Do intentions lead to action? Results of a longitudinal study assessing determinants of Tdap vaccine uptake during pregnancy in Quebec, Canada
Bibliographic record
Abstract
BACKGROUND: In Canada, vaccination against pertussis (Tdap) during pregnancy has been recommended since 2018, with suboptimal uptake. We aimed to assess the determinants of intention and uptake of Tdap vaccine among pregnant women in Quebec. METHODS: Participants (< 21 weeks of pregnancy) were recruited in four Quebec regions. Two online surveys were administered during pregnancy (< 21 weeks and > 35 weeks). One measured vaccination intention and the other assessed the actual decision. Questionnaires were informed by the Theory of Planned Behaviour (TPB). We used logistic multivariate analysis to identify determinants of Tdap vaccination uptake during pregnancy using responses to both questionnaires. RESULTS: A total of 741 women answered the first survey and 568 (76.7%), the second survey. In the first survey most participants intended to receive the Tdap vaccine during their pregnancy (76.3%) and in the second survey, 82.4% reported having been vaccinated against Tdap during their pregnancy. In multivariate analysis, the main determinants of vaccine uptake were: a recommendation from a healthcare provider (OR = 7.6), vaccine intention (OR = 6.12), social norms (or thinking that most pregnant women will be vaccinated (OR = 3.81), recruitment site (OR = 3.61 for General Family Medicine unit) perceived behavioral control (or low perceived barriers to access vaccination services, (OR = 2.32) and anticipated feeling of guilt if not vaccinated (OR = 2.13). Safety concerns were the main reason for not intending or not receiving the vaccine during pregnancy. CONCLUSION: We observed high vaccine acceptance and uptake of pertussis vaccine in pregnancy. The core components of the TPB (intention, social norms and perceived behavioral control) were all predictors of vaccine uptake, but our multivariate analysis also showed that other determinants were influential: being sufficiently informed about Tdap vaccination, not having vaccine safety concerns, and anticipated regret if unvaccinated. To ensure high vaccine acceptance and uptake in pregnancy, strong recommendations by trusted healthcare providers and ease of access to vaccination services remain instrumental.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| 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".