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All commercial gambling games are constructed so that the gamblers will on average lose money over time. This fact is often communicated to gamblers on virtual gambling games as the “return-to-player.” A return-to-player of 90% means that for every £100 bet, on average £90 is paid back out in prizes. In previous work, gamblers were better informed, and perceived a lower chance of winning, when this information was equivalently reframed as a “house-edge” of 10%, whereby the game keeps 10% of all money bet on average. This paper explores whether there are further risk communication advantages to using currency framing for the house-edge format, by directly stating the amount kept as: “This game keeps £10 for every £100 bet on average.” Online gamblers (N = 1,007) reported their perceived chances of winning for hypothetical games with house-edges of either 0.5%, 7.5%, or 15%, presented as either percentages or currency units. Gamblers’ perceived chances of winning were only minimally affected by this framing of house-edge information.
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Percentage and Currency Framing of House-Edge
Gambling Warning Labels
Philip W. S. Newall
&Lukasz Walasek
&Elliot A. Ludvig
#Springer Science+Business Media, LLC, part of Springer Nature 2020
All commercial gambling games are constructed so that the gamblers will on average lose
money over time. This fact is often communicated to gamblers on virtual gambling games
as the return-to-player.A return-to-player of 90% means that for every £100 bet, on
average £90 is paid back out in prizes. In previous work, gamblers were better informed,
and perceived a lower chance of winning, when this information was equivalently
reframed as a house-edgeof 10%, whereby the game keeps 10% of all money bet on
average. This paper explores whether there are further risk communication advantages to
using currency framing for the house-edge format, by directly stating the amount kept as:
This game keeps £10 for every £100 bet on average.Online gamblers (N = 1,007)
reported their perceived chances of winning for hypothetical games with house-edges of
either 0.5%, 7.5%, or 15%, presented as either percentages or currency units. Gamblers
perceived chances of winning were only minimally affected by this framing of house-
edge information.
Keywords Framing effect .Behavioral science .Risk communication .Betting
All commercial gambling games are constructed so that gamblers will on average lose money
over time. Some games, however, take a greater proportion of money wagered than others,
effectively meaning that these games are sold at a higher pricefor the enjoyment derived from
wagering a given amount of money (Harrigan and Dixon 2009;Woolleyetal.2013). Some
fraction of real-world gambling behavior might be influenced by the fact that gamblers are poorly
informed about the price of gambling (Eggert 2004). An issue facing gambling warning labels for
communicating the price of different gambling products is that the price of gambling is inherently
statistical, and that proper understanding therefore requires a degree of risk literacy (Cokely et al.
International Journal of Mental Health and Addiction
*Philip W. S. Newall
Experimental Gambling Research Laboratory, School of Health, Medical and Applied Sciences,
CQUniversity, 120 Spencer St, Melbourne, VIC 3000, Australia
Department of Psychology, University of Warwick, Coventry CV4 7AL, UK
2012). Therefore, an important question is not only what information to show to gamblers but
how best to display that information (Gigerenzer and Edwards 2003). This question is important
for policy makers, because moves toward more informative labelling of gambling product risk
would be considered the most freedom-preserving way of intervening on the public health costs of
gambling (Gambling Commission 2019; Nuffield Council on Bioethics 2007).
Currently, gambling warning labels for virtual gambling games in jurisdictions such as the UK
and the Australian state of Victoria present the priceof electronic gambling machines to
gamblers with what is known as the return-to-playerpercentage. For example, This game
has an average percentage payout of 90%,means that for every £100 bet on this game £90 is paid
out on average in prizes (Collins et al. 2014). This is a statistical average payout that occurs over
the lifetime of the machine and does not refer to every play or even to each session of play. This
information also means, indirectly, that the remaining £10 from the £100 bet is kept as profit for
the game operator. A number of previous studies have shown that many gamblers fail to correctly
understand what the return-to-player means, for example by thinking that the return-to-player
percentage refers to the percentage of winning gamblers, or the percentage of individual winning
plays (Beresford and Blaszczynski 2019; Collins et al. 2014;Harriganetal.2017).
