Knowledge, attitude and disinformation regarding vaccination and immunization practices among healthcare workers of a third-level paediatric hospital
Bibliographic record
Abstract
Background \nVaccination represents one of the most effective means of preventing infections for the population and for the public health in general. Recently there has been a decline in vaccinations, also among healthcare workers (HCWs). The aim of the study is to detect the knowledge, skills, attitudes and barriers of HCWs regarding vaccinations in a tertiary children’s hospital in order to support clinical management in immunisation practices. \n \nMethods \nAn observational study was conducted on 255 subjects over a period of 8 months. The 31-item questionnaire considered profession, level of instruction and different ages. It included questions taken from a questionnaire used for a Canadian research and one used by the Bellinzona hospital. A 4-point Likert scale and closed-ended questions were used. A confidence interval of 95%, p value ≤ 0.05, Chi-square, ANOVA and the Kruskal-Wallis test were considered. \n \nResults \nIn the last 5 years less than one third of the sample were vaccinated against flu. 77.8% (n.130) of nurses and 45.8% (n.19) of doctors were not vaccinated (p < 0.0001). \n \nAs for risk perception, 51.5% of nurses and 90.6% of doctors believe that their risk of contracting influenza is greater than that of the general population. \n \nIn relation to the injection site, in all the age ranges there was a high level of knowledge except for those aged over 61 who responded incorrectly. Doctors were more prepared (p < 0.0001). \n \n50% of the sample used internet only as a source of information for vaccines. Generally, scientific sources were used infrequently. The higher the education level, the more frequent the utilisation of trustworthy scientific resources and literature. (p = 0.0002). \n \nConclusions \nIn line with the attitude observed in recent years, nurses are not inclined to get vaccinated themselves although they agree to having their children vaccinated. HCWs have a good level of knowledge about vaccines and immunisation practices. \n \nWith the nurses we found that the higher the education level, the greater the knowledge about vaccines which leads to the conclusion that low levels of adherence are not due to a lack of knowledge, but rather, to a low perception of risks. Hence the need to strengthen the vaccination strategies inside the companies.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".