Repository logo
Research Outputs
Projects
People
Statistics
  1. Home
  2. HSG CRIS
  3. HSG Publications
  4. Personality traits predict smartphone usage
Details

Personality traits predict smartphone usage

Journal
European Journal of Personality
Type
journal article
Date Issued
2017
Author(s)
Stachl, Clemens  
;
Hilbert, S.
;
Au, J.-Q.
;
Buschek, D.
;
De Luca, A.
;
Bischl, B
;
Hussmann, H.
;
Bühner, M.
DOI
10.1002/per.2113
Abstract (De)
The present study investigates to what degree individual differences can predict frequency and duration of actual behaviour, manifested in mobile application (app) usage on smartphones. In particular, this work focuses on the identification of stable associations between personality on the factor and facet level, fluid intelligence, demography and app usage in 16 distinct categories. A total of 137 subjects (87 women and 50 men), with an average age of 24 (SD = 4.72), participated in a 90–min psychometric lab session as well as in a subsequent 60–day data logging study in the field. Our data suggest that personality traits predict mobile application usage in several specific categories such as communication, photography, gaming, transportation and entertainment. Extraversion, conscientiousness and agreeableness are better predictors of mobile application usage than basic demographic variables in several distinct categories. Furthermore, predictive performance is slightly higher for single factor—in comparison with facet–level personality scores. Fluid intelligence and demographics additionally show stable associations with categorical app usage. In sum, this study demonstrates how individual differences can be effectively related to actual behaviour and how this can assist in understanding the behavioural underpinnings of personality. Copyright © 2017 European Association of Personality Psychology
Language
English
Keywords
Big Five
factor and facets
behaviour
smartphones
app usage
Refereed
Yes
Publisher
SAGE
Volume
31
Number
6
Start page
701
End page
722
Official URL
https://doi.org/10.1002/per.2113
URL
https://www.alexandria.unisg.ch/handle/20.500.14171/103486
Subject(s)

computer science

social sciences

behavioral science

Division(s)

IBT - Institute of Be...

Eprints ID
264555
File(s)
Thumbnail Image
Name

per.2113.pdf

Size

201.86 KB

Format

Adobe PDF

Checksum (MD5)

b11f29f232b59aacf2ae6996ccbd426d

Support
HSG researchers can find instructions here for adding or importing publications (DOI, ORCID). Please send questions to alexandria@unisg.ch

Built with DSpace-CRIS software - Extension maintained and optimized by 4Science

  • Accessibility settings
  • Privacy policy
  • End User Agreement
  • Send Feedback
Repository logo COAR Notify