Sprout: Using a Visual Metaphor to Support Customizable and Collaborative Health Tracking

Paper Title

Sprout: Using a Visual Metaphor to Support Customizable and Collaborative Health Tracking

Publication Info

• Topic area: Health tracking through qualitative visualization, customization, and collaboration.
• Keywords: self-tracking, health informatics, qualitative visualization, customization, collaborative tracking, garden metaphor, personal informatics, social features, privacy, user engagement.

Background and Problem

• Problem / challenge: Existing self-tracking tools often fail to sustain user engagement due to overwhelming quantitative feedback, limited customization, and discouraging social features based on comparison.
• Significance: Addressing these challenges could improve long-term engagement, motivation, and reflection in health tracking, supporting diverse user needs and goals.
• Motivation and related work: Prior research has explored qualitative visualizations, customization, and collaborative tracking separately or in pairs, but little is known about how these strategies interact when combined. This paper investigates how these elements coexist in a single system and their effects on user experience.

Solution

• Proposed approach: Sprout, a mobile health tracking application that integrates qualitative visualization, customization, and collaborative features using a garden metaphor.
• Novelty:
  1. Combines qualitative, customizable, and collaborative tracking in one system.
  2. Introduces a garden metaphor for non-judgmental, intuitive feedback on progress and collective growth.
  3. Provides empirical insights into how users prioritize and negotiate these design elements.
• Procedure and key techniques:
  • Users track health data (e.g., steps, sleep) mapped to customizable garden elements (trees, flowers).
  • Community gardens encourage cooperative goal achievement, unlocking shared features.
  • Anonymity preserves privacy while enabling group interaction.
  • Apple Health integration automates data collection.

Results

• Concrete findings:
  • Social features drove the highest engagement (38 minutes average usage in the Social condition).
  • Customization was primarily used during onboarding, with limited ongoing interaction.
  • Collaborative goals motivated users but caused frustration due to dependency on inactive group members.
  • Anonymity protected privacy but reduced social connection and translucence.
• Advantage over baselines:
  • Sprout’s qualitative visualization complemented existing quantitative tools, enhancing reflection and engagement.
  • Cooperative social features increased motivation compared to competitive approaches in prior systems.
• Experiments / evaluation:
  • 2-week field study with 22 participants across four conditions (Full, Social, Customization, Control).
  • Metrics included usage time, session count, goal achievement, and qualitative feedback from exit interviews.
• Limitations and future work:
  • Short study duration limited observations of long-term customization behavior.
  • Sample skewed toward young, experienced trackers, limiting generalizability.
  • Daily garden resets constrained reflection to short-term goals; longer timescales could be explored.

Summary

Sprout integrates qualitative visualization, customization, and collaborative tracking into a cohesive system using a garden metaphor. A 2-week field study revealed that social features drove engagement, customization was primarily used during onboarding, and cooperative goals motivated users but introduced frustrations due to group dependency. Anonymity protected privacy but hindered social connection. These findings suggest that future tracking systems should balance qualitative and quantitative visualizations, distinguish between aesthetic and functional customization, and design for both accountability and privacy in collaborative contexts. Sprout demonstrates the potential to expand self-tracking by offering alternative pathways for motivation and reflection.