Recovery from Stressors via Step Count Data Post COVID-19 Lockdown

Overview

This multi-country study of 226 participants analyzed step count data before and after the COVID-19 lockdown to assess recovery from physical activity disruptions. The local dynamic complexity metric significantly predicted the rate of recovery to pre-lockdown activity levels, highlighting its potential for guiding timely interventions.

Background

Physical activity is crucial for health but is sensitive to stressors that disrupt regular engagement. Stressors can be intra-individual or extra-individual, affecting physical activity differently across individuals. Advances in mobile sensing allow detailed tracking of step counts, a practical biomarker for physical activity, enabling the study of dynamic stressor-response trajectories. Understanding these trajectories can inform just-in-time interventions to support recovery after disruptive events like the COVID-19 lockdown.

Data Highlights

Key Findings

• Step count decreased significantly after the COVID-19 lockdown, from a median of over 10,000 to approximately 6,500 steps per day.
• About half of the participants (49%) returned to pre-lockdown step levels within a median of 88 days; the other half had not recovered by 6.5 months post-lockdown.
• Local dynamic complexity (DC) in step count data predicted the rate of recovery, with higher DC associated with slower or reversed recovery trajectories.
• Step count serves as a scalable, unobtrusive biomarker to monitor physical activity recovery after stressors.
• Tracking step count dynamics enables modeling of individual stressor-response trajectories and identification of critical moments for intervention.

Clinical Implications

Monitoring step count and its dynamic complexity can help clinicians identify individuals at risk of delayed recovery in physical activity after major stressors like lockdowns. This approach supports the development of just-in-time interventions to provide timely, targeted support to accelerate recovery and prevent prolonged inactivity. Incorporating wearable activity data into patient management may enhance personalized rehabilitation strategies.

Conclusion

The study demonstrates that local dynamic complexity in step count data is a valuable predictor of physical activity recovery following disruptive stressors such as the COVID-19 lockdown. These insights pave the way for leveraging wearable technology to optimize interventions and promote resilience in physical activity behaviors.

References

1. Study Authors 2024 -- Assessing Recovery from Stressors Through Step Count Data from Activity Trackers