This limitation of the return-to-player as a risk communication tool suggests that alternative
approaches for communicating the price are needed. Newall et al. (2020) investigated the effects of
reframingthe return-to-player as an equivalent statement which puts the emphasis on how much
money the game operator keeps on average: e.g., This game keeps 10% of all money bet on
average.This statement, which is known as the house-edgepercentage, is formally equivalent to
a return-to-player of 90% (Parke et al. 2016). The house-edge statement was, however, understood
correctly by more regular gamblers, and led to a lower perceived chance of winning, than the
equivalent return-to-player statement (Newall et al. 2020). These two factors combined suggest that
the house edge would make gamblers better informed and more aware of the price of gambling
products. This is an example of a framing effect,where the way risk is communicated can impact
judgment and decision making (Levin et al. 1985; Tversky and Kahneman 1981). Given that
equivalent information is not always processed equally, it is therefore important to explore potential
further improvements in the communication of the price of gambling.
Previous research suggests that percentages are an imperfect risk communication tool (Chen
and Rao 2007; Gigerenzer and Hoffrage 1995). For example, reframing the percentage manage-
ment fees charged by mutual funds as corresponding currency equivalents can help nudge
investors toward the rational strategy of choosing a low-fee fund (Choi et al. 2010; Hastings
and Tejeda-Ashton 2008). Participants in those studies with a hypothetical portfolio of $10,000
put more weight on a management fee of $100/year than a fee of 1% a year, even though the
information conveyed by the two formats is identical. In the present context, we predict that, This
game keeps £10 for every £100 bet on average,helps gamblers to be more wary of the price of a
gambling game than equivalently saying, This game keeps 10% of all money bet on average.
The benefits of currency over equivalent percentage framing, however, are not always
uniform. In general, people are more risk-seeking for small amounts of money, which is known
as the peanutseffect (Weber and Chapman 2005). For example, for a small investor whose
mutual fund management fees correspond to $10$15 a year, the currency framing actually
makes them less likely than percentage framing to choose a low-fee fund (Newall & Love
Such a combination of effects of converting percentages into currency amounts could be
useful in the current context, because this would make gamblers more wary of high house-
International Journal of Mental Health and Addiction
edge games, while increasing the relative attractiveness of low house-edge games. This would
effectively increase gamblerssensitivity to the price of different gambling products.
Therefore, the present research explored the impact of percentage and currency framing for
house-edge warning labels on gamblersperceived chances of winning across a wide range of
values (0.5 to 15%). This range of values was chosen because 0.5% is about the lowest house
edge possible to allow an operator to recoup the cost of providing a game, while 15% is the top
end for the house edge found previously in Canada (Harrigan and Dixon 2009) and Australia
(Woolley et al. 2013).
Our preregistered hypothesis was that there would be an interaction between label framing
and house-edge value. Specifically, we expected the dependent variable (a gamblers perceived
chance of winning), to vary more under currency than percentage framing. That is, we
expected participants to be more sensitive to variations in a gambling productspricewith
currency framing. Data, materials, analysis code, and the preregistration document can be
accessed from
A total of 1007 participants were recruited on Prolific Academic and were paid £0.50 each.
Participants took an average of 3.6 min to complete the study, so this translated to an average
payment of £8.33/h. Prolific Academic is a crowdsourcing platform similar to Amazon Mechanical
Turk, where researchers post experiments for a pool of registered potential participants to complete
(Palan and Schitter 2018). Prolific Academic has the benefit compared with Mechanical Turk of
various pre-screening filters that can be set by the experimenter to ensure that only a relevant subset
of the participant pool can take part. In this case, participants were pre-screened to be aged 18 or
older, UK residents, and to have played at least one online luck-based casino gambling game (i.e.,
one or more of Baccarat, Craps, Pachinko, Roulette, Slots, Video poker, and Virtual sports betting).
Participants were 54.3% female (0.1% other), and had a mean age of 35.9 years (SD = 10.1).
