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A comparison of temporal and location-based sampling strategies for GPS-triggered electronic diaries

Törnros, Tobias; Dorn, Helen; Reichert, M.; Ebner-Priemer, Ulrich W.; Salize, Hans-Joachim; Tost, H.,; Meyer-Lindenberg, Andreas; Zipf, A

Self-reporting is a well-established approach within the medical and psychological sciences. In order to avoid recall bias, i.e. past events being remembered inaccurately, the reports can be filled out on a smartphone in real-time and in the natural environment. This is often referred to as ambulatory assessment and the reports are usually triggered at regular time intervals. With this sampling scheme, however, rare events (e.g. a visit to a park or recreation area) are likely to be missed. When addressing the correlation between mood and the environment, it may therefore be beneficial to include participant locations within the ambulatory assessment sampling scheme. Based on the geographical coordinates, the database query system then decides if a self-report should be triggered or not. We simulated four different ambulatory assessment sampling schemes based on movement data (coordinates by minute) from 143 voluntary participants tracked for seven consecutive days. Two location-based sampling schemes incorporating the environmental characteristics (land use and population density) at each participant’s location were introduced and compared to a time-based sampling scheme triggering a report on the hour as well as to a sampling scheme incorporating physical activity. ... mehr

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Volltext §
DOI: 10.5445/IR/1000056262
DOI: 10.4081/gh.2016.473
Zitationen: 11
Web of Science
Zitationen: 13
Zitationen: 13
Cover der Publikation
Zugehörige Institution(en) am KIT Institut für Sport und Sportwissenschaft (IfSS)
Publikationstyp Zeitschriftenaufsatz
Publikationsjahr 2016
Sprache Englisch
Identifikator ISSN: 1827-1987, 1970-7096
KITopen-ID: 1000056262
Erschienen in Geospatial health
Verlag PAGEpress
Band 11
Heft 3
Seiten 335-341
Schlagwörter Ambulatory assessment, Ecological momentary assessment, Experience sampling method, Natural surroundings; GIScience.
Nachgewiesen in Web of Science
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