Problem gambling Wikipedia

To determine the global PG prevalence rate, evaluate gender- and age-based differences, and measure the level of heterogeneity between studies. Heterogeneity across studies was assessed using the Q statistic and the I2 statistic, with values of I2 ≥ 50% indicating substantial heterogeneity (Higgins & Green, 2011). Potential sources of heterogeneity were explored through subgroup analyses and meta-regression, where the effects of covariates such as geographical region were examined.

• The gambling industry continually evolves, and online gambling in particular has made access easier, which is only making it harder for people to recover.
• “This has coincided with a huge spike in online gambling – more than half of all gambling in Australia is now happening online.
• Gambling addiction is a treatable condition.Start by speaking with a mental health or addiction professional.
• To enhance transparency and robustness in future research, we recommend the standardisation of reporting diagnostic methods, explicitly stating whether DSM criteria are assessed via self-report or diagnostic interviews.
• While some studies were peer-reviewed and internationally accessible, others were local and less readily available.

However, research indicates certain patterns and higher-risk groups, including those with mental health disorders, a history of substance abuse, or high impulsivity. College students and adolescents are among those most at risk due to early exposure and a lack of awareness around gambling-related consequences. Overall, gambling behaviours and addictions are issues that are largely overlooked in clinical practice and research priorities in India. Given the commonalities in etiology and characteristics between pathological gambling and other addiction-related problems, the former should not be viewed independently in research and clinical inquiry (Rash et al., 2016). Also, future research is needed to examine trends in the prevalence of gambling disorders, given its relation with social and legal sanctions.

Third, more research would be needed on the effects of different types of online gambling (computer-based or mobile-based) on gambling behaviors and harms. There is a partial overlap in diagnostic criteria between problem gambling and substance use disorders; pathological gamblers are also likely to have a substance use disorder. The “telescoping phenomenon” reflects the rapid development from initial to problematic behavior in women compared with men. This phenomenon was initially described for alcoholism, but it has also been applied to pathological gambling.

Cumulative Weekly GE by Income Tertiles

This difference in types of gambling7 is relevant when considering targeted interventions. It should also highlight the devastating rates of addiction in gambling as a whole, regardless of gender. This paper has investigated how land-based, online, and multimode gambling differ in terms of socio-demographics, gambling participation, gambling settings, and addictive behaviors. The results confirm that the three modes have specific characteristics that may also be related to their harm potential.

To date, there has not been a comprehensive examination to determine whether this risk pattern holds consistently across different jurisdictions. These apps track your play patterns and learn the best time to prompt you to play more. So even when you try to take a break from gambling, the apps may give you a $10 bonus to entice you to come back. Now with improvements in artificial intelligence, we will likely see even more strategies for getting people to gamble more. When asked to rate their feelings towards gambling out of 10, where 10 represented that they loved it, and 0 represented that they hated it.

Gambling participation and harm on the rise in Australia, new study reveals

The current study also leaves a few additional gaps that should be addressed in future research. Further studies should assess whether smoking status or other addictive behaviors are connected to different gambling modes (cf. Wardle et al. 2011). Second, further studies should also address the question of how gambling modes are connected to other health and wellbeing issues. As online gambling may be connected to poorer mental health at least among men (Edgren et al. 2017), it is possible that multimode gamblers also have a different profile in terms of health.

While the study found most Australians — around 50 per cent — were considered non-risk gamblers, which means they did not experience harm related to the practice, the study found there had been a rise in people who experienced some form of gambling-related harm. Of the three gambling modes, land-based gambling (52.6 %) was the most common, followed by multimode gambling (29.1 %). Gambling severity and risky alcohol consumption were used as measures of addictive behavior. Problem gambling was measured using the South Oaks Gambling Screen including 20 items (SOGS; Lesieur and Blume 1987; 1993). SOGS has been used as the primary instrument for assessing the prevalence of problem gambling in Finland (Salonen et al. 2020a).

Current students

WalletHub’s 2025 report ranks these states among the most gambling-addicted in the U.S.11 Regional differences often reflect the types of gambling available and regulatory approaches taken by state governments. In this systematic review, the Joanna Briggs Institute (JBI, 2020) Critical Appraisal Checklist for Studies Reporting Prevalence Data was employed to assess the methodological quality of included studies. This checklist is specifically designed to evaluate the validity and reliability of prevalence data, ensuring that our synthesis is based on robust evidence. It addresses key aspects such as sampling technique, data collection methods, and appropriate statistical analysis, providing a thorough framework for assessing the trustworthiness of the reported prevalence rates. Based on the checklist assessments, decisions were made to include studies, exclude them, or seek further information to resolve ambiguities in reporting or methodology.

Gambling participation and harms have also been connected to channels or modes of access. The socio-demographic profile of online gamblers has also been shown to differ from that of land-based gamblers (Mora-Salgueiro et al. 2021). Even the same activity provided in online modalities may lead to more harms than in land-based environments (Gainsbury et al. 2019; Gainsbury 2015). Factors reflecting socio-demographics, gambling participation, and addictive behaviors were https://gameaviatorofficial.com/ analyzed using multinomial regression analysis (Table 2).

Gambling frequency, the number of game types gambled, and gambling mode were recoded into four categories. Young or emerging adults, specifically those between 18 and 24, face the highest risk for developing gambling disorders. Several factors contribute to this heightened vulnerability, including impulsivity, ongoing brain development, and the increasing normalization of gambling through easily accessible apps and video games. In the U.S., gambling is a growing industry4—alongside it, gambling addiction is quietly affecting millions. Studies also suggest that this number will only continue to grow, with involvement in sports gambling5 quadrupling from 2004 to 2018. It’s one that touches families, communities, and lives in deeply personal ways.