Vaccines – beliefs and concerns: the voice of patients with inflammatory immunomediated diseases
Bibliographic record
Abstract
BACKGROUND: Vaccination is a key issue in patients with immunomodulated inflammatory diseases on immune-mediated therapy. Still, vaccination rates in these patients are low. This study aimed to assess the knowledge and fears of patients with immune-mediated inflammatory diseases (IMIDs) regarding vaccines, with the ultimate goal of increasing vaccination rates through the definition and implementation of more effective communication strategies with the patient. METHODS: This study was conducted in a Portuguese hospital, between January 2019-December 2020, and included adult patients with an IMID. A questionnaire was developed and applied to evaluate knowledge and fears regarding vaccines. RESULTS: From the 275 included patients, more than 90% answered correctly to all questions on general knowledge, with an exception for the question related to protection from severe disease, without differences between age groups or education levels, except for the question about vaccine contraindications (P = 0.017). Regarding vaccines in immunocompromised hosts, the proportion of correct answers was lower and significantly different between education levels (P = 0.00-0.042),. More than 50% of the participants showed moderate to very high concern about several aspects of vaccines, with differences between age groups (P = 0.018). CONCLUSION: Our patients have general knowledge of vaccines but regarding vaccines in immunocompromised patients knowledge is lower and dependent on the education level. In addition, age influences the pattern of concerns related to vaccines. The information gathered in this study shall be considered to identify potential local interventions targeted to improve vaccination.
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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 | 0.001 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".