empirical research on gambling

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Published: 04 February 2021

The association between gambling and financial, social and health outcomes in big financial data

Naomi Muggleton ORCID: orcid.org/0000-0002-6462-3237 1 , 2 , 3 ,
Paula Parpart 2 , 3 , 4 ,
Philip Newall ORCID: orcid.org/0000-0002-1660-9254 5 , 6 ,
David Leake 3 ,
John Gathergood ORCID: orcid.org/0000-0003-0067-8324 7 &
Neil Stewart ORCID: orcid.org/0000-0002-2202-018X 2

Nature Human Behaviour volume 5 , pages 319–326 ( 2021 ) Cite this article

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Gambling is an ordinary pastime for some people, but is associated with addiction and harmful outcomes for others. Evidence of these harms is limited to small-sample, cross-sectional self-reports, such as prevalence surveys. We examine the association between gambling as a proportion of monthly income and 31 financial, social and health outcomes using anonymous data provided by a UK retail bank, aggregated for up to 6.5 million individuals over up to 7 years. Gambling is associated with higher financial distress and lower financial inclusion and planning, and with negative lifestyle, health, well-being and leisure outcomes. Gambling is associated with higher rates of future unemployment and physical disability and, at the highest levels, with substantially increased mortality. Gambling is persistent over time, growing over the sample period, and has higher negative associations among the heaviest gamblers. Our findings inform the debate over the relationship between gambling and life experiences across the population.

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Data availability.

The data that support the findings of this study are available from LBG but restrictions apply to the availability of these data, which were used under license for the current study, and so are not publicly available. Data are available from the authors upon reasonable request and with permission of LBG.

Code availability

Data were extracted from LBG databases using Teradata SQL Assistant (v.15.10.1.9). Data analysis was conducted using R (v.3.4.4). The SQL code that supports the analysis is commercially sensitive and is therefore not publicly available. The code is available from the authors upon reasonable request and with permission of LBG. The R code that supports this analysis can be found at github.com/nmuggleton/gambling_related_harm . Commercially sensitive code has been redacted. This should not affect the interpretability of the code.

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Acknowledgements

We thank A. Trendl and H. Wardle for comments on an earlier draft of this manuscript. We thank R. Burton, Z. Clarke, C. Henn, J. Marsden, M. Regan, C. Sharpe and M. Smolar from Public Health England and L. Balla, L. Cole, K. King, P. Rangeley, H. Rhodes, C. Rogers and D. Taylor from the Gambling Commission for providing feedback on a presentation of this work. We thank A. Akerkar, D. Collins, T. Davies, D. Eales, E. Fitzhugh, P. Jefferson, T. Bo Kim, M. King, A. Lazarou, M. Lien and G. Sanders for their assistance. We thank the Customer Vulnerability team, with whom we worked as part of their ongoing strategy to help vulnerable customers. We acknowledge funding from LBG, who also provided us with the data but had no other role in study design, analysis, decision to publish or preparation of the manuscript. The views and opinions expressed are those of the authors and do not necessarily reflect the views of LBG, its affiliates or its employees. We also acknowledge funding from Economic and Social Research Council (ESRC) grants nos. ES/P008976/1 and ES/N018192/1. The ESRC had no role in study design, data collection and analysis, decision to publish or preparation of the manuscript.

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Department of Social Policy and Intervention, University of Oxford, Oxford, UK

Naomi Muggleton

Warwick Business School, University of Warwick, Coventry, UK

Naomi Muggleton, Paula Parpart & Neil Stewart

Applied Science, Lloyds Banking Group, London, UK

Naomi Muggleton, Paula Parpart & David Leake

Department of Experimental Psychology, University of Oxford, Oxford, UK

Paula Parpart

Warwick Manufacturing Group, University of Warwick, Coventry, UK

Philip Newall

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School of Economics, University of Nottingham, Nottingham, UK

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Contributions

P.P. and P.N. proposed the initial concept. All authors contributed to the design of the analysis and the interpretation of the results. J.G. and N.S. wrote the initial draft; all authors contributed to the revision. N.M. and P.P. constructed variables and N.M. prepared all figures and tables. D.L. established collaboration with LBG. D.L., J.G. and N.S. secured funding for the research. P.N. conducted a review of the existing literature.

Corresponding author

Correspondence to Naomi Muggleton .

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Competing interests.

N.M. was previously, and D.L. is currently, an employee of LBG. P.P. was previously a contractor at LBG. They do not, however, have any direct or indirect interest in revenues accrued from the gambling industry. P.N. was a special advisor to the House of Lords Select Committee Enquiry on the Social and Economic Impact of the Gambling Industry. In the last 3 years, P.N. has contributed to research projects funded by GambleAware, Gambling Research Australia, NSW Responsible Gambling Fund and the Victorian Responsible Gambling Foundation. In 2019, P.N. received travel and accommodation funding from the Spanish Federation of Rehabilitated Gamblers and in 2020 received an open access fee grant from Gambling Research Exchange Ontario. All other authors have no competing interests.

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Muggleton, N., Parpart, P., Newall, P. et al. The association between gambling and financial, social and health outcomes in big financial data. Nat Hum Behav 5 , 319–326 (2021). https://doi.org/10.1038/s41562-020-01045-w

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Received : 26 March 2020

Accepted : 23 December 2020

Published : 04 February 2021

Issue Date : March 2021

DOI : https://doi.org/10.1038/s41562-020-01045-w

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Emerging Gambling Problems and Suggested Interventions: A Systematic Review of Empirical Research

Affiliations.

1 Faculty of Arts, Department of Political Science, University of Alberta, Edmonton, AB, Canada. [email protected].
2 Faculty of Arts, Department of Political Science, University of Alberta, Edmonton, AB, Canada.
PMID: 35460439
DOI: 10.1007/s10899-022-10122-w

The goal of the present systematic review is to identify emerging gambling problems and the harm minimization strategies proposed to address them. Our interdisciplinary research team conducted this systematic literature review in 5 nations between which there is significant gambling research exchange. A keyword search of the Scopus and Web of Science databases followed by filtering using inclusion criteria identified 1292 empirical gambling studies from peer-reviewed journals. The data obtained from the articles were analyzed using the content analysis technique. We then used a unique approach to identify relationships between harm minimization strategies and gambling problems. The findings reveal that the most frequently reported gambling problems are related to young gamblers, online gambling, electronic gaming machines, and children and adolescents (underage gamblers). Harm minimization strategies to address these included creating educational and awareness programs, further restrictions on gambling advertising, developing an intervention mechanism for online gambling, and remote gambling-related help (i.e., online counseling, online treatment).

Keywords: Gambling problems; Interventions; Systematic review.

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Published: 01 September 2023

Is gambling like a virus?: A conceptual framework and proposals based on empirical data for the prevention of gambling addiction

Mariano Chóliz 1

BMC Public Health volume 23 , Article number: 1686 ( 2023 ) Cite this article

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The objective of this study is to present a conceptual framework for the prevention of gambling disorder and try to corroborate some of its postulates. The assumption of gambling as if it were acting like a virus may have important considerations in terms of preventing gambling disorder in society and, therefore, it could be a relevant public health issue.

Like COVID-19, gambling disorder is a disease which is caused by the action of an external agent. The external agent was already in existence, but certain environmental conditions (absence of regulatory measures based on the prevention of gambling disorder) favored its propagation. Regarding immunization, for SARS-CoV-2, it is obtained through vaccination and prevention of exposure. However, it is unlikely that immunization can be developed for any gambling addiction prevention program to immunize everyone who is exposed to the “gambling virus”. So, in the case of gambling disorder, preventive strategies should rather prevent gambling from affecting most people by limiting availability (supply) and accessibility (ease of access) to gambling.

Study design

This research is a quasi-experimental investigation aimed to evaluate the effects of anti-COVID measures on the frequency of gambling and evolution of gambling disorder. The present study analyzed gambling patterns and the problems caused by gambling in 2,903 people, including those who were at-risk gamblers or had a gambling disorder.

In general terms, restrictive measures to combat COVID-19 worked to prevent the consolidation of gambling habits and the appearance of gambling disorder, but they did not seem to be sufficient for people who already had this disorder. The most affected games were electronic games machines (EGMs) that took place in public places (gambling halls, bars and restaurants, etc.).

Conclusions

The findings of this work support the hypothesis that, just as the SAR-CoV-2 virus is responsible for the global pandemic of COVID-19, which can only be stopped with vaccines and social distancing, in the case of gambling, the absence of an effective vaccine for "gambling virus" can lead to an epidemic of gambling disorders in societies, if the environmental conditions that are favorable for the spread of such virus are not modified. Some preventive strategies that can be useful from a public health frame of reference are suggested.

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Introduction

The assumption of gambling as if it were acting like a virus may have important considerations in terms of preventing gambling disorder in society and, therefore, it is a relevant public health issue. So, the comparison between gambling and SARS-CoV-2 seems appropriate to guide health policies that aim to prevent gambling disorder, just as they have been taken worldwide for the prevention of COVID-19.

Gambling disorder shares some characteristics of infectious viral spread, such as that of the COVID-19 pandemic. The consideration of gambling as a virus is metaphorical, but it seems adequate for describing the increasing prevalence of gambling disorder in countries where gambling has been legalized and promoted; just as for COVID-19, preventive measures must be developed for this disorder.

First, gambling disorder shares some of the characteristics of infectious spread caused by viral transmission with COVID-19. Some of the most relevant include the following:

Like COVID-19, gambling disorder is a disease. Not all psychological problems are considered illnesses. Only the psychological problems listed in DSM-5-TR or ICD-11 are considered mental disorders [ 1 , 2 ].

The disease is caused by the action of an external agent. The agent of COVID-19 is SARS-CoV-2, whereas the activity of betting itself is ultimately responsible for the genesis of gambling disease. This assertion is based on the guidelines in the Diagnostic and Statistical Manual of Mental Disorders (Fifth Edition Text Revision) of the American Psychiatric Association (APA), which states that “ gambling behaviors activate reward systems similar to those activated by drugs of abuse and produce some behavioral symptoms that appear comparable to those produced by substance use disorders” (DSM-5-TR, p. 543) [ 1 ].

