Skip to main content

Advertisement

SpringerLink
Log in

Exploring the relationship between personality structure and smartphone usage

  • Published:
Current Psychology Aims and scope Submit manuscript

Abstract

This study aimed to investigate the relationship between personality dispositions and actual and observed behavior expressed through several smartphone apps categories (relying on a built-in function of the smartphone, the app usage from the battery information menu), as well as to investigate the association between personality traits and the number of installed apps per category. The research sample consisted of 341 participants that monitored their app usage. In addition, participants completed measures related to personality structure (Big Five, HEXACO, and the Dark Triad). The findings of the study showed that personality dispositions predicted smartphone apps usage in various categories such as entertainment apps, music apps, gaming apps, business apps, e-health apps, and dating apps. In conclusion, this study showed that actual behavior expressed through various app categories is associated with broad and important personality dimensions. The findings of this research can be useful in integrating actual behavior in psychological research.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Similar content being viewed by others

References

  • Andrews, S., Ellis, D. A., Shaw, H., & Piwek, L. (2015). Beyond self-report: Tools to compare estimated and real-world smartphone use. PLoS One, 10(10).

  • Avram, E., Burtaverde, V., & Zanfirescu, A. Ș. (2019). The incremental validity of career adaptability in predicting academic performance. Social Psychology of Education, 1–16.

  • Arpaci, I. (2018). The moderating effect of gender in the relationship between narcissism and selfie-posting behavior. Personality and Individual Differences, 134, 71–74.

    Google Scholar 

  • Arpaci, I., Baloğlu, M., & Kesici, Ş. (2018). The relationship among individual differences in individualism-collectivism, extraversion, and self-presentation. Personality and Individual Differences, 121, 89–92.

    Google Scholar 

  • Ashton, M. C., & Lee, K. (2009). The HEXACO–60: A short measure of the major dimensions of personality. Journal of Personality Assessment, 91(4), 340–345.

    PubMed  Google Scholar 

  • Barrick, M. R., & Mount, M. K. (1991). The big five personality dimensions and job performance: A meta-analysis. Personnel Psychology, 44(1), 1–26.

    Google Scholar 

  • Bass, B. M. (1999). Two decades of research and development in transformational leadership. European Journal of Work and Organizational Psychology, 8(1), 9–32.

    Google Scholar 

  • Baumeister, R. F., Vohs, K. D., & Funder, D. C. (2007). Psychology as the science of self-reports and finger movements: Whatever happened to actual behavior? Perspectives on Psychological Science, 2(4), 396–403.

    PubMed  Google Scholar 

  • Burtăverde, V., & De Raad, B. (2019). Taxonomy and structure of the Romanian personality lexicon. International Journal of Psychology, 54(3), 377–387.

  • Burtăverde, V., Chraif, M., Aniţei, M., & Mihăilă, T. (2016). The incremental validity of the dark triad in predicting driving aggression. Accident Analysis & Prevention, 96, 1–11.

    Google Scholar 

  • Butt, S., & Phillips, J. G. (2008). Personality and self-reported mobile phone use. Computers in Human Behavior, 24(2), 346–360.

    Google Scholar 

  • Chittaranjan, G., Blom, J., & Gatica-Perez, D. (2013). Mining large-scale smartphone data for personality studies. Personal and Ubiquitous Computing, 17(3), 433–450.

    Google Scholar 

  • de Montjoye, Y. A., Quoidbach, J., Robic, F., & Pentland, A. S. (2013). Predicting personality using novel mobile phone-based metrics. In International Conference on Social Computing, behavioral-cultural modeling, and prediction (pp. 48–55). Springer, Berlin, Heidelberg.

  • Dunning, D., Heath, C., & Suls, J. M. (2005). Picture imperfect. Scientific American Mind, 16(4), 20–27.

