Trait emotional intelligence: Evidence from italian adolescents and adults

Emotional intelligence (EI) represents an attribute of contemporary attractiveness for the scientific psychology community. Of particular interest for the present thesis are the conundrum related to the representation of this construct conceptualized as a trait (i.e., trait EI), which are in turn reflected in the current lack of agreement upon its constituent elements, posing significant challenges to research and clinical progress. Trait EI is defined as an umbrella personality-alike construct reflecting emotion-related dispositions and self-perceptions. The Trait Emotional Intelligence Questionnaire (TEIQue) was chosen as main measure, given its strong theoretical and psychometrical basis, including superior predictive validity when compared to other trait EI measures. Studies 1 and 2 aimed at validating the Italian 153-items forms of the TEIQue devoted to adolescents and adults. Analyses were done to investigate the structure of the questionnaire, its internal consistencies and gender differences at the facets, factor, and global level of both versions. Despite some low reliabilities, results from Studies 1 and 2 confirm the four-factor structure of the TEIQue. Study 3 investigated the utility of trait EI in a sample of adolescents over internalizing conditions (i.e., symptoms of anxiety and depression) and academic performance (grades at math and Italian language/literacy). Beyond trait EI, concurrent effects of demographic variables, higher order personality dimensions and non-verbal cognitive ability were controlled for. Study 4a and Study 4b addressed analogue research questions, through a meta-analysis and new data in on adults. In the latter case, effects of demographics, emotion regulation strategies, and the Big Five were controlled. Overall, these studies showed the incremental utility of the TEIQue in different domains beyond relevant predictors. Analyses performed at the level of the four-TEIQue factors consistently indicated that its predictive effects were mainly due to the factor Well-Being. Findings are discussed with reference to potential implication for theory and practice.

L'intelligenza emotiva in età evolutiva

Emotional Intelligence (EI) has increasingly gained widespread popularity amongst both lay people and scientists in a wide range of contexts and across several research areas. In spite of rigorous inquiry into its applications in educational, social, health and clinical settings, substantial disagreement exists regarding the definition of EI, with respect to both terminology and operationalizations. Actually, there is a consensus about a conceptual distinction between Trait EI, or trait emotional self-efficacy (Petrides & Furnham, 2001), and Ability EI, or cognitive-emotional ability (Mayer & Salovey, 1997). Trait EI is measured via self-report questionnaires, whereas Ability EI is assessed via maximum performance tests. Moreover, EI is the broadest of the emotional constructs, and it subsumes various constructs, as Emotional Awareness (Lane & Schwartz, 1987). To date, EI research has focused primarily on adults, with fewer studies conducted with child samples. The aim of the present study is to investigate the role of different models of EI in childhood and early adolescence (N = 670; 353 females; Mage= 10.25 years ; SD = 1.57). In addition, a further goal is to evaluate the relationship of each construct with personality, non verbal cognitive intelligence, school performance, peer relationships, and affective disorders (anxiety and depression). Results shows significant correlations between Trait EI and Emotional Awareness, whereas Trait and Ability EI appear as independent constructs. We also found significant positive associations between age and Ablity EI and Emotional Awareness (although with add of verbal productivity), while gender differences emerged in favour of females in all EI-related measures. The results provide evidence that Trait EI is partially determined by all of the Big Five personality dimensions, but independent of cognitive ability. Finally, the present study highlights the role of EI on social interactions, school performance and, especially, a negative relationship between Trait EI and psychopathology.

The relationship between eating behavior and psychological distress among overweight and obese people: is there a role for mindfulness?

