Evidence of a two-factor structure for Internet Gaming Disorder and Social Media Disorder: Psychometric properties of a new screening instrument for adolescents and adults

Abstract

Currently, there is no screening instrument available for assessing both internet gaming disorder (IGD) and social media disorder (SMD). This study aimed to examine the reliability and factor structure of a new screening instrument for adolescents and adults, the Gaming and Social Media Questionnaire (GSMQ-9), and to investigate its association with psychosocial outcomes (i.e., psychosomatic problems, self-concept, and social problems for adults and quality of life for adolescents). Survey data were collected from 995 university students and 626 adolescents. Results showed that a two-factor solution, representing Heavy Involvement and Negative Consequences, had a better model fit compared to a one-factor solution for both IGD and SMD and for both adolescents and adults. The internal consistency was acceptable, and the test-retest reliability was excellent. Negative Consequences were significantly more strongly related to all psychosocial outcomes compared to Heavy Involvement. The proportion of participants meeting the DSM-5 symptom criteria according to self-ratings on the GSMQ-9 was 1.4% (adolescents) and 1.8% (adults) for IGD and 2.6% (adolescents) and 4.0% (adults) for SMD. Conclusively, the GSMQ-9 appears to be a reliable two-factor screening instrument for IGD and SMD among adults and adolescents.

Screen time and addictive use of gaming and social media in relation to health outcomes

“…In line with the DSM-5 (American Psychiatric Association, 2013), an individual was considered to meet the full symptom criteria for IGD if meeting ≥5 of 9 symptoms and the same cut-off was used for SMD. The psychometric properties of the GSMQ-9 has been shown to be adequate in previous research (Burén et al, 2023) and the internal consistency was adequate also within the present study for both IGD (Heavy involvement: α = 0.85, ω = 0.85; Negative consequences: α = 0.70, ω = 0.73) and SMD (Heavy involvement: α = 0.79, ω = 0.79; Negative consequences: α = 0.73, ω = 0.74).…”

“…IGD and SMD criteria were measured using the Gaming and Social Media Questionnaire (GSMQ-9; Burén et al, 2023 ), which contains the nine symptom criteria for IGD ( American Psychiatric Association, 2013 ) and identical nine items for SMD. Each item is rated on a scale from 0 = strongly disagree to 4 = strongly agree .…”

“…Each item is rated on a scale from 0 = strongly disagree to 4 = strongly agree . Factor analysis ( Burén et al, 2023 ) has shown that this scale includes two subscales, with the subscale Heavy involvement including the first four criteria and subscale Negative consequences including the last five criteria (see Table 1 for more details). The mean values for each subscale for IGD and SMD were used in the analyses.…”

“…As the validity of these nine symptom criteria have been questioned (e.g., Griffiths et al, 2016 ; Castro-Calvo et al, 2021 ), it should be considered important to investigate how each one of these symptoms are related to both screen time and negative health outcomes. To better understand the importance of specific DSM-5 symptoms, some previous studies have made a distinction between symptoms linked to heavy involvement (i.e., criteria 1 to 4 as presented above) and those associated with negative consequences (criteria 5 to 9), with the former being more strongly associated with screen time but less strongly associated with negative psychosocial outcomes ( Wichstrøm et al, 2019 ; Burén et al, 2021 , 2023 ). Few studies have included both social media and gaming within the same study, even though it has been argued that the DSM-5 criteria presented for IGD can also be used for SMD (e.g., van den Eijnden et al, 2016 ).…”

Consumer-Perceived Risks and Sustainable Development of China’s Online Gaming Market: Analysis Based on Social Media Comments

“…However, due to the massive and difficult-to-obtain amount of social media comments, much of the research involving social media and online games has predominantly focused on discussing the relationship between social media and gaming [42][43][44], with minimal studies delving into analysis of the perceptions related to online games through comment analysis. As a result, social media comments and NLP methods provide researchers with unparalleled opportunities to access a vast array of textual data and advanced technology for exploring individuals' psychological states of perception.…”