Objective: The aim of this study was to examine the relationship between personality traits, impulsive behaviors and gambling tendencies among individuals who invest in cryptocurrency.Methods: The study was cross-sectional and correlational. Data were collected both online and face-to-face between September 2022 and March 2023 from 300 individuals registered at a financial center who met the inclusion criteria. Four scales were used: the Descriptive Information Form, the South Oaks Gambling Screening Scale, the Five-Factor Personality Scale, and the UPPS Impulsive Behavior Scale. Descriptive statistics and correlation analyses were used to evaluate the data.Results: The mean age of the individuals who participated in the study was 31.68±8.06 years. 79.3% of the individuals were male, 49.7% were single and 39.3% had children. While there was a statistically significant, positive correlation between the South Oaks Gambling Screening Scale scores and the agreeableness subscale scores among individuals who invest in cryptocurrency (p
Jack McGarrigle, Jessica Smith, J. Gwyn Griffiths, Jamie Torrance · 6 authors
Background and aims: Dark patterns are online platform design features that influence consumer behaviour to the advantage of the interface designer. In online gambling, such designs may exacerbate gambling-related harms, particularly among vulnerable consumers. This study aims to provide the first scoping review of dark patterns in online gambling. Methods: Following established scoping review frameworks, we systematically searched databases and grey literature using terms related to dark patterns and online gambling. The review protocol was preregistered. Results: Included articles (n = 16) addressed a variety of gambling-related dark patterns: hidden gambling management tools, inducements with complex conditions, minimum balances required to withdraw funds, unnecessary frictions involved in closing an account, high defaults in stake, deposit, reality check and deposit limit settings, and urgency-based gambling prompts. To address inconsistent terminology across studies, we synthesised existing literature by mapping identified dark patterns to a transdisciplinary framework, providing greater conceptual clarity and direction for future research. Discussions and conclusions: The potential for harm from dark patterns is evident, yet evidence on behavioural impacts is limited, hindered by restricted access to proprietary gambling operator data. Research in this area is sparse and fragmented, often using inconsistent terminology. Future studies should empirically investigate the influence of dark patterns on consumer behaviour, especially among vulnerable populations, and evaluate safer design alternatives. We recommend mandating gambling operators to collaborate with researchers to assess platform safety, and shifting the burden of proof onto operators to demonstrate that their platforms prioritise consumer safety and foster responsible gambling environments.
Project Title Understanding Financial Counsellor Perspectives On Cryptocurrency Investing Principal Investigator Ajith Perera (PhD Candidate, RMIT University) Supervisors: Dr. James Collett (Primary), Dr. Russell Conduit (Secondary) Project Description This qualitative research explores how financial counsellors conceptualise and respond to cryptocurrency-related financial harm in their professional practice. The study examines counsellors' perspectives on whether cryptocurrency engagement represents gambling, investment, or hybrid behaviours, and investigates how these conceptualisations influence intervention strategies. Financial counsellors encounter diverse presentations including voluntary problematic trading patterns and cryptocurrency-related fraud victimisation, both potentially exhibiting gambling-like psychological mechanisms such as loss-chasing and escalating commitment. Research Aims and Objectives Primary Aim: To understand how financial counsellors view and interact with clients who engage with cryptocurrencies across the gambling-investment-fraud continuum. Research Questions: How do financial counsellors decide if someone's cryptocurrency trading reflects gambling versus investment behaviours (including voluntary problematic trading and exploitation through fraudulent schemes)? What role does financial literacy play in whether clients develop problematic cryptocurrency engagement patterns? How do counsellors identify and help clients with problematic cryptocurrency engagement? What challenges do counsellors face and what training or resources do they need to address cryptocurrency-related financial harm effectively? Rationale Cryptocurrency trading has emerged as a novel phenomenon with concerning parallels to gambling addiction. Research