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

Dario Baretta; Sarah Koch; Joren Buekers; Judith Garcia-Aymerich; Lenka Knapova; Steriani Elavsky; Job Godino; Merlijn Olthof; Anna Lichtwarck-Aschoff; Ruud den Hartigh; Guillaume Chevance

doi:10.1038/s41746-025-01998-0

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

NPJ Digit Med. 2025 Oct 9;8(1):606. doi: 10.1038/s41746-025-01998-0.

Authors

Dario Baretta¹, Sarah Koch^{2

3}, Joren Buekers^{3

4}, Judith Garcia-Aymerich^{3

5}, Lenka Knapova⁶, Steriani Elavsky⁶, Job Godino^{7

8}, Merlijn Olthof⁹, Anna Lichtwarck-Aschoff⁹, Ruud den Hartigh⁹, Guillaume Chevance^{3

10}

Affiliations

¹ Institute of Psychology, University of Bern, Bern, Switzerland. dario.baretta@unibe.ch.
² University of Basel, Basel, Switzerland.
³ ISGlobal, Barcelona, Spain.
⁴ CIBER Epidemiología y Salud Pública (CIBERESP), Barcelona, Spain.
⁵ Universitat Pompeu Fabra (UPF), Barcelona, Spain.
⁶ University of Ostrava, Ostrava, Czechia.
⁷ Family Health Centers of San Diego, San Diego, CA, USA.
⁸ UC San Diego, San Diego, CA, USA.
⁹ Faculty of Behavioural and Social Sciences, University of Groningen, Groningen, The Netherlands.
¹⁰ Univ Rennes, Inserm, EHESP, Irset (Institut de recherche en santé, environnement et travail), Rennes, France.

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.

Abstract

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