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 characteristics—volatility, 24/7 availability, minimal barriers to entry—may 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 Africa–Zimbabwe 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 transformer–GNN 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 Africa’s FIC, Zimbabwe’s 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 (ε = 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 Africa’s 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.
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 Türkiye. 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 Fisher’s 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, Qian’ang 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 issues—such as partial rather than complete decentralization, economic inequalities and speculation-driven markets, psychological complexities around player motivation, and technological hurdles like scalability and interoperability—complicate 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.
Purpose Using the high-frequency intraday data of the top 100 most liquid cryptocurrencies, this study aims to examine the presence of the MAX effect in the cross-sectional pricing of cryptocurrencies. Additionally, it delves into the pricing implications of idiosyncratic volatility (IVOL) and skewness, both idiosyncratic and systematic, across the cross-section of cryptocurrency returns and their interaction with the MAX measure. Design/methodology/approach Driven by the growing influence of high-frequency trading (HFT) in the cryptocurrency market, the study modifies Bali et al. ’s (2011) MAX measure by incorporating an hourly forecast horizon and 5-min log returns from the preceding hour. The relationship between MAX, IVOL and skewness over the past hour and expected returns is examined using portfolio-level analysis and Fama and Macbeth’s (1973) cross-sectional regressions. Findings The findings indicate that an increase of one standard deviation in MAX corresponds to a 0.043% decline in subsequent returns for cryptocurrencies, suggesting overvaluation due to increased demand. These results are robust to other traditional price determinants. Untangling the MAX from other proxies of the lottery, the study reveals that MAX is the true effect in the cryptocurrency market. The results are robust to several sensitivity checks, such as varying MAX measures and holding periods. Originality/value The study pioneers the investigation of lottery-like demand within cryptocurrency markets at the intraday frequency. To the best of the author’s knowledge, this is the first paper untangling the association between MAX and IVOL in the cryptocurrency market and thus offers valuable insights into investor behavior in these emerging markets.
Concerns regarding loot box fairness, along with increased exploitations of video game players and a lack of trustworthiness in video games and their merchandise, continue to rise, yet these issues have received limited attention and research. In response, this study introduces an Ethereum blockchain-based solution aimed at addressing the lack of transparency and fairness in loot box markets. Emphasizing transparency, fairness, and player trust, our model employs smart contracts to disclose reward probabilities to players, promoting informed decision-making. Central to our approach is the integration of a Random Number Generator (RNG) within the smart contract to ensure impartial outcomes. Deployed on the Sepolia testnet, designed to closely replicate the real Ethereum mainnet, our evaluation highlights improved transaction transparency and fairness. Analysis of Sepolia testnet's performance provides valuable and positive insights into blockchain operational dynamics. This paper contributes to ethical gaming practices by proposing a framework that could reshape how virtual rewards are managed, advocating for blockchain adoption to enhance gaming equity.
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.
Scott Barlowe, Kaushal Patel, Noah Hassett, Kristi Van Anderson · 5 authors
Cryptocurrencies such as Bitcoin, Ethereum, and many more use blockchain technology to facilitate a decentralized, secure, and anonymous network of financial transactions. Although desirable for legal (licit) activities, these characteristics make defining and locating patterns that potentially signal illegal (illicit) activities in an increasing number of transactions difficult. Adding to this difficulty is that transaction interactions evolve over time and may be classified as neither licit nor illicit. There has been much effort in applying both machine learning and interactive visualization to a range of cryptocurrency applications. Unfortunately, the efforts for analyzing illicit cryptocurrency transactions have mostly occurred separately, neglecting the potential of combining machine learning and interactive visualization. In this paper, we present a complete, integrated pipeline and system designed for discovering and exploring illicit transactions in a Bitcoin data set. Specifically, we use machine learning to define locations of interest by classifying all unknown transactions as either licit or illicit and then pass the fully classified data set as input to a novel, interactive visualization system. Our system’s effectiveness is illustrated with an extensive use case showing how illicit transactions can be identified and their connections explored.
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.
This chapter introduces the key issues and debates concerning esports gambling, which is becoming an increasingly substantial part of the esports industry. Various aspects of esports gambling are explored, including those that occur within games themselves and those supported by third-party platforms. Elements of esports gambling are situated within the wider ongoing convergence between digital gaming and gambling, as well as the growing interest of gambling companies in sponsoring and promoting esports events. The analysis is divided into three sections: forms, implications, and new developments in esports gambling. Concerns regarding loot boxes, skin and match betting, problem gambling, match-fixing, and the impact of new developments such as non-fungible tokens (NFTs), fantasy esports, and live streaming are addressed. Through this overview, it is demonstrated that esports gambling is a key and growing aspect of the esports domain as more money, corporate actors, and sport-like practices increasingly pervade competitive gaming. Key highlights include: (1) an overview of the main forms of esports gambling; (2) a review of the major implications of esports gambling; and (3) an introduction to emerging technological developments in esports gambling.
Ádám Bereczk, Erika Szilágyiné Fülöp, Bettina Hódiné Hernádi
The Web3 gaming and blockchain gaming landscapes have emerged as dynamic and transformative forces within the entertainment industry. A comprehensive analysis encompassing qualitative and quantitative approaches is essential to grasp these emerging sectors’ potential and trajectory fully. The study delves into the intricacies of Web3 gaming and blockchain gaming, exploring their current market size, growth drivers, prevailing challenges, and anticipated future trends. A thorough analysis of industry reports provided insights into current trends, challenges, and promising startups within the gaming space. As per our results, the Web3 gaming and blockchain gaming markets are experiencing and expecting significant growth, especially in future outlooks. The integration of Web3 into blockchain gaming is expected to accelerate, further enhancing player ownership, control, and monetization opportunities. The capital attraction of Web3 and blockchain gaming is highly correlated with the overall cryptocurrency market, suggesting that investor interest in these projects tends to rise and fall with cryptocurrency prices.
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.