Cookies on this website

We use cookies to ensure that we give you the best experience on our website. If you click 'Accept all cookies' we'll assume that you are happy to receive all cookies and you won't see this message again. If you click 'Reject all non-essential cookies' only necessary cookies providing core functionality such as security, network management, and accessibility will be enabled. Click 'Find out more' for information on how to change your cookie settings.

Background: The shift in the last decades to screen-based and increasingly online gaming activity has raised concerns about its impact on the development of children and adolescents. Despite decades of research into gaming and related psychosocial effects, the question remains on how to best identify what degree or context of gaming may be a cause for concern. Objective: The present study aimed to classify adolescents into gamer profiles based on both gaming behaviours and well-being. Once we distinguished the different gaming profiles, we aimed to explore whether membership to a specific profile could be predicted based on a range of personal characteristics and experiences that could then help identify those at risk. Methods: We explored gaming and well-being in an adolescent school population (aged 12-18 years) in England as part of the 2021 OxWell Student Survey. Self-report measures of time spent playing games on computers/consoles, time spent playing games on phones, game addiction scale (GAS) scores, and well-being scores (WEMWBS) were used to classify adolescent heavy gamers (playing games for at least 3.5 hours a day) into different gamer profiles using Latent Profile Analysis (LPA). We used multinomial logistic regression to the predict the profile membership based on a range of personal characteristics and experiences. Results: 12,725 participants answered the OxWell gaming questions. One third indicated that they play games on an electronic device for at least 3.5 hours a day. The correlation between time spent playing video games overall and well-being was not significant (P = .41). The LPA distinguished six profiles of adolescent heavy gamers: ‘adaptive computer gamers’ (44%), ‘casual computer gamers’ (22%), ‘casual phone gamers’ (15%), ‘unknown device gamers’ (12%), ‘maladaptive computer gamers’ (6%), and ‘maladaptive phone gamers’ (2%). In comparison to ‘adaptive computer gamers’, ‘maladaptive phone gamers’ were mostly female (OR=0.08) and were more likely to have experienced abuse or neglect (OR=3.18). ‘Maladaptive computer gamers’, who reported gaming both on their phones and on the computer, were mostly male and more likely to report anxiety (OR=2.25), aggressive behaviour (OR=2.83), and online gambling (OR=2.18). Conclusions: A substantial number of school-aged children are spending more than 3.5 hours gaming each day with almost one in ten (8%) reporting co-occurring gaming and well-being issues. Long hours gaming using mobile phones, particularly common in females, may signal poorer functioning and indicate a need for additional support. Although increased time gaming might be changing how the adolescent population spend their free time and, might thus have public health implications, it does not appear to relate to co-occurring well-being issues or mental ill-health for the majority of adolescent gamers.

Original publication

DOI

10.2196/41480

Type

Journal article

Journal

JMIR Pediatrics and Parenting

Publisher

JMIR Publications Inc.

Publication Date

27/07/2022

Keywords

gaming, adolescents, latent profile analysis, mobile phone, well-being, mental ill-health, mental health, digital technology