Under-diagnosis of mood disorders in Canada
Bibliographic record
Abstract
AIMS: Under-diagnosis of mood disorders occurs worldwide. In this study, we characterized and compared Canadians with symptoms compatible with a mood disorder by diagnosis status; and described the associated health impacts, use of health services and perceived need for care. METHODS: Respondents to the 2012 Canadian Community Health Survey - Mental Health, a nationally representative sample of Canadians age ≥15 years were assessed for symptoms compatible with mood disorders based on a Canadian adaptation of the World Health Organization Composite International Diagnostic Interview (n = 23 504). Descriptive and multivariate regression analyses were performed. RESULTS: In 2012, an estimated 5.4% (1.5 million) Canadians aged 15 years and older reported symptoms compatible with a mood disorder, of which only half reported having been professionally diagnosed. The undiagnosed individuals were more likely to be younger (mean age: 36.2 v. 41.8), to be single (49.5 v. 32.7%), to have less than a post-secondary graduation (49.8 v. 41.1%) and to have no physical co-morbidities (56.4 v. 35.7%), and less likely to be part of the two lower income quintiles (49.6 v. 62.7%) compared with those with a previous diagnosis. Upon controlling for all socio-demographic and health characteristics, the associations with age and marital status disappeared. While those with a previous diagnosis reported significantly greater health impacts and were more likely to have consulted a health professional for their emotional and mental health problems in the previous 12 months compared with those undiagnosed (79.4 v. 31.0%), about a third of both groups reported that their health care needs were only partially met or not met at all. CONCLUSIONS: Mood disorders are prevalent and can profoundly impact the life of those affected, however, their diagnosis remains suboptimal and health care use falls short of apparent needs. Improvements in mental health literacy, help-seeking behaviours and diagnosis are needed. In light of the heterogeneity of mood disorders in terms of symptoms severity, impacts and prognosis, interventions must be tailored accordingly.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".