Key Insight III
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Data Behavioral Patterns
I note my weight changes on my phone along with special days like buddhist holidays. I don't do this daily, just when something's different. At first, I keep it private.
![[headshot] image of customer sharing feedback (for a environmental conservation nonprofit)](https://cdn.prod.website-files.com/68501fba736f44187f475e26/685291d8ead31a7ca287a8c0_Property%201%3DVariant7.svg)
If I walk less than usual, I might mention it if it’s significant. It’s just a normal, casual exchange, talking about it in a chillax way, nothing serious.
![[headshot] image of customer sharing feedback (for a environmental conservation nonprofit)](https://cdn.prod.website-files.com/68501fba736f44187f475e26/685291d7c9fd166defd1161b_Property%201%3DDefault.svg)
I feel like this has two kinds of value. The first is functional, it acts like a family database. The other is emotional, it seems to help strengthen family bonds a bit. It feels like it helps bring the family closer together.”
![[headshot] image of customer sharing feedback (for a environmental conservation nonprofit)](https://cdn.prod.website-files.com/68501fba736f44187f475e26/685291d7512c96a4d1fe10e8_Property%201%3DVariant2.svg)
Key Insights
These behavioral patterns revealed deeper insights about how relationships, trust, and care shape family health data sharing. Each insight points toward design principles that can guide technology development.
Trust and Care Define
How Data is Shared
Trust relationships and family roles determine what flows between people, not app features or privacy settings. People want data received with care, not judgment, and what's shared reflects personal values and relational connection.
Data Sharing Enables Mutual Understanding and Care, Not Monitoring
For families, ongoing habits of sharing data build mutual understanding and quiet awareness, opening doors to check-ins, deeper conversations, and coordination, not just updates. Both Data Collaborators and Daily Carers focus on connection and care rather than tracking each other's compliance.
Sharing and Care are Reciprocal, and Uneven Sharing is Natural
People share more when others share back, even when the data types differ. Asymmetric sharing reflects different caring roles, not lack of care. People are not fixed in their traits but adapt throughout their life situations. Busy college students might be Alert Responders while retired parents become Data Collaborators.
Different Data Engagement Styles: Deep Divers and Summary Seekers
Some family members want detailed exploration while others prefer simple overviews and emotional cues. An Independent Tracker dad might share only practical information that impacts family routines, while a Data Collaborator mom shares medication details so children can help with ordering.
Data Should Support, Not Replace, Ongoing Conversation
Technology should enhance existing family communication patterns rather than substitute for human connection. Some families prefer in-person conversations using data as collective logging, while others prefer quiet updates with clear boundaries.
These insights reveal that successful family health data sharing isn't about finding the "right" way to share, but about designing systems that work with the diverse ways families already care for each other.
Take a moment to consider how these findings might apply to your own work and challenge common assumptions about health technology.
Which pattern do you recognize in your own family's health sharing?
How do you and your family balance transparency with privacy around health?
How does your family influence each other's health habits and sharing?
How might current health technology better support different engagement styles?
What would health technology look like if it enhanced ongoing conversation rather than replacing it?
What if health technology enabled reciprocal care instead of monitoring?
Methods & Toolkits
These insights emerged from co-design sessions with family pairs where we observed how families naturally negotiate health data sharing.
Key Takeaways: Pair sessions reveal authentic family dynamics better than individual interviews. Let families lead the conversation to discover their real practices, not ideal behaviors.
Here are simple ways to explore these patterns:
Context Mapping with Own Data in Pairs
Let the people track own health data for a week, then filter what feels safe to share before the session, ask them to reflex, yet provide flexible formats.
Some people know their numbers by heart, while others might say "I never looked at this before."
Then, let them discuss together what they discovered and what feels worth sharing. Observe how they naturally navigate privacy and care.
Pattern Self-Assessment
in Pairs
Show the two dimensions (Open vs. Selective + Deep Divers vs. Summary Seekers) and help them reflect: "Are you a data geek or summary person? How do you naturally share when it comes to health information?"
Then explore the future: "How would you want to share ideally? What obstacles make it not ideal yet? How might you shift?"
Then, let relationship pairs discuss and negotiate their perspectives.
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