Risk Factors for Suicide Completion in Major Depression: A Case-Control Study of Impulsive and Aggressive Behaviors in Men
Bibliographic record
Abstract
OBJECTIVE: Major depression is a major risk factor for suicide. However, not all individuals with major depression commit suicide. Impulsive and aggressive behaviors have been proposed as risk factors for suicide, but it remains unclear whether their effect on the risk of suicide is at least partly explained by axis I disorders commonly associated with suicide, such as major depression. With a case-control design, a comparison of the level of impulsive and aggressive behaviors and the prevalence of associated psychopathology was carried out with control for the presence of primary psychopathology. METHOD: One hundred and four male suicide completers who died during an episode of major depression and 74 living depressed male comparison subjects were investigated with proxy-based interviews by using structured diagnostic instruments and personality trait assessments. RESULTS: The authors found that current (6-month prevalence) alcohol abuse/dependence, current drug abuse/dependence, and cluster B personality disorders increased the risk of suicide in individuals with major depression. Also, higher levels of impulsivity and aggression were associated with suicide. An analysis by age showed that these risk factors were more specific to younger suicide victims (ages 18-40). A multivariate analysis indicated that current alcohol abuse/dependence and cluster B personality disorder were two independent predictors of suicide. CONCLUSIONS: Impulsive-aggressive personality disorders and alcohol abuse/dependence were two independent predictors of suicide in major depression, and impulsive and aggressive behaviors seem to underlie these risk factors. A developmental hypothesis of suicidal behavior, with impulsive and aggressive behaviors as the starting point, is discussed.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".