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Early stressful events negatively affect emotional and physical well-being. Cardiac vagal tone (CVT), which is associated with better emotional and physical well-being, usually gradually increase in early childhood. Nonetheless, children's CVT developmental trajectories are greatly variable, such that CVT can increase or decrease across the years. The present study examines the longitudinal effects of early stressful events and the role of 4 years CVT developmental trajectory on children's emotional and physical well-being. Forty-two 4-year-old children were enrolled. Number of stressful events and resting electrocardiogram (ECG) were collected at T1. ECG was registered again after one (T2), two (T3) and three (T4) years. Children's emotional and physical well-being were assessed at T4 through the Child Health and Illness Profile - Child Edition (CHIP-CE). CVT development was calculated as the angular coefficient, reflecting the developmental trajectory of CVT across the four timepoints. Results yielded that higher experienced stressful events predicted poorer emotional and physical well-being after 4 years. The interaction between the number of stressful events and CVT development emerged on physical well-being. Early stressful events negatively affect long-term children's emotional and physical well-being while a positive CVT development seems to mitigate the negative effects of early stressful events on physical well-being.

espanolRESUMEN La investigacion en EE.UU. ha demostrado que la mentoria juvenil es una estrategia prometedora para aumentar la autoestima y la conexion escolar en jovenes en situacion de riesgo. Sin embargo, ha habido escasa confirmacion de estos hallazgos a nivel internacional. El estudio actual evalua el impacto de la mentoria por parte de estudiantes universitarios capacitados en autoestima y conexion escolar de los ninos en comparacion con los companeros de escuela que no participaron en el programa. Mentor-UP es un programa de mentoria semanal llevado a cabo en la escuela y la comunidad que se implemento en el norte de Italia durante un periodo de siete meses. Los participantes (209 estudiantes, 34 en el grupo experimental y 175 en el grupo de comparacion de edades comprendidas entre 11 y 13 anos, 56% hombres, 27% inmigrantes) informaron de su nivel de autoestima y conexion escolar al principio y al final del programa. Los resultados mostraron un aumento significativo en la autoestima de los ninos mentorizados en comparacion con el grupo de control, mientras que la diferencia en la conexion escolar no fue significativa. Los hallazgos respaldan la efectividad de Mentor-UP para fomentar la autoestima de los jovenes. EnglishABSTRACT Research in the United States has shown that youth mentoring is a promising strategy for increasing self-esteem and school connectedness in at-risk youth. There has been little confirmation of those findings internationally. The current study evaluates the impact of mentoring by trained university students on children’s self-esteem and school connectedness compared to schoolmates not involved in the program. Mentor-UP is a school- and community-based weekly mentoring program implemented in northern Italy over a period of seven months. Participants (209 students – 34 in the experimental group and 175 in the comparison group – aged between 11 and 13, 56% male, 27% immigrants) reported their levels of self-esteem and school connectedness at the beginning and at the end of the program. Results showed a significant increase in mentees’ self-esteem compared to the control group, while the difference in school-connectedness was nonsignificant. The findings support the effectiveness of Mentor-UP in nurturing youth’s self-esteem.

Contains fulltext : 232434.pdf (Publisher’s version ) (Closed access) The complexity of homeless service users' characteristics and the contextual challenges faced by services can make the experience of working with people in homelessness stressful and can put providers' well-being at risk. In the current study, we investigated the association between service characteristics (i.e., the availability of training and supervision and the capability-fostering approach) and social service providers' work engagement and burnout. The study involved 497 social service providers working in homeless services in eight different European countries (62% women; mean age = 40.73, SD = 10.45) and was part of the Horizon 2020 European study "Homelessness as Unfairness (HOME_EU)." Using hierarchical linear modeling (HLM), findings showed that the availability of training and supervision were positively associated with providers' work engagement and negatively associated with burnout. However, results varied based on the perceived usefulness of the training and supervision provided within the service and the specific outcome considered. The most consistent finding was the association between the degree to which a service promotes users' capabilities and all the aspects of providers' well-being analyzed. Results are discussed in relation to their implications for how configuration of homeless services can promote social service providers' well-being and high-quality care.

Using a mouse-tracking technique, we measured the strength and the temporal unfolding of the conflict when people categorize objectified and nonobjectified human stimuli in the human or object category. We recorded participants’ hand movements when they categorized male and female, objectified and nonobjectified, human, and doll-like stimuli in the person and object categories. As expected, objectified women created a stronger categorization conflict compared to all other human stimuli. The nature of the mouse trajectories indicated that this response competition was caused by the distractor (object category) rather than the target (person category) and showed to be smooth rather than abrupt suggesting dynamic competition between the object–human categories rather than the sequential unfolding of a dual process. These findings demonstrate that the human–object divide fades when women (but not men) are objectified. The implications of the current findings for theorizing on processes of sexual objectification are discussed.

Emotion regulation plays a crucial role in an individual's well-being, as it is known that deficits in regulating emotions can lead to psychological and psychiatric disorders. Cognitive reappraisal is widely considered to be an adaptive and effective emotion-regulation strategy. People are more or less able to apply it, but it is still not clear how reappraisal affects brain structures and the psychological profile of individuals. In our study we thus aimed to explore the impact of applying reappraisal at both the neural and the psychological level. Source-based morphometry (SBM), a whole-brain multivariate method based on the Independent Component Analysis that extracts patterns of covariation of gray matter ("independent networks"), was applied to the MRI images of 37 participants. In order to enrich their psychological profiles, we measured their experienced affectivity (PANAS) and their empathic abilities (IRI). Based on the frequency of applying reappraisal (ERQ), participants were divided into low and high reappraisers (18 vs. 19). An independent source of gray matter emerged as being different between the groups: specifically, low reappraisers showed more gray matter volume concentration in a network including the frontal, temporal, and parietal regions as compared to high reappraisers. At the psychological level, low reappraisers reported a more strongly experienced negative affect, while no difference among reappraisers emerged with regard to empathic abilities. Capitalizing on a multivariate method for structural analysis that is innovative in this field, this study extends previous observations on individual differences in the ability to regulate emotions, and it describes a plausible impact of reappraisal on brain structures and affectivity.

