Digital health technology often treats data as individual metrics, missing the relational dynamics that sustain long-term care. This gap matters in cultures like Thailand, where intergenerational caregiving is embedded in family practices. This creates an opportunity to explore how health data might become relational material that supports families' natural caregiving culture.
This research explores how Thai parent-child pairs (n=8) managing metabolic conditions like high blood pressure, high cholesterol, and elevated blood sugar share health data within their family relationships.
Working with parents (60+) and adult children (25-40) through participatory design and contextmapping methods, we examined how families currently navigate health data sharing and co-designed adaptive sharing approaches across different health journey phases.
This research is grounded in data humanism philosophy, treating health data as personal, situated, and relational rather than objective metrics. The study explores data intimacy — how people develop closeness through sharing personal health data with trust and intention, allowing family members to understand and care for each other across changing health situations rather than fixed sharing patterns.
Explore this research
The Challenge
Thai Family Care Background
In Thai culture, health and care are family matters. Thai families practice 'natural caregiving' — care that extends beyond physical tasks to include emotional presence and wellbeing monitoring, often starting before practical support is needed.Adult children feel obligated to monitor and support their parents' wellbeing (Wongsawang et al., 2013). However, this study reveals that parents might be reluctant to share health information to avoid causing worry for their adult children.
Meet Mali and Pam
To understand what this looks like in real life, here's a story that captures experiences shared by families in our study.
Meet Mali, a retired mom in her 60s who tracks her blood pressure and keeps an eye on her cholesterol. Her numbers have been mostly stable, but her doctor recently mentioned some changes worth paying attention to.
Pam, her daughter, has a busy working life.
Mali tracks and logs her blood pressure daily like her doctor told her to, and wears a smartwatch her daughter bought her to encourage her to walk more.
Her daughter, Pam, tracks her own steps and logs sleep patterns between her busy schedule, working toward better sleep habits while feeling the need to stay aware of her mother's wellbeing.
The Tension
Mali sometimes shares how many steps she got or what healthy meals she's trying in the family chat, but when her blood pressure numbers start looking worrying, she quietly keeps track of them to discuss with her doctor at her next appointment rather than alarming Pam during her busy work days.
She wants to share enough to reassure Pam that she's taking care of herself, but struggles with when and how to bring up concerns without causing unnecessary anxiety or feeling like a burden.
Pam receives notifications every time Mali takes a walk, but these daily updates make it hard to see the bigger picture of her mother's overall health.
She wants to stay aware of her mom's wellbeing without becoming a constant health monitor, and hopes to notice if something's wrong before it becomes serious. At the same time, she decides not to share her own sleep struggles because she doesn't want her mom to worry, even though she'd like to reassure her mom that she's working on better sleep habits.
Current health apps often assume fixed sharing preferences: we set permissions once and they stay the same. But family relationships exist in nuanced spaces where sharing decisions depend on context, timing, and what's happening in each other's lives. When Mali's readings look concerning, Pam wants more details; during stable periods, occasional check-ins feel just right.
Mali and Pam's story reflects patterns we saw across families managing chronic conditions. Family health sharing isn't just a technical problem to solve, but a relational journey to support.
Through research sessions with family pairs,
three key perspectives emerged about this journey.
When Health Data Meets Family Relationships
Chronic conditions unfold slowly, across weeks, months, and years.
Imagine health as a shared journey at sea. Sometimes waters are calm, sometimes storms build gradually, sometimes crisis hits suddenly.
This metaphor, which emerged from our participatory design sessions, helps us explore how sharing could naturally evolve as health conditions and life circumstances change.
A ship isn't a bad metaphor, it's like, okay, as a family, we're all on this journey together. We need to take care of each other and make sure we all make it safely to the other side.
