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Smartphone users engage extensively with their devices, on an intermittent basis for short periods of time. These patterns of behaviour have the potential to make mobile gambling especially perseverative. This paper reports the first empirical study of mobile gambling in which a simulated gambling app was used to measure gambling behaviour in phases of acquisition and extinction. We found that participants showed considerable perseverance in the face of continued losses that were linearly related to their prior engagement with the app. Latencies between gambles were associated with the magnitude of reinforcement; more positive outcomes were associated with longer breaks between play and a greater propensity to end a gambling session. Greater latencies were associated with measurements of problem gambling, and perseverance with gambling-related cognitions and sensation-seeking behaviour., (© 2019 The Author(s) Published by S. Karger AG, Basel.)

In their position paper, Aarseth et al. (2016) bring to light several timely issues concerning the categorization of gaming disorder as a form of addiction and as a discrete mental disorder. In our commentary, we welcome their caution toward this move and their discussion of the equivocal scientific data in its support and the potential negative consequences for gamers. We suggest that a more heterogeneous approach is required for understanding any behavioral addiction, as concepts from gambling appear to be more relevant for aspects of mobile gaming than for video games more generally. In addition to a greater need for clinical research, we argue that studying gaming at a different level of analysis than the epidemiological study is required to gain a meaningful understanding of the harm video games may or may not entail.

This manuscript reviews the extant literature on key issues related to mobile gambling and considers whether the potential risks of harm emerging from this platform are driven by pre-existing comorbidities or by psychological processes unique to mobile gambling. We propose an account based on associative learning that suggests this form of gambling is likely to show distinctive features compared with other gambling technologies. Smartphones are a rapidly growing platform on which individuals can gamble using specifically designed applications, adapted websites or text messaging. This review considers how mobile phone use interacts with psychological processes relevant to gambling, the games users are likely to play on smartphones, and the interactions afforded by smartphones. Our interpretation of the evidence is that the schedules of reinforcement found in gambling interact with the ways in which people tend to use smartphones that may expedite the acquisition of maladaptive learned behaviours such as problem gambling. This account is consistent with existing theories and frameworks of problem gambling and has relevance to other forms of mobile phone use., (© 2016 The Authors. British Journal of Psychology published by John Wiley & Sons Ltd on behalf of the British Psychological Society.)

Analyses of disordered gambling assessment data have indicated that commonly used screens appear to measure latent categories. This stands in contrast to the oft-held assumption that problem gambling is at the extreme of a continuum. To explore this further, we report a series of latent class analyses of a number of prevalent problem gambling assessments (PGSI, SOGS, DSM-IV Pathological Gambling based assessments) in nationally representative British surveys between 1999 and 2012, analysing data from nearly fifty thousand individuals. The analyses converged on a three class model in which the classes differed by problem gambling severity. This identified an initial class of gamblers showing minimal problems, a additional class predominantly endorsing indicators of preoccupation and loss chasing, and a third endorsing a range of disordered gambling criteria. However, there was considerable evidence to suggest that classes of intermediate and high severity disordered gamblers differed systematically in their responses to items related to loss of control, and not simply on the most 'difficult' items. It appeared that these differences were similar between assessments. An important exception to this was one set of DSM-IV criteria based analyses using a specific cutoff, which was also used in an analysis that identified an increase in UK problem gambling prevalence between 2007 and 2010. The results suggest that disordered gambling has a mixed latent structure, and that present assessments of problem gambling appear to converge on a broadly similar construct.

Aims: To test whether problem gambling is a categorical or dimensional disorder on the basis of two problem gambling assessments. This distinction discriminates between two different conceptualizations of problem gambling: one that problem gambling is defined by its addictive properties, the other that it is a continuum of harm., Method: Using The British Gambling Prevalence Survey 2010, a nationally representative sample of the United Kingdom conducted by the National Centre for Social Research, five different taxometric analyses were carried out on cases from two problem gambling screens: the Problem Gambling Severity Index (PGSI) and a measure derived from the DSM-IV Pathological Gambling criteria. Two further analyses were conducted on the total scores for these measures., Results: There was strong evidence that both scales were measuring a categorical construct. Fit indices consistently supported a categorical interpretation [comparison curve fit index (CCFI) > 0.6]. The PGSI analysis indicated the presence of a taxon (CCFIs = 0.633, 0.756). The analysis conducted on the adapted DSM-IV criteria indicated stronger quantitative support for a taxon (CCFIs = 0.717, 0.811 and 0.756) but items probing a loss of control were inconsistent. The taxometric analyses of both scales support a categorical interpretation (CCFIs = 0.628, 0.567), but extreme caution should be used due to high nuisance covariance., Conclusions: Two problem gambling screens (the Problem Gambling Severity Index and a measure derived from the DSM-IV Pathological Gambling criteria) appear to measure a categorical construct that taps into a categorical, loss of control model of problem gambling. There is some evidence that the two screens measure different aspects of an addiction construct., (© 2014 Society for the Study of Addiction.)

