Serum BDNF levels in patients with gambling disorder are associated with the severity of gambling disorder and Iowa Gambling Task indices.

Background and aims Gambling disorder (GD) shares many similarities with substance use disorders (SUDs) in clinical, neurobiological, and neurocognitive features, including decision-making. We evaluated the relationships among, GD, decision-making, and brain-derived neurotrophic factor (BDNF), as measured by serum BDNF levels. Methods Twenty-one male patients with GD and 21 healthy sex- and age-matched control subjects were evaluated for associations between serum BDNF levels and the Problem Gambling Severity Index (PGSI), as well as between serum BDNF levels and Iowa Gambling Task (IGT) indices. Results The mean serum BDNF levels were significantly increased in patients with GD compared to healthy controls. A significant correlation between serum BDNF levels and PGSI scores was found when controlling for age, depression, and duration of GD. A significant negative correlation was obtained between serum BDNF levels and IGT improvement scores. Discussion These findings support the hypothesis that serum BDNF levels constitute a dual biomarker for the neuroendocrine changes and the severity of GD in patients. Serum BDNF level may serve as an indicator of poor decision-making performance and learning processes in GD and help to identify the common physiological underpinnings between GD and SUDs.

Latent class analysis on internet and smartphone addiction in college students.

PURPOSE: This study aimed to classify distinct subgroups of people who use both smartphone and the internet based on addiction severity levels. Additionally, how the classified groups differed in terms of sex and psychosocial traits was examined. METHODS: A total of 448 university students (178 males and 270 females) in Korea participated. The participants were given a set of questionnaires examining the severity of their internet and smartphone addictions, their mood, their anxiety, and their personality. Latent class analysis and ANOVA (analysis of variance) were the statistical methods used. RESULTS: Significant differences between males and females were found for most of the variables (all <0.05). Specifically, in terms of internet usage, males were more addicted than females (P<0.05); however, regarding smartphone, this pattern was reversed (P<0.001). Due to these observed differences, classifications of the subjects into subgroups based on internet and smartphone addiction were performed separately for each sex. Each sex showed clear patterns with the three-class model based on likelihood level of internet and smartphone addiction (P<0.001). A common trend for psychosocial trait factors was found for both sexes: anxiety levels and neurotic personality traits increased with addiction severity levels (all P<0.001). However, Lie dimension was inversely related to the addiction severity levels (all P<0.01). CONCLUSION: Through the latent classification process, this study identified three distinct internet and smartphone user groups in each sex. Moreover, psychosocial traits that differed in terms of addiction severity levels were also examined. It is expected that these results should aid the understanding of traits of internet and smartphone addiction and facilitate further study in this field.

Age of pathological gambling onset: clinical and treatment-related features.

OBJECTIVES: This study examined differences in the clinical and treatment-related features of pathological gambling (PG) on the basis of the age of PG onset among pathological gamblers who sought treatment. METHODS: A total of 702 male outpatients with a primary diagnosis of PG and who were treated in a clinical practice were assessed by retrospective chart review. We selected the age of 25 years and younger as the threshold for "group 1." We then stratified the participants into 4 groups on the basis of the age of PG onset in 10-year intervals. Analysis of covariance with a covariant of age and the Pearson χ test were used for analyses. RESULTS: We found that the earlier-onset gamblers were less likely to be escape type (P < 0.05), used significantly more Internet-based gambling (P < 0.001), and were less likely to engage in nonstrategic gambling (P < 0.05) than the later-onset gamblers. In addition, the earlier-onset gamblers took anticraving medication, such as naltrexone, significantly more often (P < 0.05), and sought treatment significantly more slowly after the onset of PG than the later-onset group (P < 0.01). Regarding adherence to treatment, however, there was no significant difference among the 4 groups on the basis of the age of PG onset. CONCLUSIONS: The age of PG onset is associated with several important clinical and treatment features. More studies are needed to advance prevention and treatment strategies for each age group.