Pathological gambling: Understanding relapses and dropouts

Núria Aragay, Susana Jiménez-Murcia, Roser Granero, Fernando Fernández-Aranda, Irene Ramos-Grille, Sara Cardona, Gemma Garrido, Mohammed Anisul Islam, José M. Menchón, Vicenç Vallès

Research output: Contribution to journalArticleResearchpeer-review

26 Citations (Scopus)

Abstract

© 2014 Elsevier Inc. There is little available information on the factors that influence relapses and dropouts during therapy for pathological gambling (PG). The aim of this study was to determine socio-demographic, clinical, personality, and psychopathological predictors of relapse and dropout in a sample of pathological gamblers seeking treatment. A total of 566 consecutive outpatients diagnosed with PG according to DSM-IV-TR criteria were included. All patients underwent an individualized cognitive-behavioral treatment program. We analyzed predictors of relapse during 6 months of treatment and during the subsequent 6 months of follow-up, and predictors of dropout over the entire therapeutic program. Eighty patients (14.1%) experienced at least one relapse during the entire follow-up of the study: 50 (8.8%) within the treatment period and 12 (2.1%) during the subsequent 6-month follow-up period. The main predictors of relapse were single marital status, spending less than 100 euros/week on gambling, active gambling behavior at treatment inclusion, and high scores on the TCI-R Harm Avoidance personality dimension. One hundred fifty-seven patients (27.8%) missed 3 or more therapeutic sessions over the entire therapeutic program. The main predictors of dropout were single marital status, younger age, and high scores on the TCI-R Novelty Seeking personality dimension. The presence of these factors at inclusion should be taken into account by physicians dealing with PG patients.
Original languageEnglish
Pages (from-to)58-64
JournalComprehensive Psychiatry
Volume57
DOIs
Publication statusPublished - 1 Jan 2015

Fingerprint

Dive into the research topics of 'Pathological gambling: Understanding relapses and dropouts'. Together they form a unique fingerprint.

Cite this