Major Depression and Mental Health Care Utilization in Canada: 1994 to 2000
Bibliographic record
Abstract
BACKGROUND: Major depression makes an important contribution to disease burden in Canada. In principle, the burden of major depression can be reduced by the provision of treatment within the health care system. In a previous data analysis, the National Population Health Survey (NPHS) reported an increase in antidepressant (AD) use between 1994 and 1998. In this paper, the analysis is extended to 2000, and additional aspects of health care utilization are described. METHODS: The NPHS provides a unique source of longitudinal data concerning major depression and its treatment in Canada. In this survey, probable cases of major depression were identified using a brief predictive instrument; health care utilization was evaluated using additional survey items; and the latest data release from Statistics Canada (that is, 2000) was used to make weighted estimates of the frequency of health care utilization in relation to major depression status. RESULTS: The use of ADs has continued to escalate. These increases have been largest in men and in persons aged under 35 years. There has been an increase in polypharmacy: in 2000, almost 9% of persons taking an AD reported taking more than 1 AD medication-a tripling since 1994. The frequency of consultations with alternative practitioners has also grown. Although the overall proportion of persons with major depression who report consulting with health professionals about their mental health has not increased, the number of persons with major depressive disorder reporting 6 or more visits to nurses, social workers, and psychologists may have. CONCLUSION: The provision of AD treatment continues to expand in Canada. This probably represents a changing pattern of practice, because the frequency of professional consultation has not increased. More detailed data are required to evaluate the extent to which treatment needs are being met.
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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 | 0.003 | 0.010 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".