Literature DB >> 27178749

Free-to-play: About addicted Whales, at risk Dolphins and healthy Minnows. Monetarization design and Internet Gaming Disorder.

M Dreier1, K Wölfling2, E Duven2, S Giralt2, M E Beutel3, K W Müller2.   

Abstract

INTRODUCTION: Video games are not only changing due to technical innovation, but also because of new game design and monetization approaches. Moreover, elite gamer groups with financial in-game-investments co-finance all users of free-to-play-games. Besides questions on youth protection, the growing popularity of free-to-play games has fostered discussions on supposed associations to Internet Gaming Disorder (IGD).
METHOD: Children and adolescents using free-to-play browser games were examined in a German school-based representative study (N=3967; age range 12 to 18). Based on a clinical self-report AICA-S (Wölfling et al., 2011), students were categorized into non-problematic, risky, and addicted users. Psycho-social problems (SDQ; Goodman, 1997), perceived stress (PSS; Cohen, Kamarck & Mermelstein, 1983), coping strategies (BriefCOPE; Carver, 1997), and Average Revenue per (Paying) User (ARPU) were investigated as dependent variables. Furthermore, an industry classification (Freeloaders, Minnows, Dolphins, and Whales) for free-to-play gamers was used for additional relations regarding IGD, SDQ, PSS, BriefCOPE, and ARPU.
RESULTS: Among free-to-play gamers the prevalence of IGD amounted to 5.2%. Subjects classified with IGD displayed higher psycho-social symptoms than non-problematic users, reported higher degrees of perceived stress, and applied dysfunctional coping strategies more frequently. Additionally, we found a higher ARPU among subjects with IGD.
CONCLUSION: ARPU is significantly associated with IGD. Whales share significant characteristics with addicted video gamers; Dolphins might be classified as risky consumers; Minnows and Freeloaders are rather non-pathological gamers. Vulnerability for stress, dysfunctional coping, and free-to-play gaming represent an unhealthy combination.
Copyright © 2016 Elsevier Ltd. All rights reserved.

Entities:  

Keywords:  Average Revenue per (paying) User (ARPU); Distress; Free-to-play; Internet Gaming Disorder; Monetarization; Psychopathology; Whales

Mesh:

Year:  2016        PMID: 27178749     DOI: 10.1016/j.addbeh.2016.03.008

Source DB:  PubMed          Journal:  Addict Behav        ISSN: 0306-4603            Impact factor:   3.913


  16 in total

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2.  Gaming Device Usage Patterns Predict Internet Gaming Disorder: Comparison across Different Gaming Device Usage Patterns.

Authors:  Soo-Hyun Paik; Hyun Cho; Ji-Won Chun; Jo-Eun Jeong; Dai-Jin Kim
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3.  The validity and psychometric properties of the Japanese version of the Compulsive Internet Use Scale (CIUS).

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Journal:  BMC Psychiatry       Date:  2017-05-30       Impact factor: 3.630

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5.  Breaking the habit.

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Authors:  Fanni Bányai; Ágnes Zsila; Gyöngyi Kökönyei; Mark D Griffiths; Zsolt Demetrovics; Orsolya Király
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7.  Patterns and Predictors of Internet Gaming Disorder: An Observational Study from Jordan.

Authors:  Reema Karasneh; Sayer Al-Azzam; Karem H Alzoubi; Mohammad B Nusair; Sahar Hawamdeh; Amal T Nusir
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Authors:  Sarah E Hodge; Max Vykoukal; John McAlaney; Reece D Bush-Evans; Ruijie Wang; Raian Ali
Journal:  PLoS One       Date:  2022-02-09       Impact factor: 3.240

9.  Cognitive distortions and gambling near-misses in Internet Gaming Disorder: A preliminary study.

Authors:  Yin Wu; Guillaume Sescousse; Hongbo Yu; Luke Clark; Hong Li
Journal:  PLoS One       Date:  2018-01-18       Impact factor: 3.240

10.  Personality and Cognition in Gamers: Avoidance Expectancies Mediate the Relationship Between Maladaptive Personality Traits and Symptoms of Internet-Gaming Disorder.

Authors:  Christian Laier; Elisa Wegmann; Matthias Brand
Journal:  Front Psychiatry       Date:  2018-07-10       Impact factor: 4.157

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