Occupation was reported as follows: student (5.6%), in work (80.8%), unemployed (7.8%), retired
(15.9%), other (4.2%). Education was reported as follows: secondary school (14.2%), college
(35.2%), undergraduate (36.1%), and postgraduate (14.5%). Ethical approval was obtained from
the University of Warwick human ethics committee prior to the study commencing.
Design and Materials
Participants were randomly assigned to either receive percentage or currency framing (be-
tween-participants). Participants then completed three trials in random order, corresponding to
a house edge of 0.5%, 7.5%, and 15%. On each trial participants were presented with some
short introductory text about online gambling and then a warning label. Figure 1shows an
example from the percentage condition. The exact wordings used were as follows:
This game keeps 0.5%/7.5%/15% of all money bet on average.
This game keeps 50p/£7.50/£15 for every £100 bet on average.
International Journal of Mental Health and Addiction
On each trial participants gave their perceived chance of winning using a 7-point Likert
scale, which can also be seen in Fig. 1.
After these three trials, participants completed an attention-check trial corresponding to an
implausibly high house edge of 95%, using the same framing that they had received over the
previous trials. As the first exclusion criterion, any participant who gave a higher perceived
chance of winning on this trial than on any previous trial was to be excluded, for reasons of
potential inattentiveness. The second exclusion criterion was to remove any participants who
gave a higher perceived chance of winning for a higher house-edge game. For example, if
participants rated a higher chance of winning with a house edge of 15% than with a house edge
of 7.5%, then they were excluded from the analysis, for an apparent failure to understand the
Fig. 1 Example of the main stimulus screen (percentage condition)
International Journal of Mental Health and Addiction
statistical nature of the house edge in gambling (which may well be due to participant
inattentiveness, in this experimental setup).
After the attention-check trial, participants completed the two individual difference scales
described below and provided demographic information.
The dependent variable was the gamblers perceived chances of winning, as measured by a 7-
point Likert scale (see Fig. 1). Participants also completed the Problem Gambling Severity
Index (Ferris and Wynne 2001), which directly measures behavioral dependence and gambling
harm, and the Consumption Screen for Problem Gambling (Rockloff 2012), a brief three-item
screen which measures gambling consumption. The latter screen has been shown to also be an
efficient method of detecting problem gamblers, as those who gamble the most frequently are
also the most likely to have gambling problems.
Participants had a mean problem gambling severity index of 3.1 (SD = 4.3), and a mean
gambling consumption screen score of 3.3 (SD = 2.7). The results of the two exclusion criteria
were as follows. The first exclusion criterion (95% house-edge catch trial) saw a loss of 6.9% of
participants in the currency condition and 3.4% in the percentage condition. The second
exclusion criterion (mistaken perceived chances of winning) saw a loss of 16.2% of participants
in the currency condition and 14.1% in the percentage condition. Across both exclusion criteria,
17.6% of participants were lost in the currency condition and 14.5% in the percentage condition.
This difference was not significantly different, as measured by logistic regression (z=1.33,
p= .184). Because this meant that attrition was not significantly different between the two
conditions, analysis could proceed on the remainder of the sample (N= 845) as preregistered.
Data were analyzed using a mixed-effects model, to account for the shared variance across
participantsthree perceived chances of winning. Perceived chances of winning were regressed on
the independent variables of framing (two levels, between-participants) and magnitude (three
levels, within-participants), and their interaction. In addition, a random intercept for participants
was included. This was performed with the afex package in R (Singmann et al. 2015).
Figure 2shows a plot of the results. There was a significant effect of magnitude (F(2,
1686) = 1557.12, p< .001), meaning that participants correctly perceived a lower chance of
winning with higher values of the house edge. There was no significant effect of condition
(F(1, 843) = 3.01, p= .08). However, an inspection of the marginal means shows there was a
trend for every level of the house edge for participants to give a higher perceived chance of
winning in the currency than percentage condition. Additionally, our hypothesis of an inter-
action between condition and magnitude was not supported (F(2, 1686) = 0.35, p= .71).
