The epidemiology of major depressive episodes: results from the International Consortium of Psychiatric Epidemiology (ICPE) surveys
Bibliographic record
Abstract
Absence of a common diagnostic interview has hampered cross-national syntheses of epidemiological evidence on major depressive episodes (MDE). Community epidemiological surveys using the World Health Organization Composite International Diagnostic Interview administered face-to-face were carried out in 10 countries in North America (Canada and the US), Latin America (Brazil, Chile, and Mexico), Europe (Czech Republic, Germany, the Netherlands, and Turkey), and Asia (Japan). The total sample size was more than 37,000. Lifetime prevalence estimates of hierarchy-free DSM-III-R/DSM-IV MDE varied widely, from 3% in Japan to 16.9% in the US, with the majority in the range of 8% to 12%. The 12-month/lifetime prevalence ratio was in the range 40% to 55%, the 30-day/12-month prevalence ratio in the range 45% to 65%, and median age of onset in the range 20 to 25 in most countries. Consistent socio-demographic correlates included being female and unmarried. Respondents in recent cohorts reported higher lifetime prevalence, but lower persistence than those in earlier cohorts. Major depressive episodes were found to be strongly co-morbid with, and temporally secondary to, anxiety disorders in all countries, with primary panic and generalized anxiety disorders the most powerful predictors of the first onset of secondary MDE. Major depressive episodes are a commonly occurring disorder that usually has a chronic-intermittent course. Effectiveness trials are needed to evaluate the impact of early detection and treatment on the course of MDE as well as to evaluate whether timely treatment of primary anxiety disorders would reduce the subsequent onset, persistence, and severity of secondary MDE.
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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 | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.007 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".