    Google Scholar 

  • Elhai, J. D., Dvorak, R. D., Levine, J. C., & Hall, B. J. (2017). Problematic smartphone use: A conceptual overview and systematic review of relations with anxiety and depression psychopathology. Journal of Affective Disorders, 207, 251–259.

    PubMed  Google Scholar 

  • Elhai, J. D., Tiamiyu, M. F., Weeks, J. W., Levine, J. C., Picard, K. J., & Hall, B. J. (2018a). Depression and emotion regulation predict objective smartphone use measured over one week. Personality and Individual Differences, 133, 21–28.

    Google Scholar 

  • Elhai, J. D., Levine, J. C., O'Brien, K. D., & Armour, C. (2018b). Distress tolerance and mindfulness mediate relations between depression and anxiety sensitivity with problematic smartphone use. Computers in Human Behavior, 84, 477–484.

    Google Scholar 

  • Elhai, J. D., Rozgonjuk, D., Yildirim, C., Alghraibeh, A. M., & Alafnan, A. A. (2019). Worry and anger are associated with latent classes of problematic smartphone use severity among college students. Journal of Affective Disorders, 246, 209–216.

    PubMed  Google Scholar 

  • Ellis, D. A., Davidson, B. I., Shaw, H., & Geyer, K. (2019). Do smartphone usage scales predict behavior? International Journal of Human-Computer Studies, 130, 86–92.

    Google Scholar 

  • Furr, R. M. (2009). Personality psychology as a truly behavioural science. European Journal of Personality: Published for the European Association of Personality Psychology, 23(5), 369–401.

    Google Scholar 

  • Goldberg, L. R. (1990). An alternative “description of personality”: The big-five factor structure. Journal of Personality and Social Psychology, 59(6), 1216.

    PubMed  Google Scholar 

  • Gosling, S. D., & Mason, W. (2015). Internet research in psychology. Annual Review of Psychology, 66, 877–902.

    PubMed  Google Scholar 

  • Gosling, S. D., Rentfrow, P. J., & Swann Jr., W. B. (2003). A very brief measure of the big-five personality domains. Journal of Research in Personality, 37(6), 504–528.

    Google Scholar 

  • Gower, A. D., & Moreno, M. A. (2018). A novel approach to evaluating mobile smartphone screen time for iPhones: feasibility and preliminary findings. JMIR mHealth and uHealth, 6(11), e11012. 

  • Haladyna, T. M., & Downing, S. M. (2004). Construct-irrelevant variance in high-stakes testing. Educational Measurement: Issues and Practice, 23(1), 17–27.

    Google Scholar 

  • Hare, R. D. (1991). The Hare Psychopathy Checklist—Revised manual. Toronto, Ontario, Canada: Multi-Health Systems.

  • Horwood, S., & Anglim, J. (2018). Personality and problematic smartphone use: A facet-level analysis using the five factor model and HEXACO frameworks. Computers in Human Behavior, 85, 349–359.

    Google Scholar 

  • John, O. P., Naumann, L. P., & Soto, C. J. (2008). Paradigm shift to the integrative big five trait taxonomy: History, measurement, and conceptual issues. In O. P. John, R. W. Robins, & L. A. Pervin (Eds.), Handbook of personality. Theory and research (3rd ed., pp. 114–158). New York: The Guilford Press.

    Google Scholar 

  • Jonason, P. K., Li, N. P., Webster, G. D., & Schmitt, D. P. (2009). The dark triad: Facilitating a short-term mating strategy in men. European Journal of Personality: Published for the European Association of Personality Psychology, 23(1), 5–18.

    Google Scholar 

  • Jones, D. N., & Paulhus, D. L. (2014). Introducing the short dark triad (SD3) a brief measure of dark personality traits. Assessment, 21(1), 28–41.

    PubMed  Google Scholar 

  • Kim, Y., Briley, D. A., & Ocepek, M. G. (2015). Differential innovation of smartphone and application use by sociodemographics and personality. Computers in Human Behavior, 44, 141–147.

