“Ultimately, the choice is theirs”: Informed choice vaccine conversations and Canadian midwives
Bibliographic record
Abstract
BACKGROUND: In Canada, vaccination that protects against pertussis and influenza is recommended in every pregnancy, but uptake remains low. Communicating the risks and benefits of vaccination is key to clinical conversations about vaccination, which may influence the uptake of pregnancy and subsequent infant vaccines. Canadian midwives use an informed choice model of care, which is distinct from informed consent and prioritizes client autonomy in decision-making. METHODS: Using institutional ethnography, which treats lived experience as expertise, we aimed to understand how Canadian midwives, governed by intersecting professional standards and regulations, navigate vaccine discussions with their clients. We conducted interviews with individuals involved in midwifery training, regulation, and continuing education, as well as key public health professionals with expertise in immunization training. Following the phases of thematic analysis outlined by Braun and Clarke, data were analyzed holistically, emergent themes identified, and coding categories developed. RESULTS: Two types of confidence emerged as important to midwives' ability to conduct a thoroughly informed choice discussion about vaccines: confidence in vaccination itself (vaccine confidence), and confidence in vaccine knowledge and counseling skills (vaccine counseling confidence). A deferred or shortened vaccine discussion could be the result of either vaccine hesitancy or counseling hesitancy. DISCUSSION: Currently, available clinical communication tools and recommended techniques for addressing vaccine hesitancy do not always adapt well to the needs of midwives working to support clients' informed choice decisions. Our findings suggest that Canadian midwives require more and clearer resources on both the risks and benefits of vaccination in pregnancy.
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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 | 0.039 | 0.067 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.053 | 0.043 |
| Scholarly communication | 0.014 | 0.008 |
| Open science | 0.004 | 0.017 |
| Research integrity | 0.006 | 0.009 |
| 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".