Barriers and facilitators to influenza and pneumococcal vaccine hesitancy in rheumatoid arthritis: a qualitative study
Bibliographic record
Abstract
OBJECTIVES: Immunization is an essential component of RA care. Nevertheless, vaccine coverage in RA is suboptimal. Contextual, individual and vaccine-related factors influence vaccine acceptance. However, barriers and facilitators of vaccination in RA are not well defined. The aim of this study was to assess perspectives of RA patients and healthcare professionals (HCPs) involved in RA care of barriers and facilitators regarding influenza and pneumococcal vaccines. METHODS: Eight focus groups (four with RA patients and four with HCPs) and eight semi-structured open-ended individual interviews with vaccine-hesitant RA patients were conducted. Data were audio recorded, transcribed verbatim and imported to MAXQDA software. Analysis using the framework of vaccine hesitancy proposed by the Strategic Advisory Group of Experts on Immunization was conducted. RESULTS: RA patients and HCPs reported common and specific barriers and facilitators to influenza vaccination that included contextual, individual and/or group and vaccine- and/or vaccination-specific factors. A key contextual influence on vaccination was patients' perception of the media, pharmaceutical industry, authorities, scientists and the medical community at large. Among the individual-related influences, experiences with vaccination, knowledge/awareness and beliefs about health and disease prevention were considered to impact vaccine acceptance. Vaccine-related factors including concerns about vaccine side effects such as RA flares, the safety of new formulations, the mechanism of action, access to vaccines and costs associated with vaccination were identified as actionable barriers. CONCLUSION: Acknowledging RA patients' perceived barriers to influenza and pneumococcal vaccination and implementing specific strategies to address them might increase vaccination coverage in this population.
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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 | 0.011 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.005 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.004 |
| 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".