    Google Scholar 

  • Lane, W., & Manner, C. (2011). The impact of personality traits on smartphone ownership and use. International Journal of Business and Social Science, 2, 22–28.  

  • Lee, K., & Ashton, M. C. (2014). The dark triad, the big five, and the HEXACO model. Personality and Individual Differences, 67, 2–5.

  • Lee, K., Ashton, M. C., Wiltshire, J., Bourdage, J. S., Visser, B. A., & Gallucci, A. (2013). Sex, power, and money: Prediction from the dark triad and honesty–humility. European Journal of Personality, 27(2), 169–184.

    Google Scholar 

  • Lievens, F., De Corte, W., & Schollaert, E. (2008). A closer look at the frame-of-reference effect in personality scale scores and validity. Journal of Applied Psychology, 93(2), 268.

    Google Scholar 

  • McElroy, J., Hendrickson, A., Townsend, A., & DeMarie, S. (2007). Dispositional factors in internet use: Personality versus cognitive style. MIS Quarterly, 31(4), 809–820.

    Google Scholar 

  • Mehl, M. R., Gosling, S. D., & Pennebaker, J. W. (2006). Personality in its natural habitat: Manifestations and implicit folk theories of personality in daily life. Journal of Personality and Social Psychology, 90, 862–877.

    PubMed  Google Scholar 

  • Montag, C., Błaszkiewicz, K., Sariyska, R., Lachmann, B., Andone, I., Trendafilov, B., ... & Markowetz, A. (2015). Smartphone usage in the 21st century: who is active on WhatsApp?. BMC research notes, 8(1), 331.

  • Moore, K., & McElroy, J. C. (2012). The influence of personality on Facebook usage, wall postings, and regret. Computers in Human Behavior, 28(1), 267–274.

    Google Scholar 

  • Morgeson, F. P., Campion, M. A., Dipboye, R. L., Hollenbeck, J. R., Murphy, K., & Schmitt, N. (2007). Are we getting fooled again? Coming to terms with limitations in the use of personality tests for personnel selection. Personnel Psychology, 60(4), 1029–1049.

    Google Scholar 

  • Özteke Kozan, H. İ., Baloğlu, M., Kesici, Ş., & Arpacı, İ. (2019). The role of personality and psychological needs on the problematic internet use and problematic social media use. Addicta: The Turkish Journal on Addictions, 6(2), 203–219.

    Google Scholar 

  • Paulhus, D. L., & Vazire, S. (2007). The self-report method. In R. R. Robins, R. C. Fraley, & R. F. Krueger (Eds.), Handbook of research methods in personality psychology (pp. 224–239). New York: The Guilford Press.

    Google Scholar 

  • Paulhus, D. L., & Williams, K. M. (2002). The dark triad of personality: Narcissism, Machiavellianism, and psychopathy. Journal of Research in Personality, 36(6), 556–563.

    Google Scholar 

  • Paulhus, D. L., Curtis, S. R., & Jones, D. N. (2018). Aggression as a trait: the Dark Tetrad alternative. Current opinion in psychology, 19, 88–92.

  • Plutchik, R., Kellerman, H., & Conte, H. R. (1979). A structural theory of ego defenses and emotions. In C. Izard (Ed.), Emotions in personality and psychopathology (pp. 227–257). Boston: Springer.

    Google Scholar 

  • Roberts, B. W., Walton, K. E., & Bogg, T. (2005). Conscientiousness and health across the life course. Review of General Psychology, 9(2), 156.

    Google Scholar 

  • Rozgonjuk, D., & Elhai, J. D. (2019). Emotion regulation in relation to smartphone use: Process smartphone use mediates the association between expressive suppression and problematic smartphone use. Current Psychology, 1–10. 

  • Rozgonjuk, D., Kattago, M., & Täht, K. (2018a). Social media use in lectures mediates the relationship between procrastination and problematic smartphone use. Computers in Human Behavior, 89, 191–198.

