Publikation: Well-being, smartphone sensors, and data from open-access databases : A mobile experience sampling study
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2019
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Field Methods. 2019, 31(3), pp. 277-291. ISSN 1525-822X. eISSN 1552-3969. Available under: doi: 10.1177/1525822X18824281
Zusammenfassung
We investigated fluctuations of well-being by using a smartphone-based mobile experience sampling method (real-time and multiple time point measurements in the field using smartphones). Moreover, temperature, longitude, latitude, altitude, wind speed, rainfall, and further environment-based indicators were included as predictors either from smartphone sensors or from open-access Internet databases. Overall, a total of 213 participants reported on their well-being (over 14 days; three measurements per day; 8,000+ well-being judgments). We were able to replicate and refine past research about the dynamics of well-being fluctuations during the day (low in the morning, high in the evening) and over the course of a week (low just before the beginning of the week, highest near the end of the week). We also show what kind of benefits empirical researchers can gain for their research using smartphones and their built-in sensors by combining these measures with data from open-access databases.
Zusammenfassung in einer weiteren Sprache
Fachgebiet (DDC)
150 Psychologie
Schlagwörter
well-being, experience sampling, smartphone, Internet science, geolocation, methodology
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STIEGER, Stefan, Ulf-Dietrich REIPS, 2019. Well-being, smartphone sensors, and data from open-access databases : A mobile experience sampling study. In: Field Methods. 2019, 31(3), pp. 277-291. ISSN 1525-822X. eISSN 1552-3969. Available under: doi: 10.1177/1525822X18824281BibTex
@article{Stieger2019Wellb-41964,
year={2019},
doi={10.1177/1525822X18824281},
title={Well-being, smartphone sensors, and data from open-access databases : A mobile experience sampling study},
number={3},
volume={31},
issn={1525-822X},
journal={Field Methods},
pages={277--291},
author={Stieger, Stefan and Reips, Ulf-Dietrich}
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<dcterms:abstract>We investigated fluctuations of well-being by using a smartphone-based mobile experience sampling method (real-time and multiple time point measurements in the field using smartphones). Moreover, temperature, longitude, latitude, altitude, wind speed, rainfall, and further environment-based indicators were included as predictors either from smartphone sensors or from open-access Internet databases. Overall, a total of 213 participants reported on their well-being (over 14 days; three measurements per day; 8,000+ well-being judgments). We were able to replicate and refine past research about the dynamics of well-being fluctuations during the day (low in the morning, high in the evening) and over the course of a week (low just before the beginning of the week, highest near the end of the week). We also show what kind of benefits empirical researchers can gain for their research using smartphones and their built-in sensors by combining these measures with data from open-access databases.</dcterms:abstract>
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