The Other Suicide Pill? Investigating the potential association between SSRI use and increased suicide risk
Bibliographic record
Abstract
Selective Serotonin Reuptake Inhibitors (SSRIs) are the most frequently prescribed antidepressant in the world (Bridge et al., 2007), and though they are meant to reduce depressive symptoms such as suicidal thoughts, some studies have associated their use with an increase in suicidal ideation, particularly in youth (defined as those under 19 years old). This study investigates the association between SSRI intake and increased risk of suicide as a consequent adverse effect. This was done by conducting a structured literature review. Two independent reviewers analyzed and compared relevant research from peer-reviewed journals obtained from online databases including PubMed, JAMA Network, and the University of Ottawa online databases. A combination of observational studies, RCTs, and meta-analyses were reviewed. These studies analyzed the association between suicide rate and self-reported suicidal ideation in relation with different durations of SSRI intake and severities of disease, and had to include a comparison between randomly selected treatment groups and placebo control groups. After reviewing 10 peer-reviewed articles, the results appear to be mixed from one study to another. Some studies report slight increases in suicidality, while others report a decrease associated with SSRI intake. Overall, the evidence is inconclusive as to an association with suicidal ideation and SSRI intake. However, as Antonuccio & Healy (2012) observed, a drug that is prescribed with the promise of treating depression should have a distinguished effect in reducing conditions such as suicidal ideation compared to placebo. The lack of conclusive evidence is thus a problem in itself, and further investigation is required as well as consideration regarding SSRI prescription.
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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 | 0.017 | 0.057 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.004 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".