Family Structure and Subjective Economic Well-Being: Some New Evidence

The paper investigates the main socio-demographic and economic determinants of subjective economic well-being in different typologies of households. Previous studies have used dummy variables to explore the effect of family structure. In this paper, however four different models—one for each family typology—have been estimated to test if each selected explanatory variable is significant and how it acts in determining the level of subjective economic well-being. To achieve this, we apply an under-used logit model—the partial proportional ordered model. Our analysis, based on data from the 2005 Italian Survey on Income and Living Conditions highlights the main variables affecting the subjective economic well-being of all household typologies. These main variables are related to income adequacy, such as being able to afford housing, clothes and holidays, and also include the work-status and level of education of the respondent. These variables produce notable differences in the level of subjective economic well-being. We find that couples with no children have the highest level of perceived economic well-being, while couples with two or more children and even more so one-person households are more economically insecure.     

Family Network Support and Mental Health Recovery

Family members often provide critical support to persons living with a serious mental illness. The focus of this study was to determine which dimensions of the family support network were most important to the recovery process from the perspective of the recovering person. Consumers of a community mental health program completed in-depth structured interviews that included separate measures of social network support and recovery. Consumers named an average of 2.6 family members on the social network, interacted with family on a weekly basis, and were quite satisfied with their contact. This study revealed that support and reciprocity with family members are important dimensions of a personal support network that relates to the recovery process.     

Spaces of Pride: A Visual Ethnography of Gay Pride Parades in Italy and the United Kingdom

Gay pride parades represent an active site of production of lesbian, gay, bisexual, transgender (LGBT), intersexual and queer identities, featuring a spatial and social articulation of political and human rights claims. While the multiplication of these events in different countries suggests the existence of a coherent and cohesive community which shares the same collective identity beyond national borders, different patterns in the organisation, part-taking and social and political connotations given to these events can be observed in different contexts. By means of a comparative visual ethnography of Italian and British Gay Pride Parades, this article investigates how the creation, mobilisation and challenge of quasi-normative LGBT identities occur within the spatial context of gay pride marches. It is argued, in particular, that while gay pride parades are sites in which the socio-political status quo can be successfully challenged, participants are also faced with the possibility of falling prey to dynamics of identity commodification and homonationalism which may ultimately deprive their claims of their subversive potential.     

Therapeutic Assessment with Children in Family Therapy

Therapeutic Assessment with Children (TA‐C) is a brief semi‐structured intervention in which psychological assessment is used to help families with children and adolescents to change. In this paper we introduce the TA‐C model, describe its semi‐structured format and exemplify how it can be applied by family therapists.     

Physical activity is inversely related to drug consumption in elderly patients with cardiovascular events

Elderly patients with cardiovascular events are characterized by high drug consumptions. Whether high drug consumptions are related to physical activity is not known. In order to examine whether physical activity is related to drug consumption in the elderly, patients older than 65 years (n?=?250) with a recent cardiovascular event were studied. Physical activity was analyzed according to the Physical Activity Scale for the Elderly (PASE) score and related to drug consumption. PASE score was 72.4?±?45.0 and drug consumption was 8.3?±?2.2. Elderly patients with greater comorbidity took more drugs (8.7?±?2.1) and are less active (PASE?=?64.4?±?50.6) than patients with Cumulative Illness Rating Scale severity score higher than 1.8 than those with a score lower than 1.8 (76.3?±?41.4, p?<?0.05, and 8.0?±?2.0, p?=?0.006, respectively). Multivariate analysis correlation confirmed that PASE score is negatively associated with drug consumption (β?=??0.149, p?=?0.031), independently of several variables including comorbidity. Thus, physical activity is inversely related to drug consumption in elderly patients with cardiovascular events. This inverse relationship may be attributable to the high degree of comorbidity observed in elderly patients in whom poor level of physical activity and high drug consumption are predominant.     

Contrasting the Gini and Zenga indices of economic inequality

The current financial turbulence in Europe inspires and perhaps requires researchers to rethink how to measure incomes, wealth, and other parameters of interest to policy-makers and others. The noticeable increase in disparities between less and more fortunate individuals suggests that measures based upon comparing the incomes of less fortunate with the mean of the entire population may not be adequate. The classical Gini and related indices of economic inequality, however, are based exactly on such comparisons. It is because of this reason that in this paper we explore and contrast the classical Gini index with a new Zenga index, the latter being based on comparisons of the means of less and more fortunate sub-populations, irrespectively of the threshold that might be used to delineate the two sub-populations. The empirical part of the paper is based on the 2001 wave of the European Community Household Panel data set provided by EuroStat. Even though sample sizes appear to be large, we supplement the estimated Gini and Zenga indices with measures of variability in the form of normal, t-bootstrap, and bootstrap bias-corrected and accelerated confidence intervals.     

Assessing the pattern of covariance matrices via an augmentation multiple testing procedure

This paper extends the scedasticity comparison among several groups of observations, usually complying with the homoscedastic and the heteroscedastic cases, in order to deal with data sets laying in an intermediate situation. As is well known, homoscedasticity corresponds to equality in orientation, shape and size of the group scatters. Here our attention is focused on two weaker requirements: scatters with the same orientation, but with different shape and size, or scatters with the same shape and size but different orientation. We introduce a multiple testing procedure that takes into account each of the above conditions. This approach discloses a richer information on the data underlying structure than the classical method only based on homo/heteroscedasticity. At the same time, it allows a more parsimonious parametrization, whenever the patterned model is appropriate to describe the real data. The new inferential methodology is then applied to some well-known data sets, chosen in the multivariate literature, to show the real gain in using this more informative approach. Finally, a wide simulation study illustrates and compares the performance of the proposal using data sets with gradual departure from homoscedasticity.     

Heterogeneity,school-effects and the North/South achievement gap in Italian secondary education: evidence from a three-level mixed model

With the aim of assessing the extent of the differences in the context of Italian educational system, the paper applies multilevel modeling to a new administrative dataset, containing detailed information for more than 500,000 students at grade 6 in the year 2011/2012, provided by the Italian Institute for the Evaluation of Educational System. Data are grouped by classes, schools and geographical areas. Different models for each area are fitted, in order to properly address the heteroscedasticity of the phenomenon. The results show that it is possible to estimate statistically significant “school effects”, i.e., the positive/negative association of attending a specific school and the student’s test score, after a case-mix adjustment. Therefore, the paper’s most important message is that school effects are different in terms of magnitude and types in the three geographical macro areas (Northern, Central and Southern Italy) and are dependent on specific students’ and schools’ characteristics.     

Functional principal component analysis for the explorative analysis of multisite–multivariate air pollution time series with long gaps

The knowledge of the urban air quality represents the first step to face air pollution issues. For the last decades many cities can rely on a network of monitoring stations recording concentration values for the main pollutants. This paper focuses on functional principal component analysis (FPCA) to investigate multiple pollutant datasets measured over time at multiple sites within a given urban area. Our purpose is to extend what has been proposed in the literature to data that are multisite and multivariate at the same time. The approach results to be effective to highlight some relevant statistical features of the time series, giving the opportunity to identify significant pollutants and to know the evolution of their variability along time. The paper also deals with missing value issue. As it is known, very long gap sequences can often occur in air quality datasets, due to long time failures not easily solvable or to data coming from a mobile monitoring station. In the considered dataset, large and continuous gaps are imputed by empirical orthogonal function procedure, after denoising raw data by functional data analysis and before performing FPCA, in order to further improve the reconstruction.