Participantsperceived chances of winning were equally responsive to variations in the price
of gambling, across both conditions. As this interaction effect was non-significant, no further
analyses were performed, following the preregistered analysis plan.
International Journal of Mental Health and Addiction
Overall, there was no reliable effect of percentage or currency framing of house-edge
warning labels, with respect to gamblersresponsiveness to variations in the price of
gambling. Although house-edge labels appear better than the return-to-player labels that
are currently in use (Newall et al. 2020), reframing the house edge as a currency amount
instead of a percentage appears limited in terms of additional improvement. There was a
weak trend toward gamblers perceiving a higher chance of winning with currency than
percentage framing, although this potential effect requires replication. However, if found,
any such effect would not say that either percentage or currency house-edge labels are
more effective than the other at communicating the price of gambling, only that they
should not be used interchangeably.
This study only used an online questionnaire about a hypothetical gamble, but bigger
differences may be found in a more ecologically valid task. In addition, participants here
only gave subjective perceived chances of winning. Future studies should investigate
whether, for example, wishful thinking may contribute to some gamblers thinking they
can beat the oddsand have a higher overall chance of winning than is communicated
through the warning label. Actual gambling behavior may also be more responsive to
changes in warning label framing than the subjective perceived chances of winning
measured here. Research should also continue to explore other potential avenues for risk
communication improvement in gambling warning labels (Ginley et al. 2017; McGivern
et al. 2019;Walkeretal.2019). For example, many electronic machine gamblers appear
confused about the return-to-player, misunderstanding that this single-play statistic does
not correspond to their expected return after gambling an initial stake repeatedly
(Harrigan et al. 2017). The currency format of house-edge warning labels may be most
effective when combined with a running total of a gamblers total amount bet, as a
potential correction for this misunderstanding surrounding repeated gambling. It might
also be that presenting house-edge information graphically is more effective than using
text (Garcia-Retamero and Cokely 2017).
Fig. 2 Experimental results. Perceived chances of winning: 7 = Very high chance of coming out ahead, 4 =
Neither high nor low chance of coming out ahead, 1 = Very low chance of coming out ahead. Error bars represent
95% confidence intervals
International Journal of Mental Health and Addiction
Gambling is increasingly seen as a public health issue (van Schalkwyk et al. 2019;Wardle
et al. 2019). The design of more effective warning labels is just one avenue that research
should explore to attempt to lessen gamblings public health impact (Nuffield Council on
Bioethics 2007).
Compliance with Ethical Standards
Conflict of Interest Philip Newall was in 2018 included as a named researcher on a grant funded by
GambleAware, and in 2019 received travel and accommodation funding from the Spanish Federation of
Rehabilitated Gamblers. Lukasz Walasek declares no conflict of interest. Elliot Ludvig was co-investigator on
a grant funded by the Alberta Gambling Research Institute that ended in February 2019.
Informed Consent All procedures followed were in accordance with the ethical standards of the responsible
committee on human experimentation (institutional and national) and with the Helsinki Declaration of 1975, as
revised in 2000 (5). Informed consent was obtained from all patients for being included in the study.
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International Journal of Mental Health and Addiction
... Samples 2 comprised of North American adults (USA & Canada) with gambling experience collected via Amazon's Mechanical Turk (MTurk), a crowdsourcing platform (Kim, Hollingshead, & Wohl, 2017;Mishra, Beshai, Wuth, & Refaie, 2019;Newall, Walasek, & Ludvig, 2020). A prescreen questionnaire (compensation $0.15 USD) established eligibility: i) English fluency, ii) age 21 or over (legal gambling age in USA), iii) and an endorsed gambling frequency statement of 'once every few months' or greater. ...
