Revisiting the Role of Impulsivity and Compulsivity in Problematic Sexual Behaviors

Impulsivity and compulsivity are transdiagnostic features associated with clinically relevant aspects of psychiatric disorders, including addictions. However, little research has investigated how impulsivity and compulsivity relate to hypersexuality and problematic pornography use. Thus, the aims of the present study were to investigate (a) self-reported impulsivity and compulsivity with respect to hypersexuality and problematic pornography use and (b) the similarities and possible differences between hypersexuality and problematic pornography use in these domains. Utilizing structural equation modeling (SEM) in a large community sample (N = 13,778 participants; female = 4,151, 30.1%), results indicated that impulsivity (β = .28, β = .26) and compulsivity (β = .23, β = .14) were weakly related to problematic pornography use among men and women, respectively. Impulsivity had a stronger relationship (β = .41, β = .42) with hypersexuality than did compulsivity (β = .21, β = .16) among men and women, respectively. Consequently, impulsivity and compulsivity may not contribute as substantially to problematic pornography use as some scholars have proposed. On the other hand, impulsivity might have a more prominent role in hypersexuality than in problematic pornography use. Future research should examine further social and situational factors associated with problematic pornography use.     

Application of the Hyper‐Poisson Generalized Linear Model for Analyzing Motor Vehicle Crashes

The hyper‐Poisson distribution can handle both over‐ and underdispersion, and its generalized linear model formulation allows the dispersion of the distribution to be observation‐specific and dependent on model covariates. This study's objective is to examine the potential applicability of a newly proposed generalized linear model framework for the hyper‐Poisson distribution in analyzing motor vehicle crash count data. The hyper‐Poisson generalized linear model was first fitted to intersection crash data from Toronto, characterized by overdispersion, and then to crash data from railway‐highway crossings in Korea, characterized by underdispersion. The results of this study are promising. When fitted to the Toronto data set, the goodness‐of‐fit measures indicated that the hyper‐Poisson model with a variable dispersion parameter provided a statistical fit as good as the traditional negative binomial model. The hyper‐Poisson model was also successful in handling the underdispersed data from Korea; the model performed as well as the gamma probability model and the Conway‐Maxwell‐Poisson model previously developed for the same data set. The advantages of the hyper‐Poisson model studied in this article are noteworthy. Unlike the negative binomial model, which has difficulties in handling underdispersed data, the hyper‐Poisson model can handle both over‐ and underdispersed crash data. Although not a major issue for the Conway‐Maxwell‐Poisson model, the effect of each variable on the expected mean of crashes is easily interpretable in the case of this new model.     

“Should I Trust the Bank or the Social Movement?” Motivated Reasoning and Debtors' Work to Accept Misinformation

How can people believe corporate and state misinformation even if a social movement organization in their community has been countering this misinformation for years? Why do people knowingly accept misinformation without even being upset about it? I address these questions by analyzing ethnographic data and interviews with 84 Chilean low‐income housing debtors, whom, like many Chileans, are victims of financial misinformation. While the state and banks had significant agency in inducing the unproblematic acceptance of misinformation, debtors also played an active role in the processes. First, debtors had to decide whom to trust, which was not only a cognitive problem about evidence but also a behavioral and practical problem involving risks. Second, debtors engaged in “motivated reasoning”—affect‐driven biased information processing—to dismiss the possibility of being misinformed, to downplay the significance of misinformation, and to direct blame away from misinforming institutions. The latter two practices reduced debtors' anger about being misinformed. The findings have implications for studies of social movement framing and counterinformation, for the cognitive psychology of misinformation, and for the sociology and social psychology of acquiescence.     

Measuring and Analysing Community Action for Health: An Indicator-Based Typology and Its Application to the Case of Barcelona

Social welfare systems face major challenges, particularly in a context of social transformation, austerity and growing inequalities. This process is highly visible in the health sector. In this context, many voices ask for public sector reforms and community action for health as a relevant practice. However, analyses and evaluations of this kind of practices are still limited, particularly beyond the cases of single community health actions or interventions. We still need to identify key indicators for measuring and characterising what community action for health consists of, as well as to what degree this kind of intervention has been developed across a city. Based on a research about 49 neighborhoods in Barcelona, this paper creates an index to measure and characterize community action for health, using different indicators: citizen engagement programs in community health, organizational transformation of the health and social protection systems, stable participatory structures with specific teams, and urban health policies. We apply the index to the case of Barcelona and build a map of community action for health in the city using 4 categories: strong community health development (one neighbourhood), middle (9 neighborhoods), emergent (25 neighborhoods) and without specific community health promotion (14 neighbourhoods). We find that community action for health is extensive within the city of Barcelona, have great potential as a response to the need for change in the relationship between the public (health) sector and the citizenry, but is still implemented unequally across the urban territory in terms of types and methods.     

The moral hazard of conditionality: Restoring the integrity of social security law

This article examines the extent to which the Australian and UK social security systems meet their legal obligations to provide basic relief to citizens in need. Conditionality and “mutual obligation” are at the core of both the UK and Australian social security systems and are based on the concept of moral hazard, the goal being to ensure that claimants do not consider living on benefits to be preferable to engaging in paid work. Yet, we argue that the element of “mutuality” is missing in both systems; welfare claimants are subject to myriad conditions and obligations, whilst the state operates free of any legal responsibility to provide even basic relief to those in need, to prevent or alleviate extreme poverty and destitution. We outline the extent to which Australian and UK social security laws require governments to relieve destitution, examining both domestic and human rights law. We conclude that legal protections are weak and that both systems fail to meet the basic conditions of humanity toward their citizens. On this basis, we argue that such failings demonstrate a lack of integrity which undermines the standing of both the UK and Australia to invoke a claim of moral hazard to defend claimant conditionality.     

Optimal classification scores based on multivariate marker transformations

AStA Advances in Statistical Analysis - Modern science frequently involves the study of complex relationships among effects and factors. Flexible statistical tools are commonly used to visualize...     

Against the De Minimis Principle

According to the class of de minimis decision principles, risks can be ignored (or at least treated very differently from other risks) if the risk is sufficiently small. In this article, we argue that a de minimis threshold has no place in a normative theory of decision making, because the application of the principle will either recommend ignoring risks that should not be ignored (e.g., the sure death of a person) or it cannot be used by ordinary bounded and information-constrained agents.     

Choice of the ridge factor from the correlation matrix determinant

Ridge regression is the alternative method to ordinary least squares, which is mostly applied when a multiple linear regression model presents a worrying degree of collinearity. A relevant topic in ridge regression is the selection of the ridge parameter, and different proposals have been presented in the scientific literature. Since the ridge estimator is biased, its estimation is normally based on the calculation of the mean square error (MSE) without considering (to the best of our knowledge) whether the proposed value for the ridge parameter really mitigates the collinearity. With this goal and different simulations, this paper proposes to estimate the ridge parameter from the determinant of the matrix of correlation of the data, which verifies that the variance inflation factor (VIF) is lower than the traditionally established threshold. The possible relation between the VIF and the determinant of the matrix of correlation is also analysed. Finally, the contribution is illustrated with three real examples.