    Google Scholar 

  • Rozgonjuk, D., Levine, J. C., Hall, B. J., & Elhai, J. D. (2018b). The association between problematic smartphone use, depression and anxiety symptom severity, and objectively measured smartphone use over one week. Computers in Human Behavior, 87, 10–17.

    Google Scholar 

  • Rozgonjuk, D., Elhai, J. D., Täht, K., Vassil, K., Levine, J. C., & Asmundson, G. J. G. (2019). Non-social smartphone use mediates the relationship between intolerance of uncertainty and problematic smartphone use: Evidence from a repeated-measures study. Computers in Human Behavior. https://doi.org/10.1016/j.chb.2019.02.013.

  • Saucier, G., Thalmayer, A. G., & Bel-Bahar, T. S. (2014). Human attribute concepts: Relative ubiquity across twelve mutually isolated languages. Journal of Personality and Social Psychology, 107, 199–216.

    PubMed  Google Scholar 

  • Schmitt, D. P., & Shackelford, T. K. (2008). Big five traits related to short-term mating: From personality to promiscuity across 46 nations. Evolutionary Psychology, 6(2), 246–282.

    Google Scholar 

  • Stachl, C., Hilbert, S., Au, J. Q., Buschek, D., De Luca, A., Bischl, B., et al. (2017). Personality traits predict smartphone usage. European Journal of Personality, 31(6), 701–722.

    Google Scholar 

  • Statistia (2018). Number of available applications in the Google Play Store from December 2009 to September 2018. Retrieved from https://www.statista.com/statistics/266210/number-of-available-applications-in-thegoogle-play-store/. Accessed 01/03/2019. 

  • Vazire, S. (2010). Who knows what about a person? The self–other knowledge asymmetry (SOKA) model. Journal of Personality and Social Psychology, 98(2), 281.

    PubMed  Google Scholar 

  • Veselka, L., Schermer, J. A., Petrides, K. V., Cherkas, L. F., Spector, T. D., & Vernon, P. A. (2009). A general factor of personality: Evidence from the HEXACO model and a measure of trait emotional intelligence. Twin Research and Human Genetics, 12(5), 420–424.

    PubMed  Google Scholar 

  • Wilcockson, T. D. W., Ellis, D. A., & Shaw, H. (2018). Determining typical smartphone usage: What data do we need? Cyberpsychology, Behavior and Social Networking, 21(6), 395–398.

    PubMed  Google Scholar 

  • Xu, R., Frey, R. M., Fleisch, E., & Ilic, A. (2016). Understanding the impact of personality traits on mobile app adoption–insights from a large-scale field study. Computers in Human Behavior, 62, 244–256.

    Google Scholar 

  • Yarkoni, T. (2010). Personality in 100,000 words: A large-scale analysis of personality and word use among bloggers. Journal of Research in Personality, 44, 363–373.

    PubMed  PubMed Central  Google Scholar 

  • Yarkoni, T. (2012). Psychoinformatics: New horizons at the interface of the psychological and computing sciences. Current Directions in Psychological Science, 21(6), 391–397.

    Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Psychology and Educational Sciences, University of Bucharest, Bucharest, Romania

    Vlad Burtăverde, Sebastian Vlăsceanu & Eugen Avram

Authors
  1. Vlad Burtăverde
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Sebastian Vlăsceanu
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Eugen Avram
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Vlad Burtăverde.

Ethics declarations

Conflict of Interest

The authors have no conflicts of interest.

Ethical Approval

The research was approved by the ethical committee of University of Bucharest.

Additional information

Publisher’s note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Burtăverde, V., Vlăsceanu, S. & Avram, E. Exploring the relationship between personality structure and smartphone usage. Curr Psychol 40, 5613–5625 (2021). https://doi.org/10.1007/s12144-019-00521-5

Download citation

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12144-019-00521-5

Keywords

Search

Navigation