Key Insight II
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Key Dimensions
Understanding how families share health data starts with recognizing two key axes that shape each family's approach to health information.
These patterns emerge from the intersection of two key dimensions:
Data Engagement
Active ↔ Passive
How people approach collecting and reflecting on personal health information.
How it Works
Family members have different preferences for how they want to engage with health data complexity. Some want detailed data exploration and comprehensive information, while others prefer simplified overviews and summarized systems that provide comfort without overwhelming detail.
Explore what they said
I want something that just gives me a summary, not too medical. If it's too detailed, I probably won't understand it. I'd rather have a short summary, then hear the doctor explain it to me. That's what I'd prefe
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We can also compare things, like what was my weight last year, what were my lab values then versus now. It helps with ongoing health management and seeing connections over time.
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Data Intimacy
Open ↔ Selective
How people balance transparency
with privacy in data sharing
in family relationships
How it Works
How families navigate the balance between transparency and privacy varies significantly across relationships and health contexts. Some families develop cultures of open health communication, while others maintain careful boundaries around personal health information.
Explore what they saidSome people know they have health issues but don't want to share because they feel it won't change anything. They're stuck in situations they can't fix. Talking about it just adds pressure on both sides
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So we have a drawer system at home, right? Each person has their own drawer. For example, when it comes to health stuff, it's all kept together but sorted by name. My husband's health stuff is in the biggest drawer. There's a cabinet at home where we keep documents, and each drawer is labeled with a name.
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These different processing preferences reflect varied comfort levels with data complexity and different approaches to feeling informed and in control of health information. Understanding these two axes helps explain why families develop such different approaches to health data sharing.
Data Behavioral Patterns
Where these dimensions meet, four family patterns emerge. Each represents a different way of balancing personal boundaries with caring for each other through health information.
Family members track their own data and prefer occasional moments to check in together, not constantly.
Safe personal spaces with intentional sharing controls that respect boundaries while enabling meaningful connection when chosen.
Each family member shares their data and uses it as a basis to collaborate and plan together to make decisions.
They want tools that help them sync information and plan effectively as a team
Family members prefer to share only when necessary and often avoid the effort of tracking.
They want a system that gently nudges them when it truly matters, with gentle reminders to check-in and step in at the right moment when their attention is truly needed.
Family members share naturally in everyday conversations, but without a system to capture it, they often lose sight of the bigger picture.
They want structure and guides to help them organize and track what's most relevant from their natural caring interactions.
It's natural that people in families share differently.
From this research, surprisingly, parents with health conditions track more seriously than their adult children and use insights they learn to manage and plan their lifestyle to keep their health under control. For example, a mother might fit the "Data Collaborator" pattern, tracking actively and wanting to share details so the family can make health decisions together. Meanwhile, her adult daughter might be more of an "Alert Responder", tracking her own health casually and wanting to support her mom, but preferring meaningful check-ins over constant updates.
Yet, these behavior patterns aren't fixed traits.
People shift over time and influence each other. When the mother's condition worsens, the daughter temporarily becomes more collaborative. When things stabilize, she returns to responsive mode. Similarly, when the mother wants to share but her daughter is busy with work, she adapts by becoming more of an individual tracker. When the daughter realizes she needs to address her own sleep issues, she starts tracking more seriously.
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.