This research based on 3 indipendent studies, sought to explore the nature of the relationship between overweight/obesity, eating behaviors and psychological distress; the construct of Mindful eating trough the validation of the Italian adaptation of the Mindful Eating Questionnaire (MEQ); the role of mindfulnessand mindful eating as respectively potential mediator and moderator between overeating behavior (binge eating and emotional overeating) and negative outcomes (psychological distress, body dissatisfaction). All the samples were divided in normal weight, overweight and obese according to BMI categories. STUDY1: In a sample of 691 subjects (69.6% female, mean aged 39.26 years) was found that BMI was not associated with psychological distress, whereas binge eating increases the psychopathological level. BMI and male gender represent negative predictors of psychological distress, but certain types of overeating (i.e., NES/grazing, overeating during or out of meals, and guilt/restraint) result as positive predictors.. STUDY 2 : A sample of 1067 subjects (61.4% female, mean aged 34 years) was analized. The Italian MEQ resulted in a 26-item 4-factor model measuring Disinhibition, Awareness, Distraction, and Emotional response. Internal consistency and test-retest reliability were acceptable MEQ correlated positively with mindfulness (FMI) and it was associated with sociodemographic variables, BMI, meditation. type of exercise and diet. STUDY 3, based on a sample of 502 subjects (68.8% female, mean aged 39.42 years) showed that MEQ and FMI negatively correlated with BES, EOQ, SCL-90-R, and BIAQ. Obese people showed lower level of mindful eating and higher levels of binge eating, emotional overeating, and body dissatisfaction, compared to the other groups Mindfulness resulted to partially mediates the relationship between a) binge eating and psychological distress, b) emotional overeating and psychological distress, c) binge eating and mental well-being, d) emotional overeating and menal well-being. Mindful eating was a moderator only in the relationship between emotional overeating and body dissatisfaction.

Modelling and classification with quantile-based distributions

In this work, we explore and demonstrate the potential for modeling and classification using quantile-based distributions, which are random variables defined by their quantile function. In the first part we formalize a least squares estimation framework for the class of linear quantile functions, leading to unbiased and asymptotically normal estimators. Among the distributions with a linear quantile function, we focus on the flattened generalized logistic distribution (fgld), which offers a wide range of distributional shapes. A novel naïve-Bayes classifier is proposed that utilizes the fgld estimated via least squares, and through simulations and applications, we demonstrate its competitiveness against state-of-the-art alternatives. In the second part we consider the Bayesian estimation of quantile-based distributions. We introduce a factor model with independent latent variables, which are distributed according to the fgld. Similar to the independent factor analysis model, this approach accommodates flexible factor distributions while using fewer parameters. The model is presented within a Bayesian framework, an MCMC algorithm for its estimation is developed, and its effectiveness is illustrated with data coming from the European Social Survey. The third part focuses on depth functions, which extend the concept of quantiles to multivariate data by imposing a center-outward ordering in the multivariate space. We investigate the recently introduced integrated rank-weighted (IRW) depth function, which is based on the distribution of random spherical projections of the multivariate data. This depth function proves to be computationally efficient and to increase its flexibility we propose different methods to explicitly model the projected univariate distributions. Its usefulness is shown in classification tasks: the maximum depth classifier based on the IRW depth is proven to be asymptotically optimal under certain conditions, and classifiers based on the IRW depth are shown to perform well in simulated and real data experiments.

Model reduction techniques in flexible multibody dynamics with application to engine cranktrain simulation

The development of a multibody model of a motorbike engine cranktrain is presented in this work, with an emphasis on flexible component model reduction. A modelling methodology based upon the adoption of non-ideal joints at interface locations, and the inclusion of component flexibility, is developed: both are necessary tasks if one wants to capture dynamic effects which arise in lightweight, high-speed applications. With regard to the first topic, both a ball bearing model and a journal bearing model are implemented, in order to properly capture the dynamic effects of the main connections in the system: angular contact ball bearings are modelled according to a five-DOF nonlinear scheme in order to grasp the crankshaft main bearings behaviour, while an impedance-based hydrodynamic bearing model is implemented providing an enhanced operation prediction at the conrod big end locations. Concerning the second matter, flexible models of the crankshaft and the connecting rod are produced. The well-established Craig-Bampton reduction technique is adopted as a general framework to obtain reduced model representations which are suitable for the subsequent multibody analyses. A particular component mode selection procedure is implemented, based on the concept of Effective Interface Mass, allowing an assessment of the accuracy of the reduced models prior to the nonlinear simulation phase. In addition, a procedure to alleviate the effects of modal truncation, based on the Modal Truncation Augmentation approach, is developed. In order to assess the performances of the proposed modal reduction schemes, numerical tests are performed onto the crankshaft and the conrod models in both frequency and modal domains. A multibody model of the cranktrain is eventually assembled and simulated using a commercial software. Numerical results are presented, demonstrating the effectiveness of the implemented flexible model reduction techniques. The advantages over the conventional frequency-based truncation approach are discussed.