The duration of major depressive episodes in the Canadian general population.
Bibliographic record
Abstract
The National Population Health Survey (NPHS) has provided a wealth of new data concerning major depression in the Canadian general population. The NPHS included a brief predictor of major depression, and also two questions (only one of which was asked of each subject) concerned with the duration of episodes in the preceding year. A striking finding was that many of the episodes identified were very brief. In this paper the NPHS data were examined from a different perspective in order to derive a complementary perspective on the episode duration data. Data from the 1994/95 and 1996/97 cycles of the NPHS were used in the analysis. The longitudinal data were used to generate approximations of age and gender-specific incidence for members of the population over the age of 12 years. An estimate of prevalence was made from the 1996/97 cross-sectional file. A basic expression relating prevalence to incidence and mean duration of illness was then applied within age and gender categories. Taken together, the incidence and prevalence data from the NPHS suggest a longer duration than was indicated by the NPHS interview duration item. A probable explanation is that the NPHS duration question had an upper limit of 52 weeks, whereas some episodes of major depression last longer than this. Particularly long episodes could have a large impact on mean duration in the population. Nevertheless, these data confirm the heterogenous nature of this condition; many people with the syndrome of major depression may have quite brief episodes.
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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 | 0.005 |
| 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 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".