Identifying perceptions and barriers regarding vaccination in patients with rheumatoid arthritis: A Canadian perspective
Bibliographic record
Abstract
AIM: Canadian guidelines recommend that patients with rheumatoid arthritis (RA) receive pneumococcal, influenza and shingles vaccinations. The aim of this study was to identify and understand vaccination rates in Canadian patients with RA. METHODS: We conducted an observational study to evaluate uptake of herpes zoster (HZ), influenza and pneumonia vaccination in a cross-section of patients with RA in Kingston, Ontario, Canada. Data were collected using a self-administered questionnaire in patients attending at an academic rheumatology clinic. If vaccination was not received, the reason was established. RESULTS: Ninety-eight out of a total of 103 patients surveyed met the inclusion criteria and were evaluated: 72.4% had received the influenza vaccination in the past year encompassing a period of 2017-2019. Of the 27.6% who did not, the most common chosen reason was personal preference not to get vaccinated (55.6%). Regarding HZ, 18.4% had received vaccination. Of the 2 available types of vaccines, more participants received Zostavax (66.7%) as compared to Shringrix (33.3%). For those not vaccinated (81.6%), "Other" was the most chosen option (37.5%) with the reasons subsequently specified as cost, concern over interaction with treatment and waiting until age ≥65 years. In terms of pneumococcal vaccination, 36.7% were vaccinated, with the majority being vaccinated with Pneumovax-23 (63.9%) compared to Prevnar-13 (16.7%) or both (19.4%). Of the 63.3% of the participants who did not receive vaccination, the most cited reason was they did not know they should receive pneumococcal vaccination (48.4%). CONCLUSIONS: Vaccination rates among Canadian patients with RA are suboptimal.
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".