Migraine and Suicidal Behaviors
Bibliographic record
Abstract
OBJECTIVE: The aim of this systematic review was to provide a picture of suicidality (suicide ideation and behavior, both fatal and nonfatal) among indviduals with migraine. BACKGROUND: Migraine is a leading cause of disability around the world. Migraine may manifest with a number of symptoms, ranging from severe headaches to neurological sensory disturbances. Comorbid psychological conditions, such as depression, have also been linked to chronic migraine. DATA SOURCES: Articles were retrieved from SCOPUS, PubMed, Proquest, and Web of Science. SEARCH TERMS: Suicid* AND migrain* in English-language peer-reviewed journals between January 1, 1966 and December 31, 2014. ELIGIBILITY CRITERIA: Original research papers providing empirical evidence about the potential link between migraine and suicidal behaviors. RESULTS: Initial search identified 510 papers; the titles and abstracts of 360 unique results were examined for their relevance to the combination of migraine and suicidality. In total, 17 papers reporting original empirical analyses were included in this review. CONCLUSIONS: Research has empirically documented a link between migraine and suicide ideation and behavior, particularly concerning the subtype of migraine with aura. Overall, nonfatal suicidal behavior among people with migraine has primarily been investigated, with only 2 studies analyzing suicide mortality. In addition, majority of studies originated from the United States or Canada (n=10). Future research should thoroughly define migraine and investigate link between migraine and suicide mortality.
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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 | 0.003 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.003 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".