Health Care Utilization and Changes in Health Status Over Time for Migraineurs
Bibliographic record
Abstract
BACKGROUND: Determining how migraineurs manage their condition from the viewpoint of health resource utilization (including both medical and personal resources) may provide insights that could lead to more effective care strategies. OBJECTIVES: To determine the relative importance of modifiable health-influencing activities for migraineurs, and to compare the effects of these activities between migraineurs and nonmigraineurs in the general population. METHODS: Linear regression analysis was applied to all persons older than 19 years of age with migraine in the Canadian Community Health Survey Cycle 1.1. The dependent variable was reported health status change over time. Explanatory variables were a series of health care utilization, health behaviour and background control variables. RESULTS: Results showed that health status was positively associated with higher levels of physical activity and negatively associated with smoking for both migraineurs and nonmigraineurs, even when controlling for all other variables. CONCLUSION: By modifying controllable resources and behaviours, the reported health status of migraineurs can be improved as effectively as nonmigraineurs.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".