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Identifying Indicators of Smartphone Addiction Through User-App Interaction
We introduce a new approach to monitoring the activity of smartphone users based on their physical interactions with the interface. Typical events are taps, scrolling and typing, carried out to interact with apps. As compared to other measures, this directly encapsulates potential problematic physic...
Autores principales: | , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Elsevier Ltd
2019
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6686626/ https://www.ncbi.nlm.nih.gov/pubmed/31582873 http://dx.doi.org/10.1016/j.chb.2019.04.023 |
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author | Noë, Beryl Turner, Liam D. Linden, David E.J. Allen, Stuart M. Winkens, Bjorn Whitaker, Roger M. |
author_facet | Noë, Beryl Turner, Liam D. Linden, David E.J. Allen, Stuart M. Winkens, Bjorn Whitaker, Roger M. |
author_sort | Noë, Beryl |
collection | PubMed |
description | We introduce a new approach to monitoring the activity of smartphone users based on their physical interactions with the interface. Typical events are taps, scrolling and typing, carried out to interact with apps. As compared to other measures, this directly encapsulates potential problematic physical smartphone behaviour as a signal. The approach contrasts against conventions such as self-reporting or timing activity sessions, and it focusses on active rather than passive smartphone activity. Using this alternative method, we collected all user interface interaction events from a sample of 64 participants over a period of 8 weeks, using a bespoke monitoring app called Tymer. User Smartphone Addiction was seen to significantly correlate with high levels of interaction with Lifestyle apps, particularly for female users. Interactions with Social apps in general were also associated with Smartphone Addiction. In particular, user interactions with Snapchat correlated with Smartphone Addiction, represented across all types of interface interaction. This is significant given the widespread usage of Snapchat by teenagers, and we hypothesise that the app's design provides a particularly strong pathway in support of Smartphone Addiction. |
format | Online Article Text |
id | pubmed-6686626 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2019 |
publisher | Elsevier Ltd |
record_format | MEDLINE/PubMed |
spelling | pubmed-66866262019-10-01 Identifying Indicators of Smartphone Addiction Through User-App Interaction Noë, Beryl Turner, Liam D. Linden, David E.J. Allen, Stuart M. Winkens, Bjorn Whitaker, Roger M. Comput Human Behav Article We introduce a new approach to monitoring the activity of smartphone users based on their physical interactions with the interface. Typical events are taps, scrolling and typing, carried out to interact with apps. As compared to other measures, this directly encapsulates potential problematic physical smartphone behaviour as a signal. The approach contrasts against conventions such as self-reporting or timing activity sessions, and it focusses on active rather than passive smartphone activity. Using this alternative method, we collected all user interface interaction events from a sample of 64 participants over a period of 8 weeks, using a bespoke monitoring app called Tymer. User Smartphone Addiction was seen to significantly correlate with high levels of interaction with Lifestyle apps, particularly for female users. Interactions with Social apps in general were also associated with Smartphone Addiction. In particular, user interactions with Snapchat correlated with Smartphone Addiction, represented across all types of interface interaction. This is significant given the widespread usage of Snapchat by teenagers, and we hypothesise that the app's design provides a particularly strong pathway in support of Smartphone Addiction. Elsevier Ltd 2019-10 /pmc/articles/PMC6686626/ /pubmed/31582873 http://dx.doi.org/10.1016/j.chb.2019.04.023 Text en © 2019 The Authors http://creativecommons.org/licenses/by/4.0/ This is an open access article under the CC BY license (http://creativecommons.org/licenses/by/4.0/). |
spellingShingle | Article Noë, Beryl Turner, Liam D. Linden, David E.J. Allen, Stuart M. Winkens, Bjorn Whitaker, Roger M. Identifying Indicators of Smartphone Addiction Through User-App Interaction |
title | Identifying Indicators of Smartphone Addiction Through User-App Interaction |
title_full | Identifying Indicators of Smartphone Addiction Through User-App Interaction |
title_fullStr | Identifying Indicators of Smartphone Addiction Through User-App Interaction |
title_full_unstemmed | Identifying Indicators of Smartphone Addiction Through User-App Interaction |
title_short | Identifying Indicators of Smartphone Addiction Through User-App Interaction |
title_sort | identifying indicators of smartphone addiction through user-app interaction |
topic | Article |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6686626/ https://www.ncbi.nlm.nih.gov/pubmed/31582873 http://dx.doi.org/10.1016/j.chb.2019.04.023 |
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