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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 = 3,333 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: https://osf.io/5npy9 (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.

The Problem Gambling Severity Index is the most commonly used population measurement of disordered gambling. However, there is some debate regarding the construct being measured, and whether it is a single factor of gambling problems, or separate indices of dependence and harms. This paper reviews existing psychometric analyses of the factor structure of the PGSI, identifying key limitations of the literature. To overcome these, exploratory structural equation modelling was applied to data from 10 nationally representative surveys of gamblers in the UK (n = 35,776) to test between these accounts. Measurement indices provided slight support for a two-factor model. However, these models were not consistent across items or datasets, and further examination provided stronger support for a one-factor model. Sensitivity analyses coarsening across categories further supported these findings. This study provides strong evidence to support the use of PGSI scores as a single-factor construct.

Loot boxes are gambling-like products found in video games that players can buy with real-world money to obtain random rewards. A positive correlation between loot box spending and problem gambling severity has been well-replicated. Some researchers recently argued that this observed positive correlation may be due to participants incorrectly interpreting problem gambling questions as applying to their loot box expenditure. We experimentally tested this alternative explanation for the observed positive correlation (N = 2,027), by manipulating whether all participants were given the problem gambling scale (the ‘non-screening’ approach; n = 1,005), or by ‘screening’ participants (n = 1,022) by only giving those reporting recent gambling expenditure the problem gambling scale. Results showed positive correlations across both experimental conditions, with the association being slightly stronger in the non-screening group. In addition, a predicted positive correlation emerged between past-year gambling participation and loot box expenditure in the screening group. These experimental results confirm that the association between loot box spending and problem gambling severity is likely not due to participants misinterpreting problem gambling questions as being relevant to their loot box spending. These results also provide support for the usage of gambling participation screening questions in further research on this topic.

Measurements of smartphone addiction weakly correlate with actual behaviour logged from smartphones. Instead, smartphone addiction may probe distress rather than disordered behaviour, but this has not been adequately tested. This study examined the relative contributions of self-reported and actual smartphone behaviour alongside key mental health and individual differences in a pre-registered, two-wave study with a two week re-test. 511 smartphone users (391 at Time 2) completed measures of smartphone usage, attitudes towards smartphone usage, smartphone and other behavioural addictions, and individual differences. Smartphone addiction is principally driven by perceived rather than actual usage, especially where these are discordant. Self-reported smartphone usage, other behavioural addictions, and the impulsive facet of negative urgency are more predictive of smartphone addiction than logged behaviour. These results fail to support the idea that volume of smartphone usage is a sufficient criterion for an addictive behaviour and questions the validity of smartphone addiction measurements.

Background While the heterogeniety of pain progression has been studied in chronic diseases, the extent to which patterns of pain progression among people in general as well as across different diseases affect social, civic and political engagement is unclear. We explore these issues for the first time. Methods Using data from the English Longitudinal Study of Ageing, latent class growth models were used to estimate trajectories of self-reported pain in the entire cohort, and within subsamples reporting diagnoses of arthritis and cancer. These were compared at baseline on physical health (e.g. body mass index, smoking) and over time on social, civic and political engagement. Results Very similar four-trajectory models fit the whole sample and arthritis subsamples, whereas a three-trajectory model fit the cancer subsample. All samples had a modal group experiencing minimal chronic pain and a group with high chronic pain that showed slight regression (more pronounced in cancer). Biometric indices were more predictive of the most painful trajectory in arthritis than cancer. In both samples the group experiencing the most pain at baseline reported impairments in social, civic and political engagement. Conclusions The impact of pain differs between individuals and between diseases. Indicators of physical and psychological health differently predicted membership of the trajectories most affected by pain. These trajectories were associated with differences in engagement with social and civic life, which in turn were associated with poorer health and well-being. Electronic supplementary material The online version of this article (10.1186/s12916-018-1031-9) contains supplementary material, which is available to authorized users.

This paper reports a series of analyses examining the predictors of gambling subtypes identified from a latent class analysis of problem gambling assessment data, pooled from four health and gambling surveys conducted in Britain between 2007 and 2012. Previous analyses have indicated that gambling assessments have a consistent three class structure showing quantitative and potentially qualitative differences. Bringing this data together is useful for studying more severe problem gamblers, where the small number of respondents has been a chronic limitation of gambling prevalence research. Predictors were drawn from sociodemographic indicators and engagement with other legal addictive behaviours, namely smoking and alcohol consumption. The pooled data was entered into a multinomial logistic regression model in which class membership was regressed along a series of demographic variables and survey year, based on previous analyses of gambling prevalence data. The results identified multiple demographic differences (age, general health, SES, being single, membership of ethnic minority groups) between the non-problem and two classes endorsing some problem gambling indicators. Although these two groups tended to share a sociodemographic profile, the odds of being male, British Asian and a smoker increased between the three groups in line with problem gambling severity. Being widowed was also found to be associated with the most severe gambling class. A number of associations were also observed with other addictive behaviours. However these should be taken as indicative as these were limited subsamples of a single dataset. These findings identify specific groups in which gambling problems are more prevalent, and highlight the importance of the interaction between acute and determinant aspects of impulsivity, suggesting that a more complex account of impulsivity should be considered than is currently present in the gambling literature., Highlights • Data was pooled from three health and gambling surveys to identify correlates of gambling subtypes. • Subclinical gambling problems correlated with being male, single, a smoker, and under 35. • Problematic gambling was more common in multiple ethnic minority, and some socioeconomic groups. • The most severe gambling group had greater odds of being male, British Asian, a smoker and widowed.

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.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.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.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.