suggests cryptocurrency's structural characteristicsâvolatility, 24/7 availability, minimal barriers to entryâmay facilitate gambling-like behaviours while also serving as a medium for investment scams exploiting similar psychological vulnerabilities. Financial counsellors occupy a unique position at the intersection of financial advice and behavioural intervention, providing direct observational evidence of how problematic cryptocurrency engagement presents in practice. Their professional experiences reveal assessment and intervention strategies unavailable through literature review alone, identifying specific training and resource needs to enhance professional capacity. This research addresses a critical knowledge gap in understanding professional responses to this emerging financial harm. Research Methodology Design: Qualitative study using semi-structured individual interviews and reflexive thematic analysis (Braun & Clarke, 2019). Theoretical Framework: Behavioural finance theory (Kahneman & Tversky, 1979), problem gambling frameworks (Blaszczynski & Nower, 2002), and professional practice theory (Schön, 1983). Data Collection: Semi-structured individual interviews (60-90 minutes each) Conducted via secure video conferencing or telephone Audio recorded with participant consent Open-ended questions exploring professional experiences, intervention strategies, and challenges Analysis Approach: Reflexive thematic analysis following Braun and Clarke's framework, allowing construction of meaningful themes through iterative engagement with rich contextual data while maintaining theoretical grounding. Participant Selection and Recruitment Sample Size: 8-15 certified financial counsellors (typical for qualitative research using reflexive thematic analysis, ensuring sufficiently rich data while maintaining analytical depth). Inclusion Criteria: Certified financial counsellors with recognized professional certification Current experience working with clients engaging in cryptocurrency-related financial presentations Able to participate in 60-90 minute interview Over 18 years of age, English-speaking Exclusion Criteria: Uncertified practitioners or those without formal financial counselling qualifications Unable to commit to interview participation requirements Under 18 years of age or non-English speakers Sampling Strategy: Purposive sampling ensuring diversity across experience levels, practice settings (private practice, non-profit, government agencies), and geographical locations (urban and regional Australia). Recruitment Methods: Professional networks and organisations (Financial Counselling Australia) Educational providers with connections to practitioners Public website searches of financial counselling practices Direct email contact using publicly available professional addresses Data Management Plan Data Collection: Audio recordings of interviews (45-60 minutes each) Interview transcripts (Word documents) Consent forms (PDF scanned documents) Participant demographic information (Excel spreadsheets) Data Storage During Project: RMIT network H: drive with password protection Separate storage of identifiable data and de-identified research data Access limited to research team only (Ajith Perera, Dr. James Collett, Dr. Russell Conduit) De-identification Protocol: Participants assigned unique codes (P01, P02, etc.) immediately following data collection Names, workplace locations, and identifying information removed from transcripts Coding key stored separately and destroyed after transcript approval by participants Audio recordings destroyed following transcription verification Data Retention: Personal identifiers: Destroyed after all participants approve transcripts De-identified research data: Retained for 5 years following publication (RMIT policy compliance) Audio recordings: Destroyed following transcription verification Ethics Approval: RMIT University Human Research Ethics Committee (Reference number: 29607) Project Benefits Individual Participants: Opportunity to reflect on professional practice and contribute to knowledge development Access to research findings that may enhance professional effectiveness Recognition of expertise in emerging area of practice Financial Counselling Profession: Evidence-based practice guidelines for addressing cryptocurrency-related financial harm Targeted training modules and specialised resources Enhanced professional capacity to support diverse client presentations Broader Community: Improved client outcomes through more effective counselling interventions Potential for early intervention reducing financial and mental health harm Contribution to public health approaches and regulatory improvements Better support for vulnerable populations (older