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Process for Rapid Co-development of a Decision Aid Prototype for Population-wide Cancer Screening
Odilon Quentin Assan1,2,3, Claude Bernard Uwizeye1,2,3, Hervé Tchala Vignon Zomahoun4
1Unité de soutien SSA Québec, Quebec, Canada.
Summary
This study outlines a 7-step process for rapidly co-developing culturally adapted decision aids (DAs) for cancer screening programs. The user-centered approach ensures DAs meet stakeholder needs, promoting adoption and shared decision-making.
Area of Science:
- Public Health
- Health Communication
- Health Services Research
Background:
- Decision aids (DAs) require stakeholder co-development and cultural adaptation for effective adoption.
- Population-wide cancer screening programs can benefit from user-centered and culturally relevant DAs.
Purpose of the Study:
- To describe a systematic, collaborative, and iterative 7-step process for the rapid co-development of a culturally adapted DA prototype for cancer screening.
- To ensure the developed DA prototype is user-centered, culturally relevant, and meets international standards.
Main Methods:
- A 7-phase methodology involving stakeholder engagement, systematic review of existing DAs, e-Delphi surveys, co-design, translation, and knowledge mobilization.
- Governance included 20 individuals from diverse sectors, including citizens.
- The User-Centred Design 11-Item Measure (UCD-11) was used to evaluate the process.
Main Results:
- The proposed process scored 10 out of 11 on the UCD-11, indicating strong user-centered design.
- The methodology facilitated the creation of a culturally adapted DA prototype for cancer screening in Quebec.
- The process incorporated international DA standards and expert consensus through iterative revisions.
Conclusions:
- The described co-development process enables the rapid production of high-quality, user-centered, and culturally adapted DAs for cancer screening.
- This approach is expected to enhance the adoption of DAs and promote shared decision-making in cancer screening.
- The methodology provides a framework for developing DAs that reflect users' interests, needs, and preferences.
