Suicide Attempts in Substance Abusers: Effects of Major Depression in Relation to Substance Use Disorders
Bibliographic record
Abstract
OBJECTIVE: The authors' goal was to investigate whether subtypes of DSM-IV depression predict suicidal behavior among patients with substance dependence. METHOD: Major depression among 602 patients with substance dependence was classified as occurring before dependence, during abstinence, or exclusively during periods of substance use. Analyses of patients with the three types of depression included logistic and linear regression. RESULTS: All three types of depression increased the risk for making a suicide attempt. Major depression that occurred before the patient became substance dependent predicted severity of suicidal intent. Major depression that occurred during abstinence predicted number of attempts. CONCLUSIONS: These results suggest the importance of establishing DSM-IV subtypes of depression based on the timing of the occurrence of depression in relation to substance dependence in evaluating suicidal risk among substance-dependent patients.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 teacher head, 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".