adults, individuals with debt, disability pension recipients, regional communities) Risk Management Minimal Risks Identified: Time commitment (60-90 minutes) Potential discomfort reflecting on challenging professional cases Confidentiality concerns regarding professional reputation Risk Mitigation: Voluntary participation with right to withdraw at any time Comprehensive de-identification protocols Secure data storage and handling procedures Mental health support resources provided (Lifeline 13 11 14, Beyond Blue 1300 22 4636) Transcript review opportunity for participants Clear communication about confidentiality protections Timeline Start Date: Upon ethics approval End Date: Three years from approval date (maximum) Current Status: Ethics application submitted [insert date] Funding and Conflicts of Interest Funding: Supported by RMIT University resources Conflicts of Interest: None declared by research team Expected Outputs PhD thesis chapter Peer-reviewed journal publications in financial counselling, gambling studies, and public health Conference presentations at professional forums Practice guidelines for financial counsellors Training resource recommendations Compliance This research adheres to: National Statement on Ethical Conduct in Human Research (2023) Australian Code for Responsible Conduct of Research (2018) RMIT University research policies and procedures Privacy legislation (Victorian Information Privacy Principles) Pre-Registration Date: [insert] Ethics Reference Number: 29607
As blockchain technology advances, Ethereum based gambling decentralized applications (DApps) represent a new paradigm in online gambling. This paper examines the concepts, principles, implementation, and prospects of Ethereum based gambling DApps. First, we outline the concept and operational principles of gambling DApps. These DApps are blockchain based online lottery platforms. They utilize smart contracts to manage the entire lottery process, including issuance, betting, drawing, and prize distribution. Being decentralized, lottery DApps operate without central oversight, unlike traditional lotteries. This ensures fairness and eliminates control by any single entity. Automated smart contract execution further reduces management costs, increases profitability, and enhances game transparency and credibility. Next, we analyze an existing Ethereum based gambling DApp, detailing its technical principles, implementation, operational status, vulnerabilities, and potential solutions. We then elaborate on the implementation of lottery DApps. Smart contracts automate the entire lottery process including betting, drawing, and prize distribution. Although developing lottery DApps requires technical expertise, the expanding Ethereum ecosystem provides growing tools and frameworks, lowering development barriers. Finally, we discuss current limitations and prospects of lottery DApps. As blockchain technology and smart contracts evolve, lottery DApps are positioned to significantly transform the online lottery industry. Advantages like decentralization, automation, and transparency will likely drive broader future adoption.
The rise in illicit financial activities across the South AfricaâZimbabwe corridor, with an estimated annual loss of $3.1 billion demands advanced AI solutions to augment traditional detection methods. This study introduces FALCON, a groundbreaking hybrid transformerâGNN model that integrates temporal transaction analysis (TimeGAN) and graph-based entity mapping (GraphSAGE) to detect illicit financial flows with unprecedented precision. By leveraging data from South Africaâs FIC, Zimbabweâs RBZ, and SWIFT, FALCON achieved 98.7%, surpassing Random Forest (72.1%) and human auditors (64.5%), while reducing false positives to 1.2% (AUC-ROC: 0.992). Tested on 1.8 million transactions, including falsified CTRs, STRs, and Ethereum blockchain data, FALCON uncovered $450 million laundered by 23 shell companies with a cross-border detection precision of 94%, directly mitigating illicit financial flows in Southern Africa. For regulators, FALCON met FAFT standards, yielding 92% court admissibility, and its GDPR-compliant design (Δ = 1.2 differential privacy) met stringent legal standards. Deployed on AWS Graviton3, FALCON processed 2 million transactions/second at $0.002 per 1000 transactions, demonstrating real-time scalability, making it cost-effective for financial institutions in emerging markets. As the first AI framework tailored for Southern Africaâs financial ecosystems, FALCON sets a new benchmark for ethical AML solutions in emerging economies with immediate applicability to CBDC supervision. The transparent validation of publicly available data underscores its potential to transform global financial crime detection.
