Subtypes of disordered gamblers: Results from the National Epidemiologic Survey on Alcohol and Related Conditions

Abstract

Aims: To derive empirical subtypes of problem gamblers based on etiological and clinical characteristics described in the Pathways Model, using data from a nationally representative survey of US adults. Design & measurement: Data were collected from structured diagnostic face-to-face interviews using the Alcohol Use Disorder and Associated Disabilities Interview Schedule DSM-IV version IV (AUDADIS-IV). Setting: The study utilized data from US National Epidemiologic Survey on Alcohol and Related Conditions (NESARC). Participants: All disordered gambling participants (n = 581) from a nationally representative cross-sectional sample of civilian non-institutionalized adults aged 18 years or older. Findings: Latent class analyses indicated that the best-fitting model was a three-class solution. Those in the largest class (class 1: 50.76%, n = 295) reported the lowest overall levels of psychopathology including gambling problem severity and mood disorders. In contrast, respondents in class 2 (20.06%, n = 117) had a high probability of endorsing past-year substance use disorders, moderate probabilities of having parents with alcohol/drug problems and of having a personality disorder, and the highest probability for past-year mood disorders. Respondents in class 3 (29.18%, n = 169) had the highest probabilities of personality and prior-to-past year mood disorders, substance use disorders, separation/divorce, drinking-related physical fights and parents with alcohol/drug problems and/or a history of antisocial personality disorder (ASPD). Conclusions: Three subtypes of disordered gamblers can be identified, roughly corresponding to the subtypes of the Pathways Model, ranging from a subgroup with low levels of gambling severity and psychopathology to one with high levels of gambling problem severity and comorbid psychiatric disorders. (PsycINFO Database Record (c) 2013 APA, all rights reserved) (journal abstract)

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