referred to one of three levels of intensive mental health treatment (in-home, day treatment or residential). Multivariate analysis determined whether model variables predicted level of care. Significant group differences were found for some variables and predictive models were significant. The enhanced model contributed to an increased understanding of the relationship between individual predisposing, enabling and need characteristics and health service access. Future research is required to test the application of this model with other samples and services.
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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 | 0.001 | 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 | 0.001 |
| 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".