Supporting Informed Vaccine Decision-Making and Communication in Pregnancy Through the Vaccines in Pregnancy Canada Intervention: Multimethod Co-Design Study (Preprint)
Bibliographic record
Abstract
BACKGROUND Vaccination in pregnancy (VIP) protects pregnant individuals and their newborns; yet, uptake remains suboptimal. Pregnant individuals face unique decision-making challenges, and communication with their health care provider (HCP) is crucial for uptake. While there is extensive data on barriers to VIP, interventions applying evidence-based behavior change strategies and co-designed with end users are scarce. Our prior work indicated that a new Canadian intervention was needed. OBJECTIVE This study aimed to co-design a multicomponent intervention to support informed decision-making and vaccine communication in pregnancy. METHODS Our multimethod study followed the Double Diamond phases (ie, Discover, Define, Develop, and Deliver) and partnered with a diverse patient advisory council and a multidisciplinary team of HCPs. During the Discover and Define phases, our previous work, we explored gaps and barriers to VIP in Canada and defined the behavior change strategies to address those needs. During the Develop phase, we co-designed and conducted iterative prototyping of four intervention components: (1) a pregnancy-specific communication approach, (2) a skills course for HCPs, (3) a practice change plan, and (4) a website with evidence-based resources for patients and HCPs. We used online and in-person participatory co-design sessions and peer-to-peer, patient-oriented online focus groups and semistructured in-depth interviews. During the Deliver phase, we refined the intervention components through functionality and usability testing. RESULTS The Vaccines in Pregnancy Canada (VIP Canada) intervention consists of four integrated components: (1) DECIDE (Determine, Elicit, Consent, Interactive discussion, Deliver, and Empower): a patient-centered, pregnancy-specific communication approach for providers to deliver a clear vaccine recommendation while respecting autonomy. (2) Skills course for HCPs: 4 self-paced, online modules to learn the rationale for VIP and the DECIDE communication approach and 2 group sessions. Providers found the skills course clear, practical, and applicable across diverse clinical roles and settings. Feedback led to enhancements, including improved audio-visual synchronization, consistent closed captioning, and the addition of downloadable reference materials to support learning. (3) Practice change plan: an action plan HCPs make to integrate vaccine communication into their practice. (4) VIP Canada website: an evidence-based website with resources to support informed vaccine decision-making for patients and providers. Patient feedback informed iterative refinements to the layout and content of the website to enhance navigation, readability, and representation of diverse identities. Functionality and usability testing demonstrated that patients found the VIP Canada website visually appealing, easy to navigate, and supportive of informed decision-making. CONCLUSIONS The VIP Canada is a promising intervention co-designed to drive behavior change by addressing key barriers to vaccine communication and informed decision-making around our patient partners’ and HCPs’ perspectives and lived experiences to bridge theoretical frameworks with real-world relevance. Next steps include a feasibility study for further refinement and a subsequent effectiveness study. CLINICALTRIAL
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 | 0.026 | 0.032 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 0.001 |
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".