![[headshot] image of customer sharing feedback (for a environmental conservation nonprofit)](https://cdn.prod.website-files.com/68501fba736f44187f475e26/685291d7c9fd166defd1161b_Property%201%3DDefault.svg)
It's that sense of being a team, like we're all crew members, each with a role in keeping the boat moving forward
![[headshot] image of customer sharing feedback (for a environmental conservation nonprofit)](https://cdn.prod.website-files.com/68501fba736f44187f475e26/685291d7512c96a4d1fe10e8_Property%201%3DVariant2.svg)
We explored how families already shared and could share different types of health data — medical records (lab results, check-ups), vitals (blood pressure, cholesterol), and behavioral data (steps, sleep, eating).
From these sessions, three key perspectives emerged
on how families navigate these health journeys with data together.
People On Board
Health phases change, and families are placed in the same boat to navigate different situations together, yet each of them could engage with data and share differently.
From this research, we found that health data sharing is shaped by how people balance two dimensions: their boundaries around sharing personal health information (being open or selective) and their level of engagement with data (being active or passive).
When these dimensions intersect, they create four different sharing patterns. These patterns describe different approaches, but they aren't fixed.
Track seriously but share selectively
Safe personal spaces with intentional sharing controls that respect boundaries while enabling meaningful connection when chosen.
Track together and share details to make health decisions collaboratively.
Tools that help them sync information and plan effectively as a team
Share casually but step up when needed
Share only when it really matters. They want a system that respects their space, but helps them notice and respond when someone might need extra care. They value gentle prompts to check in at the right moment, without pressure or constant tracking.
Share naturally in conversation but need help organizing it
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.
Mali fits the "Daily Carer" pattern — she tracks purposefully and shares openly as part of family conversations. Pam is more of an "Alert Responder" — she tracks her own health casually and wants to support her mom, but prefers meaningful check-ins over constant updates.Yet these behavior patterns aren't fixed traits.
People shift over time and influence each other.
When Mali's recent lab results showed her cholesterol creeping up, her sharing became more thoughtful — she didn't want to worry Pam unnecessarily, but she also didn't want to handle it alone. When Mali's numbers started trending upward, they could temporarily became more of a Data Collaborator, checking in more frequently and asking detailed questions. When things stabilized, she returned to Alert Responder mode. Similarly, when Mali wants to share but Pam is busy with work, Mali adapts by becoming more of an Independent Tracker. When Pam realized she needed to fix her sleeping habits, she started tracking more seriously.
Riding the waves
Second, health unfolds over time. Families deal with chronic conditions as a journey with different phases. Each phase needs different levels of attention and involvement. These phases don't follow a straight line — families move back and forth as things change.
Stable Sea
Windy Wave
Stormy Moment
Calm Water
Stable Sea
Windy Wave
Stormy Moment
From our sessions, we learned that families envisioned their sharing needs changing across four phases: stable periods wanting casual check-ins, small changes requiring gentle alerts, critical events needing intensive coordination, and recovery periods for building collective memory.
From participants' experiences, these health phases don't always unfold predictably. Families could skip directly from stable to crisis, or cycle back and forth based on changing conditions. What feels routine to one family might feel concerning to another, depending on their health experience and comfort with managing chronic conditions.
Private Cabins and Shared Decks
Third, data becomes meaningful through lived experiences. Sharing health data isn't about perfect tracking. it's about sustaining care and mutual understanding.
Families desire both personal spaces and collective spaces for family health data. Not everything gets shared—they need space to process personal notes and reflections, sharing only meaningful insights over time. People also want to add their own context and understanding before deciding what to share. If someone needs details, they can look deeper or simply ask.
Picture Mali and Pam's health journey as traveling together on a ship. Mali and Pam need their private cabins - space to process readings and reflect before sharing. Tracking patterns differ because of different conditions and personal interests. But they also need a shared deck - a common place to discuss their health and build collective knowledge that won't get buried in daily chat..
Some people see tracking as a burden, but they're willing to share if it helps their family over time. Sustainable sharing and ongoing conversation matter more than perfect tracking or precise numbers. It's the ongoing conversation, bringing personal insights to shared spaces where everyone can learn, that keeps the relationship alive.
This perspective raises design questions: How might we design health data spaces that provide both private reflection space and sustained ongoing conversations, rather than treating everything as either completely private or fully shared?