Background: The Coronavirus Disease of 2019 (COVID-19) resulted in a global shift in gambling and trading behaviors. At present, a gap exists in understanding the relationship between excessive trading behavior and problem gambling, especially during the COVID-19 period. This narrative review analyzed (1) the changes in trading and gambling activity during the COVID-19 pandemic, (2) whether the pattern of trading activity resembles problem gambling, and (3) whether excessive trading and problem gambling share similar consequences. Methods: We searched databases such as Medline, PsychINFO, Scopus, and Google Scholar using relevant keywords, and included 60 reports for narrative synthesis. Results: During the COVID-19 pandemic, there were major changes to trading behavior, possibly due to market sentiments and psychology, personal financial needs, social media influence, and the behavior of other investors. The progression of the pandemic led to an increase in brokerage account openings and an increase in trading activities among existing investors, likely due to the development of digital trading platforms that enhanced accessibility for technology-adept investors. There was also a shift from gambling at physical destinations to online gambling, with an increase in frequency and spending among individuals who continued gambling. Feelings of boredom, stress, and the need for relaxation may motivate people to engage in gambling. Conclusion: Individuals who engaged in excessive trading and problem gambling shared similar traits and may thus face similar psychiatric consequences. The findings indicate that we can apply the diagnostic criteria for pathological gambling and gambling disorders to excessive trading, given that many of these individuals meet the criteria for an addictive disorder.
Ece Mumcu, Osman Hasan Tahsin Kılıç, Aysel BaĆer
Introduction There is a continuum between gambling and investing behaviors, with speculative investment instruments positioned in the middle. Cryptocurrencies, being significantly more volatile than traditional investment tools, have increasingly been linked to gambling disorder (GD). This study aims to examine the relationship between cryptocurrency trading behavior and GD, high-risk substance use, high-risk alcohol use, and tobacco dependence among healthcare professionals in TĂŒrkiye. Methods A total of 192 healthcare professionals were assessed using the Problematic Cryptocurrency Trading Scale (PCTS), Gambling Disorder Screening Test (GDST), and the Addiction Profile Index Risk Screening Form (APIRS) (Alcohol and Drug Scales). Categorical data comparisons between two independent groups were conducted using Chi-square or Fisherâs Exact tests. Spearman correlation coefficients were used to examine relationships between PCTS scores and APIRS/GDST scores. Additionally, linear regression models assessed the predictive relationships between PCTS scores and APIRS/GDST scores. Results Among the participants, 25.5% reported engaging in cryptocurrency trading, 41.7% had tobacco dependence, 15.1% reported high-risk alcohol use, 5.7% had high-risk substance use, and 8.9% met the criteria for GD. Cryptocurrency traders demonstrated higher rates of substance use ( p = 0.033), tobacco dependence ( p < 0.001), and GD ( p = 0.043). Additionally, the severity of problematic cryptocurrency trading behavior was positively correlated with the severity of substance use ( r = 0.172, p = 0.017) and GD ( r = 0.455, p < 0.001). Conclusion The findings indicate a significant relationship between cryptocurrency trading behavior and addiction. Further research with clinical interviews and larger sample sizes is required to validate these findings. The high rates of alcohol, substance, tobacco, and gambling addictions observed among healthcare professionals underscore the need for targeted preventive measures and interventions in this population.
Jiaxin Wang, Qianâang Mao, Hongliang Sun, Jiaqi Yan
With the development of blockchain technology, crypto gambling has gained popularity due to its high level of anonymity. However, similar to traditional casinos, crypto casinos are controlled by a few internal Delegatees, making it impossible for them to achieve complete transparency and fairness. These delegatees are hidden among gamblers and are difficult to identify and distinguish in anonymous and large-scale blockchain transaction networks. This paper proposes an unsupervised dual-stage role identification method to adaptively identify key roles and hidden delegatees in label-sparse crypto casinos. Specifically, inspired by voting-style transaction patterns, we propose a novel voting influence metric for key node identification. This metric is based on one-dimensional structural entropy to capture global dissemination capability. Subsequently, we develop a multi-view graph neural network framework enhanced with two-dimensional global structural entropy minimization and self-supervised contrastive learning to improve the robustness and interpretability of hidden role partitioning. Experiments on real-world cases of the most mainstream blockchains-Ethereum, TRON, and Arbitrum-demonstrate that our proposed method effectively reveals distinct role compositions and collusion patterns, distinguishing between gamblers and delegatees. Our results achieve a higher match with identities confirmed by judicial authorities than existing methods, indicating the effectiveness and generalizability of our approach in enhancing security and regulation oversight.
