Phenotypes associated with problematic online gaming and gambling
BACKGROUND AND OBJECTIVES: Excessive engagement in online gaming and gambling is increasingly prevalent among young individuals, particularly first-year university students, and is associated with significant psychosocial damage. The aim of the present study was to identify empirical clusters among...
| Autores: | , , , |
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| Tipo de recurso: | artículo |
| Fecha de publicación: | 2026 |
| País: | España |
| Institución: | Universitat Autònoma de Barcelona |
| Repositorio: | Dipòsit Digital de Documents de la UAB |
| Idioma: | inglés |
| OAI Identifier: | oai:dnet:uabarcelona_::3ce4bfa338c14744b6bb918be4b2e353 |
| Acceso en línea: | https://ddd.uab.cat/record/328666 https://dx.doi.org/urn:doi:10.1016/j.abrep.2026.100702 |
| Access Level: | acceso abierto |
| Palabra clave: | Online gaming disorder Online gambling disorder Cluster University students Problematic internet use |
| Sumario: | BACKGROUND AND OBJECTIVES: Excessive engagement in online gaming and gambling is increasingly prevalent among young individuals, particularly first-year university students, and is associated with significant psychosocial damage. The aim of the present study was to identify empirical clusters among university students reporting problematic online gaming and gambling behaviors and to examine the extent to which these clusters differ from a control group of students without gaming- and gambling-related problems. METHOD: The sample included 273 first-year university students (180 women and 93 men, aged 18-25 years). Participants were first classified into a subgroup with problematic online gaming or gambling (n = 100) and a non-problematic (control) group (n = 173), based on DSM-5 criteria. A two-step cluster analysis was then conducted exclusively within the problematic subgroup to identify latent profiles, using indicators of addictive behavior severity, engagement with social networks and the internet, impulsivity, emotion dysregulation, gambling-related cognitive distortions, and psychological distress. Subsequently, the identified clusters were compared with each other and with the control group across a broad range of psychological and behavioral indicators. RESULTS: Two clusters were identified, primarily differentiated by the severity of gaming-gambling involvement and associated psychological vulnerabilities. Cluster profiles revealed distinct patterns of impulsivity, emotional deficit, and cognitive biases. Both clusters significantly differed from the control group, with higher scores on all clinical and cognitive measures except for the social internet use and sensation seeking. CONCLUSION: The findings provide empirical support for the heterogeneity of problematic gaming and gambling among young university students. The identification of discrete subgroups underscores the relevance of individualized prevention and intervention strategies, tailored to the severity and psychological correlates of the addictive behavior(s). These results also highlight the need to refine screening and diagnostic tools within this target population. |
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