Attitudes of new mothers toward childhood vaccinations in Rzeszow, Poland
Bibliographic record
Abstract
Introduction The purpose of this research is to identify the key beliefs and understanding, sources of trust and information, and planned actions regarding childhood vaccinations of mothers to newborns in Rzeszow, Poland. Material and methods A survey aiming to identify the above factors was disseminated to mothers who had given birth in Rzeszow, Poland. In total, 143 surveys were analyzed, and a χ2 statistical analysis was used to test for significance between the variables. Results Demographic factors did not have a significant association with the beliefs, sources of trust and information, or actions of new mothers regarding childhood vaccinations in Rzeszow. The most common vaccine adverse beliefs (VAB) concerned the vaccine schedule and whether childhood vaccines should be mandatory. The number of adverse beliefs mothers were unsure about showed no statistically significant association with the planned action of choosing to vaccinate or not. The top source of information about vaccinations was the internet, while the most trusted source for vaccine information was pediatricians/family doctors. Factors that did have a statistically significant association included beliefs about vaccines and sources of information and trust. Conclusions Overall, the most common VAB and key sources of information and trust about vaccinations in our study population in Rzeszow are similar to previous studies done elsewhere. We also identified that some mothers who vaccinated their older children could be changing their minds amidst the growing movement of vaccine hesitancy. This highlights that it is a key time for physicians to increase education and stress the importance about childhood vaccines, and creating reputable internet sources backed by physicians could help stop the spread of vaccine hesitancy and misinformation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".