Co-Designing Situated Displays for Family Co-Regulation with ADHD Children

Title of the Paper

Co-Designing Situated Displays for Family Co-Regulation with ADHD Children

Paper Information

• Subject Area: Health Informatics, Collaborative Technologies for Children and Families, Attention Deficit Hyperactivity Disorder (ADHD)
• Keywords: Family Informatics, Situated Displays, Smartwatches, Co-Design, ADHD, Health Tracking

Research Background and Issues

• Identified Problems or Challenges:

  • Existing family health tracking interfaces (e.g., data dashboards) are often limited to increasing awareness of each other's health status but fail to provide actionable guidance for improving health behaviors and family functioning.
  • Families with ADHD children face unique challenges in health coordination, including high supervision demands, medication adherence issues, and increased risk of family conflicts.
  • Research on family-oriented situated displays for shared data to support collective health behavior improvement is still limited, especially for families dealing with chronic health conditions.

• Significance:

  • ADHD is one of the most common childhood mental disorders, with far-reaching impacts on emotional regulation, attention, and behavior control.
  • Promoting family collaboration and reflection on health data can not only improve individual health but also enhance overall family functioning and relationships.

• Research Motivation and Related Work:

  • Self-regulation and co-regulation for children with ADHD require optimization through digital interventions, as existing approaches (e.g., serious games, daily schedule management) have limitations, necessitating the design of integrated family tools.
  • Previous family health tracking studies have primarily focused on parental monitoring of children, highlighting the need to explore methods that balance parent-child roles and encourage greater child participation.
  • Family information sharing of health data shows potential, but current systems mostly remain at the level of superficial data display, lacking in-depth analysis and actionable guidance.

Solution

• Proposed Method or Solution:

  • The authors conducted three rounds of co-design workshops with eight families (each including at least one ADHD child and at least one parent), totaling 24 sessions, to explore ideal designs for situated family data displays.
  • Using smartwatches (e.g., Apple Watch) to collect data on children’s emotions, exercise, and daily goal tracking, the study inspired design ideas and identified preferences, needs, and complex use cases for family health data displays.

• Innovations:

  • Combined family co-design methods to deeply explore self-regulation and co-regulation related to ADHD.
  • The system emphasizes multiple family use intentions, supporting both collaborative use and individual autonomy (independent reflection and data utilization).
  • Explored how to integrate clinical professional guidance and real-life family scenarios, incorporating external recommendations (e.g., feedback from teachers and doctors) into family life.

• Implementation Steps and Key Technologies:

  1. Data Collection Phase: Use smartwatches to record children’s activity, emotions, and goal achievement.
  2. Co-Design Phase:
     • Session 1: Familiarize participants with design tools and systems, and design emotional representations for family members.
     • Session 2: Discuss how shared emotional data can promote co-regulation.
     • Session 3: Design data display solutions for goal and activity tracking, and discuss motivational mechanisms (e.g., family exercise goals).
  3. Qualitative Analysis: Extract needs from the workshops and user-generated designs, and generate themes through coding.

Research Findings

• Specific Outcomes:

  1. Meaningful Use of Family Time:
     • The system should actively prompt families to regularly review data and help plan future behavioral adjustments.
     • Support family members in reflecting on past performance while learning and practicing specific behavioral regulation skills.
  2. Support for Personalized Needs:
     • Parents desire in-depth analysis features to identify behavioral patterns and health risks, as well as to evaluate their influence on their child’s self-management.
     • Children prefer emotional and gamified interface styles and need more assistance in interpreting data and guidance on how to regulate behaviors.
  3. Integration of External Professional Support:
     • Families expect the display system to incorporate feedback and guidance from schools or medical institutions, such as collaborating with educators and clinicians through data.

• Advantages Over Existing Solutions:

  • Provides more guidance features to help transition from data awareness to actionable steps.
  • Specifically addresses the emotional and behavioral regulation needs of ADHD families, covering both collaborative reflection and individual regulation.
  • Facilitates interaction between families and external support networks, contrasting with existing "one-way data dashboards."

• Experimental or Evaluation Results:

  • The co-design process revealed specific family needs for interactive data displays.
  • Demonstrated the potential of family systems to support health behaviors and educational interventions, such as enhancing family cohesion through motivational mechanisms and data visualization.

• Limitations and Future Directions:

  • Limitations: Small sample size, primarily middle-to-upper-class families in the U.S., insufficiently reflecting cultural differences and the needs of low-resource families; other family types (e.g., single-parent or multigenerational households) were not considered.
  • Future Directions: Expand sample diversity, explore the feasibility of joint design with educational and healthcare institutions, and further investigate system interventions among siblings.

Conclusion

This study thoroughly explores the design potential of situated family health data displays, particularly in the context of supporting co-regulation and self-regulation for ADHD children and their families. Future work could further optimize the current model and expand its application potential to other behavioral or health domains (e.g., diet or sleep).