On the contrary, many other mental illnesses (i.e., schizophrenia and psychotic, bipolar, obsessive-compulsive, neurocognitive, and personality disorders, etc.) are not typically caused by an external agent.

The external agent was already in existence, but certain environmental conditions favored its propagation, which then occurred to a greater extent with a greater speed. SARS-CoV-2 jumped from other animals to humans and spread extremely quickly. In the case of gambling, it has always been present, but when economic interests and favorable regulations generate a “breeding ground,” its expansion in society is favored. Global commercial gambling has grown to be an industry of extraordinary size and power [ 3 ]. The effects of the expansion of gambling not only harm the most vulnerable people [ 4 ], but also condition government policies, affecting society in general [ 5 ].

This turns gambling disorder from a mental health problem into a public health problem [ 6 ], since they are the environmental conditions that favor the appearance, development and spread of gambling disorder. Not all mental disorders caused by an external agent are a public health problem (i.e., trauma and stressor-related disorders, feeding and eating disorders, etc.). For that reason, gambling addiction requires policy action to prevent harm [ 7 , 8 ], mainly reduce availability, make access difficult and restrict (or forbid) the commercial promotions [ 9 ].

Second, if gambling is a disease that is transmitted due to favorable environmental conditions, which is why it has become a public health problem, it is worth asking whether the principles upon which measures to prevent the spread of COVID-19 are based would be useful in preventing gambling addiction in society.

Prevention of COVID-19 is based on two principles: immunization against the virus and prevention of the contagion.

Regarding immunization, for SARS-CoV-2, it is obtained through vaccination. The effect of virus inoculation in provoking the body's autoimmune response is well known in Medicine. However, there is nothing quite like it in Psychology when it comes to gambling, since gambling a bit (even "responsibly") does not prevent the onset of gambling disorder [ 10 ]. Rather, on the contrary, it favors the spread of the disease because, with responsible gambling actions, governments and gambling companies make the gambling look better [ 11 , 12 ]. So, it is unlikely that immunization can be developed for any gambling addiction prevention program to immunize everyone who is exposed to the “gambling virus”. Actually, the psychological resources that could immunize anyone involved in gambling are unknown. But even if those resources were discovered, what would not be possible is to train all citizens in such skills, contrary to what has happened with the vaccination of SARS-CoV-2.

Thus, in the case of gambling disorder, preventive strategies should rather reflect the second tier of action against COVID-19, that is, prevent gambling from affecting most people by limiting availability (supply) and accessibility (ease of access) to gambling [ 9 ]. This is especially important for the more dangerous variants of gambling, such as electronic gaming machines (EGMs) and online gambling [ 13 , 14 ]. Unlike the variants of SARS-CoV-2, in the case of gambling we can identify previously where the different variants of "gambling virus" are, which would allow us to implement appropriate preventive measures for specific games. Likewise, just as there are less contagious and lethal variants of SARS-CoV-2, there are also games, such as lotteries, that are less addictive and harmful than EGMs and various types of online gambling. In the case of COVID-19, the danger posed depends on the DNA structure whereas, for gambling, the structural characteristics of the games are the most important factors [ 15 , 16 , 17 ]. Therefore, measures to prevent gambling addiction must be adapted to each type of game.

However, once a person has been exposed to the effects of gambling, the next phase of prevention (selective prevention) would be to control the effect that gambling has on people who risk their money; i.e., recognizing the appearance of symptoms and acting effectively in response. As with the vaccine, it is not possible to train all gamblers to carry out gambling behaviors that prevent the development of gambling disorder. It is not possible for players to develop responsible gambling behaviors if the conditions in which gambling is offered in society do not drastically change [ 18 ]. In the case of selective prevention, again it must be public health policies that must be implemented.

Probably the most effectives preventive strategies in selective prevention are to limit losses and prevent affected people’s access to gambling [ 18 ]. In these cases, governmental regulation of gambling seems essential, because those affected are not able to reduce their exposure to gambling, nor are companies interested in reducing their income, which mainly comes from people who suffer from gambling addiction [ 19 ].

Finally, once a person has been infected and suffers from gambling disorder, it is necessary to use other measures beyond access control or limit losses. Gambling disorder is a clinical phenomenon [ 20 ] characterized by a loss of control over behavior that results not only in spending excessive amounts of money but also in alterations in emotional adjustment and interpersonal relationships. Psychological treatments for gambling disorder should not only reduce or eliminate gambling behavior, but also promote other alternatives that favor a new lifestyle without gambling [ 21 ]. Behavior modification techniques have been shown to be effective in reducing or eliminating excessive behaviors, training in coping techniques and in promoting alternative adaptive behaviors [ 21 , 22 , 23 ]. This is the only way to immunize against the effects of the “gambling virus”, but it is not a universal prevention procedure, since it is not possible to "immunize" the entire population in this way, but only patients undergoing psychological treatment. Effective preventive measures for the entire population must be carried out through gambling policies, that is, through gambling regulation [ 8 ].

In this sense, the effect on the pattern of gambling and gambling problems of the measures carried out for the prevention of COVID-19 can guide legislators and governments on the specific measures that must be taken to prevent gambling disorder from a public health perspective [ 15 ].

In a recent systematic review of 34 studies from 12 countries [ 24 ], it was concluded an overall reduction in gambling amongst the general population during the COVID-19 pandemic at the level of the general population. However, marked increases in gambling amongst young adults (18–30 year olds) and people with pre-existing at-risk gambling. There was conflicting evidence among the different studies regarding educational, employment status or socioeconomic level.

The main objective of the research is to describe the changes in gambling patterns and addiction that have occurred in Spain one year after the lockdown was implemented to counteract the COVID-19 pandemic. The results of this study analyzed from the conceptual framework that we have just described, will serve to guide gambling policies based on public health.

The first research hypothesis is that the frequency of gambling will decrease because the measures to prevent COVID-19 also restrict access to gambling. However, such measures will not affect all types of gambling equally, only those types that take place in public spaces (e.g., gambling halls, casinos, etc.). Online gambling via electronic devices (e.g., mobile phones, computers, and tablets) will not be affected.

The second hypothesis is that the type of game is relevant when it comes to causing addiction, due to the structural characteristics of the different games. Therefore, people who play landscape gambling and online gambling (e.g., casinos, bingo, and slots online) are more likely to suffer from gambling disorder than those who play lotteries.

Participants

In total, 2,903 people (55.6% women and 44.4% men) between the ages of 15 and 85 (Mean = 36.5; SD = 14.6) years participated in this study by responding to an Internet survey during the period from May–November, 2021. The survey was distributed over the Internet by 251 professionals and attendees of gambling addiction prevention training courses from several regions of Spain. The participants knew the objective of the research and freely agreed to participate.

Instruments

Gambling participation.

A survey on gambling behavior was administered. In this survey, participation in gambling before and after the measures taken to combat the COVID-19 pandemic was evaluated by self-report. The results were categorized into three groups based on the restriction conditions applied by government authorities aiming to prevent COVID-19, as follows:

No restrictions: online gambling .

Moderate restrictions: lotteries . There were 2 months without lottery draws at the beginning of the restriction period. After the restriction period, the lotteries returned to pre-pandemic conditions.

Severe restrictions: landscape gambling . For several months access to some game types was prevented and subsequently the capacity of gaming halls was limited.

Gambling problems

Gambling participation and gambling problems before and after the measures taken to minimize SARS-CoV-2 virus transmission were evaluated in the same survey. To avoid response bias, two different diagnostic questionnaires were used, both of which met the necessary methodological requirements:

Brief Problem Gambling Screen [ 25 ]. A five-item questionnaire to identify people who suffer from gambling disorder and at-risk gambling. The psychometric analysis of the scale performed with the data from this study showed adequate internal consistency ( Cronbach α = .76).

NORC DSM-IV Screen for Gambling Problems, NODS [ 26 ]. A 17-item yes/no scale that aims to diagnose pathological gambling according to the diagnostic criteria of the DSM-IV-TR. It was adapted to the current DSM-5 criteria. The range of the scale scores is 0–9. The psychometric analysis of the scale using the data from this study showed high internal consistency ( Cronbach α = .94).

People who regularly (≥ 1–2 times per month) played different types of games based on the above categories were selected for analysis. Responses pertaining to gambling participation and the incidence of problem gambling were compared between two time points: before the implementation of preventive measures against the pandemic (March 20, 2020) and approximately 1 year later (May–November 2021), once the restrictive measures had been eliminated and it was possible to play again with relative normality.

To avoid bias in the response to the gambling addiction evaluation questionnaires, two different diagnostic questionnaires (BPGS and NODS) were used. The diagnosis of pathological gambling before the pandemic was made with the BPGS scale, while the evaluation of this disorder after the measures taken to minimize SARS-CoV-2 virus transmission was done using NODS.

Table 1 gives the percentages of people in this study who regularly played some game (> 1–2 times per month) before and after COVID-19 preventive measures were in place.

There was a reduction in frequent participation in all types of gambling, with the greatest reductions for landscape games.

A complementary way to understand the changes that occurred is to study whether current regular gamblers were also regular players before the pandemic. Table 2 shows the percentage of regular gamblers after implementation of the COVID-19 preventive measures who already were frequent gamblers, considering the different game types.

The type of gambling with a lower percentage of new gamblers was lotteries (5.33%). No differences were found in the percentage of new gamblers between landscape and online gambling.

Differences according to sex

The percentage of women and men affected by gambling problems (risk gambling and gambling disorder) in this study are indicated in Table 3 .

Women who participated in this study reported fewer gambling problems than men, both in terms of gambling disorder ( χ 2 = 20.65; p < 0.001; φ = 0.09) and risk gambling ( χ 2 = 45.77; p < 0.001; φ = 0.13).

Changes in gambling disorder incidence

Regarding gambling disorder, Table 4 lists the percentages of participants who exhibited gambling disorder before and after the implementation of pandemic-related preventive measures.

