Related Experiment Video
Updated: Aug 15, 2026

An Application for Pairing with Wearable Devices to Monitor Personal Health Status
Published on: February 3, 2022
Shall we walk? A user study of an app tracking time in nature in everyday life
Sigbjørn Litleskare1,2, Rossano Schifanella3,4, Giovanna Calogiuri1
1Centre for Health and Technology, Department of Nursing and Health Sciences, University of South-Eastern Norway, Drammen, Norway.
Objective:
Little is known about how smartphone apps can encourage nature visits, and previous research suggests that human perceptions are key to both app development and understanding the quality of natural environments. This study developed and tested an app feature that tracks time in nature by calculating a green index to estimate the amount of nature at a location using map data and estimated levels of traffic noise.
Methods:
A formative evaluation was conducted in which 29 participants visited five pre-selected locations representing various types of urban nature, and provided ratings of "perceived nature", perceived environmental restorativeness, and overall feeling. Additional measures included age, gender, baseline nature connectedness, perceived weather conditions, and an unstructured interview.
Results:
The green index vs perceived nature ratings (mean ± SD) at each location was 88 vs 49.9 ± 22.9 at location 1 (Pedestrian bridge); 63 vs 61.8 ± 15.7 at location 2 (Park); 31 vs 63.5 ± 18.7 at location 3 (River, green); 21 vs 44.8 ± 22.4 at location 4 (Trafficked bridge); and 50 vs 48.0 ± 21.4 at location 5 (River, grey), reflecting both underestimation and overestimation of the green index, with significant inter-individual differences. Perceived environmental restorativeness and feeling were positively correlated with perceived nature ratings. Qualitative data revealed varying preferences for green vs blue environments and the extent to which traffic noise influenced their perceptions.
Conclusion:
The divergence between app-based and user assessments suggests that such assessments should be calibrated using individualized user feedback, and that careful consideration is needed regarding the level of statistical detail presented to users.