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Objective Schizotypal personality (schizotypy) is a cluster of traits in the general population, including alterations in belief formation that may underpin delusional thinking. The psychological processes described by schizotypy could also fuel cognitive distortions in the context of gambling. This study sought to characterize the relationships between schizotypy, gambling-related cognitive distortions, and levels of problem gambling. Methods Analyses were conducted on three groups, a student sample ( n = 104) with minimal self-reported gambling involvement, a crowdsourced sample of regular gamblers (via MTurk; n = 277), and an additional crowdsourced sample with a range of gambling involvement (via MTurk; n = 144). Primary measures included the Schizotypal Personality Questionnaire – Brief (SPQ-B), the Peters et al. Delusions Inventory (PDI-21), the Gambling Related Cognitions Scale (GRCS), and the Problem Gambling Severity Index (PGSI). Luck was measured with either the Belief in Good Luck Scale (BIGLS) or the Beliefs Around Luck Scale (BALS). Results Small-to-moderate associations were detected between the components of schizotypy, including delusion proneness, and the gambling-related variables. Schizotypy was associated with the general belief in luck and bad luck, but not beliefs in good luck. A series of partial correlations demonstrated that when the GRCS was controlled for, the relationship between schizotypy and problem gambling was attenuated. Conclusions This study demonstrates that schizotypy is a small-to-moderate correlate of erroneous gambling beliefs and PG. These data help characterize clinical comorbidities between the schizotypal spectrum and problem gambling, and point to shared biases relating to belief formation and decision-making under chance.
... However, these results pertain only to the house edge rather than the theoretical loss, which is the product of the house edge and the total amount bet. Some preliminary evidence suggests that gamblers' perceived chances of winning in a hypothetical scenario do not differ when the house edge is instead restated in terms of the theoretical loss (e.g., 'This game keeps £10 for every £100 bet on average; Newall et al., 2020b). Personalized theoretical loss information, however, which reflects a gambler's stakes and speed of play, may be able to improve upon this result. ...
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Gambling is considered a public health issue by many researchers, similarly to alcohol or obesity. Statistical risk warnings on gambling products can be considered a public health intervention that encourages safer gambling while preserving freedom of consumer choice. Statistical risk warnings may be useful to gamblers, given that net gambling losses are the primary driver of harm and that gambling products vary greatly in the degree to which they facilitate losses. However, there is some doubt as to whether statistical risk warnings are, in their current form, effective at reducing gambling harm. Here, we consider current applications and evidence, discuss product-specific issues around a range of gambling products and suggest future directions. Our primary recommendation is that current statistical risk warnings can be improved and also applied to a wider range of gambling products. Such an approach should help consumers to make more informed judgements and potentially encourage gambling operators to compete more directly on the relative 'price' of gambling products.
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Objectives Systematic mapping of evaluations of tools and interventions that are intended to mitigate risks for gambling harm. Design Scoping Review and z-curve analysis (which estimates the average replicability of a body of literature). Search strategy We searched 7 databases. We also examined reference lists of included studies, as well as papers that cited included studies. Included studies described a quantitative empirical assessment of a game-based (i.e., intrinsic to a specific gambling product) structural feature, user-directed tool, or regulatory initiative to promote responsible gambling. At least two research assistants independently performed screening and extracted study characteristics (e.g., study design and sample size). One author extracted statistics for the z-curve analysis. Results 86 studies met inclusion criteria. No tools or interventions had unambiguous evidence of efficacy, but some show promise, such as within-session breaks in play. Pre-registration of research hypotheses, methods, and analytic plans was absent until 2019, reflecting a recent embracement of open science practices. Published studies also inconsistently reported effect sizes and power analyses. The results of z-curve provide some evidence of publication bias, and suggest that the replicability of the responsible product design literature is uncertain but could be low. Conclusion Greater transparency and precision are paramount to improving the evidence base for responsible product design to mitigate gambling-related harm.