More survey participants exhibited pathological gambling after the pandemic than before the restrictive measures were taken (231 vs. 67). Most people who exhibited gambling disorder before the pandemic also manifested it later (74.6%), whereas only 6.4% of those who did not engage in pathological gambling before the pandemic developed gambling disorder after the measures were implemented. Of the people with gambling disorder after the pandemic, 21.6% had a gambling disorder before, while only 0.6% of those without current gambling disorder showed pathological gambling before the restrictive measures were taken. The difference in these percentages was significant ( χ 2 = 416.21; p < 0.001; φ = 0.38).

Gambling disorder with regard to the different types of gambling

Regarding gambling disorder among those who frequently engaged in different types of gambling, we summarize the main results in Table 5 . Our results also consider whether gamblers regularly partake in a single type of gambling (lotteries, landscape, or online gambling) or several types.

Conclusions and discussion

The objective of the research was to analyze the effect on gambling behavior and gambling disorder that the measures to restrict access to public places that were taken to avoid COVID. Some preventive strategies based on the the conceptual framework and the results of this research are suggested.

The results were partially consistent with the hypotheses, because the main reduction in gambling frequency occurred in landscape gambling, which is the type of gambling that suffered the most from restrictive access measures. There was also a reduction in the frequency of lottery gambling, although the measures were temporary. These results are congruent with other research showing a reduction in gambling frequency during lockdown measures [ 27 , 28 , 29 , 30 ]. Unexpectedly, there was also a decrease in the frequency of online gambling, even though it was widely promoted and advertised and there was a very noticeable increase in spending on online gambling during this period of time [ 31 ]. This result may be due to the fact that this research is not an epidemiological study, in which it is intended to evaluate the prevalence of gambling behavior before and after the measures adopted to prevent COVID-19, but the changes produced in the gambling behavior after the implementation of such measures. For that reason, only the results for people who gambled regularly were analyzed.

The percentage of people who participated in different betting games regularly decreased markedly after preventive measures were taken, especially in games that take place in gambling venues or public places with slot machines, as is the case for bars and restaurants in Spain. Therefore, it seems that the measures taken globally to prevent the spread of SARS-CoV-2 could have had an effect in reducing the frequency of gambling, because at one year after implementation of the most restrictive measures, the percentage of people who frequently participate in gambling seemed to be lower. This is a positive outcome in terms of preventing gambling addiction, because frequent gambling is one of the main factors favoring the development of gambling disorder.

This reduction occurred especially in games that take place in venues (gambling halls, bars, etc.) where gamblers have to be physically present and can spend several hours playing at a time. Many of the people who gambled frequently stopped doing so, especially those who previously went to gambling venues or gambled in public places. It is likely that the increase in new frequent players will be at a rate similar to that found in this study, in the range of 1.5–3%. With the restrictive measures taken against the expansion of COVID-19, many of the frequent gamblers who had not yet consolidated the habit of gambling or developed gambling disorder before the pandemic may not return to a frequent pattern of gambling when conditions return to normal, at least for now. If this has helped people to modify their lifestyles, it would have served as a positive preventive measure against gambling addiction.

When it comes to gambling disorder, the majority of those who currently suffer from pathological gambling had already suffered from it before the implementation of COVID-19 measures, whereas only a small percentage of people who did not currently suffer from gambling disorder exhibited symptoms before the pandemic. This may be related to the restrictive measures implemented to prevent the spread of SARS-CoV-2 being useful in also preventing the promotion of new cases of pathological gambling. However, the measures were not sufficient to solve the problem for those who were already suffering from gambling disorder. That is to say: pathological gamblers need specialized treatment. These results are consistent with other investigations that have found no significant reduction in gambling frequency for those who were most engaged in gambling pre-lockdown, especially pathological gamblers [ 32 ].

Not all types of gambling were equally affected by the restrictive measures. Hence, when analyzing the changes associated with pathological gambling after the implementation of preventive measures, differences in the addictive potential of the different types of gambling (landscape, lotteries, and online gambling) must be considered. The addictive potential of the different types of gambling is evidenced when comparing the percentage of pathological gamblers in the groups that regularly gamble in only one type of game. Regular lottery players had five to six times lower rates of gambling disorder and risky gambling behavior compared to those who frequently played landscape gambling or online gambling. Approximately 80% of the people who regularly played these games were found to suffer from pathological or at-risk gambling, which is a very high figure in our opinion. This is due to the structural characteristics of electronic games [ 15 , 16 , 17 ] (landscape gambling) and online gambling [ 33 ].

For this reason, we consider it necessary to take measures restricting access to these specific games (EGMs and online gambling) to prevent the development of pathological gambling in society, i.e., to avoid the spread of the “gambling virus.” However, once a person has been infected and suffers from gambling disorder, it is probably necessary to use other therapeutic measures beyond access control itself.

This study had some limitations. Like most studies that have analyzed the effect of COVID-19 on gambling behavior [ 24 ], it is a cross-sectional study, rather than longitudinal, and may have been affected by recall bias. Another limitation is that we focused on self-report data. Although this study was carried out with general population (that is, it was not a study with clinical population), the sample is not random and it was selected by addiction prevention professionals. Therefore, it is not an epidemiological study and, accordingly, data on the prevalence of gambling disorder in general population cannot be concluded. The fact that there were more participants in the survey with problem gambling after the pandemic than before does not necessarily mean that there was an increase in the incidence of pathological gambling, but rather that people with a current problem with pathological gambling were more interested in responding to the survey. However, most of the analyses conducted on problem gambling have been conducted, not with the general population, but with people who frequently participate in gambling. This allows us to assume that the conclusions deduced here about differences in the risk of addiction for the different types of gambling and the differential impacts of preventive measures are somewhat valid. However, the conclusions must be treated with caution because it is a correlational study and, although the number of respondents is high, it lacks an experimental design.

The main conclusions of this study are the following:

Conceiving of gambling as a virus has important implications for the prevention of gambling disorder. Although it is not possible to implement universal vaccination for consequences of gambling, such that people are immune to it, some measures taken to prevent the spread of SARS-CoV-2 based on lockdown and social distancing may be also useful to prevent gambling disorder. Some examples could be regulating long distances between bookies and schools or among gambling rooms, authorizing EGMs only in gambling rooms and casinos (not in bars or restaurants), etc [ 18 ].

Just as there are less contagious and lethal variants of SARS-CoV-2, there are also gambling games, such as lotteries, that are less addictive and harmful than EGMs and various types of online gambling. In the case of COVID-19, the danger posed depends on the DNA structure, whereas for gambling the structural characteristics of the games are the most important factors. Some preventive measures could include the modification, by law, of some parameters of the games to make the game virus less addictive. For example: restrictions on gambling speed; delaying the time between the bet and the outcome; reduction of maximum bet size; diminishing the percentage of win; posting the payoff probabilities; reducing the frequency of “near-miss” outcomes on EGMs; or prevent, through the use of gambling smart cards, gamblers from losing large amounts of money [ 18 ].

As in the case of virus infections, measures to prevent the spread of disease must also be adapted to social and environmental conditions, placing special emphasis on the most socially and economically vulnerable groups. Therefore, gambling advertising and commercial promotions must be limited. Even in capitalist societies, public health must take precedence over the economic benefits of companies. Paraphrasing the philosopher Michel Sandel, moral limits must be applied to the market [ 34 ]; in the case of gambling virus, such moral limits should enforce to gambling companies.

Availability of data and materials

For security reasons, the datasets generated and/or analysed during the current study are not publicly available due none Gambling and Technological Addictions Research Unit databases can be found on the Internet (Management agreement), but are available from the corresponding author on reasonable request.

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Acknowledgements

• Addictions Service of the Government of the Valencia City Council (PMD).

• Addictions Service of the Government of the Balearic Islands (PADIB).

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Chóliz, M. Is gambling like a virus?: A conceptual framework and proposals based on empirical data for the prevention of gambling addiction. BMC Public Health 23 , 1686 (2023). https://doi.org/10.1186/s12889-023-16610-x

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J Behav Addict
v.5(4); 2016 Dec 1

The conceptual and empirical relationship between gambling, investing, and speculation

Jennifer n. arthur.

1 Faculty of Health Sciences, School of Psychology, The University of Adelaide, Adelaide, Australia

Robert J. Williams

2 Faculty of Health Sciences, University of Lethbridge, Lethbridge, Canada

Paul H. Delfabbro

Background and aims.

To review the conceptual and empirical relationship between gambling, investing, and speculation.

An analysis of the attributes differentiating these constructs as well as identification of all articles speaking to their empirical relationship.

Gambling differs from investment on many different attributes and should be seen as conceptually distinct. On the other hand, speculation is conceptually intermediate between gambling and investment, with a few of its attributes being investment-like, some of its attributes being gambling-like, and several of its attributes being neither clearly gambling or investment-like. Empirically, gamblers, investors, and speculators have similar cognitive, motivational, and personality attributes, with this relationship being particularly strong for gambling and speculation. Population levels of gambling activity also tend to be correlated with population level of financial speculation. At an individual level, speculation has a particularly strong empirical relationship to gambling, as speculators appear to be heavily involved in traditional forms of gambling and problematic speculation is strongly correlated with problematic gambling.

Discussion and conclusions

Investment is distinct from gambling, but speculation and gambling have conceptual overlap and a strong empirical relationship. It is recommended that financial speculation be routinely included when assessing gambling involvement, and there needs to be greater recognition and study of financial speculation as both a contributor to problem gambling as well as an additional form of behavioral addiction in its own right.

Introduction

The relationship between financial market activity and gambling has been debated for quite some time (e.g., Dewey, 1905 ; Lapp, 1909 ; MacDougall, 1936 ; McMath, 1921 ; Proctor, 1887 ). This debate continues today. Within the financial sector, it is common to identify certain stock market activities as gambling-like (e.g., Boyer & Vorkink, 2014 ; Dorn, Dorn, & Sengmueller, 2012 ; Hazen, 1991 ; Kumar, 2009 ; Skeel, 2009 ). Similarly, within the gambling field, population surveys of gambling participation sometimes include questions about high-risk stocks, speculative investments, and/or day trading in addition to traditional forms of gambling ( Williams, Volberg, & Stevens, 2012 ; Williams, Volberg, Stevens, Williams, & Arthur, 2016 ).

