Beyond Self-Report: Tools to Compare Estimated and Real-World Smartphone Use.

Sally Andrews,Lukasz Piwek,Heather Shaw,David A Ellis,Jakob Pietschnig

doi:10.1371/journal.pone.0139004

Abstract

Psychologists typically rely on self-report data when quantifying mobile phone usage, despite little evidence of its validity. In this paper we explore the accuracy of using self-reported estimates when compared with actual smartphone use. We also include source code to process and visualise these data. We compared 23 participants’ actual smartphone use over a two-week period with self-reported estimates and the Mobile Phone Problem Use Scale. Our results indicate that estimated time spent using a smartphone may be an adequate measure of use, unless a greater resolution of data are required. Estimates concerning the number of times an individual used their phone across a typical day did not correlate with actual smartphone use. Neither estimated duration nor number of uses correlated with the Mobile Phone Problem Use Scale. We conclude that estimated smartphone use should be interpreted with caution in psychological research.

Highlights

Around 2 billion people use smartphones across the globe, with over half the population in developed countries relying on them daily [1]. This ubiquity means that there is the potential for objective smartphone data to be used to address research questions in the real world [2]
Smartphones themselves have yet to become a standard item in the psychologist’s research toolbox, and little is known about the validity of self-reported estimates of smartphone use
We explore the claim that people engage in habitual smartphone checking behaviours, by correlating self-report smartphone use estimates with actual smartphone use and standardised measures of problem mobile phone use [14]

Summary

Introduction

Around 2 billion people use smartphones across the globe, with over half the population in developed countries relying on them daily [1]. This ubiquity means that there is the potential for objective smartphone data to be used to address research questions in the real world [2]. Perhaps the biggest barrier to exploring the objective (actual) use of smartphone data includes developing suitable apps and the appropriate tools for processing, analysing and visualising big-data sets [10]. Whereas open source software to create Android apps is freely available for those with no programming experience [11], there remains no open source software for analysing and visualising the resulting data

Methods

Results

Conclusion