Mental Health Service Use in a Nationally Representative Canadian Survey
Bibliographic record
Abstract
BACKGROUND: Previous Canadian surveys have noted a wide range of prevalence rates for mental health service use and found no consistent relation between type of contact with mental health professionals and severity of illness. This study is the first investigation to examine the prevalence and correlates of mental health service use in a nationally representative Canadian survey. METHODS: The Canadian Community Health Survey Cycle 1.1 was conducted between 2000 and 2001 (n = 125,493; respondent age 12 years and over; response rate; 84.7%). Respondents were asked whether they had contacted a professional because of emotional symptoms in the past year and about their experience of barriers to treatment. DSM-IV major depression and alcohol dependence diagnoses were assessed with the Composite International Diagnostic Interview Short Form. The relation between a range of measures of clinical severity and the type of professional contacted for emotional symptoms was examined. RESULTS: The prevalence of 12-month help seeking for emotional symptoms was 8.3% (99%CI, 8.10 to 8.55); an additional 0.6% (99%CI, 0.49 to 0.62) of the sample perceived a need for treatment without seeking care. Respondents endorsing contact with multiple professionals or with psychiatrists only had higher levels of severity than those who had contact with family doctors only or nonphysician professionals only. CONCLUSIONS: Although untreated depression remains a significant problem in Canada, more severe illness was more likely to be associated with seeing a psychiatrist (or multiple professionals), indicating a relation between greater severity of mental illness and receiving more specialized care.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| 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) | 0.002 | 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".