Patient and Healthcare Provider Experience With Rheumatoid Arthritis in Northern Ontario, Canada: A Qualitative Descriptive Study
Bibliographic record
Abstract
BACKGROUND: Rheumatoid arthritis (RA) is a disabling common chronic inflammatory joint disease. In Ontario, the burden is higher in those aged 65 and older, in females, and in northern communities. This study examined patient disease impact and healthcare provider access and satisfaction as well as provider satisfaction, patient experience and educational suggestions. METHODS: Semi-structured interviews and reflexive thematic analysis were used. RESULTS: Interviews occurred with: (1) 18 Northern (N) Ontario patients, (2) 6 N Ontario family physicians, (3) 6 N Ontario pharmacists and (4) a rheumatologist and 4 advanced clinical practitioners in arthritis care (ACPACs) who treat N Ontario patients. Patients emphasised the need to: (1) act on early symptoms, (2) self-advocate, (3) attract more N Ontario rheumatologists, (4) educate the public, (5) recognise that medication can change over time and (6) pace physical tasks. Satisfaction was expressed with providers. Family physicians mentioned the need to: (1) be front-line educators, (2) commence initial treatment, (3) enhance undergraduate medical curricula and (4) require rheumatology rotations. Pharmacists expressed: (1) acting as patient educators, (2) assisting with insurance plans, (3) encouraging family physicians to commence treatment, (4) monitoring medication interactions and (5) professional collaboration. The ACPACs and rheumatologist stressed the value of: (1) patient advocates, (2) family physicians initiating treatment, (3) pharmacists monitoring for drug interactions, (4) expanding undergraduate medical school rheumatology curricula and (5) accessing local care. CONCLUSION: Additional patient and public education are needed. Enhancing undergraduate and graduate medical school rheumatology curricula, rotations, continuing rheumatology education and interprofessional collaboration were recommended.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.011 | 0.004 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 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".