Mapping the links between sexual addiction and gambling disorder: a Bayesian network approach

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Hunt, Brian ORCID: 0000-0003-0779-9866, Zarate, Daniel ORCID: 0000-0002-1508-8637, Gill, Peter ORCID: 0000-0001-7772-4849 and Stavropoulos, Vasileios ORCID: 0000-0001-6964-4662 (2023) Mapping the links between sexual addiction and gambling disorder: a Bayesian network approach. Psychiatry Research, 327. ISSN 0165-1781


Contemporary literature and recent classification systems have expanded the field of addictions to include problematic behaviours such as gambling and sexual addiction. However, conceptualisation of behavioural addictions is poorly understood and gender-based differences have emerged in relation to how these behaviours are expressed. The current research conducted partial-correlation and Bayesian network analyses to assess the symptomatic structure of gambling disorder and sexual addiction. Convenience community sampling recruited 937 adults aged 18 to 64 years (315 females, Mage = 30.02; 622 males, Mage = 29.46). Symptoms of problematic behaviours were measured using the Online Gambling Disorder Questionnaire (OGDQ) and the Bergen Yale Sex Addiction Scale (BYSAS). Results indicate distinct gender-based differences in the symptom networks of sexual addiction and gambling disorder, with a more complex network observed amongst men for both conditions. Addiction salience, withdrawal and dishonesty/deception were important components of the addictive network. Interpersonal conflict was more central for women while intrapsychic conflict a more prominent issue for men. Differences in the two symptom networks indicate separate disorders as opposed to a single underlying construct. Treating practitioners and community initiatives aimed at addressing sexual addiction and disordered gambling should consider gender, when designing educational or therapeutic interventions.

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Item type Article
DOI 10.1016/j.psychres.2023.115366
Official URL
Subjects Current > FOR (2020) Classification > 5299 Other psychology
Current > Division/Research > Institute for Health and Sport
Keywords sexual addiction, gambling disorder, Bayesian network, network analysis, gender based differences
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