Self-Tracking to Do Less: An Autoethnography of Long COVID That Informs the Design of Pacing Technologies

Title of the Paper

Self-Tracking to Do Less: An Autoethnography of Long COVID That Informs the Design of Pacing Technologies

Paper Information

• Research Domain: Human-Computer Interaction (HCI), Health Tracking Technologies
• Keywords: self-tracking, phenomenology, long COVID, COVID-19, Fitbit, heart rate monitoring, step counting, post-COVID syndrome, pacing technologies, autoethnography, health tracking technologies

Research Background and Problems

• What issues or challenges did the authors identify?

  • Long COVID patients need to continuously manage symptoms and avoid overexertion, which can worsen their condition.
  • Existing fitness tracking technologies are primarily designed to promote physical activity and are not optimized for the need to reduce activity.
  • The dynamic and unpredictable nature of long COVID symptoms makes it difficult for patients to effectively manage daily activities.

• Why is this issue important?

  • Long COVID is a newly emerging disease affecting millions globally, with its pathology not yet fully understood by the medical community and no effective treatments currently available.
  • Addressing chronic disease management has a direct impact on the quality of life for millions of patients.

• Research Motivation and Related Work

  • Previous studies on self-tracking technologies for chronic diseases have primarily focused on symptom tracking and patient self-management, with little exploration of using health tracking technologies to limit activity.
  • This study employs an autoethnographic approach, using the researcher’s personal experience with long COVID to explore the potential of “reverse use” of fitness tracking technologies.

Solutions

• What methods or solutions did the authors propose?

  • Using autoethnography to document how the researcher utilized a Fitbit tracker to reduce activity and alleviate long COVID symptoms.
  • Introducing a design concept called “pacing technologies” to help chronic disease patients manage daily activities and avoid symptom exacerbation.

• What is innovative about this solution?

  • Redefining the purpose of fitness tracking technologies: shifting from encouraging increased activity to helping users reduce activity.
  • Proposing three functional modes of pacing technologies: diagnostic pacing, real-time pacing, and preventative pacing.
  • Emphasizing the need for technology design to account for users’ dynamic bodily changes and interoceptive information.

• What are the implementation steps and key technologies used?

  • Utilizing Fitbit devices to record data such as heart rate and step count, combined with contextual self-recording (e.g., voice notes, written records) to extract behavioral patterns.
  • Conducting thematic analysis to highlight various pacing modes in daily health management.
  • Offering design recommendations for future pacing technologies, including dynamic disease support tools and adaptive tracking based on users’ physical states.

Research Outcomes

• What specific outcomes were achieved?

  • Demonstrating through autoethnography how Fitbit devices can be used in reverse to reduce stress and manage symptoms for patients.
  • Outlining the design possibilities of pacing technologies and the complexities of long-term use of health tracking technologies.

• How does this compare to existing solutions?

  • Existing technologies primarily focus on health optimization and behavioral change, while this study highlights how technology can assist patients in balancing energy and quality during symptom management.
  • Proposing a new design framework based on users’ dynamic bodily changes.

• What were the experimental or evaluation results?

  • The author identified three “pacing modes”—diagnostic pacing, real-time pacing, and preventative pacing—which helped her manage symptoms differently at various health stages.
  • Highlighting the lack of adaptability in current fitness technology designs to users’ dynamic physical states.

• Limitations and Future Directions

  • Limitations:
    • The study is based solely on the personal experience of a single author, lacking broader user or patient testing.
    • Existing technologies like Fitbit are insufficient to fully support the pacing needs of chronic disease patients.
    • The applicability of pacing technologies to other types of chronic diseases and symptom management remains unexplored.
  • Future Directions:
    • Designing more comprehensive pacing technologies to support diverse chronic disease management.
    • Exploring the integration of users’ interoceptive awareness with technological data in design.
    • Developing adaptive interfaces and algorithms that dynamically adjust to users’ changing states.

Conclusion

This paper, from the perspective of a long COVID patient, demonstrates how fitness trackers can be used to alleviate symptoms and introduces the concept of “pacing technologies” as a new design framework. The study makes significant contributions to the understanding of chronic disease management technology design and provides three new design modes and exploratory directions for the HCI field.