Health-related quality of life among women and men living with migraine: a Canada-wide cross-sectional study
Bibliographic record
Abstract
BACKGROUND: Migraine is a prevalent neurologic disorder that affects women more than men. Examining health-related quality of life (HRQoL) by gender can aid decision makers in prioritizing future treatment and prevention programs. We aimed to quantify HRQoL by different levels of migraine disability and by gender. METHODS: As part of a Canada-wide cross-sectional study, we administered an online survey to employed adults who self-reported a diagnosis of migraine. Migraine disability level was assessed using the Migraine Disability Assessment questionnaire (MIDAS). MIDAS scores were used to categorize respondents as having little to no, mild, moderate, or severe level of migraine-related disability. Physical and mental component summary scores (PCS and MCS) and health utilities were derived from responses to the Veterans Rand 12 Item Health Survey. PCS, MCS, and health utilities were summarized by migraine-related disability levels and gender. Covariate-adjusted linear regressions were used to examine the association between migraine disability level and health utility by gender. RESULTS: A total of 441 participants completed the survey. The sample was predominantly women (60.1%), White race (75.5%), and had a mean age of 37 years. Mean health utility, PCS, and MCS scores were 0.61 (0.22), 45.0 (7.7), and 43.4 (11.0), respectively. All three scores decreased with increased migraine disability level. Gender differences on HRQoL within each migraine disability level were not statistically significant, except in the little to no disability level where women had lower mean MCS scores and health utility relative to men [mean (SD) MCS: women 44.0 (11.3); men 55.1 (8.1), p < 0.001; health utility: women 0.66 (0.18); men 0.81 (0.18), p < 0.001]. Linear regressions showed women with severe migraine-related disability had reduced health utility compared to women with little to no disability [adjusted difference: -0.16 (95%CI -0.24,-0.09)]. Associations among men increased in magnitude with migraine disability level [adjusted differences: mild - 0.16 (95%CI -0.24,-0.09); moderate - 0.18 (95%CI -0.26,-0.10); severe - 0.28 (95%CI -0.37,-0.20)]. CONCLUSIONS: Findings contribute to the literature on the association between migraine disability level and HRQoL by examining trends by gender. Model results emphasize the importance of future treatments reducing severe disability due to migraine among both women and men.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".