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Background and aims: The same information may be perceived differently depending on how it is described. The risk information given on many gambling warning labels tends to accentuate what a gambler might expect to win e.g., "This game has an average percentage payout of 90%,"(return-to-player), rather than what a gambler might expect to lose, e.g., "This game keeps 10% of all money bet on average" (house-edge).. We compared gamblers' perceived chances of winning and levels of warning label understanding under factually equivalent return-to-player and house-edge formats. Design: Online surveys. Experiment 1 was designed to test how gamblers' perceived chances of winning would vary under equivalent warning labels, and Experiment 2 explored how often equivalent warning labels were correctly understood by gamblers. Setting: UK PARTICIPANTS: UK nationals, aged 18 and over and with experience of virtual online gambling games such as online roulette, were recruited from an online crowdsourcing panel (Experiment 1 N = 399, Experiment 2 N = 407). Measurements: The main dependent variables were a gambler's perceived chances of winning on a 7-point Likert scale (Experiment 1), and a multiple-choice measure of warning label understanding (Experiment 2). Findings: The house-edge label led to lower perceived chances of winning in Experiment 1, F(1, 388) = 19.03, p < .001. In Experiment 2, the house-edge warning label was understood by more gamblers (66.5, 95% CI = 60.0%, 73.0%) than the return-to-player warning label (45.6%, 95% CI = 38.8%, 52.4%, z = 4.22, p < .001). Conclusions: House-edge warning labels on electronic gambling machines and online casino games, which explain what a gambler might expect to lose, could help gamblers to pay greater attention to product risk and would be better understood by gamblers than equivalent return-to-player labels.
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Background: 'Pop-up' warning messages have potential as a Responsible Gambling tool, but many warning messages in the literature are generic. The present study simulated digital roulette to compare the effectiveness of expenditure-specific, generic and control messages, during online roulette. Methods: Forty-five casual gamblers participated in a laboratory setting. Gambles were 'rigged' such that participants suffered a net loss. Total 'play money' wagers from individual bets after the presentation of the messages were measured. Results: Expenditure-specific warning messages demonstrated significant reductions in wager amounts compared with other message types - Generic (p = .035) and Control messages (p < .001). No significant differences were found between Generic and Control messages (p > .05). Thus expenditure-specific warning messages about current losses were more effective than generic messages for reducing expenditure. Conclusions: Expenditure-specific warning messages exhibit potential for ameliorating potentially harmful gambling behaviour. Expenditure-specific messages should be tested in a broader range of gambling contexts to examine their generalizability and potential for implementation in the gambling industry.
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The domain of gambling is rife with both diagnostic and non-diagnostic information. Previous studies examining scratch card gambling have demonstrated that people are often biased by intuitively appealing, yet non-diagnostic information (i.e., unclaimed prize information). The current study investigated how varying the presentation format of a diagnostic piece of information (i.e., payback percentage) could influence participants’ use of this information when in conflict with unclaimed prize information. We hypothesized that when payback percentage information was presented in a graphical, as opposed to a numerical format, participants would be better at ignoring unclaimed prize information and correspondingly have their preferences become congruent with the true value of the presented scratch cards. In Experiment 1 (N = 201), with payback percentage presented in a numerical format, participants displayed a non-optimal preference for cards with greater numbers of unclaimed prizes and lower payback percentages. This preference was reversed in Experiment 2 (N = 201) when payback percentage was presented in a graphical format. In conclusion, the results of the current study demonstrate how judgments in a scratch card gambling domain can be improved by simply changing the presentation format of a single piece of information.
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The addictive potential of electronic gaming machines (EGMs) is currently explained within a cognitive-behavioural framework. This framework explains that various erroneous cognitions regarding players’ likelihood of winning contribute to persistent EGM gambling behaviour. Related to these cognitions is the pervasive misunderstanding among players regarding the operation of EGMs. However, little research has focussed specifically on player understanding of the theoretical proportion returned to players over the lifetime of a machine; return to player percentage. This study aimed to investigate the extent to which players understand the concept return to player percentage presented in different educative formats. A sample of 112 university students were randomly allocated to one of four conditions pertaining to a different mode of information delivery; infographic, vignette, brochure, or mandated legislation (control). Participants completed post-intervention measures to determine changes in knowledge. As predicted, participants exhibited a lack of understanding of the concept of return to player at baseline. However, contrary to predictions, exposure to any of the experimental conditions did not result in a greater understanding of return to player than controls. The study findings emphasise the difficulty individuals have in understanding complex concepts related to return to player percentages when presented in current formats and content. Treatment and responsible gambling policies need to adopt strategies to effectively improve knowledge of this aspect of the structural characteristics of gaming machines.
