Background and aims

Gaming Disorder (GD) is characterized by a pattern of persistent and uncontrolled gaming behavior that causes a marked impairment in important areas of functioning. The evolution of the worldwide incidence of this disorder warrants further studies focused on examining the existence of different subtypes within clinical samples, in order to tailor treatment. This study explored the existence of different profiles of patients seeking treatment for GD through a data-driven approach.

Methods

The sample included n = 107 patients receiving treatment for GD (92% men and 8% women) ranging between 14 and 60 years old (mean age = 24.1, SD = 10). A two-step clustering analysis approach explored the existence of different underlying GD profiles based on a broad set of indicators, including sociodemographic features, clinical course of the condition (e.g., onset or evolution), psychopathological symptoms, and personality traits.

Results

Two GD profiles emerged. The first cluster grouped together patients who presented with a lower psychological impact (n = 72, 66.1%), whereas the second cluster comprised patients with a higher psychological impact (n = 35, 32.7%). Cluster comparisons revealed that those patients presenting the higher impact were older, with a later onset of pathological gaming patterns, and more pronounced psychopathological symptoms and dysfunctional personality profiles.

Conclusions

GD severity is influenced by specific demographic, clinical, and psychopathological factors. The identification of two separate profiles provides empirical evidence that contributes to the conceptualization of this disorder, as well as to the development of reliable and valid screening tools and effective intervention plans focused on the precise characteristics of the treatment-seeking patients.

中文翻译：

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寻求治疗的游戏障碍患者的亚型

背景和目标

游戏障碍 (GD) 的特征是一种持续且不受控制的游戏行为模式，导致重要功能领域的显着损害。这种疾病在世界范围内发病率的演变需要进一步研究，重点检查临床样本中不同亚型的存在，以便制定治疗方案。本研究通过数据驱动的方法探讨了寻求 GD 治疗的患者的不同情况。

方法

样本包括n  = 107 名接受 GD 治疗的患者（92% 男性和 8% 女性），年龄在 14 至 60 岁之间（平均年龄 = 24.1，SD  = 10）。两步聚类分析方法基于一系列广泛的指标探索了不同的潜在 GD 概况的存在，包括社会人口学特征、病症的临床过程（例如，发作或演变）、精神病理学症状和人格特征。

结果

出现了两个 GD 配置文件。第一个集群将心理影响较低的患者分组在一起 ( n  = 72, 66.1%)，而第二个集群包含具有较高心理影响的患者 ( n  = 35, 32.7%)。集群比较显示，那些表现出较高影响的患者年龄较大，病态游戏模式发生较晚，精神病理学症状和人格障碍更明显。

结论

GD 的严重程度受特定人口统计学、临床和精神病理学因素的影响。确定两个独立的特征提供了经验证据，有助于对这种疾病的概念化，以及开发可靠和有效的筛查工具和有效的干预计划，重点是寻求治疗的患者的确切特征。