Search

Background: The heterogeneity of gambling disorder (GD) has led to the identification of different subtypes, mostly including phenotypic features, with distinctive implications on the GD severity and treatment outcome. However, clustering analyses based on potential endophenotypic features, such as neuropsychological and neuroendocrine factors, are scarce so far. Aims: This study firstly aimed to identify empirical clusters in individuals with GD based on sociodemographic (i.e., age and sex), neuropsychological (i.e., cognitive flexibility, inhibitory control, decision making, working memory, attention, and set-shifting), and neuroendocrine factors regulating energy homeostasis (i.e., leptin, ghrelin, adiponectin, and liver-expressed antimicrobial peptide 2, LEAP-2). The second objective was to compare the profiles between clusters, considering the variables used for the clustering procedure and other different sociodemographic, clinical, and psychological features. Methods: 297 seeking-treatment adult outpatients with GD (93.6% males, mean age of 39.58 years old) were evaluated through a semi-structured clinical interview, self-reported psychometric assessments, and a protocolized neuropsychological battery. Plasma concentrations of neuroendocrine factors were assessed in peripheral blood after an overnight fast. Agglomerative hierarchical clustering was applied using sociodemographic, neuropsychological, and neuroendocrine variables as indicators for the grouping procedure. Comparisons between the empirical groups were performed using Chi-square tests (χ2) for categorical variables, and analysis of variance (ANOVA) for quantitative measures. Results: Three-mutually-exclusive groups were obtained, being neuropsychological features those with the greatest weight in differentiating groups. The largest cluster (Cluster 1, 65.3%) was composed by younger males with strategic and online gambling preferences, scoring higher on self-reported impulsivity traits, but with a lower cognitive impairment. Cluster 2 (18.2%) and 3 (16.5%) were characterized by a significantly higher proportion of females and older patients with non-strategic gambling preferences and a worse neuropsychological performance. Particularly, Cluster 3 had the poorest neuropsychological performance, especially in cognitive flexibility, while Cluster 2 reported the poorest inhibitory control. This latter cluster was also distinguished by a poorer self-reported emotion regulation, the highest prevalence of food addiction, as well as a metabolic profile characterized by the highest mean concentrations of leptin, adiponectin, and LEAP-2. Conclusions: To the best of our knowledge, this is the first study to identify well-differentiated GD clusters using neuropsychological and neuroendocrine features. Our findings reinforce the heterogeneous nature of the disorder and emphasize a role of potential endophenotypic features in GD subtyping. This more comprehensive characterization of GD profiles could contribute to optimize therapeutic interventions based on a medicine of precision.

Aim: To explore the preferences of young adults with regard to the development of a new digital add-on alcohol intervention to complement depression treatment. Methods: This qualitative study included young adults (18–35 years) with experience of either problematic alcohol use or depression or both (n = 29). Two rounds of focus groups were conducted, with two focus groups in each round. All focus groups were recorded, transcribed and analysed deductively and inductively on the basis of qualitative content analysis of the intervention type, features and design. Results: Young adults preferred a mobile health application with a clear and simple objective and navigation which was also accessible on a computer. With regard to intervention features, participants indicated a preference for in-depth, gain-framed information on alcohol use and a main feature enabling them to record their alcohol use and mood, which would be rewarded. Other preferences included personal goal-setting and monitoring, an activity list, experience stories, peer contact, guidance from experts by experience or volunteers and receiving notifications from the application. In terms of design, participants preferred short, animated videos and animation figure illustrations to complement written text. Moreover, participants rated the design of the intervention as highly important, yet very personal. Generally, participants preferred a light pastel colour scheme. Once again, participants indicated a need for a clear dashboard using pictograms to reduce the amount of text and fast, easy-to-use navigation. Conclusion: The preferences indicated by young adults with regard to the intervention type, features and design may enhance the development of a new digital add-on alcohol intervention to complement depression treatment.

