Is the pre-natal period a missed opportunity for communicating with parents about immunizations? Evidence from a longitudinal qualitative study in Victoria, British Columbia
Bibliographic record
Abstract
Abstract Background Growing evidence shows that many parents begin the decision-making process about infant vaccination during pregnancy and these decisions – once established – may be resistant to change. Despite this, many interventions targeting vaccination are focused on communicating with parents after their baby is born. This suggests that the prenatal period may constitute a missed opportunity for communicating with expectant parents about infant vaccination.Methods Using a longitudinal qualitative design, we conducted two interviews (prepartum and postpartum) with women (n = 19) to explore the optimal timing of vaccination information. The data were analyzed thematically, and examined across all sets of pre- and post-partum interviews as well as within each individual participant to draw out salient themes.Results Most participants formed their intentions to vaccinate before the baby was born and indicated that they would welcome information about vaccination from their maternity care providers. However, few individuals recalled their maternity care providers initiating vaccination-related conversations with them.Conclusion The prenatal period is an important time to begin conversations with expectant parents about vaccinating their infants, particularly if these conversations are initiated by trusted maternity care providers. More information is needed on how maternity care providers can be better supported to have these conversations with their patients.
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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 | 0.017 | 0.029 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.015 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".