Supporting Informed Vaccine Decision-Making and Communication in Pregnancy Through the Vaccines in Pregnancy Canada Intervention: Multimethod Co-Design Study
Notice bibliographique
Résumé
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.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,030 | 0,030 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,001 | 0,001 |
| Études des sciences et des technologies | 0,006 | 0,002 |
| Communication savante | 0,002 | 0,001 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,002 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,008 | 0,001 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».