Course of Major Depressive Disorder and Suicide Outcome
Bibliographic record
Abstract
BACKGROUND: There is considerable debate as to whether suicide is more likely to occur early in the course of major depressive disorder or by cumulative risk, with an increasing risk with each subsequent major depressive episode (MDE). By considering the number of MDEs among representative suicides, we aimed to further investigate the relationship between suicide outcome and the course of major depressive disorder. METHOD: A psychological autopsy method with best informants was used to investigate 154 consecutive suicides who died in the context of a DSM-IV MDE. Proxy-based interviews were conducted by using the Structured Clinical Interview for DSM-III-R; the Structured Clinical Interview for DSM-IV Axis II; and a series of behavioral and personality-trait assessments. Second, 143 living depressed outpatients of comparable age to the suicide group were assessed for their history of MDEs. The study was conducted between 2000 and 2005. RESULTS: The distribution of MDEs among depressed suicide completers was as follows: first MDE, 74.7%; second MDE, 18.8%; more than 2 MDEs, 6.5%. This distribution is compared to 32.9% of depressed living outpatients with a single MDE. Increased levels of hostility were associated with single MDE suicide completers. The anxious trait of harm avoidance increased among multiple MDE suicide completers. Alcohol abuse increased among first MDE suicide completers. CONCLUSIONS: Suicide in major depressive disorder is most likely to occur during the first MDE, and this appears to be related to increased levels of the impulsive-aggressive diathesis.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 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".