Although financial market activity and gambling both entail financial risk, most people tend to regard these things as fundamentally different. The purchase of guaranteed investment certificates (GICs), government or corporate bonds, and company shares (stocks) are often thought of as “investments,” with the term investment having connotations of low risk, positive expected returns, influenced by skill and knowledge, and a wise thing to engage in. In contrast, gambling has connotations of being high risk, with negative expected returns, influenced primarily by chance, potentially addictive and/or financially ruinous, and involving a completely different set of activities. As will be discussed in this paper, there is a fair bit of truth to these distinctions. Indeed, the harmful and addictive potential of gambling is well established, attributable in part to the short-term time frame of most gambling activities (usually seconds or minutes), the existence of “continuous forms” of gambling (e.g., slot machines, casino table games) that allow for a rapid series of bets, and the negative expected return of most games. As these structural features tend to be absent in investment, “problematic investing” is expected to be extremely rare, if it exists at all.

That being said, within the financial sector there is a continuum between investment and more “speculative” activities that are shorter term, higher risk, and with a primary focus on making a monetary profit. Examples of speculation are:

– Day trading and high-frequency trading , where stocks are bought and sold in the same day with the express purpose of making an immediate profit on minor changes in valuation.
– Penny stocks (also known as “lottery stocks”) of companies with relatively little or no actual assets (the reason their stock price is usually so low) but with a small chance of increasing to many multiples of their current value if their venture is successful.
– Shorting : This involves borrowing the stock, immediately selling it, and then hoping the market value of the stock declines so the person can repurchase it at this lower price, return it to the lender, and make a profit.
– Derivatives : There are speculative elements to the derivatives market, where people enter into off-exchange contracts relating to the performance of a stock, commodity, or index on the actual exchange and where the asset may in fact never actually be purchased. The purchase of “options” to buy or sell a commodity or stock at a specified price before a specified date is one example. “Futures contracts” and “forward contracts” are another type of derivative where the buyer agrees to purchase an asset (and the seller agrees to sell the asset) at a specific future point in time for a price that is currently determined.

The extent to which financial speculation is similar to gambling is the extent to which it may have similar addictive and harmful aspects. The primary purpose of the present paper is to identify the similarities and differences between gambling, speculation, and investment by a review of both their conceptual and empirical relationship. Aside from the academic value of this investigation, the overlap between these activities has important clinical implications. Although problem gambling is a well-recognized entity, the contribution of speculative financial activity to problem gambling is not well researched, and very little is known about problematic financial speculation as a potential behavioral addiction in its own right.

The first part of this paper consists of a comprehensive analysis of the conceptual similarities and differences between gambling, speculation, and investment. The second part of the paper involves the identification of all articles speaking to their empirical relationship and a summary of these findings.

A two-stage search strategy was used to identify relevant articles. It started with the use of the keywords “gambling,” “speculation,” “investment,” in combination with the words “definition” “versus,” and “relationship” in the following electronic databases, restricting the search to articles published in English:

– ABI/INFORM Global
– Academic Search Complete
– Business Source Complete
– EconLit
– MEDLINE
– National Bureau of Economic Research
– PsycINFO
– ScienceDirect

As a significant percentage of gambling-related literature is contained in non-academic sources, this literature search was supplemented by a search of gambling-specific databases:

– Alberta Gambling Research Institute Digital Collection
– Australian Gaming Council’s eLibrary
– E-Library – Responsible Gambling Council (Ontario)
– Gambling Research Australia’s Gambling Research Database
– Gambling Research Database (GambLIB)
– Gambling Research Exchange Ontario Knowledge Repository
– Problem Gambling Library (New Zealand)
– Responsible Gambling Infohub

The second part of the search strategy involved checking the reference list of all relevant articles to identify other potentially relevant articles.

Conceptual relationship between gambling, investing, and speculation

Close to 60 articles and books were identified that either proposed definitions of gambling, speculation, and/or investment and/or have attempted to delineate one of these entities from the others (e.g., Allen, 1952 ; Angel & McCabe, 2009 ; Arthur, 2000 ; Borna & Lowry, 1987 ; Brenner, 1996 ; Brenner & Brenner, 1990 ; Clark, 1987 ; Cohen, 1970 ; Hazen, 2005 ; Holliday & Fuller, 1975 ; Jacoby, 1950 ; Kreitner, 2000 ; Lynch, 2012 ; McMillen, 1996 ; O’Malley, 2003 ; Productivity Commission, 2010 ; Smith, Hodgins, & Williams, 2007 ; Szado, 2011 ; Williams et al., 2016 ).

Fortunately, there is reasonable consistency in the various definitions that have been proposed for “investing” with the following, capturing the sentiments of most: “purchasing or allocating money into an asset with the expectation of long term capital appreciation or profits deriving from that asset” (e.g., Bogle, 2012 ). Similarly, although there have been dozens of definitions of gambling proposed over the years, the following definition is fairly representative “staking money or material goods on an event having an uncertain outcome in the hope of winning additional money and/or material goods” ( Williams et al., 2016 ). There has been less consistency in the definitions proposed for speculation. Nonetheless, there is general agreement that compared to investing, speculation usually refers to financial market activities that tend to be shorter term, higher risk, with higher and lower gains and losses, and with a primary focus on making a monetary profit from price movement without regard for the fundamental value of the asset.

These above articles also contain diverse opinion concerning the attributes that differentiate gambling, speculation, and investment. The remainder of this section will review these attributes, as conceptual clarity can be advanced by a thorough understanding of how these activities are best differentiated. The attributes that are most commonly invoked as differentiating gambling, investing, and speculation are: the types of activities and instruments used, time frame, level of risk, positive or negative expected return, and role of chance versus skill. Less commonly invoked attributional differences involve: whether an asset has been purchased or not, whether a stake has been made, whether there is a definitive outcome associated with a definitive event, and the economic utility of the activity.

Activities and instruments

Investment and speculation generally involve a set of activities and instruments quite distinctive from gambling activities. Gambling typically involves the purchase or participation in lottery tickets, scratch tickets, bingo, horse racing, sports betting, private wagers, electronic gambling machines (slots, video lottery machines, pokies, fruit machines, and fixed-odd betting terminals), and various classic casino table games (e.g., poker, roulette, craps, blackjack, and baccarat). In contrast, investment and speculation are typically associated with the purchase of GICs, bonds, stocks, commodities, currencies, real estate, derivatives, and collectibles.

However, there are a few activities that involve intersections between gambling and investment/speculation. One is lottery-linked savings accounts and premium bonds. These are savings accounts and bonds where part of the accrued interest is won in periodic lotteries by a small number of people who hold these bonds and/or savings accounts ( Guillén & Tschoegl, 2002 ; Tufano, 2008 ). Another is financial indices wagering . This is when a person places a bet on the direction of a financial index (e.g., composite index, currency value, and commodity value) or the specific future value of a stock or financial index (“spread betting”), with an agency external to the financial exchange. Financial indices betting is actually a very old type of gambling popular in the late 1800s and early 1900s known as “bucketeering” with the venues offering this activity being known as bucket shops ( Fabian, 1999 ; Woodlock, 1908 ). When this activity was eventually made illegal it was put into the gambling section of most legal codes. Also consistent with its gambling affiliation is the fact that the recent reintroduction of financial indices betting was made by well-established online gambling providers (in 2007 by Bet365, Ladbrokes, Paddy Power, and William Hill; Williams, Wood, & Parke, 2012 ; Wood & Williams, 2007 ). Most countries (not Australia, Malta, Cyrus, or the Netherlands) have also deemed this activity to be gambling, and therefore do not subject the profits to taxation (the United States does tax gambling profits), unlike capital gains on financial markets which are subject to taxation ( Rayman, 2013 ).

It is more difficult to separate investment from speculation on the basis of the instruments and activities engaged in, although GICs and bonds tend to be associated with the former, and derivatives with the latter. Stocks, commodities, currencies, real estate, and collectibles can be either investments or speculative depending on the specific risk profile of the instrument.

Most forms of investment are held for a period of months or years. In contrast, in most forms of gambling the outcome is known within just seconds (scratch tickets, electronic gambling machines, and casino table games), minutes (bingo, horse racing, keno), or days (i.e., lotteries, and sports betting). However, while this is a fairly strong distinction, there are some forms of sports betting with much longer horizons (e.g., betting on which sports team will eventually win the championship several months later). The time frame for speculation is quite variable depending on the type of activity. Day trading and high-frequency trading involve a time frame of seconds, minutes, and hours whereas penny stocks, shorting, options, and futures generally have time frames of weeks, months, and sometimes years.

Level of risk

Risk is defined as the likelihood of one’s wager or investment being completely lost. There is a high risk of losing one’s stake in most forms of gambling, although there are some exceptions to this rule. For example, betting on the heavy favorite in horse racing or sports betting confers both low risk and low return. Investment vehicles such as GICs, bonds, mutual funds, and blue-chip stocks tend to entail low risk. In contrast, speculative activities such as day trading, penny stocks, shorting, and options and futures tend to be high risk, although the overall financial risk can sometimes be mitigated when these high risk vehicles are hedged with an offsetting position or contained in a more diversified portfolio.

Positive or negative expected return

Risk is related to expected return. Investments in the form of GICs have positive expected returns as long as the financial institution offering the GIC continues to exist. Positive expected return is also true of most bonds and stocks over time ( Dimson, Marsh, & Staunton, 2009 ; Liu, Whited, & Zhang, 2009 ; O’shaughnessey, 1998 ; Siegel & Coxe, 2002 ). In contrast, virtually all commercially provided forms of gambling are designed to have a negative mathematical expectation over time for the player (e.g., Hannum & Cabot, 2005 ). However, this is not the case for all forms of gambling. Sports and horse race betting, card counting at blackjack, and person-to-person games (e.g., poker, mahjong) are types of gambling where a long-term positive expected return occurs for a small number of more knowledgeable and skilled gamblers ( Hayano, 1984 ; Silberstang, 1988 ).

