Validity of a Global Positioning System-Based Algorithm and Consumer Wearables for Classifying Active Trips in Children and Adults

in Journal for the Measurement of Physical Behaviour

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Chelsea SteelCenter for Children’s Healthy Lifestyles & Nutrition, Children’s Mercy Hospital, Kansas City, MO, USA

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Katie CristDepartment of Family Medicine, University of California, San Diego, La Jolla, CA, USA

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Amanda GrimesSchool of Nursing and Health Studies, University of Missouri-Kansas City, Kansas City, MO, USA

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Carolina BejaranoClinical Child Psychology Program, University of Kansas, Lawrence, KS, USA

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Adrian OrtegaClinical Child Psychology Program, University of Kansas, Lawrence, KS, USA

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Paul R. HibbingCenter for Children’s Healthy Lifestyles & Nutrition, Children’s Mercy Hospital, Kansas City, MO, USA

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Jasper SchipperijnDepartment of Sport Sciences and Clinical Biomechanics, University of Southern Denmark, Odense, Denmark

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Jordan A. CarlsonCenter for Children’s Healthy Lifestyles & Nutrition, Children’s Mercy Hospital, Kansas City, MO, USA
Department of Pediatrics, Children’s Mercy Hospital, University of Missouri Kansas City, Kansas City, MO, USA

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DOI:
https://doi.org/10.1123/jmpb.2021-0019
Keywords:
cycling; fitbit; Garmin; transportation; walking
First Published Online:
25 Oct 2021
In Print:
Volume 4: Issue 4
Page Range:
321–332
Restricted access

Objective: To investigate the convergent validity of a global positioning system (GPS)-based and two consumer-based measures with trip logs for classifying pedestrian, cycling, and vehicle trips in children and adults. Methods: Participants (N = 34) wore a Qstarz GPS tracker, Fitbit Alta, and Garmin vivosmart 3 on multiple days and logged their outdoor pedestrian, cycling, and vehicle trips. Logged trips were compared with device-measured trips using the Personal Activity Location Measurement System (PALMS) GPS-based algorithms, Fitbit’s SmartTrack, and Garmin’s Move IQ. Trip- and day-level agreement were tested. Results: The PALMS identified and correctly classified the mode of 75.6%, 94.5%, and 96.9% of pedestrian, cycling, and vehicle trips (84.5% of active trips, F1 = 0.84 and 0.87) as compared with the log. Fitbit and Garmin identified and correctly classified the mode of 26.8% and 17.8% (22.6% of active trips, F1 = 0.40 and 0.30) and 46.3% and 43.8% (45.2% of active trips, F1 = 0.58 and 0.59) of pedestrian and cycling trips. Garmin was more prone to false positives (false trips not logged). Day-level agreement for PALMS and Garmin versus logs was favorable across trip modes, though PALMS performed best. Fitbit significantly underestimated daily cycling. Results were similar but slightly less favorable for children than adults. Conclusions: The PALMS showed good convergent validity in children and adults and were about 50% and 27% more accurate than Fitbit and Garmin (based on F1). Empirically-based recommendations for improving PALMS’ pedestrian classification are provided. Since the consumer devices capture both indoor and outdoor walking/running and cycling, they are less appropriate for trip-based research.

Carlson (jacarlson@cmh.edu) is corresponding author, https://orcid.org/0000-0002-6008-7983

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