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  4. To Challenge the Morning Lark and the Night Owl: Using Smartphone Sensing Data to Investigate Day–Night Behaviour Patterns
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To Challenge the Morning Lark and the Night Owl: Using Smartphone Sensing Data to Investigate Day–Night Behaviour Patterns

Journal
European Journal of Personality
Type
journal article
Date Issued
2020
Author(s)
Schoedel, R.
;
Pargent, F.
;
Au, Q.
;
Völkel, S. T.
;
Schuwerk, T.
;
Bühner, M.
;
Stachl, Clemens  
DOI
10.1002/per.2258
Abstract
For decades, day–night patterns in behaviour have been investigated by asking people about their sleep–wake timing, their diurnal activity patterns, and their sleep duration. We demonstrate that the increasing digitalization of lifestyle offers new possibilities for research to investigate day–night patterns and related traits with the help of behavioural data. Using smartphone sensing, we collected in vivo data from 597 participants across several weeks and extracted behavioural day–night pattern indicators. Using this data, we explored three popular research topics. First, we focused on individual differences in day–night patterns by investigating whether ‘morning larks’ and ‘night owls’ manifest in smartphone–sensed behavioural indicators. Second, we examined whether personality traits are related to day–night patterns. Finally, exploring social jetlag, we investigated whether traits and work weekly day–night behaviours influence day–night patterns on weekends. Our findings highlight that behavioural data play an essential role in understanding daily routines and their relations to personality traits. We discuss how psychological research can integrate new behavioural approaches to study personality.
Language
English
Keywords
chronotype
day–night behaviour patterns
diurnal activity
personality
smartphone sensing data
Refereed
Yes
Publisher
SAGE
Volume
34
Number
5
Start page
733
End page
752
Official URL
https://journals.sagepub.com/doi/10.1002/per.2258
URL
https://www.alexandria.unisg.ch/handle/20.500.14171/113090
Subject(s)

computer science

social sciences

behavioral science

Division(s)

IBT - Institute of Be...

Eprints ID
264544
File(s)
Thumbnail Image
Name

per.2258.pdf

Size

5.65 MB

Format

Adobe PDF

Checksum (MD5)

e758ab5c489ae2a15377a5fc62f3cc6b

Support
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