This mixed pattern of returns in gambling is not that dissimilar to the mixed returns with speculation. Although the limited evidence on short-selling suggests it often tends to be profitable ( Choie & Hwang, 1994 ), the evidence is mixed for futures contracts (e.g., Dusak, 1973 ; Kearns & Manners, 2004 ), and largely negative for day traders. Most day traders lose money over the long run, with the minority having positive expected returns largely capitalizing on the overall positive trend of the stock markets over time ( Barber, Lee, Liu, & Odean, 2014 ; Jordan & Diltz, 2003 ; Ryu, 2012 ). Penny stocks, in addition to their association with fraudulent promotion ( Goldstein & Cox, 1990 ; Tillman, 2005 ), tend to significantly underperform the market over time ( Bali, Cakici, & Whitelaw, 2011 ; Boyer, Mitton, & Vorkink, 2010 ; Bradley, Cooney, Dolvin, & Jordan, 2006 ; Eraker & Ready, 2015 ).

It is also worth noting that there is a significant difference in the variability of returns for gambling versus investment and speculation, as commercial gambling has a precise and mathematically determined negative return, whereas both the size and the direction of the month-to-month and year-to-year changes in financial markets are much more variable and uncertain.

Role of chance versus skill

Chance or randomness is one of the features of gambling that has been historical used to distinguish it from investing and/or speculation (e.g., O’Malley, 2003 ; Reith, 2002 ). However, as mentioned earlier, while randomness is a central feature of many gambling games (e.g., lotteries, scratch tickets, electronic gambling machines, bingo, and most casino table games), skill does have a significant influence on the outcome of some gambling activities (i.e., horse race betting, sports betting, and all person-to-person games such as poker, golf, etc.).

What many people fail to realize is the central role that chance also has in the financial markets. Most economists agree that the major financial markets are fairly “efficient,” meaning the current bid/ask price of a stock or commodity is a fairly accurate valuation, as it is an aggregate real-world reflection of what investors know about the stock/commodity in terms of company management, cash and capital assets, and future prospects ( Chan, Gup, & Pan, 2003 ; Malkiel, 2003 ; Verheyden, De Moor, & Van den Bossche, 2015 ). Two important corollaries of efficient markets are that (a) day-to-day directional changes in stock valuation are largely independent of the previous valuation (i.e., random) ( Fama, 1995 ; Malkiel, 2003 ), and (b) the only way of obtaining higher than average returns on the general market is if the person has information that the general public is unaware of (“insider information”), and/or he/she has superior analytical powers in judging the relative importance of the publicly available information.

The evidence indicates that despite the heavy reliance on research and information to select investments, only a small percentage of professional analysts and traders are able to consistently outperform the average return of the market ( Andersson, 2004 ; Bhootraa, Dreznerb, Schwarzc, & Stohsd, 2015 ; Cuthbertson, Nitzsche, & O’Sullivan, 2010 ; Dickens & Shelor, 2003 ; Fama & French, 2010 ; Porter, 2004 ). [Nonprofessional investors generally underperform the market due to higher rates of trading (thereby incurring higher transaction costs) and choosing higher-risk financial products ( Barber & Odean, 2000 ; Barber, Lee, Liu, & Odean, 2009 ; Grinblatt & Keloharju, 2000 ; Kumar, 2009 ; Schlarbaum, Lewellen, & Lease, 1978a , 1978b ).] The recognition that most investment managers do not perform above chance accuracy has led to the popularity of “index funds” that simply attempt to track the performance of the general market (and that have very low management fees).

Asset purchase

Although not often mentioned as a distinguishing feature, asset purchase is actually one of the most distinguishing features of investment versus gambling. By its very definition, investment involves creation or purchase of an asset, with financial gains or losses being due to capital appreciation or depreciation of the asset. In contrast, there is no asset purchase in gambling, rather one’s own money or material goods are put forward as a “stake.” Furthermore, external monies are provided when the bet is won (no external monies are usually provided for investment gains).

Some forms of speculation involve purchase of an asset (i.e., day trading, penny stocks, and shorting), but other forms do not. One example is an options contract that gives someone the ability to purchase or sell an asset but does not oblige them to. Some types of futures contracts also do not involve purchase of an asset (e.g., weather derivatives related to future precipitation and/or temperature). Although buying futures contracts usually involves the future acquisition of an asset, futures contracts are often resold for a profit or loss before physical delivery of the asset actually occurs. It is notable that up to the 1930s futures contracts for commodities and stocks in North America were unenforceable (and sometimes illegal), as they were legally considered wagers rather than contracts due to the fact that a physical delivery of an asset was not required ( Hazen, 1991 ; Kreitner, 2000 ). Finally, with respect to penny stocks, it is questionable whether ownership of stock in a company that itself has little or no assets actually qualifies as purchase of an asset.

All forms of gambling involve the staking or proffering money or material goods. In contrast, the asset is never explicitly staked in investment. Similar to gambling, most forms of speculation can be construed as staking material goods (i.e., a recently purchased asset or a contract) in the hope of a favorable future valuation of that asset so that this asset or stake can be sold and a profit realized.

Definitive event and outcome

All forms of gambling have a definitive outcome associated with a definitive event. In contrast, there is no specific point in time in which there is a definitive outcome or event associated with investment. In some situations, the investor may not have any intent of ever selling the asset.

Some forms of speculation do not have a definitive outcome associated with a definitive event. Penny stocks are an example. Short selling also does not have a definitive date in which the shares have to be repurchased and returned. However, short sales are virtually always “covered” at some point, as the borrower is often paying interest on a margin account and/or dividend costs for the sold shares. Most other forms of speculation have fairly definitive outcomes associated with definitive events, as all options have expiry dates, futures contracts have to be fulfilled by a certain date, and day traders and high frequency traders generally sell the asset on the same day the purchase is made.

Economic utility

The economic value of traditional financial market activity and investing is fairly clear. For example, purchasing government bonds or stocks in a company provides funds to support government or industry endeavors. In contrast, gambling is largely a sterile transfer of wealth from one sector of the economy to another ( Borna & Lowry, 1987 ; Williams, Rehm, & Stevens, 2011 ). While there is some truth to distinction, it is too broad a generalization, as there are some situations where gambling does have economic value. This occurs when the patron base of the gamblers is from outside the jurisdiction, resulting in an influx of new wealth to the local economy ( Williams et al., 2011 ). It is also true that adding a new and interesting service/good to the economy (e.g., gambling) can have economic value by at least temporarily spurring increased overall monetary circulation and increasing GDP ( Walker, 2007 ; Walker & Jackson, 1998 , 2007 ).

Speculation does not have the same economic utility as investing ( Lynch, 2012 ). Warren Buffett has described derivatives as “financial weapons of mass destruction” ( Buffett, 2003 ) and many people have pointed to credit default swaps as having an important contributing role to the financial crisis of 2007–2009 ( Financial Crisis Inquiry Commission, 2011 ). While it is true that options and futures potentially do have some economic value when used to hedge risk ( Bartram, Brown, & Conrad, 2011 ; Moschini & Lapan, 1995 ), they do not have this value when used for speculative purposes, which they often are. Furthermore, the latest research would suggest that options and futures contribute to destabilization of market prices ( Somanathan & Anantha Nageswaran, 2015 ). Evidence does indicate that short selling facilitates market liquidity and decreased volatility ( Beber & Pagano, 2013 ; Sobaci, Sensoy, & Erturk, 2014 ). However, concern about their negative economic impacts has commonly led to short-selling bans ( Beber & Pagano, 2013 ; Boehmer, Jones, & Zhang, 2013 ; Jones, 2012 ). The consensus on day trading and high frequency trading is that they either have a negligible impact or negative impact on the markets through increased volatility ( Chung, Choe, & Kho, 2009 ; De Long, Shleifer, Summers, & Waldmann, 1987 ; Kyröläinen, 2008 ; Rebonato, 2015 ).

Table 1 summarizes the similarities and differences identified in the above analysis. Several observations are warranted. First, gambling differs from investment virtually on all the attributes reviewed, and therefore it is reasonable to consider these two activities as conceptually distinct. Second, gambling and investment differ to the greatest extent on attributes that are not commonly identified (i.e., asset purchase, and stake) and differ the least on an attribute that is often suggested (i.e., role of chance). Third, speculation is conceptually intermediate between gambling and investment, with one of its attributes being investment-like (i.e., activities/instruments), three of its attributes being gambling-like (i.e., level of risk, stake, and definitive event/outcome), and four of its attributes being neither clearly gambling nor investment-like (i.e., time frame, expected returns, asset purchase, and economic utility). Fourth, the definitions of gambling and investing outlined earlier do a good job of capturing and delineating the unique attributes of these respective activities. Fifth, a reasonable definition of speculation deriving from the present analysis would be “financial market activities that, when compared to investments, tend to be shorter term, higher risk, sometimes with higher potential losses and gains, and with a primary focus on making a monetary profit from price movements without regard for the fundamental value of the asset.”