Missing the Relational Opportunity
This opens an opportunity to explore how health data sharing might support the conversations, connections, and care that families already want to have with each other.
Health apps design for individual users, missing the reality that families already share health insights and coordinate care together.
If we keep this data and make it viewable to family members, it becomes a way to share information with each other. Then maybe once a month, we can talk about it ,like, should we improve something? Or decide to play badminton together every Saturday afternoon or something like that.
![[headshot] image of customer sharing feedback (for a environmental conservation nonprofit)](https://cdn.prod.website-files.com/68501fba736f44187f475e26/685291d78d81058885191008_Property%201%3DVariant3.svg)
Meaningful health shares get lost in daily conversations, missing valuable reference points.
The point is, having everything related to this one topic in one place matters. I want it to be separated from general conversations so it’s easier to go back and review.
Data doesn't stand alone—it becomes meaningful when families can discuss it together, gaining different perspectives that create mutual understanding and awareness.
Maybe someone says they're just a bit sore, not a big deal, but when you look at the data, it's clear they've been in pain, their walking has dropped by 60%
![[headshot] image of customer sharing feedback (for a environmental conservation nonprofit)](https://cdn.prod.website-files.com/68501fba736f44187f475e26/685291d7e9e59005c0e4ef04_Property%201%3DVariant4.svg)
These insights reveal opportunities for designing health data sharing with family relationships in mind. Here are the key principles that emerged:
Windy Wave
From Insights to Practice
Building on these insights, we developed eleven principles organized around three pillars for designing health data sharing with relationships in mind
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 are relational beings who care for and depend on each other. How we share health data is shaped by who we are, who we trust, and how we naturally communicate.
Challenge "one shares, one monitors" sharing dynamics. People share more when they witness mutual vulnerability or know others care, even with different health data. Encourage reciprocal sharing that enables care and voluntary participation from both sides rather than pressured one-way surveillance.
Beyond practical coordination, health data sharing can also support emotional connection, shared decision-making, and collective learning. Recognize that families share not just to manage tasks, but to understand, cope, prepare, and simply be present for one another.
Allow people to express health concerns and get updates in ways that feel comfortable, whether through conversation, notes, or quiet logs. Some people in relationships 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 could be intentional, not automatic constant updates, 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 what their data means to them personally before deciding what to share, and systems should 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.
Support multiple ways of knowing by combining clinical metrics with lived experience stories. Allow families to add context to numbers and respect different health perspectives, encouraging personal stories alongside clinical data.
Recognize that care and tracking naturally fluctuate based on life circumstances. Support inconsistent data engagement patterns without guilt or pressure, understanding that sporadic, or short-term 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 sharing with relationships in mind. Start by using these reflection questions to examine your own family health experiences, evaluate current technology through a relational lens, and imagine how data sharing could better fit relationships.
While grounded in Thai parent-child relationships managing metabolic conditions, these insights need validation across different cultural contexts, family structures, and health situations. You might need research methods that go beyond individual user interviews—approaches that embrace the lived experiences of people navigating health together.
We invite you to test these principles in your design practice, adapt them to your specific context, and share your learnings about what works—and what doesn't—with the community working toward more human-centered health technology.
Using this framework and principles as guide, international participants (n=5) generated practical applications grounded in their family experiences:
In validation sessions, designers used the framework to reflect on their own family health relationships, then ideated solutions based on their personal experiences and needs. These are samples of ideas...
Beyond practical coordination, health data sharing can also support emotional connection, shared decision-making, and collective learning. Recognize that families share not just to manage tasks, but to understand, cope, prepare, and simply be present for one another.
Behind the insights
This research worked with Thai family pairs (n=8) managing metabolic conditions like high blood pressure, high blood sugar, and cholesterol that raise the risk of heart disease, together with their adult children through co-creation sessions.
These participants were already tracking their own behavioral data, such as steps, sleep, or food.
