Perceived Met and Unmet Health-Care Needs in a Community Population with Multiple Sclerosis
Bibliographic record
Abstract
Community-based studies are required to accurately describe the supportive services needed by people with multiple sclerosis (MS). Characteristics that influence (or result from) care-seeking may introduce bias into other types of studies. The Participation and Activity Limitation Survey (PALS) was a post-census survey conducted by Statistics Canada in association with a 2006 national census. The PALS collected data from a sample of 22,513 respondents having health-related impairments according to their census forms. The survey collected self-reported diagnostic data and obtained ratings for items assessing impairment as well as perceived met and unmet needs for care and support. It identified 245 individuals with MS, leading to an estimated (weighted) population prevalence of 0.2% (200 per 100,000). As expected, those with MS reported more-severe health problems than did those with other types of disability, particularly in the areas of mobility, dexterity, and cognition; they were also more likely to report having multiple caregivers. People with MS also reported more unmet health-care needs than did those with other forms of disability, particularly with respect to meal preparation, housework, shopping, and chores. Despite their more negative health status and greater reliance on caregivers, people with MS reported participation in society comparable to that of people without MS. Thus, people with MS report greater needs than do people with other forms of health-related disability and utilize supportive services more often. However, they also report higher levels of unmet needs. The substantial needs of people with MS are only partially addressed by existing services.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".