Moderator effect of sex in the clustering of treatment-seeking patients with gambling problems
Background: There are no studies based on a person-centered approach addressing sex-related differences in the characteristics of treatment-seeking patients with gambling disorder (GD). The main objective of the current study is to identify empirical clusters of GD based on several measures of the s...
| Autores: | , , , , , , , , , , , , , , , , |
|---|---|
| Formato: | artículo |
| Fecha de publicación: | 2020 |
| País: | España |
| Recursos: | Universitat Autònoma de Barcelona |
| Repositorio: | Dipòsit Digital de Documents de la UAB |
| Idioma: | inglés |
| OAI Identifier: | oai:ddd.uab.cat:301909 |
| Acesso em linha: | https://ddd.uab.cat/record/301909 https://dx.doi.org/urn:doi:10.1007/s40211-020-00341-1 |
| Access Level: | acceso abierto |
| Palavra-chave: | Clustering Gambling disorder Personality Psychopathology Sex SDG 3 - Good Health and Well-being |
| Resumo: | Background: There are no studies based on a person-centered approach addressing sex-related differences in the characteristics of treatment-seeking patients with gambling disorder (GD). The main objective of the current study is to identify empirical clusters of GD based on several measures of the severity of gambling behavior, and considering the potential role of patient sex as a moderator. Methods: An agglomerative hierarchical clustering method was applied to an adult sample of 512 treatment-seeking patients (473 men and 39 women) by using a combination of the Schwarz Bayesian Information Criterion and log-likelihood function. Results: Three clusters were identified in the subsample of men: cluster M1 (low-mild gambling severity level, 9.1%), cluster M2 (moderate level, 60.9%), and cluster M3 (severe level, 30.0%). In the women subsample, two clusters emerged: cluster W1 (mild-moderate level, 64.1%), and cluster W2 (severe level, 35.9%). The most severe GD profiles were related to being single, multiple gambling preference for nonstrategic plus strategic games, early onset of the gambling activity, higher impulsivity levels, higher dysfunctional scores in the personality traits of harm avoidance, and self-directedness, and higher number of lifespan stressful life events (SLE). Differences between the empirical men and women clusters were found in different sociodemographic and clinical measurements. Conclusions: Men and women have distinct profiles regarding gambling severity that can be identified by a clustering approach. The sociodemographic and clinical characterization of each cluster by sex may help to establish specific preventive and treatment interventions. |
|---|