Personality Traits Predict Smartphone Usage

被引:86
作者
Stachl, Clemens [1 ]
Hilbert, Sven [1 ,2 ]
Au, Jiew-Quay [3 ]
Buschek, Daniel [4 ]
De Luca, Alexander [4 ]
Bischl, Bernd [3 ]
Hussmann, Heinrich [4 ]
Buehner, Markus [1 ]
机构
[1] Ludwig Maximilians Univ Munchen, Dept Psychol, Psychol Methods & Assessment, D-80802 Munich, Germany
[2] Univ Regensburg, Fac Psychol Educ Sci & Sport Sci, Munich, Germany
[3] Ludwig Maximilians Univ Munchen, Computat Stat, Dept Stat, Munich, Germany
[4] Ludwig Maximilians Univ Munchen, Media Informat Grp, Munich, Germany
关键词
Big Five; factor and facets; behaviour; smartphones; app usage; GENDER; PSYCHOLOGY; BEHAVIOR; FACETS; CONSEQUENCES; INTELLIGENCE; INFORMATION; NEUROTICISM; TECHNOLOGY; DEPRESSION;
D O I
10.1002/per.2113
中图分类号
B84 [心理学];
学科分类号
04 ; 0402 ;
摘要
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 factorin 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 (c) 2017 European Association of Personality Psychology
引用
收藏
页码:701 / 722
页数:22
相关论文
共 91 条
  • [1] Individual differences in Internet usage motives
    Amiel, T
    Sargent, SL
    [J]. COMPUTERS IN HUMAN BEHAVIOR, 2004, 20 (06) : 711 - 726
  • [2] Incremental criterion prediction of personality facets over factors: Obtaining unbiased estimates and confidence intervals
    Anglim, Jeromy
    Grant, Sharon L.
    [J]. JOURNAL OF RESEARCH IN PERSONALITY, 2014, 53 : 148 - 157
  • [3] [Anonymous], 2016, NUMB APPS AV LEAD AP
  • [4] [Anonymous], 2005, Educational and Psychological Measurement, DOI [10.1177/0013164404272507, DOI 10.1177/0013164404272507]
  • [5] [Anonymous], CURRENT DIRECTIONS P, DOI DOI 10.1177/0963721414560811
  • [6] [Anonymous], 2016, R FOUND STAT COMPUT
  • [7] [Anonymous], 2021, RTS RATER TIME SERIE
  • [8] [Anonymous], 1992, Psychological Assessment, DOI DOI 10.1037/1040-3590.4.1.5
  • [9] [Anonymous], 2020, MANUAL INTELLIGENCE
  • [10] Arendasy M, 2009, BFSI: Big-Five Struktur-Inventar (Test& Manual)