Journal of Gambling Studies最新文献

The Gambling Motives Questionnaire - Financial (GMQ-F) is the most widely used scale for assessing gambling motives. Although previous research supports the reliability and validity of GMQ-F scores, no study has examined its psychometric properties among sports bettors, which present distinct demographics and clinical characteristics. To this end, this study evaluated the psychometric properties and measurement invariance of the GMQ-F among 920 sports bettors. We hypothesized that the GMQ-F would exhibit a four-factor structure and conducted a confirmatory factor analysis (CFA) and exploratory structural equation modelling (ESEM) to test model fit. Participants completed measures assessing their demographic characteristics, sports betting behaviours (frequency, time spent, bet type), and problem gambling. Results indicated that the ESEM model provided an excellent fit, outperforming the CFA model, with a clear four-factor structure (social, enhancement, coping, financial) that better captured the relationship between gambling motives while allowing for minimal cross-loadings. Measurement invariance testing revealed that the GMQ-F was consistent across different types of sports bettors (in-play, single-event, and traditional), gender (man vs. woman), and ethnicity (White vs. Racialized). Regression analyses showed that social, coping, and financial motives were positively associated with problem gambling severity, while enhancement motives were negatively related to problem gambling severity among sports bettors. These findings provide evidence supporting the validity and reliability of GMQ-F scores for assessing gambling motives, and suggest its utility across a range of demographic and sports betting subgroups.

Delayed reward discounting (DRD) refers to the phenomenon where future rewards are perceived as less valuable compared to immediate rewards. The extent of this devaluation has been repeatedly linked to addictive behaviors. DRD could play an important role in the development and maintenance of problem gambling. We aim to better understand the relationship between DRD and problem gambling, examine temporal changes in DRD, and evaluate its predictive value for adherence. We conducted a secondary analysis of data from participants in the Win Back Control study (n = 345), a two-arm RCT that demonstrated effectiveness in reducing problematic gambling behavior. DRD was assessed using the Monetary Choice Questionnaire (MCQ), the severity of problem gambling was measured with the Problem Gambling Severity Index (PGSI), and gambling symptom severity was evaluated using the Gambling Symptom Assessment Scale (G-SAS). DRD is significantly positively associated with gambling symptom severity (G-SAS: b = 13.90, p = 0.002) and problem gambling severity (PGSI: b = 9.39, p < 0.001). DRD decreased significantly on a weekly basis over the three measurement time points (b = -0.001, p < 0.001). DRD could not be identified as a mediator, which should be further investigated in future studies. DRD is significantly positively associated with problem gambling severity and gambling symptom severity. DRD does not serve as a predictor of adherence. DRD decreases over the three time points along with severities of gambling behavior and gambling symptoms. However, the findings are correlational and may be affected by attrition bias.

The illusion of control (IoC) is a cognitive distortion implicated in risky and problem gambling. This study aimed to validate a comprehensive IoC measure, the Multi-Dimensional Rating Scale for Illusion of Control in Gambling (EEMDIC), in a large non-clinical sample of adult and aging gamblers, and to clarify how IoC relates to gambling severity, game type, and age. A total of 1,311 participants aged 40-75 completed the EEMDIC, the Problem Gambling Severity Index (PGSI), and questions on gambling habits and sociodemographics. Exploratory (n = 649) and confirmatory (n = 662) factor analyses assessed scale structure. ANOVAs, linear regressions, Mann-Whitney U tests, and Spearman correlations examined associations with game category, PGSI scores, education, occupation, and age. Factor analyses supported a reduced 14-item EEMDIC with four coherent factors: Luck, Skill, Strategy, and Rituals/Superstitious Behaviors. Higher EEMDIC scores, especially on primary-control dimensions (Skill, Strategy), were associated with greater gambling severity and engagement in strategic betting (sports, horse racing). Education correlated negatively with IoC, and occupational differences emerged. Age was modestly but significantly associated with lower IoC: it explained ≈ 2.8% of total variance and 0.9-4.1% across factors. Framing on gains or losses showed no age effect after controlling for PGSI. The EEMDIC is a reliable, multidimensional tool distinguishing primary and secondary control beliefs. Findings link primary-control beliefs to gambling harm and show modest age-related declines in IoC. The scale can inform targeted prevention and tailored interventions across game types and sociodemographic groups.

Mobile sports betting is an increasingly popular way to wager in the United States, but few studies have examined the social cognitive predictors of engaging in this specific form of gambling. The present studies were designed to do so with the application of the Reasoned Action Approach (RAA; Fishbein & Ajzen, 2010). Study 1 was a belief elicitation study that identified the most common behavioral, normative, and control beliefs regarding mobile sports betting. Study 1 also reported an initial test of the degree to which attitude, perceived normative pressure, and perceived behavioral control predict intentions to place mobile sports bets. Study 2 examined the predictive validity of the identified beliefs and tested whether future betting behavior can be predicted from the model. The RAA significantly predicted mobile sports gambling intentions and future behavior. The most important beliefs contributing to the prediction of mobile sports gambling were the degree that participants endorsed gambling is fun and easy, leads to addiction, and results in winning money. Implications for future research and interventions are discussed.

