Interactive, Personalized Patient Decision Aid for COVID-19 Vaccination in Canada: User-Centered Design Approach

Clinical Snapshot

Key Findings

• P Value: Not applicable - qualitative design study

• Effect Size: Not applicable - qualitative design study

• Primary Outcome: Successful iterative development of VaxDA-C19 decision aid through four design cycles

• Nnt Or Sensitivity: 82% of users (9/11) favored in-depth vaccine development explanations in cycle 2

• Confidence Interval: Not applicable - qualitative design study

Clinical Application

Web-based bilingual tool designed for broad accessibility, though implementation effectiveness requires further RCT evaluation Methodology transferable to Australian context for developing culturally appropriate decision aids, though content would require adaptation for TGA-approved vaccines and Australian health system Canadian adults making COVID-19 vaccination decisions, potentially applicable to other vaccine decisions

Abstract

BACKGROUND: The COVID-19 pandemic highlighted the need for practical digital health tools to support informed decision-making amid rapidly evolving evidence and widespread misinformation. OBJECTIVE: We iteratively developed and refined VaxDA-C19, a bilingual (English and French) web-based patient decision aid designed to support informed decision-making in Canada about COVID-19 vaccination. VaxDA-C19 integrates interactive and personalized features aimed to enhance vaccine confidence, reduce cognitive overload, and respond to diverse informational needs. METHODS: VaxDA-C19 was developed using an iterative, user-centered design approach. Throughout the development process, we involved a citizen panel, health care professionals, user experience designers, and scientific experts to guide refinements. We also conducted usability testing sessions with adults in Canada, using semistructured interviews, comparative testing, and think-aloud protocols with thematic analysis. We ultimately conducted 4 design cycles in total with adults in Canada (users) and expert reviewers (experts). Cycle 1 involved 9 people (9 users), cycle 2 involved 22 people (22 users), cycle 3 involved 9 people (3 users and 6 experts), and cycle 4 involved 9 people (9 experts). RESULTS: In cycle 1, user feedback guided design decisions about how to present quantitative information and technical vaccine descriptions more simply. In cycle 2, while most users (9/11, 82%) favored in-depth explanations of vaccine development, a few raised concerns about content that could be perceived as politically charged. Cycle 3 identified usability improvements, including more explicit navigation controls, simplified medical terminology, and optimized interactive components (avatars and sliders). Expert reviews in cycle 4 refined linguistic consistency, mobile responsiveness, content transparency, and scientific accuracy, emphasizing explicit instructional guidance and bilingual accessibility. CONCLUSIONS: Our iterative process produced a personalized, bilingual digital decision aid to support evidence-informed, values-congruent decisions about COVID-19 vaccination. A randomized controlled trial will further evaluate VaxDA-C19's impact on vaccination intentions, knowledge retention, emotional responses, decisional conflict, and decisional regret. If it proves effective, the patient decision aid may also be used as a platform to support other vaccine decisions, namely, influenza, measles, shingles, pertussis, and potentially other emerging infectious diseases.

References

1. 1.Etienne, D., Archambault, P. M., Bogoch, I. I., Chambers, C. T., Chittle, A. D., Demers, J., Driedger, S. M., Dubé, È., Gagnon, M.-P., Gavaruzzi, T., Giguère, A., Grandvaux, N., Grindrod, K., Hakim, H., Jeimy, S., Kindrachuk, J., LeBlanc, A., MacDonald, S. E., Ndjaboue, R., Noubi, M., Orji, R., Paquette, J.-S., Parent, E., Renaud, J.-S., Sander, B., Taljaard, M., Tannenbaum Greenberg, D., Tremblay, M.-C., Vohra-Miller, S., Welch, V. A., & Witteman, H. O. (2026). Interactive, personalized patient decision aid for COVID-19 vaccination in Canada: User-centered design approach. JMIR Human Factors. https://doi.org/10.1080/14760584.2020.1742111