Conceptual similarities and differences between gambling, speculation, and investment

	Gambling	Speculation	Investment
Activities & instruments	Fairly distinctive from speculation and investment	Fairly distinctive from gambling, less distinctive from investment	Fairly distinctive from gambling, less distinctive from speculation
Time frame	Usually short	Variable	Long
Level of risk	Usually high	Usually high	Low
Expected returns	Usually negative with low variability	Mixed & highly variable	Usually positive and somewhat variable
Role of chance	High	High	High
Asset purchase	No	Sometimes	Yes
Stake	Yes	Yes	No
Definitive event/outcome	Yes	Usually	Usually not
Economic utility	Low	Mixed	High

Empirical relationship between gambling, investing, and speculation

Because of the conceptual overlap between speculation and gambling, it would be reasonable to expect that (a) similar people might engage in both, and/or (b) activity in financial markets bears some relationship to gambling turnover, and/or (c) problematic play in one would be associated with problematic play in the other. Surprisingly, despite the large amount of literature on the conceptual relationship between these entities, there is relatively little research on the empirical relationship between speculation and gambling, or between gambling and stock market activity more generally. The research that exists on this topic is summarized below:

Cognitive, motivational, and personality similarities

One line of investigation has documented cognitive similarities between gamblers and investors. It appears that many investors have the same erroneous cognitions as gamblers, such as (a) being overconfident in their investment skills ( Barber & Odean, 2001 ; Kuo & Lin, 2013 ; Statman, 2002 ) and (b) only attending to information that confirms their opinion (confirmation bias; Rabin & Schrag, 1999 ), and have an illusion of knowledge and control over stock purchase outcome ( Barber & Odean, 2000 ; 2001 ; Langer, 1975 ). Similarly, several studies (e.g., Brunnermeier, Gollier, & Parker, 2007 ; Green & Hwang, 2012 ; Kumar, 2009 ) have found that non-professional investors tend to gravitate toward “lottery-type” stocks (i.e., stocks with a low price but with a small chance of increasing many multiples of their current value), which is analogous to gamblers” preference for products with low participation costs and high potential return (e.g., “penny slots,” large lottery jackpots) independent of the actual payback percentage or odds of winning ( Garrett & Sobel, 2004 ; Schwartz, 2010 ; Turner & Ferentzy, 2010 ). Finally, it is fairly clear that investors, like gamblers, are highly loss-averse ( Kahneman & Tversky, 1979 ; Linnainmaa, 2005 ; Odean, 1999 ; Shefrin & Statman, 1985 ).

Motivations also have some parallels. While it is well known that a large portion of gamblers engage in gambling for fun and excitement (e.g., Binde, 2009 , 2013 ), this also appear to be true of a significant portion of stock traders ( Dorn & Sengmueller, 2009 ; Gao & Lin, 2015 ; Kumar, 2009 ; Ladley, Liu, & Rockey, 2016 ). Dorn and Sengmueller ( 2009 ) identified three forms of enjoyment that people derive from trading stock: (a) leisure, (b) aspirations of high payoffs, and (c) sensation seeking, with the latter two types of enjoyment being characterized as “gambling motives.”

Similarities also exist in certain personality attributes ( Jadlow & Mowen, 2010 ), with sensation-seeking and/or risk-taking being a driving factor for both gambling and financial trading (e.g., Powell et al., 1999 ; Wong & Carducci, 1991 ). For example, in a group of male Finnish investors, the highest trading volumes occurred in the group with the most speeding tickets ( Grinblatt & Keloharju, 2009 ). Further evidence of this relationship is seen in the fact that people who score high on gambling risk-taking propensity also tend to have a high frequency of stock trading, including day trading ( Markiewicz & Weber, 2013 ). It is also interesting to note that risk-taking tends to be somewhat domain specific and in the development of their widely used domain-specific risk-taking scale (DOSPERT), Weber, Blais, and Betz ( 2002 ) found that involvement in financial investment (e.g., mutual funds) was statistically distinct from gambling involvement (e.g., poker) (resulting in a scale with two subtypes of financial risk: gambling and investment). Finally, Jadlow and Mowen ( 2010 ) found that material needs, competitiveness, financial conservatism, and numeracy proficiency were predictive of a tendency to engage in both gambling and stock trading, but that impulsivity and emotional instability were negatively related to stock market trading but positively related to gambling.

Overall level of gambling is related to overall level of speculation

Considering the similarities in cognitions, motivations, and personality, it is perhaps not surprising that there is also some relationship between overall levels of speculative stock market activity and overall levels of gambling. Barber et al. ( 2009 ) found that when Taiwan first introduced their national lottery, trading volume on the Taiwanese Stock Exchange dropped by 25%. Most research has found this impact to be fairly specific to lottery-style stocks having low prices, high volatility, and highly skewed returns. Gao and Lin ( 2015 ) demonstrated that when lottery jackpot size in Taiwan was high, stock market trading volume in lottery-type stocks declined by 7%–9%. This same relationship between large lottery jackpots and decreased stock trading volume has also be observed in both the United States and Germany ( Dorn et al., 2012 ), with the impact being specific to small traders, options, and individual stocks (with no impact on bonds, mutual funds, or retirement accounts). Similarly, Chen, Kumar, and Zhang ( 2015 ) found that in the U.S. where interest in the lottery was high (as evidenced by higher rates of Google searches for lottery-related terms), (a) stocks with lottery-like characteristics earned positive returns, and (b) initial public offerings of stocks with lottery-like characteristics earned higher first-day returns. Kumar ( 2009 ) found that lottery-stock purchase was higher in regions of the United States with demographic characteristics associated with lottery ticket purchase (i.e., lower income, unemployment, minority group race/ethnicity, Catholic, less educated, and younger). Similarly, Kumar, Page, and Spalt ( 2011 , 2016 ) found that regions of the United States with higher Catholic to Protestant ratios had a stronger propensity to hold lottery-type stocks.

A couple of studies have examined the relationship between casinos and financial markets. Liao ( 2015 ) found that casino openings in the United States were related to subsequent increases in financial portfolio risk among individuals with demographic propensities associated with gambling. Cookson ( 2015 ) found that the introduction of lottery-linked savings accounts in Nebraska was associated with a 7%–15% decline in casino expenditure.

Individual speculators are heavily involved in most forms of gambling but have some demographic differences

While the above research has identified many parallels and aggregate relationships between gambling and stock market activity, there is very little research on the level of gambling involvement within individual stock traders and/or the amount of stock trading within individual gamblers.

One of the first investigations on this issue was by Ozorio and Fong ( 2004 ) who found that in a sample of 302 Macau casino gamblers, the level of gambling risk was positively correlated with level of investment risk. Investment risk was assessed by asking about how large the possible gain from an investment had to be for them to risk one-half their current wealth in a venture having a 50–50 chance of succeeding as well as asking them to rank nine different ventures for investing 10% of their net worth that varied in expected rate of turn and variation in expected return.

In a secondary analysis of a large scale Canadian prevalence study of gambling ( n = 8,498) as well as an Ontario-based longitudinal study of gambling ( n = 4,121), Arthur, Delfabbro, and Williams ( 2015 ) found that high-risk stock traders to be overwhelmingly people who also engaged in traditional forms of gambling such as lotteries, slot machines, and sports betting. However, the reverse relationship was relatively weak – most gamblers did not engage in high-risk stock trading. In addition, high-risk stock traders (a) were found to engage in a significantly wider range of gambling activities and gambled more frequently than traditional gamblers, and (b) had a preference for skill-based games (i.e., casino table games, games of skill for money, sports betting, and horse/dog race betting). Demographically, compared to traditional gamblers, high-risk stock traders were more likely to be male, have a higher income, be better educated, be of Asian or “other” descent, not be divorced, widowed, or separated, and be self-employed or employed full-time.

These findings were replicated in a study of day traders in South Australia derived from a secondary analysis of a state-wide prevalence study of gambling ( n = 9,245) ( Arthur & Delfabbro, in press ). The large majority of South Australian day traders (90.8%) were found to also engage in traditional forms of gambling, with this level of participation being significantly higher than the past-year gambling participation rate of the general adult population (68.8%). Day traders also had a higher frequency of gambling involvement compared to the general population and had a distinct preference for skill-based formats such as poker, casino table games, sports betting, and horse and dog racing. Further evidence of a connection to skill-based formats was seen in a principal component analysis, which found gambling to dimensionalize into chance-based formats and skill-influenced formats, with day trading loading primarily on the latter. (This relationship between engagement in stock trading and skill-based gambling is something that has also been found by Odlaug, Marsh, Kim, and Grant ( 2011 ) among problem gamblers.) Similar to Arthur et al. ( 2015 ), day traders in Arthur and Delfabbro ( in press ) had a fairly distinct demographic and health-related profile, with the most robust differences relative to both the general population and to other gamblers were that day traders had significantly higher incomes, were significantly older, more likely to be employed, less likely to have any stress-related problems, and were more likely to be occasional, but not regular smokers. Compared to the general population, day traders were also more likely to be male, non-indigenous, in poorer general health, married, and to have higher educational attainment.

Significant overlap between problem gambling and problematic stock trading

There is mounting evidence that stock market trading can become excessive and addictive similar to other behaviors (e.g., Grall-Bronnec et al., 2015 ; Marković, Nikolac, Tripković, Haluga-Golubović, & Ćustović, 2012 ; Turner, 2011 ). In a sample of 582 active Greek stock traders, gamblers, and a control group, Konstantaras and Piperopoulou ( 2011 ) found that 11.2% of stock traders demonstrated problematic/compulsive levels of trading. Similarly, in a study of 111 Croatian online stock traders, Marković et al. ( 2012 ) found that the majority of the sample exhibited one of more signs of addiction.

The clinical profiles of problem gamblers and problematic stock traders have been found to be comparable. Shin, Choi, Ha, Choi, and Kim ( 2015 ) studied 144 South Koreans who sought treatment for problem gambling due to horse race betting (71.4% of the sample) or financial speculation (28.6% of the sample). The two groups were equivalent in terms of addiction severity, age of onset, debt size, and comorbidity profile. However, financial speculators tended to be better educated, live with a spouse, and to be employed full-time. Granero et al. ( 2012 ) found high overlap in the clinical profiles of 1,376 Spanish pathological gamblers who did not have problematic stock market activities ( n = 1,376), compared to both pathological gamblers who had stock market trading either as a secondary problem ( n = 76) or as their primary problem ( n = 18). As was found with Shin et al. ( 2015 ), pathological gamblers who engaged in stock market activities tended to have higher educational attainment, and pathological gamblers with stock market trading as their primary problem had higher levels of both educational attainment and the personality trait of cooperativeness.

