Deviations from typical paths: a novel approach to working with GPS data in the behavioral sciences.

Area of Science:

• Behavioral Science
• Geospatial Analysis
• Data Science

Background:

• Behavioral science increasingly uses detailed location data (e.g., GPS tracking) due to lower costs.
• Traditional methods focus on individual differences, limiting the study of lived experience variability.
• Novel methods are needed to quantify behavior from location data, considering context and intraindividual variability.

Purpose of the Study:

• Introduce a novel data processing technique: deviations from typical paths.
• Separate typical travel behavior from location data to identify atypical behavior.
• Provide a new outcome measure for behavioral variability.

Main Methods:

• Propose 'deviations from typical paths' as a data processing technique.
• Apply the method to location tracking datasets.
• Utilize simulated data to demonstrate the technique's functionality.

Main Results:

• The method quantifies deviation measures from location data.
• Analysis of deviations provides insights beyond traditional measures (e.g., max distance from home).
• Demonstrates how the technique highlights atypical travel behavior.

Conclusions:

• The 'deviations from typical paths' method can reveal atypical behavior.
• This approach can be integrated into research on behavior change predictors and mechanisms.
• Enables deeper understanding of intraindividual variability in lived experiences.