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Background: Different classification models have been proposed to explain the heterogeneity of alcohol-related problems in general populations. Such models suggest quantitatively or qualitatively different symptom endorsement characteristics between subgroups of alcohol drinkers., Objectives: The present study aimed to identify homogenous subgroups of drinkers in a general population sample in addition to examining the relationship between the subgroups and psychopathological symptoms., Method: Data of past-year alcohol users (n = 1,520) were analyzed from the nationally representative sample of the National Survey on Addiction Problems in Hungary 2015. Latent class analysis (LCA) was conducted to identify subgroups of drinkers based on the dichotomous indicator items of the Alcohol Use Disorders Identification Test questionnaire. Multinomial logistic regression and multiple comparisons were performed to explore the relationship between latent classes and socio-demographical variables and psychopathological symptoms., Results: LCA suggested a 3-class model: "Light alcohol drinkers" (71.6%), "Alcohol drinkers with low risk of dependence" (19.3%), and "Alcohol drinkers with severe dependence symptoms" (9.1%). More severe subgroups showed significantly higher level of anxiety, depression, hostility, obsessive-compulsivity, interpersonal sensitivity, and psychiatric or alcohol use disorder-related treatment involvement. Male gender, younger age, lower level of educational achievement, and earlier onset of the first alcoholic drink were associated with membership of more severe subgroups., Conclusions: The present results indicated that severity-based subgroups of drinkers can be discriminated. Approximately 9% of the alcohol users showed severe symptoms of alcohol dependence. The present data also supported the association between more severe forms of alcohol consumption, and internalizing and externalizing characteristics. Although the 2 at-risk classes of alcohol drinkers did not differ in terms of alcohol consumption-related measures, they were distinguished by the level of harmful consequences due to alcohol use, psychopathological symptoms and psychiatric treatment history., (© 2019 S. Karger AG, Basel.)

Background: Work has a crucial role in individuals' productivity, social life, and psychological well-being. Despite various definitions of work addiction in the literature, the number of psychometrically reliable instruments is limited., Objectives: The aim of this study was to psychometrically test and revise the factor structure of the Work Addiction Risk Test (WART), one of the most widely used instruments assessing work addiction., Method: The full version of the WART [Robinson, Post, & Khakee, 1992] was assessed using a nationally representative sample of Hungary (n = 2,710). To increase validity, the analyses were conducted among individuals who worked at least 40 h a week (n = 1,286, 43% women, mean age = 38.9 years, SD = 10.8)., Results: Using confirmatory factor analysis, the originally proposed 4- and 5-factor solutions did not have adequate model fit indices. Thus, the sample was randomly divided into 2 subsamples. Exploratory factor analysis conducted in the first half of the sample supported a 4-factor solution, which was confirmed in the other half of the sample. The Work Addiction Risk Test Revised (WART-R) comprises 17 items and 4 factors (i.e., Overcommitment, Impatience, Hard-working, and Salience). Using a latent class analysis, a cutoff score (51 points out of 68) for the high risk of work addiction was determined. Almost one in 10 participants (9.3%) were identified as being symptomatic of work addiction, and these individuals also reported an elevated level of mental distress and hostility., Conclusions: As a conclusion, the WART-R is suitable to be used as an indicator of work addiction based on clinically relevant symptom dimensions., (© 2019 S. Karger AG, Basel.)

Aim: The aim of our study was to analyze psychometric properties of the Cannabis Abuse Screening Test (CAST)., Methods: Our sample comprised Hungarian high school (n = 476; male 56.3%; mean age 19.0 years, SD = 0.65 years) and college students (n = 439; male 65.1%; mean age 23.9 years, SD = 1.56 years) who reported cannabis use in the past year. The sample covered the five biggest universities of Hungary. Besides the CAST, participants responded to the Munich-Composite International Diagnostic Interview. Factor structure was analyzed by a confirmatory factor analysis. Receiver operating characteristic curve analysis was made to assess cut-off scores. Data collection took place in 2010., Results: CAST proved to be a reliable (Cronbach's α 0.71 and 0.76) one-dimensional measure. Regarding both cannabis dependence and cannabis use disorders, a cut-off of 2 points proved to be ideal in both samples, resulting in optimal specificity, negative predictive values and accuracy, but less than optimal positive predictive values (dependence) and low sensitivity (cannabis use disorder)., Discussion and Conclusions: In line with former results, the CAST proved to be an adequate measure for the screening of cannabis-related problems among adolescents and young adults in an Eastern European country where this scale has not been studied before., (© 2013 S. Karger AG, Basel.)