This study conducted a systematic literature review (SLR) on the function and potential of non-fungible tokens (NFTs) and blockchain technology with regard to ownership in gaming. We explored theoretical viewpoints, analytical frameworks, measures, relationships, and procedures up to 2024 to examine the relationship between NFTs, blockchain, and ownership in gaming. A four-step methodology (planning, execution, analysis, and reporting) was followed, based on Tranfield et al.'s (2003) approach. The widely adopted PRISMA technique was utilized to ensure transparency and rigor in conducting the systematic literature review. The contribution of this study lies in its exploration of how NFTs and blockchain transform ownership in gaming, marking the first comprehensive SLR on this topic from the standpoint of digital asset ownership transformation. The [*expected*] findings suggest that NFTs and blockchain significantly transform traditional ownership structures in gaming by enabling decentralized, verifiable, and transferable digital assets. However, fully realizing this potential remains challenging. Persistent issuesâsuch as partial rather than complete decentralization, economic inequalities and speculation-driven markets, psychological complexities around player motivation, and technological hurdles like scalability and interoperabilityâcomplicate the path toward sustainable NFT-based ecosystems. Adoption appears influenced as much by hype and financial incentives as by informed choice. These insights underscore the necessity for developers, policymakers, and stakeholders to collaborate on clear legal frameworks, robust security measures, equitable economic models, and player-centric designs. In doing so, the gaming industry can foster genuine, enduring ownership experiences that align innovation with fairness, trust, and meaningful engagement.
Lakshit Jain, Luis Velez-Figueroa, Surya Karlapati, Mary Forand · 6 authors
BACKGROUND: Cryptocurrency trading seemingly mirrors the high-risk, high-reward nature of gambling, and may cause significant psychological challenges to traders. As cryptocurrency trading becomes mainstream, this scoping review aims to synthesize evidence from empirical studies to understand the emotional, cognitive, and social influences on cryptocurrency traders, and identify associated mental health traits/attributes influencing their behaviors. METHODS: This review adhered to PRISMA-ScR guidelines, pooling in 13 studies involving 11,177 participants across multiple countries. A detailed literature search was conducted up to August 4, 2024, and was rerun on October 9, 2024 using databases including PubMed/Medline, Web of Science, Embase, and Scopus. Keywords used included psychiatry, psychology, mental health, cryptocurrency, trading behavior, mental health, substance use, gambling, investment, and/or emotional impact. These terms were refined through iterative searches to retrieve the most relevant studies. RESULTS: The scoping review found several key psychological factors affecting cryptocurrency trading behaviors. Many traders exhibited addiction-like behaviors, compulsively trading even when it leads to financial losses. Social media was found to have a strong influence, encouraging herd behavior and impulsive decision-making to follow trends. High levels of psychological distress, including anxiety and depression, were found to be linked to the market's volatility and risks. Overconfidence bias was observed to make traders underestimate risks and overestimate their ability to predict the market. Cognitive biases like confirmation bias and the disposition effect caused traders to hold onto losing investments and sell winning ones too early. CONCLUSION: Due to the shared psychological traits between cryptocurrency trading and gambling, it is imperative to implement targeted early interventions to mitigate the risk of its progression into a pathological condition. Tools like the Problematic Cryptocurrency Trading Scale may help identify and manage risky behaviors. Ongoing research is crucial to identify both positive and negative impact of cryptocurrency trading to develop effective support systems and regulatory policies to address traders' mental well-being.
