Comparing Mental Health of Francophones in Canada, France, and Belgium: 12-Month and Lifetime Rates of Mental Health Service Use (Part 2)
Bibliographic record
Abstract
OBJECTIVES: To compare 12-month and lifetime service use for common mental disorders in 4 francophone subsamples using data from national mental health surveys in Canada, Quebec, France, and Belgium. This is the second article in a 2-part series comparing mental disorders and service use prevalence of French-speaking populations. METHODS: Comparable World Mental Health-Composite International Diagnostic Interviews (WMH-CIDI) were administered to representative samples of adults (aged 18 years and older) in Canada during 2002 and in France and Belgium from 2001 to 2003. Two groups of francophone adults in Canada, in Quebec (n = 7571) and outside Quebec (n = 500), and respondents in Belgium (n = 389) and France (n = 1436) completed the French version of the population survey. Prevalence rates of common mental health service use were examined for major depressive episodes and specific anxiety disorders (that is, agoraphobia, social phobia, and panic disorder). RESULTS: Overall, most francophones with mental disorders do not seek treatment. Canadians consulted more mental health professionals than their European counterparts, with the exception of psychiatrists. CONCLUSIONS: Patterns of service use are similar among francophone populations. Variations that exist may be accounted for by differences in health care resources, health care systems, and health insurance coverage.
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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) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".