Contribution of sex on the underlying mechanism of the gambling disorder severity.

Significant increasing prevalences have been observed in gambling disorder (GD) in the last decades. This study analyzed the underlying mechanisms of the gambling severity with path analysis (implemented through Structural Equation Modeling, SEM), and assessed the potential moderator effect of the patients' sex. A sample of n = 512 treatment-seeking patients was assessed for sociodemographics and clinical state previously to the treatment. Results obtained in two separate SEM (for men and women) revealed differences in the direct effects and the mediational links. Among the male subsample, higher GD severity was directly related to the higher cognitive bias and the younger age of onset of the problematic gambling, while impulsivity levels and age of onset achieved an indirect effect on the disordered gambling mediated by the cognitive bias. Among females, GD severity was directly increased by younger age of onset, higher cognitive bias and lower self-directedness, while lower socioeconomic positions, and higher levels in harm avoidance achieved an indirect effect on the gambling severity mediated also by the distortions related to the gambling activity. These results provide new empirical evidence for a better understanding of the GD etiology, suggesting that the underlying complex links mediating the GD severity are strongly related to the patients' sex. The results can also contribute to design more effectiveness and precise therapy programs of patient-centered care.

Gambling Phenotypes in Online Sports Betting.

BACKGROUND AND OBJECTIVES: The Internet provides easy access to multiple types of gambling and has led to changes in betting habits. A severe rise in problematic gambling has been predicted among all sectors of the population, and studies are required to assess the emerging phenotypes related to the new structures of gambling activities. This study aimed to explore the existence of latent classes associated with gambling habits among treatment-seeking gamblers due to Online Sports Betting (OSB). METHOD: Initial sample included n = 4,516 patients consecutively admitted for treatment in a hospital unit specialized in behavioral addictions. Two-step clustering analysis was used within the subsample of n = 323 patients who reported problems related with OSB, within a set of indicators including sociodemographics, psychopathological distress, personality, and severity of the gambling activity. RESULTS: The prevalence of OSB as a main type of gambling problem in the study was 7.2% (95% confidence interval: 6.4 to 7.9%). Two latent clusters were identified, with differences in sociodemographics and clinical status. Cluster 1 (n = 247, 76.5%) grouped patients that were more affected due to the OSB behaviors, and it was characterized by non-married patients, lower socioeconomic position index, higher comorbidity with other substance related addictions, younger age, and early onset of the gambling activity, as well as higher debts due to the OSB, higher psychopathological distress, and a more dysfunctional personality profile. Cluster 2 (n = 76, 23.5%) grouped patients that were less affected by OSB, mostly married (or living with a stable partner), with higher social position levels, older age and older onset of the gambling activity, as well as a more functional psychopathological and personality profile. CONCLUSION: The increasing understanding of latent classes underlying OSB phenotypes is essential in guiding the development of reliable screening tools to identify individuals highly vulnerable to addictive behaviors among Internet gamblers, as well as in planning prevention and treatment initiatives focused on the precise profiles of these patients.

Response trajectories of gambling severity after cognitive behavioral therapy in young-adult pathological gamblers.

BACKGROUND AND AIMS: The significant increase in the prevalence of gambling disorder (GD) among young adults in recent years has attracted interest in determining therapeutic efficiency in this sector of the population. The aim of this work was to estimate the response trajectories of gambling severity during the six-month follow-up after a cognitive behavioral therapy (CBT) program in young adult patients and to identify the main variables associated with each trajectory. METHODS: The sample included n = 192 patients, aged 19-35 years old, seeking treatment for GD. Response trajectories were identified through latent class growth analysis. RESULTS: Three trajectories emerged: T1 (n = 118, 61.5%), composed of patients with severe GD at pre-treatment and good evolution to recovery; T2 (n = 62, 32.3%), with patients with moderate-high GD affectation at baseline and good evolution to recovery; and T3 (n = 12, 6.3%), with participants with severe baseline GD severity and poor evolution after CBT (Abbott, 2019). The highest risk of poor therapeutic outcomes was related to lower social index positions, high emotional distress, high scores in harm avoidance and low scores in self-directedness. DISCUSSION AND CONCLUSIONS: Differences in the response trajectories at short-term follow-up after CBT reveal heterogeneity in the samples including young and young-adult GD patients. Patients' phenotype at baseline should be considered when developing efficient, person-centered intervention programs, which should comprise strategies aimed at increasing emotional regulation capacities, self-esteem and self-efficacy, with the aim of avoiding relapses in the medium-long term after therapy.

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 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.

Gambling Phenotypes in Older Adults.

Participation in gambling is rising in older adults. Indeed, in the coming years, engagement in gambling as a social activity is expected to increase more sharply in the elderly than in any other age group. Due to their exposure to powerful age-specific risk factors such as isolation, inactivity and failing health, older people are highly vulnerable to gambling-related problems. This study aimed to explore the existence of empirical clusters related to gambling habits in a sample of elderly participants from the general population. The sample included n = 361 participants, age range 50-90 years (mean 73.8, SD 8.4). Empirical clusters were identified through a two-step clustering analysis based on a broad set of indicators, including sociodemographic features, psychopathological state, substance use, life events, gambling preferences and scores on screening measures of gambling severity. The prevalence of GD in the study was 1.4%. Two clusters were identified: (a) cluster 1 (labeled as "low risk of gambling problems", n = 265, 73.4%), which included the higher proportion of non-gamblers or individuals who engage only in non-strategic gambling, women, widowed, and lower levels of education (no individual into this group met criteria for GD); and (b) cluster 2 (labeled as "higher risk of gambling problems", n = 96, 26.6%), which included the higher proportion of men, who reported both non-strategic and strategic gambling preferences (all participants diagnosed of GD were grouped into this cluster), older age, longer history of gambling, higher gambling severity, higher use of substances and worse psychopathological state. The elderly constitute a heterogeneous group with regard to gambling phenotypes. The results of this study may prove particularly useful for developing reliable screening tools able to identify older patients at a high risk of gambling problems, and for designing effective prevention and intervention programs.