The Use of Mental Health Services in Ontario: Epidemiologic Findings
Bibliographic record
Abstract
Objective: To describe the distribution and predictors of mental health service use for a survey of Ontario household residents aged 15 to 64 years. Method: Service use was defined as any past-year contact with formal or informal health care providers for mental health reasons. Data from the Mental Health Supplement (the Supplement) to the Ontario Mental Health Survey were used to compare the sociodemographic, geographic, and diagnostic status characteristics of service users with these characteristics among nonusers. Results: Mental health services were used by 7.8 % of respondents in the past year. The majority (57.8%) had a past-year University of Michigan Composite International Diagnostic Interview (UM-CIDI) diagnosis, although 27.1 % had never met diagnostic criteria. Other significant predictors were marital status, household public assistance, gender, age, and urban/rural residence. Conclusion: Although diagnosis is the strongest predictor of use, the fit between “need ” and “care ” in Ontario is not perfect. Help seeking differs within specific sociodemographic and geographic groups. Furthermore, the association of marital disruption and economic disadvantage with utilization indicates that prevention and intervention should address needs beyond the medical or psychological. (Can J Psychiatry 1996;41:572–577)
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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 | 0.002 | 0.005 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".