Finally, there is significant overlap in the prevalence of problem gambling and problematic stock trading. Arthur et al. ( 2015 ) found the rate of problem gambling to be two to three times higher in high risk stock traders compared to gamblers who did not also engage in high risk stocks. The same result was obtained in Arthur and Delfabbro’s ( in press ) study, where the rate of problem gambling was found to be 7.6% among day traders, compared to 1.7% among individuals who did not engage in day trading. In a convenience sample of 178 Greeks who traded on the Athens stock exchange, Piperopoulou ( 2004 ) found that more than one-third of the sample was probable pathological gamblers and up to half had problematic levels of stock trading.

Discussion and Conclusions

Our conceptual review of gambling, speculation, and investment showed that investing is clearly distinct from gambling on many different attributes. The attributes that most clearly distinguish the two are: the investment involves creation or purchase of an asset, which does not occur with gambling, and the asset is never explicitly staked, whereas this always occurs with gambling. In addition, investment tends to involve a different set of activities and instruments, has a longer term perspective, has lower risk, a greater likelihood of positive expected returns, greater economic utility, and there is usually no specific point in time where there is an outcome or event associated with the asset (whereas gambling always involves a definitive outcome associated with a definitive event). Although the role of chance versus skill is often identified as something distinguishing gambling from investment, this is a not a strong differentiator, in that (a) several forms of gambling are highly influenced by skill, and (b) although most investors heavily research their choice of investments, their choices usually do not achieve higher returns than the market average, a result which could be equally well achieved by simply choosing a random selection of stocks.

Our conceptual review also revealed that financial speculation is conceptually intermediate between gambling and investment. Some of speculation’s attributes are similar to investment, such as the activities and instruments engaged in (e.g., stocks, commodities). On the other hand, some of its attributes are very gambling-like. For example, in most forms of speculation something is being staked (e.g., money or a recently purchased asset). Also, as occurs in gambling, most forms of speculation have a definitive outcome associated with a definitive event. However, many of speculation’s attributes are intermediate between gambling and investment. This includes: (a) time frame, which can be quite short as occurs in gambling or quite long, as occurs in investment; (b) level of risk, which can be quite high like gambling, or quite low, like investment; (c) expected return, which can be negative like gambling or positive like investment; (d) asset purchase, which does not occur in some cases and does occur in other cases; and (e) economic utility, which can be either low, like gambling, or high, like investment.

There is comparatively little literature on the empirical relationship between gambling, speculation, and investment relative to the amount of literature on their conceptual relationship. One line of investigation has identified similar personal attributes of gamblers, speculators, and investors. For example, there appear to be similar cognitive biases, with all three groups tending to be overconfident in their decisions, having a propensity to seek out confirming evidence for their beliefs and actions, having an illusion of control, and being highly loss-averse. Motivations also have parallels, with evidence suggesting that the dominant motivations for all three groups are often the same: i.e., to realize financial gains and for fun and excitement. Personality overlap is seen in the fact that sensation-seeking, risk-taking, material needs, competitiveness, financial conservatism, and numeracy proficiency are common to all three groups, although impulsivity and emotional instability may be more strongly associated with gambling, and high risk tolerance being specifically associated with gambling and speculation.

At a population level, there is evidence of a consistent association between overall lottery activity and overall involvement in speculative lottery-type stocks. Similarly, there is evidence that the introduction of casino gambling increases portfolio risk and that the introduction of lottery-linked savings accounts has a negative impact on casino expenditure. A similar relationship between gambling and speculation has been observed at an individual level. Although there are some distinct demographic differences between speculators and gamblers (the former more likely to be male, have higher incomes, and be employed), there are indications that the large majority of speculators are heavily involved in traditional forms of gambling, with this being especially true for skill-based formats, such as certain casino table games, games of skill for money against other individuals, sports betting, and horse/dog race betting. Potentially because of their heavy involvement in traditional forms of gambling, there is also tentative evidence that (a) the rates of problem gambling are significantly higher among speculators, and (b) the problematic levels of speculation are strongly correlated with problematic levels of gambling.

The empirical relationship between gambling and speculation is likely due to their conceptual overlap, which results in similar types of people being attracted to both activities. Financial speculation ostensibly entails a high degree of skill and knowledge, which helps explain why speculators are highly involved in skill-based forms of gambling. (The reverse relationship will not be as strong, as many skill-based gamblers will not perceive themselves to have the level of knowledge or income needed for financial speculation.) A propensity for high levels of financial risk is another common conceptual attribute driving both activities ( Liao, 2015 ; Markiewicz & Weber, 2013 ; Mishra, Lalumiere, & Williams, 2010 ). Financial risk-taking, in turn, is likely influenced by things such as perceived relative deprivation ( Mishra, Lalumiere, Williams, & Daly, 2012 ) as well as some lack of understanding about the expected returns in gambling and speculative financial activities. In contrast, people who eschew high risk, do not perceive themselves to be less well off compared to others, and are knowledgeable about how both gambling and the financial markets work will be more inclined to avoid gambling and speculation in favor of investment.

Implications and future research

More research is needed to further elucidate the empirical relationship between gambling, investment, and speculation as well as the basis for their similarities and differences, as most of the above results are somewhat tentative. However, an implication of the existing research is that because of its apparent strong empirical relationship and moderate conceptual relationship, financial speculation should arguably be listed as an additional activity when assessing both gambling involvement and problem gambling. Although this is sometimes done in population surveys ( Williams et al., 2012 ), and/or in some problem gambling treatment centers (e.g., Grall-Bronnec et al., 2015 ), it is not routinely included.

A second implication of these findings is that there needs to be greater recognition and study of financial speculation as both a contributor to problem gambling as well as an additional form of behavioral addiction in its own right ( Granero et al., 2012 ). The true prevalence and nature of this condition and its natural comorbidity with problem gambling is somewhat unclear, as there have only been a few studies that have directly investigated this issue. Rather, most of what we know about this condition is derived from population surveys of gambling and people who have presented themselves to problem gambling treatment centers. However, it is uncertain the extent to which traditional problem gambling assessment instruments capture problematic stock trading. Most speculators probably do not consider themselves “gamblers” and may not consider these questions to be appropriate to their situation. It is notable that the high levels of problematic stock play found by both Marković et al. ( 2012 ) and Konstantaras and Piperopoulou ( 2011 ) were obtained using adaptations of existing instruments to make them more relevant to stock trading (i.e., DSM-IV criteria for substance dependence in the case of Marković et al., 2012 and the South Oaks Gambling Screen in the study by Konstantaras & Piperopoulou, 2011 ). The other issue is that although it is evident that a portion of problematic stock traders present themselves to problem gambling treatment centers, it seems likely that only a minority of speculators would think to seek help at such a facility, with these individuals likely having disproportionately high rates of comorbid gambling-related problems.

Authors’ contribution:

JNA and RJW wrote this review. PHD provided commentary and edits to the manuscript.

Conflicts of interest:

The authors declare no conflict of interest.

Funding Statement

Funding sources: No financial support was received for this study.

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An Empirical Analysis of Individual Level Casino Gambling Behavior

Gambling and gaming is a very large industry in the United States with about one-third of all adults participating in it on a regular basis. Using novel and unique behavioral data from a panel of casino gamblers, this paper investigates three aspects of consumer behavior in this domain. The first is that consumers are addicted to gambling, the second that they act on “irrational” beliefs, and the third that they are influenced by marketing activity that attempts to influence their gambling behavior.

We use the interrelated consumer decisions to play (gamble) and the amount bet in a casino setting to focus on addiction using the standard economic definition of addiction. We test for two irrational behaviors, the “gambler’s fallacy” and the “hot hand myth” - our research represents the first test for these behaviors using disaggregate data in a real (as opposed to a laboratory) setting. Finally, we look at the effect of marketing instruments on the both the decision to play and the amount bet.

Using hierarchical Bayesian methods to pin down individual-level parameters, we find that about 8% of the consumers in our sample can be classified as addicted. We find support in our data for the gambler’s fallacy, but not for the hot hand myth. We find that marketing instruments positively affect gambling behavior, and that consumers who are more addicted are also affected by marketing to a greater extent. Specifically, the long-run marketing response is about twice as high for the more addicted consumers.

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Volume 39, Issue 3

Prevalence of problem gambling: a meta-analysis of recent empirical research (2016–2022).

Eliana Gabellini
Fabio Lucchini
Maria Elena Gattoni

Prevalence of gambling disorder and its correlates among homeless men in Osaka city, Japan

Chiyoung Hwang
Taichi Takano
Toshi A. Furukawa

Prevalence and Clinical Characteristics of Recreational and At-Risk/Problematic Gambling in a National Sample of U.S. Military Veterans

Elina A. Stefanovics
Marc N. Potenza
Robert H. Pietrzak

The scratch card gambler: a hidden reality

Daniela Maurício
Nuno Rodrigues-Silva

Profiling of Gamblers and Problem Gamblers Among Casino Patrons in Macao SAR

Wai Ming To
Gui-Hai Huang

Clinical Differences of mild, Moderate, and Severe Gambling Disorder in a Sample of Treatment Seeking Pathological Gamblers in Sweden

Mikael Mide
Elin Arvidson
Anna Söderpalm Gordh

Behavioral Responses to Losses Disguised as Wins: A Field Study of Slot Machine Players

Florina Salaghe
Federico Guerrero
James Sundali

The Influence of Alcohol Consumption on Gambling: Do the Laboratory Study Findings Generalize to Natural Environments?

