A Shorter and Multidimensional Version of the Gambling Attitudes and Beliefs Survey (GABS-23)

The Gambling Attitudes and Beliefs Survey (GABS) is a questionnaire which explores gambling-related dysfunctional beliefs in an unidimensional way. The present research aims to investigate the dimensionality of the scale. 343 undergraduate student gamblers and 75 pathological gamblers seeking treatment completed the GABS and the south oaks gambling screen. Exploratory and confirmatory factor analyses revealed that the original one-factor structure of the GABS did not fit the data effectively. We then proposed a shorter version of the GABS (GABS-23) with a new five-factor structure, which fitted with the data more efficiently. The comparisons between students (problem vs. non-problem gamblers) and pathological gamblers seeking treatment indicated that the GABS-23 can discriminate between problem and non-problem gamblers as efficiently as the original GABS. To ensure the validity and the stability of the new structure of the GABS-23, analyses were replicated in an independent sample that consisted of 628 gamblers (256 non problem gamblers, 169 problem gamblers who are not treatment-seeking and 203 problem gamblers seeking treatment). Analyses showed satisfactory results, and the multidimensional structure of the GABS-23 was then confirmed. The GABS-23 seems to be a valid and useful assessment tool for screening gambling-related beliefs, emotions and attitudes among problem and non-problem gamblers. Moreover, it presents the advantage of being shorter than the original GABS, and of screening irrational beliefs and attitudes about gambling in a multidimensional way. The five-factor model of the GABS-23 is discussed based on the theory of locus of control.     

Clinical Profiles as a Function of Level and Type of Impulsivity in a Sample Group of At-risk and Pathological Gamblers Seeking Treatment

Level and type of impulsivity are essential variables to be taken into consideration during the initial evaluation of a pathological gambler. The aim of this study was to measure the score for 4 impulsivity-related traits (Urgency, (lack of) Premeditation, (lack of) Perseverance and Sensation seeking) in a sample group of at-risk and pathological gamblers, and to highlight any links with certain elements of clinical data. The UPPS Impulsive Behaviour Scale was administered to 84 problem gamblers seeking treatment. The severity of gambling disorders was evaluated using the diagnostic criteria of the DSM-IV. Psychiatric and addictive comorbidities were also explored. The results indicated that the score for the Urgency facet had a positive correlation with the severity of gambling disorders. It appeared that participants displayed different clinical profiles according to the level and type of impulsivity. Several of the UPPS scales were identified as risk factors for mood disorders, risk of suicide, alcohol use disorders, and Attention Deficit/Hyperactivity Disorder (ADHD). The results confirm both the complexity of the multi-dimensional concept of impulsivity and the reason why the UPPS is of interest for a more in-depth study of the subject.     

An Assessment and Extension of the Mechanism-Based Approach to the Identification of Age-Period-Cohort Models

Many methods have been proposed to solve the age-period-cohort (APC) linear identification problem, but most are not theoretically informed and may lead to biased estimators of APC effects. One exception is the mechanism-based approach recently proposed and based on Pearl’s front-door criterion; this approach ensures consistent APC effect estimators in the presence of a complete set of intermediate variables between one of age, period, cohort, and the outcome of interest, as long as the assumed parametric models for all the relevant causal pathways are correct. Through a simulation study mimicking APC data on cardiovascular mortality, we demonstrate possible pitfalls that users of the mechanism-based approach may encounter under realistic conditions: namely, when (1) the set of available intermediate variables is incomplete, (2) intermediate variables are affected by two or more of the APC variables (while this feature is not acknowledged in the analysis), and (3) unaccounted confounding is present between intermediate variables and the outcome. Furthermore, we show how the mechanism-based approach can be extended beyond the originally proposed linear and probit regression models to incorporate all generalized linear models, as well as nonlinearities in the predictors, using Monte Carlo simulation. Based on the observed biases resulting from departures from underlying assumptions, we formulate guidelines for the application of the mechanism-based approach (extended or not).     

