Increased Risk of Suicidal Ideation in Smokers and Former Smokers Compared to Never Smokers: Evidence from the Baltimore ECA Follow‐Up Study
Bibliographic record
Abstract
The incidence rate of suicidal ideation among current and former smokers versus never smokers is not known. In this study, the age-adjusted incidence of suicidal ideation was highest among current smokers, followed by former, then never smokers. The adjusted hazard for suicide ideation was 2.22 (95%CI = 1.48, 3.33) and 1.19 (95%CI = 0.78, 1.82) for current and former smokers, respectively, compared to never smokers. Results indicate that current smokers have increased risks of suicidal ideation above and beyond the risk for never and former smokers regardless of age, gender, history of depressive disorder or anxiety symptoms, and alcohol abuse/dependence. Smoking cessation might be beneficial for some suicide prevention efforts.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| 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".