Introduction: Previous research has established co-occurrence between substance use disorders (SUDs) and gambling disorder (GD). Less well understood is the temporal sequencing of onset between these disorders, and in particular whether SUD is a risk factor for GD. The present study examined the temporal order between registered diagnoses of SUD and GD, stratified by sex. Methods: A study with a longitudinal design using objective registry data drawn from the Norwegian Patient Registry was carried out. Among the patients with a registered diagnosis of GD between 2008 and 2018 (N = 5,131; males = 81.8%), those (who in addition) had a registered diagnosis of any SUD (n = 1,196; males = 82.1%) were included. The measures included a registered diagnosis using the ICD-10 of both GD (code F63.0) and SUDs (codes F10-F19) by a health care professional. Binomial tests were used to identify the temporal order between SUD(s) and GD. Co-occurring cases (i.e., cases diagnosed within the same month) were removed in the main analyses. Results: Results showed a significant directional path from SUD to GD but no support for the reversed path (i.e., from GD to SUD). This finding was similar overall for (i) both males and females, (ii) when different SUDs (alcohol, cannabis, sedatives, and polysubstance) were examined individually, and (iii) when specifying a 12-month time-lag between diagnoses. Conclusions: The findings suggest that experiencing SUD(s) is a risk marker for GD given the temporal precedence observed for patients in specialised healthcare services seeking treatment. These results should be considered alongside screening and prevention efforts for GD.

Global concern about problematic usage of the internet (PUI), and its public health and societal costs, continues to grow, sharpened in focus under the privations of the COVID-19 pandemic. This narrative review reports the expert opinions of members of the largest international network of researchers on PUI in the framework of the European Cooperation in Science and Technology (COST) Action (CA 16207), on the scientific progress made and the critical knowledge gaps remaining to be filled as the term of the Action reaches its conclusion.A key advance has been achieving consensus on the clinical definition of various forms of PUI. Based on the overarching public health principles of protecting individuals and the public from harm and promoting the highest attainable standard of health, the World Health Organisation has introduced several new structured diagnoses into the ICD-11, including gambling disorder, gaming disorder, compulsive sexual behaviour disorder, and other unspecified or specified disorders due to addictive behaviours, alongside naming online activity as a diagnostic specifier. These definitions provide for the first time a sound platform for developing systematic networked research into various forms of PUI at global scale. Progress has also been made in areas such as refining and simplifying some of the available assessment instruments, clarifying the underpinning brain-based and social determinants, and building more empirically based etiological models, as a basis for therapeutic intervention, alongside public engagement initiatives.However, important gaps in our knowledge remain to be tackled. Principal among these include a better understanding of the course and evolution of the PUI-related problems, across different age groups, genders and other specific vulnerable groups, reliable methods for early identification of individuals at risk (before PUI becomes disordered), efficacious preventative and therapeutic interventions and ethical health and social policy changes that adequately safeguard human digital rights. The paper concludes with recommendations for achievable research goals, based on longitudinal analysis of a large multinational cohort co-designed with public stakeholders.

Gender-related differences in the susceptibility, progression and clinical outcomes of alcohol dependence are well-known. However, the neurobiological substrates underlying such differences remain unclear. Therefore, this study aimed to investigate gender differences in the neuroanatomy (i.e. regional brain volumes) of alcohol dependence. We examined the volume of a priori regions of interest (i.e., orbitofrontal cortex, hippocampus, amygdala, nucleus accumbens, caudate, putamen, pallidum, thalamus, corpus callosum, cerebellum) and global brain measures (i.e., total grey matter (GM), total white matter (WM) and cerebrospinal fluid). Volumes were compared between 660 people with alcohol dependence (228 women) and 326 controls (99 women) recruited from the ENIGMA Addiction Working Group, accounting for intracranial volume, age and education years. Compared to controls, individuals with alcohol dependence on average had (3–9%) smaller volumes of the hippocampus (bilateral), putamen (left), pallidum (left), thalamus (right), corpus callosum, total GM and WM, and cerebellar GM (bilateral), the latter more prominently in women (right). Alcohol-dependent men showed smaller amygdala volume than control men, but this effect was unclear among women. In people with alcohol dependence, more monthly standard drinks predicted smaller amygdala and larger cerebellum GM volumes. The neuroanatomical differences associated with alcohol dependence emerged as gross and widespread, while those associated with a specific gender may be confined to selected brain regions. These findings warrant future neuroscience research to account for gender differences in alcohol dependence to further understand the neurobiological effects of alcohol dependence.