Clustering of treatment-seeking women with gambling disorder Cover Image

Clustering of treatment-seeking women with gambling disorder
Clustering of treatment-seeking women with gambling disorder

Author(s): Roser Granero, Fernando Fernández-Aranda, Gemma Mestre-Bach, Trevor Steward
Subject(s): Behaviorism
Published by: Akadémiai Kiadó
Keywords: gambling disorder; personality traits; women; psychopathology; assessment

Summary/Abstract: The prevalence of gambling disorder (GD) in women has increased, but, to date, few studies have explored the features of clinical GD subtypes in female samples. Aims. The aim of this study is to identify empirical clusters based on clinical/sociodemographic variables in a sample of treatment-seeking women with GD. Methods. Agglomerative hierarchical clustering was applied to a sample of n = 280 patients, using sociodemographic variables, psychopathology, and personality traits as indicators for the grouping procedure. Results. Three mutually exclusive groups were obtained: (a) Cluster 1 (highly dysfunctional; n = 82, 29.3%) endorsed the highest levels in gambling severity, comorbid psychopathology, novelty seeking, harm avoidance, and self-transcendence, and the lowest scores in self-directedness and cooperativeness; (b) Cluster 2 (dysfunctional; n = 142, 50.7%) achieved medium mean scores in gambling severity and psychopathological symptoms; and (c) Cluster 3 (functional; n = 56, 20.0%) obtained the lowest mean scores in gambling severity and in psychopathology, and a personality profile characterized by low levels in novelty seeking, harm avoidance, and self-transcendence, and the highest levels in self-directedness and cooperativeness. Discussion and conclusions. This study sheds light on the clinical heterogeneity of women suffering from GD. Identifying the differing features of women with GD is vital to developing prevention programs and personalized treatment protocols for this overlooked population.

  • Issue Year: 7/2018
  • Issue No: 3
  • Page Range: 770-780
  • Page Count: 11
  • Language: English