Background: Financial trading is often categorized separately from traditional forms of gambling (e.g., blackjack, poker, lottery, slot machines), as it is often viewed from an investing lens. However, the arbitrary line separating investing from gambling has become increasingly questioned, especially as it relates to high-risk trading behaviors (e.g., day trading, trading on margin) and riskier financial assets (e.g., options, cryptocurrencies). Further, the risk of gambling-related harms among financial traders appears to be amplified by new financial technologies, which have increased access to riskier financial assets and have encouraged riskier trading behaviors. Thus, the aim of the present study is to systematically review the literature assessing problem gambling among financial traders as well as the association between financial trading frequency and problem gambling. Methods: Twelve articles from three databases (SCOPUS, PsycINFO, and Web of Science) met the inclusion criteria, and were reviewed. Results: The prevalence of problem gambling was generally higher among individuals who engage in trading financial products, but rates varied substantially (1.4% to 47.2%) due in large part to differences in the study population, the problem gambling measures used, and the cutoff scores employed. Similarly, financial trading frequency was consistently associated with more severe problem gambling, but the strength of these associations ranged across studies. Conclusion: Collectively, while findings from these studies suggest that financial traders are at greater risk for problem gambling, it is evident that trading riskier assets and engaging in riskier trading behaviors place individuals at a substantially greater risk for problem gambling. Recommendations for future research include focusing on at-risk populations, practical implications for the intervention and policy, and emerging issues of digital technologies.

Smartphone overdependence among South Korean adolescents, affecting nearly 40%, poses a growing public health concern, with usage patterns varying by regional context. Leveraging conceptually informed AI/ML models, this study (1) develops a high-performing low-risk screening tool to monitor disease burden, (2) leverages AI/ML to explore psychologically meaningful constructs, and (3) provides place-based policy implication profiles to inform public health policy. This study uses data from 1873 adolescents in the 2023 Smartphone Overdependence Survey by the National Information Society Agency (NISA) in South Korea. Across the sample, the adolescents were about 14 years old (SD = 2.4) and equally distributed by sex (48.1% male). We then conceptually selected 131 features across two domains and 10 identified constructs. A nested modeling approach identified a low-risk screening tool using 59 features that achieved strong predictive accuracy (AUC = 81.5%), with Smartphone Use Case features contributing approximately 20% to performance. Construct-specific models confirmed the importance of Smartphone Use Cases, Perceived Digital Competence and Risk, and Consequences and Dependence (AUC range: 80.6–89.1%) and uncovered cognitive patterns warranting further study. Place-stratified analysis revealed substantial regional variation in model performance (AUC range: 71.4–91.1%) and distinct local feature importance. Overall, this study demonstrated the value of integrating conceptual frameworks with AI/ML to detect adolescent smartphone overdependence, offering novel approaches to monitoring disease burden, advancing construct-level insights, and providing targeted place-based public health policy recommendations within the South Korean context.

Smartphone overdependence among South Korean adolescents, affecting nearly 40%, poses a growing public health concern, with usage patterns varying by regional context. Leveraging conceptually informed AI/ML models, this study (1) develops a high-performing, low-risk screening tool to monitor disease burden, (2) leverages AI/ML to explore psychologically meaningful constructs, and (3) provides place-based policy implication profiles to inform public health policy. This study uses data from 1,873 adolescents in the 2023 Smartphone Overdependence Survey by the National Information Society Agency (NISA) in South Korea. Across the sample, adolescents were about 14 years old (SD=2.4) and equally distributed by sex (48.1% male). We then conceptually selected 131 features across 2 domains and 10 identified constructs. A nested modeling approach identified a low-risk screening tool using 59 features that achieved strong predictive accuracy (AUC = 81.5%), with smartphone use case features contributing approximately 20% to performance. Construct-specific models confirmed the importance of Smartphone Use Cases, Perceived Digital Competence & Risk, and Consequences & Dependence (AUC range: 80.6%–89.1%) and uncovered cognitive patterns warranting further study. Place-stratified analysis revealed substantial regional variation in model performance (AUC range: 71.4%–91.1%) and distinct local feature effects. Overall, this study demonstrated the value of integrating conceptual frameworks with AI/ML to detect adolescent smartphone overdependence, offering novel approaches to monitoring disease burden, advancing construct-level insights, and providing targeted, place-based public health policy recommendations within the South Korean context.

Depression is arguably the most common mental health problem. The World Health Organization (2022) estimates over 280 million people suffer from depression, with millions more likely suffering at s...

As video games increasingly incorporate gambling-like mechanics, such as loot boxes and gacha microtransactions, concern has grown over their association with problematic video gaming (PVG) and mental health outcomes. This study explores how parasocial relationships (PRs) with fictional characters, a growing phenomenon in video gaming, may influence the negative effects of in-game gambling on depression. A sample of 584 players (Mage = 24.98, SD = 5.70; 81.6% male), recruited from Reddit forums centered on video games featuring gacha, completed scales assessing risky loot box and gacha use, PVG, depressive symptoms, and whether they had a PR. Using structural equation modeling, mediation and moderated mediation models were tested. Results show that having PR is indirectly linked to depression via PVG, and that while risky in-game gambling behaviors alone did not predict depression via PVG in the general sample, PRs significantly altered this dynamic. Specifically, for individuals who reported having a PR, both risky loot box and gacha engagement indirectly predicted depression through PVG. These associations were absent, or even negative, among participants without a PR. Findings suggest that PRs with fictional characters may exacerbate gaming-related harms by increasing emotional investment and gameplay frequency, particularly in games designed to foster emotional attachment or feature in-game gambling. This study highlights PRs as a key psychological mechanism linking in-game gambling to poor mental health, reinforcing the importance of considering player–character relationships in future research and policy efforts on gaming disorder and digital spending risks.