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      Video Game Streaming in Young People and Teenagers: Uptake, User Groups, Dangers, and Opportunities

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          Abstract

          In recent years, live video streaming platforms for video games have been gaining popularity. These types of services, which enable anyone to broadcast and consume live content, are revolutionising the current video game landscape. Users approach the emergence of and participation in these platforms driven by a range of motivations. It is essential to characterise the different forms of participation in services such as Twitch to evaluate the phenomenon and reflect on its advantages and disadvantages. To that end, a survey was carried out of 580 young people and adolescents aged between 14 and 24. The aim of this study is thus to explore the uptake of these platforms, as well as identify user groups, distinguish between different motivations, and address the associated benefits and harms. Applying a methodology based on factor analysis and cluster analysis, user profiles were characterised according to their specific features, gaming/viewing hours, self-perception of their skill level as a player, devices used, and type or genre of video game. Four subgroups of gamers/viewers were thus identified: casual, social, hobby, and problematic. The results showed that older users and female users feature more prominently in the first two groups, as do those spending less time on video games and live streaming platforms. Conversely, in the hobby and problematic groups, we observe just the opposite. The existence of profiles at possible risk of addiction underlines how, at a preventive level, there is a need for more in-depth research on these types of services and greater public awareness of the dangers of uncontrolled use.

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          The psychological impact of the COVID-19 epidemic on college students in China

          Highlights • Methods of guiding students to effectively and appropriately regulate their emotions during public health emergencies and avoid losses caused by crisis events have become an urgent problem for colleges and universities. Therefore, we investigated and analyzed the mental health status of college students during the epidemic for the following purposes. (1) To evaluate the mental situation of college students during the epidemic; (2) to provide a theoretical basis for psychological interventions with college students; and (3) to provide a basis for the promulgation of national and governmental policies.
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            The relationship between addictive use of social media and video games and symptoms of psychiatric disorders: A large-scale cross-sectional study.

            Over the last decade, research into "addictive technological behaviors" has substantially increased. Research has also demonstrated strong associations between addictive use of technology and comorbid psychiatric disorders. In the present study, 23,533 adults (mean age 35.8 years, ranging from 16 to 88 years) participated in an online cross-sectional survey examining whether demographic variables, symptoms of attention-deficit/hyperactivity disorder (ADHD), obsessive-compulsive disorder (OCD), anxiety, and depression could explain variance in addictive use (i.e., compulsive and excessive use associated with negative outcomes) of two types of modern online technologies: social media and video games. Correlations between symptoms of addictive technology use and mental disorder symptoms were all positive and significant, including the weak interrelationship between the two addictive technological behaviors. Age appeared to be inversely related to the addictive use of these technologies. Being male was significantly associated with addictive use of video games, whereas being female was significantly associated with addictive use of social media. Being single was positively related to both addictive social networking and video gaming. Hierarchical regression analyses showed that demographic factors explained between 11 and 12% of the variance in addictive technology use. The mental health variables explained between 7 and 15% of the variance. The study significantly adds to our understanding of mental health symptoms and their role in addictive use of modern technology, and suggests that the concept of Internet use disorder (i.e., "Internet addiction") as a unified construct is not warranted.
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              Data clustering: a review

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                Author and article information

                Contributors
                Role: Academic Editor
                Role: Academic Editor
                Journal
                Healthcare (Basel)
                Healthcare (Basel)
                healthcare
                Healthcare
                MDPI
                2227-9032
                10 February 2021
                February 2021
                : 9
                : 2
                : 192
                Affiliations
                Department of Statistics, Econometrics, Operations Research, Business Organization and Applied Economics, Faculty of Law, Business and Economic Sciences, University of Córdoba, Puerta Nueva s/n, 14071 Córdoba, Spain; guzman.munoz@ 123456uco.es (G.A.M.-F.); td1sarol@ 123456uco.es (L.S.-R.)
                Author notes
                [* ]Correspondence: r62caral@ 123456uco.es ; Tel.: +34-957-212-688
                Author information
                https://orcid.org/0000-0002-5603-2365
                https://orcid.org/0000-0003-4521-4793
                Article
                healthcare-09-00192
                10.3390/healthcare9020192
                7916337
                33578675
                2d794a9a-b72a-4a09-81d5-727dde7c44a2
                © 2021 by the authors.

                Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license ( http://creativecommons.org/licenses/by/4.0/).

                History
                : 12 January 2021
                : 06 February 2021
                Categories
                Article

                digital motivation,cyber behaviour,live streaming,cluster analysis,video games,e-health,problematic online gaming and gambling

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