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Determining typical smartphone usage: What data do we need?

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journal contribution
posted on 03.04.2019, 14:28 by Thom WilcocksonThom Wilcockson, David A. Ellis, Heather Shaw
Problematic smartphone use is an emerging issue in behavioral addiction research. At the same time, measuring smartphone use with mobile apps has become increasingly common. However, understanding how much data are necessary requires careful consideration if the field is to move forward. Here, we examine how much time should be spent measuring mobile phone operation to reliably infer general patterns of usage and repetitive checking behaviors. In a second analysis, we consider whether a self-report measure of problematic smartphone use is associated with real-time patterns of use. Results suggest that smartphone usage collected for a minimum of 5 days will reflect typical weekly usage (in hours), but habitual checking behaviors (uses lasting <15 seconds) can be reliably inferred within 2 days. These measurements did not reliably correlate with a self-reported measure. We conclude that patterns of smartphone use are repetitive and our results suggest that checking behavior is a particularly consistent and efficient measure when quantifying typical and problematic smartphone usage.

Funding

This work was partially funded by a Faculty of Science and Technology research grant (PSA7866) from Lancaster University, and by a Research Investment Fund (RIF2014-31) from the University of Lincoln.

History

School

  • Sport, Exercise and Health Sciences

Published in

Cyberpsychology, Behavior, and Social Networking

Volume

21

Issue

6

Pages

395 - 398

Citation

WILCOCKSON, T.D.W., ELLIS, D.A. and SHAW, H., 2018. Determining typical smartphone usage: What data do we need?. Cyberpsychology, Behavior, and Social Networking, 21 (6), pp.395-398.

Publisher

© Mary Ann Liebert, Inc.

Version

AM (Accepted Manuscript)

Publisher statement

This work is made available according to the conditions of the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International (CC BY-NC-ND 4.0) licence. Full details of this licence are available at: https://creativecommons.org/licenses/by-nc-nd/4.0/

Acceptance date

01/06/2018

Publication date

2018-06-01

Notes

Final publication is available from Mary Ann Liebert, Inc., publishers https://doi.org/10.1089/cyber.2017.0652

ISSN

2152-2715

eISSN

2152-2723

Language

en