Between Control and Uncertainty: Understanding Self-Tracking Practices in Enigmatic Disease Management

Paper Title

Between Control and Uncertainty: Understanding Self-Tracking Practices in Enigmatic Disease Management

Publication Info

• Topic area: Self-tracking practices in the management of enigmatic diseases.
• Keywords: Self-tracking, enigmatic diseases, chronic illness, personal informatics, health technology, disease management, symptom tracking, emotional impact, adaptive design, patient agency.

Background and Problem

• Problem / challenge: Existing self-tracking tools assume that tracking health variables leads to actionable insights, but this assumption is untested in contexts of uncertainty and fluctuating health needs, such as enigmatic diseases.
• Significance: Enigmatic diseases, including fibromyalgia, Crohn’s disease, and endometriosis, are poorly understood and highly individualized, complicating effective self-tracking and disease management.
• Motivation and related work: Prior research has explored self-tracking for specific conditions (e.g., migraines, endometriosis) and its role in clinical communication, self-experimentation, and emotional support. However, less attention has been paid to the temporal dynamics of tracking—how goals evolve, when tracking is abandoned, and how uncertainty shapes engagement.

Solution

• Proposed approach: A qualitative study examining self-tracking practices across multiple enigmatic diseases to understand shifting goals, fluctuating engagement, and emotional impacts.
• Novelty:
  1. Broadens research on health tracking by focusing on shifting needs and evolving goals across diverse enigmatic diseases.
  2. Highlights the double-edged nature of tracking, which can foster agency but also amplify frustration and self-blame.
  3. Advances design knowledge for adaptive, inclusive self-tracking tools that support fluctuating goals and cross-condition needs.
• Procedure and key techniques:
  • Conducted semi-structured interviews with 23 participants diagnosed with enigmatic diseases.
  • Analyzed qualitative data using a thematic coding approach to identify patterns in tracking goals, transitions, and emotional experiences.
  • Explored the interplay between symptom fluctuations and tracking engagement.

Results

• Concrete findings:
  • Participants used an average of four tools, including apps, wearables, and paper-based formats, with 28 unique apps mentioned.
  • Five primary tracking goals emerged: attributing fluctuations, anticipating flare-ups, ensuring continuity in care, establishing diagnoses, and documenting symptoms.
  • Tracking was episodic, intensifying during flare-ups and lapsing during stable periods or good days.
  • Tracking fostered a sense of control but also led to frustration, self-blame, and emotional distress when insights failed to materialize.
• Advantage over baselines: Provides a multi-condition perspective that highlights shared challenges across enigmatic diseases, moving beyond single-disease studies.
• Experiments / evaluation:
  • Recruitment targeted specific enigmatic diseases through online communities and patient associations.
  • Interviews explored disease journeys, tracking practices during good and bad days, and reflections on past data.
  • Findings were analyzed using thematic coding to identify patterns and insights.
• Limitations and future work:
  • Sample may not represent the broader population due to gender imbalance, geographic concentration in Europe and North America, and recruitment bias toward digitally literate individuals.
  • Future work should explore culturally diverse populations and investigate community-driven module designs for multi-condition tracking tools.

Summary

This study examines self-tracking practices among individuals with enigmatic diseases, revealing how fluctuating symptoms drive shifting goals and episodic engagement. While tracking fosters agency and control, it can also amplify frustration and self-blame when expectations fail to align with the unpredictable nature of these conditions. The findings highlight the need for adaptive, non-judgmental tools that normalize uncertainty, support evolving goals, and accommodate comorbidities. By adopting a multi-condition perspective, the study offers design recommendations for inclusive, layered tracking systems that balance shared experiences with condition-specific needs.