Evidence map›Paper›PMID 31582873›Full record

ArticleComputers in human behavior2019

Identifying Indicators of Smartphone Addiction Through User-App Interaction.

Beryl Noë, Liam D Turner, David E J Linden, Stuart M Allen, Bjorn Winkens, Roger M Whitaker

Open access · hybridAbstract read
In one paragraph

Article in Computers in human behavior, 2019. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 26 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
26citing papers in PubMed, 1 pooled it
41.4field-weighted citation impact, top 1% of its field
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

26 citing papers in PubMed, 1 synthesis or guideline pooled it, 130 citations in OpenAlex.

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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

6 authors at 2 institutions in 2 countries.

Beryl NoëSchool of Computer Science and Informatics, Cardiff University, 5 The Parade, CF24 3AA, Cardiff, UK.
Liam D TurnerSchool of Computer Science and Informatics, Cardiff University, 5 The Parade, CF24 3AA, Cardiff, UK.
David E J LindenSchool for Mental Health and Neuroscience, Faculty of Health, Medicine and Life Sciences, Maastricht University, Universiteitssingel 40, 6229 ET Maastricht, the Netherlands.
Stuart M AllenSchool of Computer Science and Informatics, Cardiff University, 5 The Parade, CF24 3AA, Cardiff, UK.
Bjorn WinkensDepartment of Methodology & Statistics, Care and Public Health Research Institute (CAPHRI), Faculty of Health, Medicine and Life Sciences, Maastricht University, Universiteitssingel 40, 6229 ET Maastricht, the Netherlands.
Roger M WhitakerSchool of Computer Science and Informatics, Cardiff University, 5 The Parade, CF24 3AA, Cardiff, UK.
Cardiff University · GBMaastricht University · NL

Funding

Wellcome Trust
6 · The paper itself

Abstract

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.

Indexed as

Device interactionSmartphone addictionSmartphone usageSnapchatSocial mediaUser interface

Identifiers

PMID31582873
PMCPMC6686626
OpenAlexW2944197951

What OpenQuestion holds

Textmetadata
LicenceCC BY
Read underepoch 390

Registered trials

None linked

Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.