This work builds on the philosophies of data humanism (Lupi, 2017) and data intimacy. Data humanism challenges the idea that data is neutral or universal, so we explored how health data becomes meaningful through the relationships and contexts families create together.
For us, data intimacy means a sense of closeness that emerges when personal data is shared with intention and trust, supporting family members to connect, understand, and care for one another.
MSc Graduation Project by Pitshaya Chonato
Design for Interaction, Medisign Specialization
Supervised by Dr.ir. J. Bourgeois (Chair) and Dr.ir. M.H. Sonneveld (Mentor)Data Centric Design Lab, Industrial Design Engineering, TU Delft
It depends on whether the big event impacts just the person or the whole family. If it's personal impact, it might only involve one close person, like my wife. But if it affects the whole family, then everyone should be told.
Imagine suddenly being told you have cancer, and worse, the app notifies your parents before you even know. That would be terrible. But if a human delivers the news, they can choose the right moment, the right way.
In the future, it could even include my child's partner or a close friend of mine, someone who doesn't have kids or family of their own, but wants to be part of a shared data circle. Maybe they just want to feel like someone cares about them, because they don't have anyone else.
I see it as folders where you can choose between personal or family. Everything gets recorded, but the default is family. If you want something to be personal, then you set it as personal.
Once I looked at the pattern, it clearly wasn't what I had thought. After just seven days of logging, it became obvious—a little bit of this, a little bit of that… but in the end, the clearest thing was that I eat way more carbs than I thought.
![[headshot] image of customer sharing feedback (for a environmental conservation nonprofit)](https://cdn.prod.website-files.com/68501fba736f44187f475e26/685291d955005ab1f9faa2bf_Property%201%3DVariant5.svg)
(Sharing health data) is not about competition...we just want to know if something happens often enough, if it's okay or if it needs attention—just that. Enough to know if it should be done.
![[headshot] image of customer sharing feedback (for a environmental conservation nonprofit)](https://cdn.prod.website-files.com/68501fba736f44187f475e26/685291d8f57357c8f21444ec_Property%201%3DVariant6.svg)
Once I started logging, I could see the difference, like, 'Oh! Today I got 3,000 steps, but yesterday I got 5,000.' It became a bit of a fun challenge with myself. But then I'd also think, 'Hmm, I've never quite hit 6,000.' Still, I know I have a lot of limitations from my previous injury.
![[headshot] image of customer sharing feedback (for a environmental conservation nonprofit)](https://cdn.prod.website-files.com/68501fba736f44187f475e26/685291d8ead31a7ca287a8c0_Property%201%3DVariant7.svg)
I'm not looking to report my behavior every day—I'm not that free. I feel like if someone wants to know something, they can just check. If they have questions, they can ask based on what they see.
![[headshot] image of customer sharing feedback (for a environmental conservation nonprofit)](https://cdn.prod.website-files.com/68501fba736f44187f475e26/685291d84e8a14b4981750cb_Property%201%3DVariant8.svg)
1. Wongsawang, N., Lagampan, S., Lapvongwattana, P., & Bowers, B. J. (2013b). Family caregiving for dependent older adults in Thai families. Journal of Nursing Scholarship, 45(4), 336–343. https://doi.org/10.1111/jnu.12035
2. Sanders, E. B.-N., & Stappers, P. J. (2016b). Convivial toolbox: Generative research for the front end of design. BIS.
3. Visser, F. S., Stappers, P. J., van der Lugt, R., & Sanders, E. B.-N. (2005). Contextmapping: Experiences from practice. CoDesign, 1(2), 119–149. https://doi.org/10.1080/15710880500135987
4. Lupi, Georgia. "Data Humanism: The Revolutionary Future of Data Visualization." Print Magazine, 30 Jan. 2017, https://www.printmag.com/article/data-humanism-future-of-data-visualization/.
Want to dive deeper? If you're interested in the complete research foundation, methodology, results, and discussion, download the full thesis document to explore our detailed approach and findings.
We welcome anyone who's curious and interested to try out, build upon this work and contribute to the growing field of health data for relational use. :-)
