Design Guidelines
Three perspectives converge into eleven principles grouped around three pillars for designing relational health data systems.
These aren't functional checklists or feature lists, but considerations for designing data sharing with sensitivity to relationships, situations, and people's lived experiences, especially when dealing with sensitive data like health.
People don't exist in isolation when it comes to health, we relational beings who carefor and depend on each other. How we share health data is shaped by who we are, who we trust, and how we naturally communicate.
Don't treat people as "one shares, one monitors", people might share more when others share, even if it's not the same data. Create visible awareness of family participation without pressure.
Beyond practical coordination, sharing enables emotional support, decision-making, and collective learning from health experiences. Recognize that families share for understanding, coping, preparing, and just being present with each other.
Allow people to express health concerns and get updates in ways that feel natural, whether through conversation, notes, or quiet visibility. Some family members prefer detailed data exploration while others want simple summaries and emotional cues.
Support users with granular sharing controls that respect their diverse relationship dynamics. Data sharing should be intentional, not automatic, allowing people to customize what they share, how much detail, when, and with whom.
Health situations change, and so should how families share and engage with data. Families naturally adapt their communication and care patterns based on what's happening, from quiet routine check-ins during stable times to intense coordination during health crises.
See health as event-based rather than "share once and for all." Support different sharing patterns based on situation intensity, from quiet routine check-ins during stable times to intense coordination during health crises and back to new normals.
Family members naturally change their involvement levels based on life circumstances, health situations, and relationship dynamics. Design systems that acknowledge and support these role transitions rather than locking people into fixed caregiving patterns.
Focus on gentle, long-term engagement rather than perfect tracking. Support families to build collective health knowledge over time, adapting through different health phases without pressure or burnout.
Behind health data are the stories, emotions, memories, and meaning that families create alongside the numbers. People need personal space to reflect on whattheir data means to them personally before deciding what to share, and systemsshould understand the human imperfection and context behind measurement.
Let people privately explore and engage with their own data without performance pressure, allowing them to makesense, contextualize and filter what they want to share, when, and how much detail to include with family.
Allow people to express health concerns and get updates in ways that feel natural, whether through conversation, notes, or quiet visibility. Some family members prefer detailed data exploration while others want simple summaries and emotional cues.
Recognize that caregiving and tracking naturally fluctuate based on life circumstances and competing priorities. Support inconsistent data engagement patterns without guilt or pressure, understanding that sporadic, meaningful tracking often serves people better than failed attempts at perfect consistency.
Personal reflection and curiosity about one's data can open the door to conversations. Data should be companions and materials to these conversations, not replace them.
These principles are a starting toolkit for designing data with relationships in mind. We invite you to test these principles, improve them, and share your learnings with the community working toward more human-centered health technology.
