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Research Report

Telecommunications Network Measurements of Online Gambling Behavior in Switzerland: A Feasibility Study

Bitar R.a · Nordt C.a · Grosshans M.b · Herdener M.a · Seifritz E.a · Mutschler J.a, c

Author affiliations

aCenter for Addictive Disorders, Department of Psychiatry, Psychotherapy and Psychosomatics, Psychiatric Hospital, University of Zurich, Zürich, bDepartment of Addictive Behaviour and Addiction Medicine, Central Institute of Mental Health Mannheim, University of Heidelberg/Medical Faculty Mannheim, Mannheim, Germany; cPrivatklinik Meiringen, Meiringen, Switzerland

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Eur Addict Res 2017;23:106-112

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Article / Publication Details

First-Page Preview
Abstract of Research Report

Received: August 23, 2016
Accepted: March 15, 2017
Published online: April 13, 2017
Issue release date: May 2017

Number of Print Pages: 7
Number of Figures: 3
Number of Tables: 1

ISSN: 1022-6877 (Print)
eISSN: 1421-9891 (Online)

For additional information: https://www.karger.com/EAR

Abstract

Background: Methodological shortcomings of gambling studies relying on self-report or on data sets derived from gambling operators tend to result in biased conclusions. The aim of this study was to analyze online gambling behavior using a novel network database approach. Methods: From October 13 to October 26, 2014, telecommunications network data from a major telecommunications provider in Switzerland were analyzed. Netflows between mobile devices and a poker operator were quantified to measure the gambling duration and session number. Results: Time spent gambling during night and working hours was compared between devices with longest (red group), intermediate (orange group), and shortest gambling time (green group). Online gambling behavior differed depending on overall gambling time, F (2, 3,143). Night and working hours gambling was the highest in the red group (53%), compared to the orange (50.1%) and the green groups (41.5%). Post hoc analyses indicated significant differences between the orange and green groups (p < 0.05). No differences were observed between the red and orange groups (p = 0.850), and the red and green groups (p = 0.053). Conclusions: On mobile devices, distinct gambling patterns were observed depending on the overall gambling time. This methodology could also be used to investigate online gaming, social media use, and online pornography.

© 2017 S. Karger AG, Basel


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Article / Publication Details

First-Page Preview
Abstract of Research Report

Received: August 23, 2016
Accepted: March 15, 2017
Published online: April 13, 2017
Issue release date: May 2017

Number of Print Pages: 7
Number of Figures: 3
Number of Tables: 1

ISSN: 1022-6877 (Print)
eISSN: 1421-9891 (Online)

For additional information: https://www.karger.com/EAR


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