Background and aims: Despite its inclusion in the 11th revision of the International Classification of Diseases, there is a virtual paucity of high-quality scientific evidence about compulsive sexual behavior disorder (CSBD), especially in underrepresented and underserved populations. Therefore, we comprehensively examined CSBD across 42 countries, genders, and sexual orientations, and validated the original (CSBD-19) and short (CSBD-7) versions of the Compulsive Sexual Behavior Disorder Scale to provide standardized, state-of-the-art screening tools for research and clinical practice.Method: Using data from the International Sex Survey (N = 82,243; M_age = 32.39 years, SD = 12.52), we evaluated the psychometric properties of the CSBD-19 and CSBD-7 and compared CSBD across 42 countries, three genders, eight sexual orientations, and individuals with low vs. high risk of experiencing CSBD.Results: A total of 4.8% of the participants were at high risk of experiencing CSBD. Country- and gender-based differences were observed, while no sexual-orientation-based differences were present in CSBD levels. Only 14% of individuals with CSBD have ever sought treatment for this disorder, with an additional 33% not having sought treatment because of various reasons. Both versions of the scale demonstrated excellent validity and reliability.Discussion and conclusions: This study contributes to a better understanding of CSBD in underrepresented and underserved populations and facilitates its identification in diverse populations by providing freely accessible ICD-11-based screening tools in 26 languages. The findings may also serve as a crucial building block to stimulate research into evidence-based, culturally sensitive prevention and intervention strategies for CSBD that are currently missing from the literature.

Potential concerns are increasing that smartphone and Internet addictions may have deleterious effects on the mental health. Despite the recognition of the important role that implicit associations may have over explicit processes in addiction, such implicit associations have not been comprehensively investigated with respect to Internet addiction. Therefore, we modified the Implicit Association Test (IAT) for smartphone and Internet addictions and investigated its validity in children and adolescents. In this experimental study, 78 at-risk children and adolescents ranging in age from 7 to 17 years completed an IAT modified with pictures captured from the most popular Internet games among youth. Furthermore, measures of Internet and smartphone addictions, mental health and problem behaviors, impulsive tendencies, self-esteem, daily stress, and quality of life were assessed simultaneously. Significant correlations were found between IAT D2SD scores and standardized scales for Internet (r = .28, p < .05) and smartphone (r = .33, p < .01) addictions. There were no significant correlations between IAT parameters and other scales measuring the constructs that are less relevant to the features of addiction, such as daily stress levels, impulsivity, and quality of life. Multiple regression analysis revealed that the IAT D2SD was independently and positively associated with smartphone addiction (p = .03) after controlling for other clinical correlates. This study demonstrated good convergent and discriminant validity of this IAT as a novel measurement relating to Internet and smartphone addictions. Further longitudinal and prospective studies are needed to evaluate its potential utility in clinical and community settings.

Background and aims: Problem gambling among adolescents has recently attracted attention because of easy access to gambling in online environments and its serious effects on adolescent lives. We proposed a machine learning-based analysis method for predicting the degree of problem gambling.Methods: Of the 17,520 respondents in the 2018 National Survey on Youth Gambling Problems dataset (collected by the Korea Center on Gambling Problems), 5,045 students who had gambled in the past 3 months were included in this study. The Gambling Problem Severity Scale was used to provide the binary label information. After the random forest-based feature selection method, we trained four models: random forest (RF), support vector machine (SVM), extra trees (ETs), and ridge regression.Results: The online gambling behavior in the past 3 months, experience of winning money or goods, and gambling of personal relationship were three factors exhibiting the high feature importance. All four models demonstrated an area under the curve (AUC) of >0.7; ET showed the highest AUC (0.755), RF demonstrated the highest accuracy (71.8%), and SVM showed the highest F1 score (0.507) on a testing set.Discussion: The results indicate that machine learning models can convey meaningful information to support predictions regarding the degree of problem gambling.Conclusion: Machine learning models trained using important features showed moderate accuracy in a large-scale Korean adolescent dataset. These findings suggest that the method will help screen adolescents at risk of problem gambling. We believe that expandable machine learning-based approaches will become more powerful as more datasets are collected.