Paul Hancock, Gert Jan van Hardeveld, Jarek Jakubcek, Babak Akhgar · 6 authors
Tracing cryptocurrency transactions is a far from trivial process. This likely explains the increasing utilisation by criminal networks for a significant amount of criminal activity, not just cybercrime, but any crime requiring monetary transfers [ 1 ]. It is, therefore, vitally important that adequate training exists and is readily available for both new and experienced investigators to ensure that they are familiar with the latest techniques, tools and trends. Traditional training methods can be costly and resource-intensive, requiring highly qualified trainers to give their time to conduct training sessions. To address this issue, a training resource, in the form of a serious game, has been created. The game aims at providing a platform to improve the skills and expertise of law enforcement officers whilst reducing the workload of experienced investigators. This article describes the collaborative design and development of the serious game Cryptopol in a partnership between Europol and CENTRIC, which is a multi-disciplinary and end-user focused Center of Excellence, located within Sheffield Hallam University. Cryptopol is the first cryptocurrency-tracing training game of its kind, used by over 1,500 people representing over 550 law enforcement agencies from across the world.
Gambling is a high-risk activity that can be addictive and has both financial and personal repercussions. There is an association between gambling risk and intensive engagement in cryptocurrency trading. The management of gambling disorder has relied on medications including naltrexone and selective serotonin reuptake inhibitors (SSRIs), which have certain limitations including adverse effects and the need for longer treatment, respectively. This case report describes the use of adjunctive endoxifen in a male patient who had overinvested in cryptocurrency. The patient had used his own funds and had borrowed as well as stolen money for this purpose. The patient was counseled and treated with endoxifen, which successfully helped him overcome the habit of cryptocurrency gambling. Endoxifen is a protein kinase C (PKC) inhibitor and PKC overactivity leads to impulsivity. Hence, the use of endoxifen could be an effective strategy in the management of gambling disorders. Larger studies exploring this approach are needed.
Hongzhou Chen, Xiaolin Duan, Abdulmotaleb El Saddik, Wei Cai
Harnessing the transparent blockchain user behavior data, we construct the Political Betting Leaning Score (PBLS) to measure political leanings based on betting within Web3 prediction markets. Focusing on Polymarket and starting from the 2024 U.S. Presidential Election, we synthesize behaviors over 15,000 addresses across 4,500 events and 8,500 markets, capturing the intensity and direction of their political leanings by the PBLS. We validate the PBLS through internal consistency checks and external comparisons. We uncover relationships between our PBLS and betting behaviors through over 800 features capturing various behavioral aspects. A case study of the 2022 U.S. Senate election further demonstrates the ability of our measurement while decoding the dynamic interaction between political and profitable motives. Our findings contribute to understanding decision-making in decentralized markets, enhancing the analysis of behaviors within Web3 prediction environments. The insights of this study reveal the potential of blockchain in enabling innovative, multidisciplinary studies and could inform the development of more effective online prediction markets, improve the accuracy of forecast, and help the design and optimization of platform mechanisms. The data and code for the paper are accessible at the following link: https://github.com/anonymous.
Hilda Hadan, Leah Zhang-Kennedy, Lennart E. Nacke, Ville MÀkelÀ
Introduction In recent years, cryptocurrency has increasingly sparked interest among investors. Many people have invested in this field without adequate knowledge. Existing research has shown that using game design elements can be an effective method of education. Such learning interventions can potentially be a good match for educating market investors, as they provide risk-free simulations for novice investors to gain practical experience without having to be concerned about real financial losses. However, it is unclear how market investors perceive gamified and game-based learning interventions and whether they would adopt them for cryptocurrency education. Research Objectives Our study investigated market investorsâ perceptions, needs and expectations regarding the integration of gamification and game-based learning interventions in cryptocurrency education. Methodology We conducted an online survey with n=413 participants, including experienced market investors and people who are interested in cryptocurrency. Within the survey, we presented the mock-ups of two cryptocurrency learning interventions: a gamified cryptocurrency learning application, and a cryptocurrency learning video game. Results From market investorsâ perspectives, our study revealed the benefits and drawbacks of incorporating gamification and game design principles to facilitate learning cryptocurrency. We identified the need to develop dynamic, accessible, reliable, and community-building gamified and game-based cryptocurrency learning interventions. Conclusion From our findings, we propose guidance for the integration of gamification and games in cryptocurrency education, and we provide design recommendations for investor-specific cryptocurrency learning interventions.
