Abstract
Positioning technologies, such as GPS are widespread in society but are used only sparingly in behavioural science research, e.g., because processing positioning technology data can be cumbersome. The current work attempts to unlock positioning technology potential for behavioural science studies by developing and testing a research tool to analyse GPS tracks. This tool—psyosphere—is published as open-source software, and aims to extract behaviours from GPSs data that are more germane to behavioural research. Two field experiments were conducted to test application of the research tool. During these experiments, participants played a smuggling game, thereby either smuggling tokens representing illicit material past border guards or not. Results suggested that participants varied widely in variables, such as course and speed variability and distance from team members in response to the presence of border guards. Subsequent analyses showed that some of these GPS-derived behavioural variables could be linked to self-reported mental states, such as fear. Although more work needs to be done, the current study demonstrates that psyosphere may enable researchers to conduct behavioural experiments with positioning technology, outside of a laboratory setting.
Highlights
Positioning technologies, such as Global Positioning Systems (GPS), Glonass, and Galileo can be used to determine the position on the globe and to record, for instance, the movement of planes, cars, and individuals (Hofmann-Wellenhof et al, 2007)
The R package psyosphere (Ziepert et al, 2018) analyses GPS data by transforming GPS tracks into descriptive variables, such as speed, direction or distance, that can be analysed with linear regression methods
It is optimised to handle multiple tracks simultaneously and to make comparisons between these tracks. This is done because comparisons between multiple participants with linear regression methods is a typical technique of conducting studies in behavioural science
Summary
Positioning technologies, such as Global Positioning Systems (GPS), Glonass, and Galileo can be used to determine the position on the globe and to record, for instance, the movement of planes, cars, and individuals (Hofmann-Wellenhof et al, 2007). Positioning technologies are omnipresent in mobile devices, such as smart phones, tablets, and laptops, which makes them potentially interesting for the study of behaviour in naturalistic settings It could, for instance, be used to identify people with early warnings signs for depression (Saeb et al, 2015; Palmius et al, 2017), partly or fully replace self-reported diaries in traffic research (Stopher et al, 2002; Wolf, 2006; Bohte and Maat, 2009; Schuessler and Axhausen, 2009), determine how populations behave after a disaster, such as an earthquake (Bengtsson et al, 2011), or to automatically detect active pickpockets in a shopping mall (Bouma et al, 2014). Only a limited number of studies has so far investigated the relationship between psychological variables and positioning
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