Short answer
Design wellbeing technologies not as individualistic monitoring tools, but as platforms that foster shared understanding, negotiation, and personalized meaning-making of health data among users.
- Field
- User-Centred Design
- Source
- Academic Publication (2023)
- Method
- Qualitative research combining home trials, diary studies, and co-design workshops.
- Sample
- 4 couples (8 participants)
- Evidence
- Moderate effect
Older adults collaboratively interpret and personalize data from wellbeing technology, demonstrating a need for systems that support shared understanding and agency. This user-centred design research insight is drawn from a 2023 study published in Academic Publication. Using Qualitative research combining home trials, diary studies, and co-design workshops. with 4 couples (8 participants), researchers explored how this design variable affects real-world outcomes. The key design takeaway: Design wellbeing technologies not as individualistic monitoring tools, but as platforms that foster shared understanding, negotiation, and personalized meaning-making of health data among users.
Data as Co-experience: Older Adults Redefine Wellbeing Technology Interaction
Older adults collaboratively interpret and personalize data from wellbeing technology, demonstrating a need for systems that support shared understanding and agency.
Academic Publication · 2023
Key Findings
- 01Data is collaboratively experienced and negotiated within couples.
- 02Older adults personalize their understanding and use of data.
- 03New embodied data representations can significantly alter user experience.
- 04The concept of 'Data as Co-experience' emerges as a framework for designing data-driven systems.
Application
Design takeaway
Design wellbeing technologies not as individualistic monitoring tools, but as platforms that foster shared understanding, negotiation, and personalized meaning-making of health data among users.
How to apply
When designing health or wellbeing technologies, consider how users might interact with and discuss data in pairs or groups, and explore non-traditional, embodied ways to represent complex information.
Project actions
- 01Consider involving pairs or small groups in your user research.
- 02Explore how different ways of showing data (e.g., physical objects, gestures) might change understanding.
Method & Evidence
Variables
Strengths & Limitations
Strengths
- +Ecological validity through home-based trials.
- +Rich qualitative data from multiple research methods.
Limitations
The findings might not apply to younger demographics or individuals who prefer solitary data interaction.
Reliability & validity
Reliability could be enhanced by using standardized protocols for diary prompts and co-design activities. Validity is supported by triangulation of data from smartwatch use, diaries, and workshops, capturing a holistic view of user experience.
Think critically
How might the 'Data as Co-experience' model be adapted for technologies where data privacy is a primary concern, and collaboration is less feasible?
Design Principles
"Design for Data as Co-experience, emphasizing collaborative interpretation, personalization, and embodied representation."
Current wellbeing technologies often overlook the nuanced ways older adults engage with their health data. This research highlights that designing for this demographic requires moving beyond individual monitoring to embrace collaborative interpretation and personalized meaning-making.
What This Means for Your Design
Older people often look at health data together and decide what it means for them, showing that technology should help them talk about and change how they see their health information.
How to use in your project
- 1.Use the concept of 'Data as Co-experience' to frame your user research and design decisions for data-driven products.
- 2.Reference the findings on collaborative interpretation when justifying design choices for shared interfaces or feedback mechanisms.
Add to My Project
Quick Cite
Paragraph starter
This design project draws inspiration from research highlighting 'Data as Co-experience,' where users, particularly older adults, collaboratively interpret and personalize wellbeing data. This approach emphasizes designing systems that support shared understanding and individual agency, moving beyond purely individualistic data monitoring to foster richer, more meaningful interactions with personal information.
Source
Academic Publication
Rethinking the Design of Human-Data Interaction through a Study of Older Adults’ Wellbeing
journal · 2023
View sourceQuestions About This Research
- What does the research say about data as co-experience: older adults redefine wellbeing technology interaction?
- Design wellbeing technologies not as individualistic monitoring tools, but as platforms that foster shared understanding, negotiation, and personalized meaning-making of health data among users. Evidence: Academic Publication (2023).
- Why does "Data as Co-experience: Older Adults Redefine Wellbeing Technology Interaction" matter for design?
- Current wellbeing technologies often overlook the nuanced ways older adults engage with their health data. This research highlights that designing for this demographic requires moving beyond individual monitoring to embrace collaborative interpretation and personalized meaning-making.
- How can designers apply this research?
- Design wellbeing technologies not as individualistic monitoring tools, but as platforms that foster shared understanding, negotiation, and personalized meaning-making of health data among users.
- What were the main findings?
- Data is collaboratively experienced and negotiated within couples.. Older adults personalize their understanding and use of data.. New embodied data representations can significantly alter user experience.. The concept of 'Data as Co-experience' emerges as a framework for designing data-driven systems.
- What research method was used?
- Qualitative research combining home trials, diary studies, and co-design workshops. with 4 couples (8 participants).
- How strong is the evidence?
- Evidence strength is rated Moderate effect, based on a 2023 journal from Academic Publication.
- What should I do differently in my next project?
- When designing health or wellbeing technologies, consider how users might interact with and discuss data in pairs or groups, and explore non-traditional, embodied ways to represent complex information.
- What are the limitations?
- Small sample size, specific demographic focus (older adults), limited duration of technology use.