In this paper, we conduct a portfolio analysis based on the lottery-like characteristics of cryptocurrencies to examine return predictability. Our results show that cryptocurrencies with higher lottery-like characteristics exhibit lower one-month ahead returns. This phenomenon, known as the lottery-like effect, suggests that investors overvalue cryptocurrencies with stronger lottery-like traits, leading to lower future returns. Moreover, the effect persists over longer horizons, and the results remain robust after controlling for other crypto-asset characteristics.
We examine the impact of a stockâs lottery-likeness on its return comovement with Bitcoin. We find that Bitcoin returns exhibit significantly stronger comovement with lottery-like stocks (LLS). Using firmsâ retail ownership and Robinhood user details to proxy for retail trading, we identify that retail investorsâ preference for speculative, high-risk, and high-reward investments, known as their gambling propensity, is the underlying channel driving the Bitcoin-LLS comovement. Our results are robust across various estimation methods, alternative measures of stock lottery-likeness, and multiple proxies for gambling sentiment including Google search volume, Baker-Wurgler sentiment index, the month of January, and the period around the Chinese Lunar New Year. These findings hold at both daily and monthly intervals and are not confounded by firms in the high-tech industry. Further analysis using Robinhood and Bitcoin usersâ net trading positions yields consistent evidence. Employing a vector autoregressive approach and an exogenous shock to Bitcoin demand, we demonstrate a spillover effect from Bitcoin to LLS. Finally, we demonstrate that Bitcoin provides more effective hedge for LLS than non-LLS.
Ahmethan Turan, Mehmet ya, Ertan lmaz, M. Munir Syam AR
Objective: Cryptocurrency trading has become widespread in recent years with developing technology and ease of use. As this is similar to gambling and pathological trading, this can produce an addiction. In this study, we aimed to examine the relationship between use of cryptocurrencies and ADHD symptoms, quality of life and sleep quality among university students. Methods: In total 921 university students were included in this study. All participants answered the sociodemographic data form, Adult Attention Deficit Hyperactivity Disorder Self-Report Scale (ASRS), 36-Item Short Form Survey (SF-36) and Pittsburgh Sleep Quality Index (PSQI) using the online questionnaire method. Cryptocurrency users additionally responded to Problematic Cryptocurrency Trading Scale (PCTS). Results: In the cryptocurrency usersâ ASRS scores were significantly higher (p<0.001), all SF-36 scores were significantly lower (for mental health subscale p=0.034, for other subscales p<0.001) in except SF-36 bodily pain scores, PSQI global scores (p<0.001) and subscales scores were found to be significantly higher (for sleep latency subscale p=0.013, for sleep disturbances subscale p=0.041, for other subscales p<0.001). Among those who cryptocurrency user, positive significant relationship was found between male gender, gambling, smoking and psychiatric history and PCTS scores (p=0.017, p=0.002, p=0.029, p=0.011 respectively). Conclusion: Cryptocurrency users have shown more ADHD symptoms, lower sleep quality and lower quality of life than non-users. Cryptocurrency use is common among university students and it should not be overlooked that it can evolve into behavioral addiction.
