Migraine and Despair: Factors Associated with Depression and Suicidal Ideation among Canadian Migraineurs in a Population-Based Study
Bibliographic record
Abstract
This study sought to (1) investigate the association between migraine and both depression and suicidal ideation and (2) to identify the factors independently associated with each of these mental health problems among Canadian men and women with migraine. Data were analyzed from the 2005 Canadian Community Health Survey (CCHS). Presence of migraine was assessed by self-report of a health professional diagnosis. Current depression was measured using the CIDI-SF, and suicidal ideation was based on a question about serious consideration of suicide at any point during the respondent's lifetime. Migraineurs were found to have elevated odds of depression (men: OR = 2.02; 95% CI = 1.70, 2.41; women: OR = 1.89; 95% CI = 1.71, 2.10) and suicidal ideation (men: OR = 1.70; 95% CI = 1.55, 1.96; women: OR = 1.72; 95% CI = 1.59, 1.86) even when adjusting for sociodemographic variables and disability status. The odds of depression and suicidal ideation were higher among both genders of migraineurs who were younger, unmarried and had more activity limitations; associations with poverty and race depended on gender and whether the focus was on depression or suicidal ideation. While screening for depression is already recommended for those with migraine, this research helps identify which migraineurs may require more immediate attention, including those who are younger, unmarried, and experiencing limitations in their activities.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".