Exploring the role of CSR fit and the length of CSR involvement in routine business and corporate crises settings

This 2 × 2 experimental study examines the influence of CSR fit and the length of CSR involvement on corporate reputation and CSR skepticism in a routine business setting and crisis responsibility in a victim crisis. The study demonstrates a significant interaction between the two variables on the construction of corporate reputation. The length of CSR involvement is also found to influence people’s attribution of crisis responsibility in a crisis. By comparing corporate reputation and CSR skepticism before and after a crisis, the study further articulates the destructive power of crises. Theoretical and practical implications are discussed.     

Mother–Infant Interaction and Child Brain Morphology: A Multidimensional Approach to Maternal Sensitivity

Emerging research suggests that normative variation in parenting quality relates to children's brain development. However, although the young brain is presumed to be especially sensitive to environmental influence, to our knowledge only two studies have examined parenting quality with infants as it relates to indicators of brain development, and both were cross‐sectional. This longitudinal study investigated whether different components of maternal sensitivity in infancy predicted the volume of two brain structures presumed to be particularly sensitive to early experience, namely the amygdala and the hippocampus. Three dimensions of sensitivity (Cooperation/Attunement, Positivity, Accessibility/Availability) were observed in 33 mother–infant dyads at 1 year of age and children underwent structural magnetic resonance imaging at age 10. Higher maternal Accessibility/Availability during mother–infant interactions was found to be predictive of smaller right amygdala volume, while greater maternal positivity was predictive of smaller bilateral hippocampal volumes. These longitudinal findings extend those of previous cross‐sectional studies and suggest that a multidimensional approach to maternal behavior could be a fruitful way to further advance research in this area, given that different facets of parenting might be differentially predictive of distinct aspects of neurodevelopment.     

Retesting the income inequality hypothesis: Pooled time‐series–cross‐section regression with a new statistical case selection method

The Wilkinson hypothesis, which posits that it is income inequality, rather than economic growth, that determines population health in wealthy societies has been widely debated over decades. This article, with an original case selection process, retests the controversial hypothesis with the time‐series–cross‐section (TSCS) regression model. The main findings are that disposable income inequality is not statistically significantly associated with life expectancy, and its influences on the health of the elderly population are counterintuitively beneficial. Infant mortality rate is the only health indicator that both has the statistically significant association with income inequality and corresponds with the Wilkinson hypothesis. Finally, the relationship between income inequality and population health is not as simple as the hypothesis suggests and found to be dynamic and complex depending on what health indicator is used for the test.     

An exponential (matching based) neighborhood for the vehicle routing problem

We introduce an exponential neighborhood for the Vehicle Routing Problem (vrp) with unit customers’ demands, and we show that it can be explored efficiently in polynomial time by reducing its exploration to a particular case of the Restricted Complete Matching (rcm) problem that we prove to be polynomial time solvable using flow techniques. Furthermore, we show that in the general case with non-unit customers’ demands the exploration of the neighborhood becomes an -hard problem.     

Multiple-shrinkage estimators of means in exponential families

Shrinkage estimators are often obtained by adjusting the usual estimator towards a target subspace to which the true parameter might belong. However, meaningful reductions in risk below the usual estimator can typically be achieved in a very small part of the parameter space. In the multivariate-normal mean estimation problem, E. George, in a series of papers, showed how multiple-shrinkage estimators (data-weighted averages of several different shrinkage estimators) can attain substantial risk reductions in a large part of the parameter space. This paper extends the multiple-shrinkage results to the case of simultaneous estimation of the means of several one-parameter exponential families. Our results are developed by using an identity similar to that of Haff and Johnson (1986). A computer simulation is reported to indicate the magnitude of reductions in risk. Our results are also applied to the problem of how to choose appropriate component variables to combine before a suitable shrinkage estimator is considered.