Clinical Scorecard: Assessing Recovery from Stressors Through Step Count Data from Activity Trackers

At a Glance

Key Highlights

• Step count data from activity monitors provide scalable, unobtrusive, and time-sensitive measures of physical activity response to stressors.
• Increased local dynamic complexity in step count predicts slower recovery or reversals in physical activity levels after stressors.
• Approximately half of participants took a median of 88 days to return to pre-lockdown step counts; the other half had not returned after 6.5 months.

Guideline-Based Recommendations

Diagnosis

• Use continuous step count monitoring via wearable devices to detect changes in physical activity patterns following stressors.
• Analyze local dynamic complexity metrics to identify early warning signals of delayed recovery.

Management

• Develop just-in-time interventions triggered by detected slowdowns or reversals in step count trajectories to support physical activity recovery.
• Target interventions during critical moments identified by changes in dynamic complexity to accelerate return to baseline activity.

Monitoring & Follow-up

• Continuously track daily step counts to model individual stressor-response trajectories over time.
• Monitor local dynamic complexity as a predictive marker for future changes in physical activity levels.

Risks

• Prolonged reduction in physical activity below recommended thresholds (e.g., <9000 steps/day) may impact health and wellbeing.
• Delayed recovery or failure to return to baseline activity levels may increase risk of physical and psychological impairments.

Patient & Prescribing Data

Generally active adults with baseline median step counts around 10,000 steps/day prior to COVID-19 lockdown

Recovery trajectories vary; interventions should be personalized and timed based on dynamic complexity signals to optimize physical activity restoration.

Clinical Best Practices

• Leverage wearable activity monitors to obtain high-resolution step count data for real-time assessment of physical activity changes.
• Incorporate complex systems theory and dynamic complexity metrics to understand and predict individual recovery patterns.
• Implement timely, targeted support interventions informed by step count trajectory analyses to prevent prolonged inactivity.

References

• Physical activity and health benefits
• Ecological models of physical activity
• Complex systems theory in health monitoring
• Step count recommendations for health