Relationships Between Personality Features and the Rubber Hand Illusion: An Exploratory Study.

The rubber hand illusion paradigm allows investigating human body ownership by inducing an illusion of owning a life-sized fake hand. Despite the wide consensus on the fact that integration of multisensory signals is the main interpretative framework of the rubber hand illusion, increasing amount of data show that additional factors might contribute to the emergence of the illusion and, in turn, explain the strong inter-individual differences of the illusory patterns. Here, we explored whether and how personality features contribute to the emergence of the illusion by administering to healthy participants the rubber hand illusion paradigm along with two well-known personality tests, i.e., the Personality Assessment Inventory (PAI) and the Rorschach test. Results showed that two Rorschach domains (i.e., "Perception and Thinking Problems" and "Self and Other Representation") were positively correlated with the illusory mislocalization of the own left hand toward the fake hand. Further analyses suggested that while the tendency to perceive unconventionally is related to mislocalizing the own hand toward the fake hand, the association of the RHI index and other personality features measured by the Rorschach remain uncertain. However, our findings in general suggest that personality features might have a role in the emergence of the rubber hand illusion. This, in turn, could explain the high inter-individual variability of the illusory effects.

Italian adaptation of the brief modified experiences in close relationships scale in a sample of cancer patients: factor analysis and clinical implications.

Many previous studies have indicated that the attachment pattern developed during infancy shapes the adult attachment style, which in turn affects responses to stress and help-seeking behaviors. It may be relevant within clinical contexts to have easy-to-administer and rapid tools aimed to investigate attachment dimensions. The current study presents the Italian adaptation of the Brief Modified Experiences in Close Relationships (ECR-M16) - a self-reported measure of the attachment-style dimensions with reference to close others - and assesses its factorial structure. The questionnaire was administered to cancer outpatients. The number of factors to be extracted was calculated via parallel analysis. Subsequently, an exploratory factor analysis was run to calculate the first-order factor structure, which was compared to the original one via Procrustes rotation and Tucker's coefficient. Finally, a second-order factor structure was calculated by factor analyzing the first-order factor scores. The Italian adaptation of the ECR-M16 is characterized by a first-order factor structure comprising four factors, like the original. The degree of similarity between the two ranges between fair and dissimilar. The second-order factor structure comprises two higher order dimensions, like in the original study. Although partially similar, the two second-order factor structures show relevant differences. A clinically oriented discussion centered on the similarities and differences between the two factor structures is provided, along with indications for future studies.

An Interrater Reliability Study of Rorschach Performance Assessment System (R-PAS) Raw and Complexity-Adjusted Scores.

Recently, the Rorschach Performance Assessment System (R-PAS; Meyer, Viglione, Mihura, Erard, & Erdberg, 2011 ) was introduced to overcome some possible limitations of the Comprehensive System (CS; Exner, 2003 ) while continuing its efforts to link Rorschach inferences to their evidence base. An important, technical modification to the scoring system is that R-PAS interpretations are based on both standard scores and complexity-adjusted scores. Two previous U.S. studies reported good to excellent interrater reliability (IRR) for the great majority of R-PAS variables; however, IRR of complexity-adjusted scores has never been investigated. Furthermore, no studies have yet investigated R-PAS IRR in Europe. To extend this literature, we examined R-PAS IRR of Page 1 and Page 2 raw and complexity-adjusted scores with 112 Italian Rorschach protocols. We collected a large sample of both clinical and nonclinical Rorschach protocols, each of which was coded separately by 2 independent raters. Results demonstrated a mean intraclass correlation of .78 (SD = .14) for raw scores and.74 (SD = .14) for complexity-adjusted scores. Overall, for both raw and complexity-adjusted values, most of the variables were characterized by good to excellent IRR.

Investigating the need for complex vs. simple scenarios to improve predictions of aquatic ecosystem exposure with the SoilPlus model.

A spatially-explicit version of the recent multimedia fate model SoilPlus was developed and applied to predict the runoff of three pesticides in a small agricultural watershed in north-eastern Italy. In order to evaluate model response to increasing spatial resolution, a tiered simulation approach was adopted, also using a dynamic model for surface water (DynA model), to predict the fate of pesticides in runoff water and sediment, and concentrations in river water. Simulation outputs were compared to water concentrations measured in the basin. Results showed that a high spatial resolution and scenario complexity improved model predictions of metolachlor and terbuthylazine in runoff to an acceptable performance (R(2) = 0.64-0.70). The importance was also shown of a field-based database of properties (i.e. soil texture and organic carbon, rainfall and water flow, pesticides half-life in soil) in reducing the distance between predicted and measured surface water concentrations and its relevance for risk assessment.

Integration of an atmospheric dispersion model with a dynamic multimedia fate model: development and illustration.

Growing attention is devoted to understand the influence of the short-term variations in air concentrations on the environmental fate of semivolatile organic compounds (SVOCs) such as polycyclic aromatic hydrocarbons (PAHs). These variations are ascribable to factors such as temperature-mediated air-surface exchange and variability of planetary boundary layer (PBL) height and structure. But when investigating the fate of SVOCs at a local scale, further variability can derive from specific point source contributions. In this context, a new modeling approach (AirPlus) which integrates a previously developed model (AirFug) with an air dispersion model (AERMOD) is presented. The integrated model is illustrated for two PAHs in a Northern Italy scenario. Results show how chemical contributions deriving from background advective inflows, local emissions and a point source interact in an hourly-varying meteorological scenario to determine air concentration rapid changes and the consequent response of the soil compartment.

Modeling short-term variability of semivolatile organic chemicals in air at a local scale: an integrated modeling approach.

Monitoring campaigns from different locations have recently shown how air concentrations of persistent semivolatile contaminants such as polychlorinated biphenyls (PCBs) often exhibit short-term (less than 24 h) variations. The observed patterns have been ascribed to different factors, such as temperature-mediated air-surface exchange and variability of planetary boundary layer (PBL) height and dynamics. Here, we present a new modeling approach developed in order to investigate the short-term variability in air concentrations of organic pollutants at a local scale. A new dynamic multimedia box model is supplied by a meteorological preprocessor (AERMET) with hourly values of air compartment height and wind speed. The resulting model is tested against an existing dataset of PCB air concentrations measured in Zurich, Switzerland. Results show the importance of such modeling approach in elucidating the short- and long-term behavior of semivolatile contaminants in the air/soil system.

A dynamic model of the fate of organic chemicals in a multilayered air/soil system: development and illustrative application.

A new site-specific, dynamic model (SoilPlus) was developed to simulate the fate of nonionized organic chemicals in the air/litter/soil system; key features of the model are the double-layered air compartment interacting dynamically with multilayered litter and soil compartments, with seasonal dissolved organic carbon (DOC) fluxes. The model describes the soil environment calculating separate mass balances for water, chemical, and organic matter. SoilPlus underwent a process of benchmarking and evaluation in order to reach a satisfying confirmation of its predictive capability. Several simulations were performed to estimate the role of litter and DOC in affecting the fate of a model contaminant for POPs (hexachlorobenzene). The model shows that litter can behave as a buffer in the process of transferring hexachlorobenzene from air to the mineral soil and as a trap when hexachlorobenzene tends to move from a contaminated field toward clean air. DOC seems to behave as a leaching-enhancer in certain climatic conditions (heavy rainfall, high DOC concentrations), but it does not appear to move significant amounts of HCB in a year calculation.

Past, present, and future controls on levels of persistent organic pollutants in the global environment.

Understanding the legacy of persistent organic pollutants requires studying the transition from primary to secondary source control.