Motivations for pornography use may vary across gender identities, sexual orientations, and geographical regions, warranting examination to promote individual and public health. The aims of this study were to validate the Pornography Use Motivations Scale (PUMS) in a diverse, multicultural sample, and develop a short form (PUMS-8) that can assess a wide range of pornography use motivations. Using data from 42 countries (N = 75,117; M_age = 32.07; SD_age = 12.37), enabled us to thoroughly evaluate the dimensionality, validity, and reliability of the Pornography Use Motivations Scale (PUMS), leading to the development of the more concise PUMS-8 short scale. Additionally, language-, nationality-, gender-, and sexual-orientation-based measurement invariance tests were conducted to test the comparability across groups. Both the PUMS and the PUMS-8 assess eight pornography use motivations, and both demonstrated excellent psychometric properties. Sexual Pleasure emerged as the most frequent motivation for pornography use across countries, genders, and sexual orientations, while differences were observed concerning other motivations (e.g. self-exploration was more prevalent among gender-diverse individuals than men or women). The motivational background of pornography use showed high similarity in the examined countries. Both the PUMS and the PUMS-8 are reliable and valid measurement tools to assess different types of motivations for pornography use across countries, genders, and sexual orientations. Both scales are recommended for use in research and clinical settings.

Aims: This study aimed to investigate in a gender-sensitive manner factors related to at-risk/problematic Internet use (ARPIU) in a sample of young Korean adolescents. Given prior findings, we hypothesized we would observe specific temperamental, social and biological measures that would statistically predict ARPIU in boys and girls, respectively. Method: Subjects included 653 middle-school students from Chuncheon, Korea who completed measures assessing Internet addiction, mood, temperament, and social interactions. Finger digit (2D:4D) ratios were also assessed. Chi-square and logistic regression models were conducted. Results: Among boys and girls, the ARPIU and non-ARPIU groups showed differences in temperament, mood, social tendencies, and gaming behaviors. In boys, IAT correlated inversely with the 2D:4D digit ratio and novelty-seeking and positively with reward-dependence scores when controlling for BDI scores; these relationships were not found in girls. Multivariate analyses showed that among boys, novelty-seeking, harm avoidance, self-transcendence, and daily time spent gaming statistically predicted ARPIU. Among girls, daily time spent gaming, number of best friends, self-directedness, and cooperation statistically predicted ARPIU. Conclusion: ARPIU was linked to specific temperamental, behavioral and biological characteristics, with specific relationships observed in boys and girls. Specific risk factors may exist for boys and girls with respect to their propensities to developing ARPIU, suggesting the need for gender-sensitive approaches to prevent ARPIU in youth.

Objective Excessive internet use has been associated with various psychiatric symptoms and psychosocial factors. This study aimed to investigate the prevalence of internet addiction (IA) and its associations with clinical (depression/social anxiety) and psychosocial (self-esteem/perceived social support) factors in medical students.Methods In total, 408 medical students at one university in Korea were included in this study. IA symptoms were assessed with Young’s Internet Addiction Test, and scores of 50 or higher were considered to indicate IA. Participants were asked to complete the Beck Depression Inventory, Social Phobia Inventory, Rosenberg Self-Esteem Scale, and Duke-University of North Carolina Functional Social Support Questionnaire. A logistic regression model was constructed to examine the impact of clinical and psychosocial factors on IA.Results Forty-seven participants (11.5%) were identified as having IA. Self-esteem was associated with a lower risk of IA, whereas depression and social anxiety were associated with a higher risk of IA. Depression, social anxiety, low self-esteem, and low perceived social support were found to be significant correlates of IA. Young’s Internet Addiction Test score positively correlated with Beck Depression Inventory and Social Phobia Inventory scores, but negatively correlated with Rosenberg Self-Esteem Scale and Duke-University of North Carolina Functional Social Support Questionnaire scores. Furthermore, the prevalence of IA was highest in first-year medical students.Conclusion This study revealed the possible risk and protective factors of IA. Our findings indicate that strengthening self-esteem and reducing depression and social anxiety may contribute to the prevention and management of IA in medical students.