CANADIAN ADOLESCENTS WITH MIGRAINE: IMPAIRED HEALTH-RELATED QUALITY OF LIFE
Bibliographic record
Abstract
Objectives: To determine the impact of migraine headaches on health-related quality of life among Canadian adolescents. Methods: The Canadian Community Health Survey (CCHS) is a cross-sectional survey that collects information related to health status, health care utilization, and health determinants for the Canadian population. Our analysis was based on the public use microdata set of the CCHS, Cycle 2.1 (2003), limited to age 12–19 years residing in the province of Manitoba. Respondents reported whether they had migraine and mood and/or anxiety disorders. Health-related quality of life (HRQOL) was measured using the SF-36 Health survey. The SF-36 questionnaire covers 8 health concepts related to functional status, well-being, and overall evaluation of health. Multivariate linear regression analysis was used to model each scale of the SF-36 against age (12–14y versus 15–19y), gender, migraine status, and the presence of a mood or anxiety disorder. Results: The CCHS was completed by 994 respondents. 9.3% (95%CI 7.3, 11.5) reported a diagnosis of migraine. Reported migraine predicted both statistically (p<0.0001) and clinically significant lower HRQOL scores in all SF-36 health domains (Ä >5 points), except the vitality dimension. Migraine was associated with profound impairment in the domains of physical role limitations, bodily pain and general health perceptions. Adolescents reporting a mood disorder (2.1%) scored significantly lower in 6 of 8 HRQOL, most pronounced for emotional role limitations, general mental health and social functioning. Those with anxiety disorders (1.8%), scored lower in 2 of 8 domains. Conclusion: Canadian adolescents with migraine report clinically and statistically significant impairment in HRQOL compared to their peers, independent of psychiatric comorbidities.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.003 | 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) | 0.003 | 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".