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Updated: Sep 10, 2025

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Optimizing Participant Engagement in Cyberhealth Co-Design: Course-of-Action Framework Analysis.

Melanie Tremblay1,2, Christine Hamel2, Anabelle Viau-Guay2

  • 1École Nationale d'Administration Publique, 555, boulevard Charest Est, Québec, QC, G1K 9E5, Canada, 1 4186413000.

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Summary
This summary is machine-generated.

Understanding participant engagement in co-design is key for effective digital health tools. Analyzing engagement themes like tool design and participant needs helps optimize co-design processes for better outcomes.

Keywords:
activity analysisaffordancescaregiversco-designcourse-of-action frameworkengagement

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Area of Science:

  • Human-Computer Interaction
  • Digital Health
  • Participatory Design

Background:

  • Co-design enhances product usability through user participation.
  • Effective outcomes require understanding participant motivations and contributions.
  • Participant engagement insights are critical for successful co-design projects.

Purpose of the Study:

  • Analyze participant engagement in a digital health co-design project.
  • Focus on developing a support-seeking tool for elderly caregivers.
  • Investigate engagement patterns across different participant groups and sessions.

Main Methods:

  • Qualitative analysis of participant testimonies using the course-of-action framework.
  • Collected data from 20 participants via self-confrontation interviews.
  • Examined engagement variations across caregivers, professionals, and community workers.

Main Results:

  • Identified three engagement themes: tool design, participant needs, and contextual situations.
  • Community workers showed a stronger focus on needs (42%) versus tool design (20%).
  • Engagement varied significantly across sessions, with design-task activities boosting tool design focus.

Conclusions:

  • Affordances play a crucial role in balancing engagement dimensions in co-design.
  • Strategic use of affordances can optimize engagement for better co-design outcomes.
  • Understanding engagement patterns informs the development of more effective digital health tools.