Prevalence and Correlates of Chronic Depression in the Canadian Community Health Survey: Mental Health and Well-Being
Bibliographic record
Abstract
OBJECTIVE: To determine the prevalence and correlates of chronic depression in comparison with nonchronic depression using a population-representative national database. METHODS: Our study used data from the Canadian Community Health Survey: Mental Health and Well-Being (CCHS 1.2) to determine the lifetime prevalence and correlates of major depression with chronic symptoms in the population. The CCHS 1.2 is a large, cross-sectional mental health survey conducted by Statistics Canada (n = 36 984, aged 15 years and older). RESULTS: The observed lifetime prevalence of major depression with chronic symptoms was 2.7%, representing 26.8% of all people with major depressive disorder (MDD). In comparison to nonchronic major depression, chronic depression was associated with more frequent psychiatric and medical comorbidity, greater disability, increased health service use, and higher likelihood of suicidal ideation and attempts. CONCLUSIONS: Major depression with chronic symptoms is common in the general population, and is associated with more severe health consequences than nonchronic depression. These observations indicate that chronic major depression is a very important subtype of MDD from a public health perspective.
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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 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".