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The number of online experiments conducted with subjects recruited via online platforms has grown considerably in the recent past. While one commercial crowdworking platform - Amazon's Mechanical Turk - basically has established and since dominated this field, new alternatives offer services explicitly targeted at researchers. In this article, we present and lay out its suitability for recruiting subjects for social and economic science experiments. After briefly discussing key advantages and challenges of online experiments relative to lab experiments, we trace the platform's historical development, present its features, and contrast them with requirements for different types of social and economic experiments.
Technical Report
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The aim of this report is to review evidence and theory regarding the gambling product through its structural characteristics (i.e., the ‘agent’ component of the epidemiological triangle). By providing a better understanding of structural characteristics, stakeholders should be better equipped to promote and evaluate responsible gambling and harm-minimisation strategies. Structural characteristics are essentially the building blocks of a gambling game. They are the basis for their differential appeal depending on how they satisfy different needs for different consumers. They combine with environmental and individual factors to determine both positive and negative outcomes of gambling participation. Structural characteristics vary considerably from game to game and evolve quickly in response to changes in technology; this renders associated policymaking challenging. The report is structured to consider categories of structural characteristics. Within each section we consider the theory and evidence concerning the possible links between characteristics and gambling problems, together with potential implications for specific interventions that may merit consideration by regulators and commercial gambling providers.
In the United States, warning messages were first included on tobacco products in the 1960 s, and were subsequently added to alcohol products in the 1980 s. However, they have yet to be applied comprehensively to gambling. Several jurisdictions, including Australia, New Zealand, and Canada, have mandated responsible gaming requirements, including pop-up warning messages to provide players feedback on potentially risky play. The aim of the current paper was to conduct a systematic review of the literature on gambling-related warning messages and to discuss the public policy implications of the research to date. Across all studies examined, the use of warning messages was largely supported. Messages informed consumers and if applied appropriately, potentially reduced harm. The mode of message display, along with placement, content, framing, and context were all found to influence the impact of messages. Messages demonstrated optimal impact when they popped-up on the center screen, created an interruption in play, and required active removal by the player. Messages were more effective at modifying behavior when they were brief, easy to read, and direct. As opportunities for gambling continue to increase, findings support that gambling-related warning messages can reduce risky gambling play and can be used to inform policy decisions around responsible gaming. Gaps in the warning-message literature to be addressed by future research efforts and to further inform prevention policy are discussed.
Background Effective risk communication is essential for informed decision making. Unfortunately, many people struggle to understand typical risk communications because they lack essential decision-making skills. Objective The aim of this study was to review the literature on the effect of numeracy on risk literacy, decision making, and health outcomes, and to evaluate the benefits of visual aids in risk communication. Method We present a conceptual framework describing the influence of numeracy on risk literacy, decision making, and health outcomes, followed by a systematic review of the benefits of visual aids in risk communication for people with different levels of numeracy and graph literacy. The systematic review covers scientific research published between January 1995 and April 2016, drawn from the following databases: Web of Science, PubMed, PsycINFO, ERIC, Medline, and Google Scholar. Inclusion criteria were investigation of the effect of numeracy and/or graph literacy, and investigation of the effect of visual aids or comparison of their effect with that of numerical information. Thirty-six publications met the criteria, providing data on 27,885 diverse participants from 60 countries. Results Transparent visual aids robustly improved risk understanding in diverse individuals by encouraging thorough deliberation, enhancing cognitive self-assessment, and reducing conceptual biases in memory. Improvements in risk understanding consistently produced beneficial changes in attitudes, behavioral intentions, trust, and healthy behaviors. Visual aids were found to be particularly beneficial for vulnerable and less skilled individuals. Conclusion Well-designed visual aids tend to be highly effective tools for improving informed decision making among diverse decision makers. We identify five categories of practical, evidence-based guidelines for heuristic evaluation and design of effective visual aids.