Prioritizing the healthcare access concerns of Canadians with MS
Bibliographic record
Abstract
BACKGROUND: Canadians with MS are high users of healthcare services, yet they report multiple unmet needs, high disease burden, and low satisfaction with care. Engaging patients in healthcare planning can lead to improvements in access and care. There is currently limited evidence that has harnessed the perspectives of Canadians with MS. OBJECTIVE: To identify and prioritize the healthcare access concerns of Canadians with MS. METHODS: A cross-sectional online survey informed by the Concerns Report Methodology was used to address the objective. Participants were recruited through multiple methods. Descriptive statistics were used to identify the main barriers to healthcare providers, and concerns report methods were used to calculate needs indexes to prioritize concerns of participants. RESULTS: 324 Canadians with MS participated in the study between November 18, 2019 and March 27, 2020. The most pressing healthcare access concerns of Canadians with MS were related to availability of healthcare providers with MS knowledge and affordability of services that aim to improve wellness. CONCLUSION: These findings provide healthcare planners with prioritized access concerns of Canadians with MS, which can be used to guide strategic planning to improve the quality of life of these individuals.
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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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".