Computational and neuropsychiatric dimensions of motivation differentially predict everyday physical activity
Abstract
Physical activity benefits physical and mental health, yet population-level engagement in physical activity is low and variable, particularly among individuals with mental health problems. We investigated how neuropsychiatric and computational variables of motivation relate to physical activity in a large, general-population sample (N = 1,105). Both neuropsychiatric (apathy and anhedonia) and computational (effort sensitivity during effort-based decision-making) measures predicted total physical activity. Decomposing physical activity into activity stage and intensity revealed clear dissociable and independent effects: Apathy and anhedonia, but not effort sensitivity, primarily predicted whether individuals participated in activity at all, as well as amount of sedentary time. Computational effort sensitivity, on the other hand, predicted the amount of activity individuals engage in, with effects scaling with intensity. Our findings suggest neuropsychiatric and computational dimensions of motivation govern distinct components of real-world physical activity, with implications for the development of targeted physical activity interventions.
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BibTeX
@misc{mehrhof2026computational,
title = {{Computational and neuropsychiatric dimensions of motivation differentially predict everyday physical activity}},
author = {Sara Z. Mehrhof and Camilla Nord},
howpublished = {PsyArXiv},
year = {2026},
month = sep,
doi = {10.31234/osf.io/m7vc2_v1},
url = {https://osf.io/preprints/psyarxiv/m7vc2_v1/},
note = {CC BY 4.0},
}
RIS
TY - UNPB
TI - Computational and neuropsychiatric dimensions of motivation differentially predict everyday physical activity
AU - Sara Z. Mehrhof
AU - Camilla Nord
PY - 2026
DA - 2026/09/27
PB - PsyArXiv
DO - 10.31234/osf.io/m7vc2_v1
UR - https://osf.io/preprints/psyarxiv/m7vc2_v1/
AB - Physical activity benefits physical and mental health, yet population-level engagement in physical activity is low and variable, particularly among individuals with mental health problems. We investigated how neuropsychiatric and computational variables of motivation relate to physical activity in a large, general-population sample (N = 1,105). Both neuropsychiatric (apathy and anhedonia) and computational (effort sensitivity during effort-based decision-making) measures predicted total physical activity. Decomposing physical activity into activity stage and intensity revealed clear dissociable and independent effects: Apathy and anhedonia, but not effort sensitivity, primarily predicted whether individuals participated in activity at all, as well as amount of sedentary time. Computational effort sensitivity, on the other hand, predicted the amount of activity individuals engage in, with effects scaling with intensity. Our findings suggest neuropsychiatric and computational dimensions of motivation govern distinct components of real-world physical activity, with implications for the development of targeted physical activity interventions.
ER -