A new Canadian primary care intervention is adapting features familiar from social media platforms to improve patient engagement and preventative care, with a focus on addressing diabetes risk. The project, currently in its design phase, aims to integrate these tools within existing electronic health record systems, while mitigating the risks associated with direct social media use.
Researchers are building on Self-Determination Theory (SDT), a framework in psychology that emphasizes the importance of autonomy, competence, and relatedness in fostering motivation and well-being. The intervention seeks to translate these principles into digital health tools. According to a recent study led by Sara Bhatti of the Alliance for Healthier Communities in Toronto, the design incorporates three key elements: personalized feeds, timelines, and moderated group exchanges.
The personalized feeds are designed to support patient autonomy by allowing users to control the topics they see, the pace at which they receive information, and providing clear explanations for why specific content is being presented. Timelines aim to build competence through short lessons, practice exercises, and feedback from healthcare coaches. Groups will foster a sense of relatedness through peer-to-peer support and goal-oriented discussions, all under the guidance of moderators.
A core component of the initiative involves a predictive service that identifies patients at high risk of developing diabetes within an eight-year timeframe. Clinicians will then be able to offer a “preventive-care prescription” – essentially, enrollment in the intervention – to eligible patients through their electronic health records. Clinicians will receive monthly reports detailing population-level data, including actionable cohorts, indicators related to SDT principles, safety metrics, and equity considerations.
The project, rooted in function done at 11 community health centres across Ontario, Canada, builds on existing research demonstrating the potential of mapping social media features to health applications. Researchers consulted with 13 stakeholders to validate the design and establish measurable criteria for implementation, addressing concerns around privacy, misinformation, engagement ethics, platform independence, peer matching, prediction accuracy, and reporting protocols.
The next steps involve finalizing the system architecture, conducting broader co-design sessions with patients and clinicians, and initiating a feasibility pilot to test the intervention in a real-world clinical setting. The research team, which includes Jennifer Rayner, Andrew D Pinto, Kate Mulligan, and Donald C Cole, is focused on creating a system that is both effective and ethically sound.