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Updated: Oct 7, 2026

Methodology for Establishing a Community-Wide Life Laboratory for Capturing Unobtrusive and Continuous Remote Activity and Health Data
Published on: July 27, 2018
Stage-Based Model of User Engagement Patterns in an Online Health Community for Cardiovascular Disease Management:
Monisola Jayeoba1,2, Yuyang Yang3, Jingzhi Yu3
1Department of Communication Studies, School of Communication, Northwestern University, Evanston, IL, United States.
Background:
Online health communities (OHCs) provide vital peer support and health information to individuals managing chronic conditions. However, sustained user engagement remains challenging, with many users reducing activity over time despite the ongoing benefits these platforms offer. While some individuals may improve or become more knowledgeable, sustained engagement remains critical because ongoing participation fosters trust, peer support, and continuous access to evolving health information that may persist beyond initial recovery or learning. Hence, it is important to consider how community needs evolve as users' health needs and information-seeking behaviors change to inform how we support users through different stages of their health and participation journeys.
Objective:
The aim of the study is to examine user engagement in a large OHC, identifying perceived stage-based behaviors, motivation, barriers, and design opportunities that could facilitate progression between stages and enhance long-term participation.
Methods:
We conducted semistructured interviews with 19 members of the American Heart Association Support Network Community. Participants were patients or survivors managing various cardiovascular diseases. Using narrative thematic analysis, we examined users' perceived engagement motivation, behavior, challenges, and design opportunities across different stages of their community involvement.
Results:
This study highlighted 4 distinct engagement stages: discovery (crisis-driven initial engagement), exploration (navigation and orientation), commitment (active engagement and information management), and integration (sustained engagement and mentorship). Key barriers included information architecture complexity, concerns about misinformation, limited support for role transitions, and decreased participation as health management improved. Participants identified opportunities through which OHCs could increase long-term engagement, including adaptive recommendation systems, health information literacy programs, structured role transition support, and alternative engagement modalities, such as synchronous interactions and health tracking tools.
Conclusions:
User engagement in OHCs is dynamic and evolves with changes in health status, knowledge, and personal circumstances. Supporting sustained engagement requires stage-appropriate interventions, including personalized content delivery, health information literacy education, structured pathways for role transitions, and diversified engagement options. These findings provide actionable insights for designing OHCs that better support users throughout their health journey.
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