Health Status and Health Care Utilization of Multiple Sclerosis in Canada
Bibliographic record
Abstract
BACKGROUND: Persons with multiple sclerosis (MS) represent a small segment of the population, but given the progression of the disease, they experience substantial physical, psychosocial and economic burdens. OBJECTIVE: The primary aim was to compare demographic characteristics, health status, health behaviours, health care resource utilization and access to health care of the community dwelling populations with and without MS. METHODS: Cross-sectional survey using data from the Canadian Community Health Survey (CCHS 1.1). Adjusted analyses were performed to assess differences between persons with MS and the general population, after controlling for age and sex. Normalized sampling weights and bootstrap variance estimates were used. RESULTS: Respondents with MS were 7.6 times (95% CI: 5.4, 10.7) more likely to have health-related quality of life scores that reflected severe impairment than respondents without MS. Respondents with MS were 12.2 times (95% CI: 8.6, 17.2) to rate their health as 'poor' or 'fair' than the general population. Urinary incontinence and chronic fatigue syndrome were 18.7 times (95% CI: 12.5, 28.2) and 21.9 times (95% CI: 11.9, 40.3), more likely to be reported by respondents with MS than those without. Differences between the two populations also existed in terms of health care resource utilization and access and health behaviours. CONCLUSION: Large discrepancies in health status and health care utilization existed between persons with MS who reside in the community and the general population according to all indicators used. Health care needs of persons with MS were also not met.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.002 | 0.000 |
| 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".