During the mid-2010s, microtransactions within digital games became more common, raising concerns that the gambling-like features in these games would contribute to increases in gambling problems. However, studies on the topic have been mostly cross-sectional. To fill this gap, this study uses longitudinal nationwide survey data collected from 949 adult Finnish participants every six months from the spring of 2021 to the fall of 2024 to investigate the impact of microtransactions on gambling problems-measured using the Problem Gambling Severity Index (PGSI)-over time. Gambling participation, mental health issues, and alcohol use were used as control variables, and age and gender were used as background variables. The results showed that although microtransactions had significant positive fixed and random effects on gambling problems, the effects disappeared when gambling participation was added to the models. Therefore, the effect of microtransactions on gambling problems may only be indirect. This implies that the main regulatory focus should be on actual gambling participation, whether or not it is encouraged by the purchasable content in some digital games.

The rapid rate of technological advancement has led to a proliferation of online gambling applications in Africa. This has resulted in an unprecedented rise in problem gambling across sub-Saharan Africa. In addition, the rapid growth of the gambling industry has outpaced laws and regulations aimed at consumer protection, limiting the scope of problem gambling interventions. Using a sample of 905 gamblers from Kenya, this study investigated the impact of peer effects and warning messages on gambling behavior using a lab-in-the-field randomized controlled trial. This study found no evidence that peer effects had an impact on gambling behavior. However, gambling warning messages reduced the total amount wagered by 8% and the number of betting rounds played by 4%. Furthermore, the peer effects and warning message condition increased the number of betting rounds played by 13%. Peer interaction likely caused riskier decisions and compulsive gambling, which could have undermined the effectiveness of the warning message. In conclusion, while warning messages offer a potential strategy for minimizing gambling-related harm, and messaging relating to the effects of peer interaction is likely to increase their effectiveness.

Emerging adults are at elevated risk for gambling-related harm, even at low-level of engagement. This study examines how gender, group identification, and social presence interact to affect gambling intensity in novice gamblers. Participants included 48 males (Mage = 18.69, SD = 1.24) and 61 females (Mage = 18.46, SD = 0.74), with ages ranging from 17 to 23 years, were screened using the Brief Sensation Seeking Scale-Chinese Version. Group identification was manipulated using the Cyberball paradigm, and social presence was varied through either a virtual audience (videoconference) or simulated co-actor win announcements. Gambling intensity was assessed using multiple gambling indicators, including remaining chips, risk-taking index, average betting time, average betting size, and total betting size. Multivariate ANOVA revealed significant main effects of gender, along with a significant interaction between gender and group identification. Notably, males with high group identification demonstrated significantly greater gambling intensity-characterized by increased betting frequency, larger wagers and higher risk-taking-compared to those with low identification. In contrast, females showed little susceptibility to group identification. These findings highlight the differential impact of social identity on gambling behavior by gender, suggesting that prevention strategies for novice gamblers should specifically target social identification processes within gambling environments.

The spread of new technologies has profoundly transformed gambling practices, extending their reach into both private and professional domains. Understanding how managers perceive these phenomena is essential for designing effective preventive interventions in organizational contexts. This qualitative study explored the perceptions of 33 Italian managers regarding gambling, associated risks, and the role of personal devices. Semi-structured interviews were conducted and analyzed using inductive thematic analysis. Seven themes emerged, organized into three main areas: (1) perceptions of gambling, including differences in prevalence, motivations for gambling, and perceived changes linked to digitalization; (2) perceptions of risk, highlighting both protective factors (e.g., education, awareness, controlled environments) and major risks such as social and family deterioration, economic difficulties, and illegality; (3) use of personal devices, with managers describing blurred boundaries between work and private life, alienating aspects of constant connectivity, but also perceived benefits in terms of efficiency and reassurance. The findings show that managers' perceptions are marked by both awareness and misconceptions, which play a crucial role in shaping organizational responses. Preventive strategies should therefore be grounded in how the phenomenon is actually perceived in workplace contexts, to ensure greater acceptability and sustainability.

Large Language Models (LLMs) have transformed information retrieval for humans. People are increasingly turning to general-purpose LLM-based chatbots to find answers to questions across numerous domains, including advice on sensitive topics such as mental health and addiction. In this study, we present the first inquiry into how LLMs respond to prompts related to problem gambling, specifically exploring how experienced gambling treatment professionals interpret and reflect on these responses. We used the Problem Gambling Severity Index to develop nine prompts related to different aspects of gambling behavior. These prompts were submitted to two LLMs, GPT-4o (via ChatGPT) and Llama 3.1 405b (via Meta AI), and their responses were evaluated via an online survey distributed to human experts (experienced gambling treatment professionals). Twenty-three experts participated, representing over 17,000 hours of problem gambling treatment experience. They provided their own responses to the prompts and selected their preferred (blinded) LLM response, along with contextual feedback, which was used for qualitative analysis. Llama was slightly preferred over GPT, receiving more votes for 7 out of the 9 prompts. Thematic analysis revealed that experts identified strengths and weaknesses in LLM responses, highlighting issues such as encouragement of continued gambling, overly verbose messaging, and language that could be easily misconstrued. These findings offer a novel perspective by capturing how experienced gambling treatment professionals perceive LLM responses in the context of problem gambling, providing insights to inform future efforts to align these tools with appropriate guardrails and safety standards for use in gambling harm interventions.