The effect of compliance-improving interventions on the cognitive-behavioural treatment of pathological gambling

This exploratory study investigated the effect of interventions designed to improve compliance and reduce dropout rates during the outpatient treatment of pathological gambling at a University-based gambling treatment clinic. Forty subjects (29 males, 11 females, mean age = 37.6) meeting DSM-IV criteria (APA, 1994) for pathological gambling were randomly assigned to either a cognitive-behavioural treatment or a cognitive-behavioural treatment combined with interventions designed to improve treatment compliance. Compliance was indicated by the completion of all treatment sessions. Outcome measures were DSM-IV criteria assessed by structured clinical interview, South Oaks Gambling Screen scores, and percentage of income gambled. Logistic regression analyses identified pretreatment characteristics predicting compliance and outcome. Compliance-improving interventions significantly reduced dropout rates, resulting in superior outcomes at posttreatment compared to the cognitive behavioural treatment alone. At 9-month follow-up, there was no difference in outcome between treatments, although both produced clinically significant change. Comorbid problem drinking, drug use, and problem gambling duration predicted poor compliance. Poor outcome was predicted by comorbid problem drinking. The clinical implications of these results are discussed in light of the exploratory nature of the study and the need for future research to address compliance, outcome, and comorbidity issues.     

Stochastic Measures of Network Resilience: Applications to Waterway Commodity Flows

Given the ubiquitous nature of infrastructure networks in today's society, there is a global need to understand, quantify, and plan for the resilience of these networks to disruptions. This work defines network resilience along dimensions of reliability, vulnerability, survivability, and recoverability, and quantifies network resilience as a function of component and network performance. The treatment of vulnerability and recoverability as random variables leads to stochastic measures of resilience, including time to total system restoration, time to full system service resilience, and time to a specific α% resilience. Ultimately, a means to optimize network resilience strategies is discussed, primarily through an adaption of the Copeland Score for nonparametric stochastic ranking. The measures of resilience and optimization techniques are applied to inland waterway networks, an important mode in the larger multimodal transportation network upon which we rely for the flow of commodities. We provide a case study analyzing and planning for the resilience of commodity flows along the Mississippi River Navigation System to illustrate the usefulness of the proposed metrics.     

A Bayesian semiparametric model for non negative semicontinuous data

When the target variable exhibits a semicontinuous behavior (a point mass in a single value and a continuous distribution elsewhere), parametric “two-part models” have been extensively used and investigated. The applications have mainly been related to non negative variables with a point mass in zero (zero-inflated data). In this article, a semiparametric Bayesian two-part model for dealing with such variables is proposed. The model allows a semiparametric expression for the two parts of the model by using Dirichlet processes. A motivating example, based on grape wine production in Tuscany (an Italian region), is used to show the capabilities of the model. Finally, two simulation experiments evaluate the model. Results show a satisfactory performance of the suggested approach for modeling and predicting semicontinuous data when parametric assumptions are not reasonable.     

Three doors anomaly, “should I stay,or should I go”: an artefactual field experiment

Theory and Decision - This work aims to identify and quantify the biases behind the anomalous behavior of people when they deal with the Three Doors dilemma, which is a really simple but...     

FINANCIAL DEVELOPMENT AND VERTICAL INTEGRATION: THEORY AND EVIDENCE

Existing evidence is mostly inconclusive on the relevance of financial development as a determinant of vertical integration. This paper presents evidence that, once industry heterogeneity in firm size distribution is taken into account, financial development is an important determinant of cross‐country differences in vertical integration. Financial development fosters entry of firms and increases competition in the industry. This reduces vertical integration of larger firms, but also leads smaller, non‐integrated, firms to exit the industry. As a result, higher financial development reduces vertical integration in industries where a high share of output is produced by small firms. The positive effect of financial development on entry also reduces vertical integration by fostering the development of input markets.     

Obamacare and the Politics of Universal Health Insurance Coverage in the United States

In the USA, universal coverage has long been a key objective of liberal reformers. Yet, despite the enactment of the Patient Protection and Affordable Care Act (PPACA) (commonly known as ‘Obamacare’) in 2010, the USA is not set to provide health care coverage to all, even if and when that reform is fully implemented. This article explores this issue by asking the following question: Why was a clear commitment to universal coverage, the norm in other industrialized countries, excluded as a core objective of the PPACA and how has post‐enactment politics at both the federal and the state level further shaped coverage issues? The analysis traces the issue of universal coverage prior to the debate over the PPACA, during the 2008 presidential race, and during consideration of the bill. The article then looks at the post‐enactment politics of coverage, with a particular focus on how states have responded to the planned use of the Medicaid programme to expand access to care. The article concludes by discussing how an explanation of the limits of the PPACA, in terms of both its commitment to universal coverage and, more importantly, the failure to provide comprehensive health insurance to all, requires an understanding of complex institutional and policy dynamics.     

Estimates for geographical domains through geoadditive models in presence of incomplete geographical information

The paper deals with the matter of producing geographical domains estimates for a variable with a spatial pattern in presence of incomplete information about the population units location. The spatial distribution of the study variable and its eventual relations with other covariates are modeled by a geoadditive regression. The use of such a model to produce model-based estimates for some geographical domains requires all the population units to be referenced at point locations, however typically the spatial coordinates are known only for the sampled units. An approach to treat the lack of geographical information for non-sampled units is suggested: it is proposed to impose a distribution on the spatial locations inside each domain. This is realized through a hierarchical Bayesian formulation of the geoadditive model in which a prior distribution on the spatial coordinates is defined. The performance of the proposed imputation approach is evaluated through various Markov Chain Monte Carlo experiments implemented under different scenarios.     

Informal Caregiving and the Politics of Policy Drift in the United States

Informal caregivers play an increasingly important role in caring for aging Americans. Yet existing social policies that could support informal caregiving have experienced “policy drift,” a failure to adapt to social risks that develop after policies are initially enacted. This article examines policy makers’ success at updating seven major policies to address caregiver needs. It draws on an original data set of legislation in this area introduced between 1991 and 2006 (n = 96). Findings indicate that drift is more likely when policy updates are costly, lack support from members of majority parties in the House and Senate, and fail to generate bipartisan support.     

Gender role identity in a sample of Italian male homosexuals

Gender role is a multifactorial concept, as gender-related attitudes, behaviors, and personality are partially autonomous. The aim of the study was to evaluate the prevalent gender role identity in a sample of male homosexuals. One hundred male homosexuals and 50 male heterosexuals matched for age and sex, have been assessed with the Italian version of the Bem Sex-Role Inventory (BSRI; Bem, 1974). Statistically significant differences have been found between the two groups at the dimensions "Masculine" (z = 1.963; p = 0.001) and "Androgyny" (z = 2.367; p < 0.0001). The results obtained from the present study tend to confirm that homosexuals view themselves as adrogynous individuals, sharing both features of masculine and feminine gender roles.