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

BACKGROUND: Behavioral science researchers are increasingly collecting detailed location data such as second-by-second GPS tracking on participants due to increased ease and affordability. While intraindividual variability has been discussed in the travel literature for decades, traditional methods...

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Autores principales: Nielsen, Karen E., Mejía, Shannon T., Gonzalez, Richard
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9206293/
https://www.ncbi.nlm.nih.gov/pubmed/35717204
http://dx.doi.org/10.1186/s12942-022-00305-4
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author Nielsen, Karen E.
Mejía, Shannon T.
Gonzalez, Richard
author_facet Nielsen, Karen E.
Mejía, Shannon T.
Gonzalez, Richard
author_sort Nielsen, Karen E.
collection PubMed
description BACKGROUND: Behavioral science researchers are increasingly collecting detailed location data such as second-by-second GPS tracking on participants due to increased ease and affordability. While intraindividual variability has been discussed in the travel literature for decades, traditional methods designed for studying individual differences in central tendencies limit the extent to which novel questions about variability in lived experiences can be answered. Thus, new methods of quantifying behavior that focus on intraindividual variability are needed to address the context in which the behavior occurs and the location tracking data from which behavior is derived. METHODS: We propose deviations from typical paths as a data processing technique to separate individual-level typical travel behavior from a location tracking data set in order to highlight atypical travel behavior as an outcome measure. RESULTS: A simulated data example shows how the method works to produce deviation measures from a location dataset. Analysis of these deviations offers additional insights compared to traditional measures of maximum daily distance from home. CONCLUSIONS: This process can be integrated into larger research questions to explore predictors of atypical behavior and potential mechanisms of behavior change. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12942-022-00305-4.
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spelling pubmed-92062932022-06-19 Deviations from typical paths: a novel approach to working with GPS data in the behavioral sciences Nielsen, Karen E. Mejía, Shannon T. Gonzalez, Richard Int J Health Geogr Methodology BACKGROUND: Behavioral science researchers are increasingly collecting detailed location data such as second-by-second GPS tracking on participants due to increased ease and affordability. While intraindividual variability has been discussed in the travel literature for decades, traditional methods designed for studying individual differences in central tendencies limit the extent to which novel questions about variability in lived experiences can be answered. Thus, new methods of quantifying behavior that focus on intraindividual variability are needed to address the context in which the behavior occurs and the location tracking data from which behavior is derived. METHODS: We propose deviations from typical paths as a data processing technique to separate individual-level typical travel behavior from a location tracking data set in order to highlight atypical travel behavior as an outcome measure. RESULTS: A simulated data example shows how the method works to produce deviation measures from a location dataset. Analysis of these deviations offers additional insights compared to traditional measures of maximum daily distance from home. CONCLUSIONS: This process can be integrated into larger research questions to explore predictors of atypical behavior and potential mechanisms of behavior change. SUPPLEMENTARY INFORMATION: The online version contains supplementary material available at 10.1186/s12942-022-00305-4. BioMed Central 2022-06-18 /pmc/articles/PMC9206293/ /pubmed/35717204 http://dx.doi.org/10.1186/s12942-022-00305-4 Text en © The Author(s) 2022 https://creativecommons.org/licenses/by/4.0/Open AccessThis article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons licence, and indicate if changes were made. The images or other third party material in this article are included in the article's Creative Commons licence, unless indicated otherwise in a credit line to the material. If material is not included in the article's Creative Commons licence and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this licence, visit http://creativecommons.org/licenses/by/4.0/ (https://creativecommons.org/licenses/by/4.0/) . The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/ (https://creativecommons.org/publicdomain/zero/1.0/) ) applies to the data made available in this article, unless otherwise stated in a credit line to the data.
spellingShingle Methodology
Nielsen, Karen E.
Mejía, Shannon T.
Gonzalez, Richard
Deviations from typical paths: a novel approach to working with GPS data in the behavioral sciences
title Deviations from typical paths: a novel approach to working with GPS data in the behavioral sciences
title_full Deviations from typical paths: a novel approach to working with GPS data in the behavioral sciences
title_fullStr Deviations from typical paths: a novel approach to working with GPS data in the behavioral sciences
title_full_unstemmed Deviations from typical paths: a novel approach to working with GPS data in the behavioral sciences
title_short Deviations from typical paths: a novel approach to working with GPS data in the behavioral sciences
title_sort deviations from typical paths: a novel approach to working with gps data in the behavioral sciences
topic Methodology
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9206293/
https://www.ncbi.nlm.nih.gov/pubmed/35717204
http://dx.doi.org/10.1186/s12942-022-00305-4
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