Predicting recovery after stressors using step count data derived from activity monitors.

This study examines the stressor-response process in physical activity among 226 participants across four countries. We analyzed their step count collected via activity monitors before and after a significant stressor: the COVID-19 lockdown. Results showed that a 'local dynamic complexity' metric significantly predicts the rate of recovery to pre-COVID levels of physical activity. These findings provide new opportunities for just-in-time interventions to support physical activity recovery after disruptive stressors.

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Publication Details

Journal
Open Access CRIS of the University of Bern
Published
2025-10-09
DOI
https://doi.org/10.48620/91815
Primary Topic
Mental Health Research Topics
Type
article
Field-Weighted Citation Impact
0.00
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article

Predicting recovery after stressors using step count data derived from activity monitors.

Open Access CRIS of the University of Bern
Mental Health Research Topics
article

Predicting recovery after stressors using step count data derived from activity monitors.

article en

Abstract

This study examines the stressor-response process in physical activity among 226 participants across four countries. We analyzed their step count collected via activity monitors before and after a significant stressor: the COVID-19 lockdown. Results showed that a 'local dynamic complexity' metric significantly predicts the rate of recovery to pre-COVID levels of physical activity. These findings provide new opportunities for just-in-time interventions to support physical activity recovery after disruptive stressors.

Open Access CRIS of the University of Bern
Institute of Behavioral Sciences (JP)
Openalex Percentile: Top 42%
Mental Health Research Topics
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Predicting recovery after stressors using step count data derived from activity monitors. · Open Access CRIS of the University of Bern (2025) | TGRS Research Map | TGRS