AbstractBackgroundMethodResultsConclusionsThe Problem Gambling Severity Index (PGSI) is a widely used assessment of disordered gambling. However, it has been claimed that instead of measuring a single factor of problem gambling severity, the PGSI measures two correlated factors of behavioral dependence and harms/consequences. The existing literature using exploratory and confirmatory factor analysis has notable limitations that mean these accounts cannot be discriminated.Secondary data from 13 nationally representative surveys of gamblers in the UK (n = 42,422) between 2007 and 2023 were used to examine five different approaches to specifying one- and two-factor models of the PGSI.Overall, the findings supported a single construct account. Fit indices provided slight support for a two-factor model. However, the composition and loadings of these factors did not replicate in the disaggregated datasets and demonstrated poor model-based reliability. The best-fitting model was a bifactor ESEM model with a general gambling severity factor and a group-specific factor subsuming additional covariance between the first three or four items.This study provides support for a unitary gambling severity construct and the use of total PGSI scores. The second factor observed elsewhere appears to consist of residual covariances between the first 3-4 PGSI items or a methods factor that can be explained by item framing (e.g. items that ask about gambling behavior). [ABSTRACT FROM AUTHOR]

The provision of information to consumers is a common input to tackling various public health issues. By comparison to the information given on food and alcohol products, information on gambling products is either not given at all, or shown in low-prominence locations in a suboptimal format, e.g. the 'return-to-player' format, 'this game has an average percentage payout of 90%'. Some previous research suggests that it would be advantageous to communicate this information via the 'house edge' format instead: the average loss from a given gambling product, e.g. 'this game keeps 10% of all money bet on average'. However, previous empirical work on the house edge format only uses this specific phrasing, and there may be better ways of communicating house edge information. The present work experimentally tested this original phrasing of the house edge against an alternative phrasing that has also been proposed, 'on average this game is programmed to cost you 10% of your stake on each bet', while both phrasings were also compared against equivalent return-to-player information (N = 3333 UK-based online gamblers). The two dependent measures were gamblers' perceived chances of winning and a measure of participants' correct understanding. Preregistered Stage 1 protocol: (date of in-principle acceptance: 28/11/2022). The alternative house edge phrasing resulted in the lowest perceived chances of winning, but the original phrasing had the highest rate of correct understanding. Compared to return-to-player information, the original phrasing had both lower perceived chances of winning and higher rates of correct understanding, while the alternative phrasing had only lower perceived chances of winning. These results replicated prior work on the advantages of the original house edge phrasing over return-to-player information, while showing that the alternative house edge phrasing has advantageous properties for gamblers' perceived chances of winning only. The optimal communication of risk information can act as an input to a public health approach to reducing gambling-related harm. [ABSTRACT FROM AUTHOR]

Online forums can be a source of support for people with gambling-related problems. Forum threads contain detailed information about these gamblers' experiences. However, because of limitations in data collection and analysis, there have been few systematic analyzes of forum content. The aim of this study is to use web scraping and correlated topic modeling to develop a bottom-up, data-driven approach to identify key issues raised by gamblers participating in an online forum, taking 2,298 posts from 1,400 unique authors over a twelve-year period. The data revealed ten themes that fall into four superordinate categories: negative emotions caused by gambling, the process of recovery, gambling products and money related concerns. Negative emotions associated with gambling was the most common topic occurring in 25% of posts. The process of recovery theme could be divided into formal and informal resources for dealing with gambling problems. Gambling products captured both traditional high street and new online forms of gambling. A final theme highlighted how family and friends become sources of finance to fund gambling. These findings can be used to design brief psychosocial education programs which highlight the consequences of gambling on oneself, one's family and the emotional impact that emerges from gambling. [ABSTRACT FROM AUTHOR]

This paper is the first to compare how major gambling brands are using the popular social media platform Twitter, looking at how gambling brands vary in the frequency of their messages, the content of their tweets and engagement with their Twitter activity. 63,913 tweets were collected from seven well-known British gambling brands (Bet365, Betfair, Betfred, Coral, Ladbrokes, Paddy Power, William Hill) and their associated Twitter accounts (Total Number of Accounts = 22) via the Twitter Application Program Interface (API) on the 1 August 2018. Companies varied in their approach to Twitter, some posting from a single account whereas others segmented their tweets by topic or purpose. Frequency analysis of tweets showed that on average major gambling brands tweeted anywhere between 89 and 202 tweets a day. Sentiment analysis of tweets showed a positivity bias with the language in tweets being associated with positive emotions like anticipation, trust and joy. Paddy Power, Bet365 and Coral produced the content that received the highest number of likes or shares from other twitter users. This study highlights the extent to which companies are using Twitter; followers could potentially be receiving hundreds of messages per day. [ABSTRACT FROM AUTHOR]