Decentralized exchanges are becoming a competitive necessity for Web3 users. However, they cannot beat centralized exchanges in terms of user experience. Due to expensive gas fees, the blockchain cannot implement the classic order book model which is the pillar for traditional finance exchanges. Instead, most decentralized exchanges operate on the Automated Market Maker (AMM) model using a pre-defined mathematical pricing rule. AMM is more efficient to run on the blockchain but the biggest tradeoff is impermanent loss for liquidity providers and price slippage for traders. This remains the most noticeable drawback of todayâs AMM. In this paper, we make the following contributions. First, we observe that if AMM is virtualized as an order book, its âorder-book" shape is awkwardly different from that of a real-world order book. We argue that this is conceptually connected to the above weakness. We are thus motivated to design an AMM, the first of its kind, that mimics the price impact behaviors of real-world order books. Second, the proposed AMM, thanks to this property, significantly outperforms the state-of-the-art AMM in impermanent loss. Interestingly, our AMM can even result in impermanent gain. We are also better for large orders where price slippage is a concern. Third, another feature is that, while todayâs AMM typically requires a fixed inventory ratio for the liquidity pool, the new AMM allows this ratio to vary, giving liquidity providers flexible options for joining or exiting the pool. All these advantages are offered without losing desirable properties of an AMM regarding split-order exploitation, arbitrage risks, and liquidity continuity. Our findings are validated by theoretical analysis with mathematical proofs and, also, experimental evaluation which was comprehensively conducted using two real-world datasets and a synthetic dataset representing different market scenarios. Our research is the first in the literature on AMM design that factors in statistical properties from the order book model.
Gambling sponsorships are common in international soccer due to the substantial funds they provide to clubs. For example, in the 2022/23 English Premier League season, eight clubs collectively received an estimated ÂŁ60 million from gambling shirt-front sponsorships.While the Premier League plans to ban gambling shirt-front sponsorships by 2026, this will not include shirt sleeves or pitch-side hoardings, which are the most frequently seen forms of in-game marketing. In contrast, Italy and Spain have fully banned gambling sponsorships and in-game marketing due to public health concerns. Relatedly, much less attention has been paid to the emergence of sponsorships associated with cryptocurrency or financial trading. These are both gambling-like products, which are engaged in disproportionately by those experiencing gambling-related harm, and which also use soccer to market themselves. Researchers have suggested that these products might look to fill the gap in high- level sports left by gambling sponsorship bans, and so have highlighted the need to monitor their use of sponsorship agreements with high-level soccer teams. We therefore provide an overview of gambling and gambling-like sponsorship of soccer teams within high-level leagues across England, France, Germany, Spain, Italy, Portugal, and Argentina. Overall, our findings indicate that gambling sponsorship remains prominent, but has reduced in comparison to previous seasons across most countries. However, we have observed betting âpartnershipsâ which circumvent gambling sponsorship prohibitions in Italy. In relation to cryptocurrency and financial trading companies, there are limited numbers of active sponsorships outside of the UK, but âpartnershipsâ between teams and these companies have become prevalent.
BACKGROUND: Cryptocurrencies are a popular investment tool today. However, some studies highlight the investing behavior of cryptocurrencies similar to pathological gambling. Investing behavior becomes risky when it is not based on proper and adequate analysis and carries the possibility of big losses as well as big gains. For this reason, we aimed to determine the potential risky investor profile by age, gender, personality traits and impulsivity levels. SUBJECTS AND METHODS: Six hundred and fifty-four cryptocurrencies investors (529 was male, 125 was female, their mean age was 35.6 ± 9.0) participated in this study between June 2022 - August 2022. Participants were administered the Sociodemographic Data Form, the South OAKS Gambling Screen Test - revised (SOGS-r), the Big Five Inventory (BFI-10), and Barratt Impulsiveness Scale-11 (BIS-11). RESULTS: We found higher neuroticism and impulsivity in possible problematic crypto investors. In addition, extraversion, agreeableness and conscientiousness scores were lower. Additionally, in our regression analyzes we found that younger age and male gender predicted SOGS-r scores. After controlling for age and gender, extraversion negatively and motor impulsivity positively predicted SOGS-r scores. DISCUSSION: Investing in cryptocurrencies can become a behavioral addiction, similar to pathological gambling. It is important to identify profiles in which investment behavior is risky. CONCLUSION: Personality traits and impulsivity may have a significant impact on identifying risky crypto investors and in the treatment process.