Tori L. Horn
James P. Whelan
Abby McPhail

An Empirical Study of the Pathway Model Link Between Cognitive Distortions and Gambling Problems

Kahlil S. Philander
Sally M. Gainsbury

Roles for Alexithymia, Emotion Dysregulation and Personality Features in Gambling Disorder: A Network Analysis

Gemma Mestre-Bach
Roser Granero
Susana Jiménez-Murcia

Mediating Role of Rumination Between Anger and Anxious-Depressive Symptomatology in Family Members of People with Gambling Disorder

P. Jauregui
N. Etxaburu

Differences Between Illegal and Legal Gamblers in Israel: Gambling Behavior, Motivation, and Substance Use

Hagit Bonny-Noach

US Taxation of Gambling Winnings and Incentives to Bet

Karl Whelan

Using artificial intelligence algorithms to predict self-reported problem gambling with account-based player data in an online casino setting

Michael Auer
Mark D. Griffiths

Second Session at the Virtual Poker Table: A Contemporary Study of Actual Online Poker Activity

Matthew A. Tom
Timothy C. Edson
Debi A. LaPlante

Attitude Towards Deposit Limits and Relationship with Their Account-Based Data Among a Sample of German Online Slots Players

Gambling and internet addiction: a pilot study among a Population of Italian Healthcare

Roberto Lupo
Elsa Vitale
Piazza F. Muratori

Gamified Problem Gambling and Psychological Distress: The Mediated-Moderated Roles of Cognitive and Economic Motives

Clemence Dupey Agbenorxevi
Stewart Selase Hevi
Ruth Kukua Ntumy Coleman

How do Gambling Providers Use the Social Network Twitter in Germany? An Explorative Mixed-Methods Topic Modeling Approach

Johannes Singer
Vadim Kufenko
Steffen Otterbach

Cyberbullying and Gambling Disorder: Associations with Emotion Regulation and Coping Strategies

Ana Estévez
Laura Macía

Number 19: Another Victim of the COVID-19 Pandemic?

Patrick Roger
Catherine D’Hondt
Arvid Hoffmann

Expenditure on Paid-for Gambling Advertising During the National COVID-19 ‘Lockdowns’: An Observational Study of Media Monitoring Data from the United Kingdom

Nathan Critchlow
Martine Stead

Psychosocial Perspective on Problem Gambling: The role of Social Relationships, Resilience, and COVID-19 Worry

Jussi Nyrhinen
Terhi-Anna Wilska

Large-Scale Web Scraping for Problem Gambling Research: A Case Study of COVID-19 Lockdown Effects in Germany

Simon Michalski

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15 Empirical Evidence Examples (2024)
The results of the empirical research. Gross Gambling Revenue in the on...
The results of the empirical research. Gross Gambling Revenue in on...
(PDF) Responsible gambling: a synthesis of the empirical evidence
(PDF) Problem gambling worldwide: An update and systematic review of empirical research (2000–2015)
(PDF) Gambling Behavior and Problems Among Older Adults: A Systematic Review of Empirical Studies

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COMMENTS

Problem gambling worldwide: An update and systematic review of
Problem gambling has been identified as an emergent public health issue, and there is a need to identify gambling trends and to regularly update worldwide gambling prevalence rates. This paper aims to review recent research on adult gambling and problem ...
Prevalence of Problem Gambling: A Meta-analysis of Recent Empirical
Gambling is widely considered a socially acceptable form of recreation. However, for a small minority of individuals, it can become both addictive and problematic with severe adverse consequences. The aim of this systematic review and meta-analysis is to provide an overview of prevalence studies published between 2016 and the first quarter of 2022 and an updated estimate of problem gambling in ...
Emerging Gambling Problems and Suggested Interventions: A ...
The goal of the present systematic review is to identify emerging gambling problems and the harm minimization strategies proposed to address them. Our interdisciplinary research team conducted this systematic literature review in 5 nations between which there is significant gambling research exchange. A keyword search of the Scopus and Web of Science databases followed by filtering using ...
The association between gambling and financial, social and health
Gambling is associated with higher financial distress and lower financial inclusion and planning, and with negative lifestyle, health, well-being and leisure outcomes.
The prevalence of gambling and problematic gambling: a systematic
Existing evidence suggests that gambling is prevalent globally, that a substantial proportion of the population engage in problematic gambling, and that rates of problematic gambling are greatest among those gambling on online formats. Given the growth of the online gambling industry and the association between gambling and a range of public health harms, governments need to give greater ...
Risk Factors for Gambling Disorder: A Systematic Review
Risk factors for men include: age 18-24, not speaking English at home, low education, living in a group household, unemployed or inactive, gambling on EGM, table games, racing, sports or lotteries, and winning at non-social gambling Reasons for money or general entertainment.
Prevalence of Problem Gambling: A Meta-analysis of Recent Empirical
The aim of this systematic review and meta-analysis is to provide an overview of prevalence studies published between 2016 and the first quarter of 2022 and an updated estimate of problem gambling in the general adult population. A systematic review and a meta-analysis were carried out using academic databases, Internet, and governmental websites.
Whose Responsibility Is It to Prevent or Reduce Gambling Harm? A
This study presents a large-scale mapping review of how the literature on gambling identifies suggested solutions to prevent or reduce gambling harm and whose responsibility it is to implement them. The purpose of this is to provide a concise reference for stakeholders who must make critical decisions regarding the enhancement of consumer protection and harm minimization measures. Two ...
Problem gambling worldwide: An update and systematic review of ...
Abstract. Background and aims Problem gambling has been identified as an emergent public health issue, and there is a need to identify gambling trends and to regularly update worldwide gambling prevalence rates. This paper aims to review recent research on adult gambling and problem gambling (since 2000) and then, in the context of a growing ...
Emerging Gambling Problems and Suggested Interventions: A ...
Our interdisciplinary research team conducted this systematic literature review in 5 nations between which there is significant gambling research exchange. A keyword search of the Scopus and Web of Science databases followed by filtering using inclusion criteria identified 1292 empirical gambling studies from peer-reviewed journals.
The Conceptual Framework of Harmful Gambling: A revised framework for
Background and aims: The Conceptual Framework of Harmful Gambling moves beyond a symptoms-based view of harm and addresses a broad set of factors related to the risks and effects of gambling harmfully at the individual, family, and community levels. Coauthored by international research experts and informed by multiple stakeholders, Gambling Research Exchange (GREO) facilitated the framework ...
Is gambling like a virus?: A conceptual framework and proposals based
This research is a quasi-experimental investigation aimed to evaluate the effects of anti-COVID measures on the frequency of gambling and evolution of gambling disorder. The present study analyzed gambling patterns and the problems caused by gambling in 2,903 people, including those who were at-risk gamblers or had a gambling disorder.
Overview of the Economic and Social Impacts of Gambling in the United
Abstract This chapter provides an overview of empirical research on the economic and social impacts of gambling. Issues examined include the effects of casino gambling on economic growth; the relationships among gambling industries and the implications of these relationships on net government tax revenue; the social costs of gambling; casinos and crime; casinos and political corruption; and ...
Responsible gambling: a synthesis of the empirical evidence
Many jurisdictions around the world have implemented Responsible Gambling (RG) programs for the purpose of preventing gambling-related harms. Using a research synthesis strategy, this paper examines the extant peer-reviewed empirical evidence underpinning RG strategies.
Problem gambling worldwide: An update and systematic review of
Background and aims: Problem gambling has been identified as an emergent public health issue, and there is a need to identify gambling trends and to regularly update worldwide gambling prevalence rates. This paper aims to review recent research on adult gambling and problem gambling (since 2000) and then, in the context of a growing liberalization of the gambling market in the European Union ...
A systematic literature review of studies on attitudes towards gambling
Future research would benefit from combining more objective measures of gambling behavior (e.g. player tracking data and clinical assessment) with self-report measures of attitudes towards gambling to reduce the influence of bias associated with self-reported gambling behavior, and to investigate the relationship between attitudes and real ...
Full article: A reasoned action approach to gambling behavior
Gambling behavior is a prevalent problem requiring the development of effective behavioral interventions targeting reductions in the behavior. Many theories of social cognition can be adopted to id...
Pathological Choice: The Neuroscience of Gambling and Gambling
First, gambling is a naturalistic and pervasive example of risky decision making, and thus gambling games can provide a paradigm for the investigation of human choice behavior and "irrationality.". Second, excessive gambling involvement (i.e., pathological gambling) is currently conceptualized as a behavioral addiction, and research on this ...
Online Gambling: A Systematic Review of Risk and Protective ...
In recent decades, internet gambling has seen strong growth and diffusion due to intrinsic characteristics that make it particularly attractive to players (accessibility, anonymity, variety of games). This paper aims to present the current state of knowledge of the risk and protective factors of online gambling. A literature search conducted in the PubMed, PsychInfo, and Scopus databases found ...
The conceptual and empirical relationship between gambling, investing
To review the conceptual and empirical relationship between gambling, investing, and speculation.An analysis of the attributes differentiating these constructs as well as identification of all articles speaking to their empirical relationship.Gambling ...
Full article: Gambling researchers' use and views of open science
Facilitating additional empirical research about the use of open science among gambling studies researchers will help the field better understand knowledge gaps for education planning and help identify disciplines that might need open science innovations to engage effectively.
An Empirical Analysis of Individual Level Casino Gambling Behavior
Gambling and gaming is a very large industry in the United States with about one-third of all adults participating in it on a regular basis. Using novel and unique behavioral data from a panel of casino gamblers, this paper investigates three aspects of consumer behavior in this domain. The first is that consumers are addicted to gambling, the second that they act on "irrational" beliefs ...
Volume 39, Issue 3
Large-Scale Web Scraping for Problem Gambling Research: A Case Study of COVID-19 Lockdown Effects in Germany. Elke Smith. Simon Michalski. Jan Peters. Original Paper Open access 27 January 2023 Pages: 1487 - 1504. Volume 39, issue 3 articles listing for Journal of Gambling Studies.

The association between gambling and financial, social and health outcomes in big financial data

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Is gambling like a virus?: A conceptual framework and proposals based on empirical data for the prevention of gambling addiction

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BMC Public Health

The conceptual and empirical relationship between gambling, investing, and speculation

Robert J. Williams

Paul H. Delfabbro

Discussion and conclusions

Introduction

Conceptual relationship between gambling, investing, and speculation

Activities and instruments

Level of risk

Positive or negative expected return

Role of chance versus skill

Asset purchase

Definitive event and outcome

Economic utility

Empirical relationship between gambling, investing, and speculation

Cognitive, motivational, and personality similarities

Overall level of gambling is related to overall level of speculation

Individual speculators are heavily involved in most forms of gambling but have some demographic differences

Significant overlap between problem gambling and problematic stock trading

Discussion and Conclusions

Implications and future research

Authors’ contribution:

Conflicts of interest:

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