Canadian Community Health Survey: Major Depressive Disorder and Suicidality in Adolescents
Bibliographic record
Abstract
BACKGROUND: Contrary to other developed countries where adolescent suicide rates have declined in the last decade, the rate in Canada has remained unchanged. Suicide is the second leading cause of death in Canadian adolescents and poses a serious public health concern. However, there is little epidemiological data examining the rates of suicidality or depression - two factors most closely associated with completed suicides. This study therefore examines the rates of depression and suicidality in adolescents aged 15-18. METHODS: Data from the Canadian Community Health Survey Cycle 1.2 on Mental Health and Well-being, a population-based survey conducted by Statistics Canada, were used to examine the rates of depression and suicidality in adolescents aged 15-18. Lifetime prevalence rates were calculated for depression and suicidality by region for males and females. Multivariate analyses were conducted to test the robustness of these results. RESULTS: The lifetime prevalence rates were 7.6% for depression and 13.5% for suicidality. There were significant gender differences for both: 4.3% of males and 11.1% of females had depression, and 8.8% of males and 18.4% of females had suicidality. After adjustment for age, sex and household income, the Maritimes had a lower rate of depression and British Columbia had a higher rate of suicidality relative to Ontario. Youth from low-income households had a higher risk of suicidality. INTERPRETATION: The findings suggest that depression and suicidality are common in adolescents and that females are more likely to be affected. The results also point to regional and socio-economic differences. Future research should examine differences that exist in mental health services provision and access. This will aid in the development of national, regional and local strategies to address the issue of depression and suicidality in Canadian adolescents.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".