How do Midwives and Physicians Discuss Childhood Vaccination with Parents?
Bibliographic record
Abstract
Even if vaccination is often described as one of the great achievements of public health, results of recent studies have shown that parental acceptance of vaccination is eroding. Health providers' knowledge and attitudes about vaccines are important determinants of their own vaccine uptake, their intention to recommend vaccines to patients and the vaccine uptake of their patients. The purpose of this article is to compare how midwives and physicians address vaccination with parents during pregnancy and in postpartum visits. Thirty semi-structured interviews were conducted with midwives and physicians practicing in the province of Quebec, Canada. Results of our analysis have shown that physicians adopt an "education-information" stance when discussing vaccination with parents in the attempt to "convince" parents to vaccinate. In contrast, midwives adopted a neutral stance and gave information on the pros and cons of vaccination to parents while leaving the final decision up to them. Findings of this study highlight the fact that physicians and midwives have different views regarding their role and responsibilities concerning vaccination. It may be that neither of these approaches is optimal in promoting vaccination uptake.
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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 | 0.006 | 0.041 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| 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".