Knowledge, attitude and behaviour of family physicians on vaccination of children with a history of food allergies
Bibliographic record
Abstract
C -statistical analysis, D -Data ınterpretation, E -Manuscript Preparation, F -literature search, G -Funds collectionBackground. routine immunisation, one of the most successful public health initiatives, has significantly decreased infectious disease-related mortality and morbidity.Family physicians in turkey avoid administering vaccines to children who have food allergies and instead refer them to a hospital setting.Objectives.ın this study, we aimed to evaluate the approaches of family physicians when applying vaccines to children with diagnosed or suspected food allergies according to the national vaccination schedule.Material and methods.this study was carried out between 01.07.2021 and 31.08.2021 with family physicians in the ankara province.using questionnaire, the participants were questioned about their sociodemographic characteristics, their vaccination approaches towards patients with diagnoses or suspicions of food allergies and their personal experiences.Results.a total of 184 family physicians participated in this study, and 82.6% of them stated that they were hesitant about the administrations of vaccines to children with diagnosed or suspected food allergies.regarding the administration of vaccines, the most concerning food allergies involved eggs (71.7%) and cow's milk (15.8%).the vaccinations they were mainly concerned about were determined as the measles-rubella-mumps (MMr) (83.7%) and measles (46.7%) vaccines in a suspected or diagnosed presence of an egg allergy and/or cow's milk allergy, respectively.Conclusions.this study showed that the surveyed family physicians are hesitant of vaccinating children with diagnoses or suspicions of food allergies and see themselves as intermediately qualified.this can cause referrals of children to higher-level centres for vaccinations, delays in vaccinations and parental vaccine hesitancies.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| 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".