Tracking human activity and well-being in natural environments using wearable sensors and experience sampling
Abstract
A growing range of studies have begun to document the health and well-being benefits associated with contact with nature. Most studies rely on generalized self-reports following engagement in the natural environment. The actual in-situ experience during contact with nature, and the environmental features and factors that evoke health benefits have remained relatively unexplored. Smartphones offer a new opportunity to monitor and interact with human subjects during everyday life using techniques such as Experience Sampling Methods (ESM) that involve repeated self-reports of experiences as they occur in-situ. Additionally, embedded sensors in smartphones such as Global Positioning Systems (GPS) and accelerometers can accurately trace human activities. This paper explores how these techniques can be combined to comprehensively explore the perceived health and well-being impacts of contact with nature. Custom software was developed to passively track GPS and accelerometer data, and actively prompt subjects to complete an ESM survey at regular intervals throughout their visit to a provincial park in Ontario, Canada. The ESM survey includes nine scale questions concerning moods and emotions, followed by a series of open-ended experiential questions that subjects provide recorded audio responses to. Pilot test results are used to illustrate the nature, quantity and quality of data obtained. Participant activities were clearly evident from GPS maps, including especially walking, cycling and sedate activities. From the ESM surveys, participants reported an average of 25 words per question, taking an average of 15 s to record them. Further qualitative analysis revealed that participants were willing to provide considerable insights into their experiences and perceived health impacts. The combination of passive and interactive techniques is sure to make larger studies of this type more affordable and less burdensome in the future, further enhancing the ability to understand how contact with nature enhances health and well-being.
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Self-reported duration is likely less accurate than measures obtained from geo-tracking individuals during specific visits or over several days.
“For instance, self-reported duration is likely to be less accurate than measures obtained from geo-tracking individuals during specific visits39, or over several days40, and individuals may have been unsure about, or reluctant to discuss, certain issues which were included as covariates (e.g. long standing illness/disability).”
From Spending at least 120 minutes a week in nature is associated with good health and wellbeing (2019) · cites this paper as [39]
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References 45 · Cited by 110
- Authors
- Doherty, S. T., Lemieux, C. J., & Canally, C.
- Affiliations
- Wilfrid Laurier University (CA)
- Corresponding author
- Doherty, Sean T.
- Venue
- Social Science & Medicine
- Publisher
- Elsevier BV
- Published
- 2014-04
- Volume
- 106
- Pages
- 83-92
- ISSN
- 0277-9536 (ISSN-L)
- OpenAlex
- W2036358912
- Cited by
- 110
- References
- 45
- Citations by year
- 2026: 4 · 2025: 7 · 2024: 9 · 2023: 8 · 2022: 7 · 2021: 12 · 2020: 8 · 2019: 16 · 2018: 12 · 2017: 10 · 2016: 8 · 2015: 6 · 2014: 3
- FWCI
- 5.93
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Social Science & Medicine (publishedVersion)
- PubMed (publishedVersion)
- RePEc: Research Papers in Economics (submittedVersion)
- Funders
- Natural Sciences and Engineering Research Council of Canada
- University of Waterloo Research Incentive Fund
- Topics
- Physical Sciences › Environmental Science › Health, Toxicology and Mutagenesis › Urban Green Space and Health
- Social Sciences › Psychology › Experimental and Cognitive Psychology › Mental Health Research Topics
- Physical Sciences › Computer Science › Human-Computer Interaction › Innovative Human-Technology Interaction
- Keywords
- nature exposure, well-being, human activity monitoring, wearable sensors, ecological momentary assessment, accelerometer data, mood and emotions, passive data collection
- MeSH terms
- Adult, Environment Design, Female, Health Status, Humans, Male, Middle Aged, Motor Activity, Ontario, Personal Satisfaction, Pilot Projects, Monitoring, Ambulatory, Qualitative Research, Geographic Information Systems, Cell Phone, Young Adult, Accelerometry
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