Niklas Meurer, Silke M Müller, Anna M Schmid, Sabine Steins-Loeber, Matthias Brand
The findings support a predominantly additive model, indicating that impulsivity traits, maladaptive motives (specifically escape), and automatization contribute cumulatively to GD severity rather than through complex interactions. The identification of distinct gamer profiles suggests a need for personalized clinical interventions: the Impulsive-Automatical cluster may benefit from interventions targeting planning deficits and behavioral disinhibition, while the Problematic-Clinical cluster requires comprehensive treatment addressing comorbid affective psychopathology alongside gaming behavior.
BACKGROUND: The Interaction of Person-Affect-Cognition-Execution model suggests that impulsivity and specific gaming motives contribute to the development of gaming disorder (GD). However, it remains unclear whether these factors interact synergistically or operate independently. This study investigated the additive versus interactive effects of specific impulsivity facets, gaming motives, and behavior automatization on GD symptom severity.
METHOD: A sample of 377 adult gamers (338 male, 38 female, 1 diverse; age 18-58 years, M = 25.44, SD = 5.51) was assessed using the Barratt Impulsiveness Scale, Motives for Online Gaming Questionnaire, and the Assessment of Criteria of Specific Internet-use Disorders (ACSID-11) screening for GD symptom severity. Depression and anxiety were also assessed via self-report. We conducted hierarchical moderated regression analyses and exploratory cluster analysis.
RESULTS: The non-planning impulsivity dimension significantly predicted GD symptom severity in the final models. Escape motive and behavior automatization emerged as robust predictors, explaining substantial additional variance. Contrary to initial hypotheses, no significant interaction effects were found. Depression and anxiety served as strong covariates across all models. Cluster analysis identified four distinct profiles: Unproblematic-Adaptive, Social-Recreational, Impulsive-Automatical, and Problematic-Clinical.
CONCLUSION: The findings support a predominantly additive model, indicating that impulsivity traits, maladaptive motives (specifically escape), and automatization contribute cumulatively to GD severity rather than through complex interactions. The identification of distinct gamer profiles suggests a need for personalized clinical interventions: the Impulsive-Automatical cluster may benefit from interventions targeting planning deficits and behavioral disinhibition, while the Problematic-Clinical cluster requires comprehensive treatment addressing comorbid affective psychopathology alongside gaming behavior.