P.031 A qualitative study of patient perspectives regarding the role of the neurologist in advanced Multiple Sclerosis
Bibliographic record
Abstract
Background: With few evidence-based disease-modifying therapies being available for patients with progressive multiple sclerosis (PMS), how can neurologists best care for their patients? Little is known about the perspectives of patients with respect to the role they would like their neurologist to play in their care. We hereby report an update to our abstract presented at the Canadian Neurological Sciences Federation’s annual congress in 2016. Methods: Patients with PMS having an Expanded Disability Status Scale (EDSS) score of 6 or more were invited to participate. Semi-structured interviews were conducted with patients and their caregivers, and written questionnaires were completed by all participants. Collected data was subjected to thematic coding. Results: We have now interviewed a total of 18 patients (compared to 10 in 2016) and have reached thematic saturation. The majority of patients identified the neurologist as a useful figure in their care. Three main reasons were identified: (1) The neurologist provides information about new research and therapies (2) The neurologist educates patients about their disease and available services (3) The neurologist is viewed as an important supportive figure. Conclusions: Despite a lack of disease-modifying treatments for progressive multiple sclerosis, patients with PMS view the neurologist as an essential provider of care.
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 | 0.016 | 0.029 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.010 |
| Scholarly communication | 0.005 | 0.006 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".