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Applying Sequence Analysis to Explore Real-World Usage Patterns in the 10,000 Steps Digital Physical Activity

Yanshu Huang1, Danielle Taylor1, Matthias Kubler1

  • 1Institute for Social Science Research, The University of Queensland, St Lucia, QLD, Australia.

Journal of Physical Activity & Health
|May 29, 2026
PubMed
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This summary is machine-generated.

Digital health programs like 10,000 Steps show varied engagement. Medium/long-term use depends on program features and device integration, influencing physical activity impact.

Area of Science:

  • Digital Health
  • Behavioral Science
  • Physical Activity Promotion

Background:

  • Digital health programs can improve physical activity, but sustained engagement is key for long-term behavioral impact.
  • Examining engagement and disengagement patterns is crucial for optimizing digital health interventions.

Purpose of the Study:

  • To analyze medium/long-term engagement and disengagement patterns within the 10,000 Steps digital health program.
  • To identify user subgroups and correlates associated with different engagement levels over time.

Main Methods:

  • Utilized sequence analysis to track program usage patterns over seven years (2018-2024) in Australian adults.
  • Employed logistic regression to determine demographic and program-related factors linked to user engagement subgroups.
Keywords:
behavioral sciencehealth behaviorpedometry

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Main Results:

  • Most users exhibited short-term engagement; however, two distinct groups demonstrated longer-term use.
  • One subgroup (7.1%) engaged intermittently, influenced by health professional referrals, family/friend recommendations, and participation in Tournaments or use of Fitbit/website.
  • A consistent, low-inactivity group (4.5%) favored individual Challenges, Tournaments, and specific devices like Garmin or the Google app.

Conclusions:

  • Medium/long-term engagement in the 10,000 Steps program is not uniform but varies significantly.
  • Engagement levels are influenced by the specific program features utilized and the type of wearable devices integrated.