COVID-19 Vaccination Perceptions in Patients With Rheumatic Disease: A Cross-Sectional Online Survey
Bibliographic record
Abstract
OBJECTIVE: To identify the factors that affect coronavirus disease 2019 (COVID-19) vaccine decision making among individuals diagnosed with a rheumatologic condition, given that previous international studies have demonstrated that a significant proportion of patients with rheumatic disease (RD) are vaccine hesitant. METHODS: This cross-sectional study involved an online survey with adult patients with RD from the Kaye Edmonton Clinic Rheumatology Clinic between June and August 2021. Quantitative results were descriptively analyzed, whereas qualitative thematic analysis was conducted for open-ended responses. RESULTS: The survey had a response rate of 70.9% (N = 231). Regarding COVID-19 vaccines, patients with RD were most concerned about the possible effect of vaccination on their rheumatic condition (45.2%) and about vaccine effectiveness (45.1%). Most patients had discussed COVID-19 vaccination (75.9%) and its risks and benefits (66.1%) with their medical team, and 83.6% of respondents were confident in the information provided. Patients' perceptions of the government's role in handling the COVID-19 pandemic varied: 33% reported that they found government-instituted public health measures effective. Surprisingly, 9.7% of patients with RD still reported concerns that they could develop COVID-19 from an approved COVID-19 vaccine. CONCLUSION: This study describes factors implicated in COVID-19 vaccine decision making among patients with RD. Three important themes included possible adverse effects of the vaccine on RD control, reduced vaccine efficacy because of RD/treatment, and risk of contracting SARS-CoV-2 from the COVID-19 vaccine. Knowledge from this study can assist healthcare providers in looking after patients with RD to initiate discussions with patients to share evidence-based vaccine information and assist with informed decision making.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".