Evaluating Vaccination Status and Barriers in Children with Rheumatic Diseases
Bibliographic record
Abstract
Background: This study aims to evaluate the vaccination status of children with rheumatic diseases (RD) compared to healthy controls (HC) and immunization barriers, as studies examining the vaccination status and factors promoting or hindering vaccination among children RD remain limited. Methods: A cross-sectional study was conducted on children with RD (in a rheumatology clinic) and HC (in a fracture clinic) at a tertiary care center in Canada. Demographics, diagnosis, treatments, and vaccine status were obtained from health records and a provincial electronic vaccine database. A patient/caregiver questionnaire was used to capture perceived immunization barriers, concerns, and satisfaction. Descriptive statistical methods were used for analysis. Results: The study involved 144 children with RD and 111 HC. Data from 94 children with RD and 86 HC, all lifelong Alberta residents, were analyzed for objective vaccination status. Most vaccines were received at rates of 80% or higher, except the influenza vaccine, which had the lowest adherence (34% in RD vs. 21% in HC). In 31% of RD children, vaccinations were withheld due to active disease, healthcare provider advice, or caregiver concerns about side effects. In 27% HC, vaccinations were withheld due to side effects. Both groups primarily relied on their family doctor for vaccination information, and 85% or more expressed satisfaction with the information received. Conclusions: Most children with RD and HC received recommended vaccines, but influenza vaccination gaps were identified. Knowledge about vaccine contraindications in RD is well understood, but perceived safety concerns limit vaccination completeness. Healthcare providers, especially family doctors, pediatricians, and rheumatologists, should be providing education resources for vaccines and be proactive in discussing the safety and necessity of vaccinations.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".