Fig. 2: Ambulatory assessment and behavioral study findings.

a, Accelerometry was used to measure physical activity, while affective valence and social contact were assessed through ecological momentary assessment. b, Exemplified sampling scheme: geolocations were continuously tracked and assigned using an advanced day reconstruction method (for example, at home, work). E-diaries were either location-based or triggered at random times. c, Study 1 (n = 317; Table 1). Physical activity engagement (x axis) offsetting the social-affective deficit (y axis) associated with the absence of real-life social contact as illustrated by the gray-shaded area between the solid (in company) and dashed (alone) green lines. The regression lines, derived from the multilevel interaction analyses (outcome: affective valence; predictor: real-life social contact; moderator: physical activity centered within-individual), demonstrate that the more participants had been physically active before an e-diary assessment, the less affective loss they experienced when being alone. Physical activity values to the very left of the x axis refer to sedentary behavior such as sitting, while values to the very right depict moderate activities such as walking. Study 2 (n = 30; Supplementary Table 7). Replication of the compensatory effect of physical activity during the COVID-19 pandemic. P values for the beta coefficients are two-sided and were derived from the t-statistics of the multilevel model. The error bars indicate the s.e. of the respective estimated mean valence scores. d, Trait loneliness. Participants with small social networks (light green) who engaged in high habitual levels of physical activity reported lower trait loneliness compared to those engaging in low habitual levels of physical activity (Supplementary Table 4). P values are two-sided and were derived from the t-statistics of the multiple linear regression. The error bars indicate the s.e. of the respective estimated mean loneliness scores. Credit: a, smartphone icon, Elisa Riva, Pixabay.com. Map in b created using OpenStreetMap.