Mouse tracker methodology has recently been advocated to explore the motor components of the cognitive dynamics involved in experimental tasks like categorization, decision-making, and language comprehension. This methodology relies on the analysis of computer-mouse trajectories, by evaluating whether they significantly differ in terms of direction, amplitude, and location when a given experimental factor is manipulated. In this kind of study, a descriptive geometric approach is usually adopted in the analysis of raw trajectories, where they are summarized with several measures, such as maximum-deviation and area under the curve. However, using raw trajectories to extract spatial descriptors of the movements is problematic due to the noisy and irregular nature of empirical movement paths. Moreover, other significant components of the movement, such as motor pauses, are disregarded. To overcome these drawbacks, we present a novel approach (EMOT) to analyze computer-mouse trajectories that quantifies movement features in terms of entropy while modeling trajectories as composed by fast movements and motor pauses. A dedicated entropy decomposition analysis is additionally developed for the model parameters estimation. Two real case studies from categorization tasks are finally used to test and evaluate the characteristics of the new approach.

Recent technological advances have provided new settings to enhance individual-based data collection and computerized-tracking data have became common in many behavioral and social research. By adopting instantaneous tracking devices such as computer-mouse, wii, and joysticks, such data provide new insights for analysing the dynamic unfolding of response process. ssMousetrack is a R package for modeling and analysing computerized-tracking data by means of a Bayesian state-space approach. The package provides a set of functions to prepare data, fit the model, and assess results via simple diagnostic checks. This paper describes the package and illustrates how it can be used to model and analyse computerized-tracking data. A case study is also included to show the use of the package in empirical case studies.

Every day cognitive and experimental researchers attempt to find evidence in support of their hypotheses in terms of statistical differences or similarities among groups. The most typical cases involve quantifying the difference of two samples in terms of their mean values using the t statistic or other measures, such as Cohen's d or U metrics. In both cases the aim is to quantify how large such differences have to be in order to be classified as notable effects. These issues are particularly relevant when dealing with experimental and applied psychological research. However, most of these standard measures require some distributional assumptions to be correctly used, such as symmetry, unimodality, and well-established parametric forms. Although these assumptions guarantee that asymptotic properties for inference are satisfied, they can often limit the validity and interpretability of results. In this article we illustrate the use of a distribution-free overlapping measure as an alternative way to quantify sample differences and assess research hypotheses expressed in terms of Bayesian evidence. The main features and potentials of the overlapping index are illustrated by means of three empirical applications. Results suggest that using this index can considerably improve the interpretability of data analysis results in psychological research, as well as the reliability of conclusions that researchers can draw from their studies.

BACKGROUND The Wechsler Intelligence Scale for Children - Fourth Edition often produces floor effects in individuals with intellectual disability. Calculating respondents' Z or age-equivalent scores has been claimed to remedy this problem. METHOD The present study applied these methods to the Wechsler Intelligence Scale for Children - Fourth Edition scores of 198 individuals diagnosed with intellectual disability. Confirmatory factor analysis and profile analysis were conducted using a Bayesian approach. RESULTS The intelligence structure in intellectual disability resembled the one previously reported for typical development, suggesting configural but not metric invariance. When Z or age-equivalent scores (but not traditional scaled scores) were used, the average profile resembled the one previously reported for other neurodevelopmental disorders. CONCLUSIONS Both methods avoided any floor effects, generating similar but not identical profiles. Despite some practical and conceptual limitations, age-equivalent scores may be easier to interpret. This was true even for a subgroup of individuals with more severe disabilities (mean IQ

Recent research on the crossmodal integration of visual and auditory perception suggests that evaluations of emotional information in one sensory modality may tend toward the emotional value generated in another sensory modality. This implies that the emotions elicited by musical stimuli can influence the perception of emotional stimuli presented in other sensory modalities, through a top-down process. The aim of this work was to investigate how crossmodal perceptual processing influences emotional face recognition and how potential modulation of this processing induced by music could be influenced by the subject’s musical competence. We investigated how emotional face recognition processing could be modulated by listening to music and how this modulation varies according to the subjective emotional salience of the music and the listener’s musical competence. The sample consisted of 24 participants: 12 professional musicians and 12 university students (non-musicians). Participants performed an emotional go/no-go task whilst listening to music by Albeniz, Chopin, or Mozart. The target stimuli were emotionally neutral facial expressions. We examined the N170 Event-Related Potential (ERP) and behavioral responses (i.e., motor reaction time to target recognition and musical emotional judgment). A linear mixed-effects model and a decision-tree learning technique were applied to N170 amplitudes and latencies. The main findings of the study were that musicians’ behavioral responses and N170 is more affected by the emotional value of music administered in the emotional go/no-go task and this bias is also apparent in responses to the non-target emotional face. This suggests that emotional information, coming from multiple sensory channels, activates a crossmodal integration process that depends upon the stimuli emotional salience and the listener’s appraisal.

In this article, we provide initial findings regarding the problem of solving likelihood equations by means of a maximum entropy (ME) approach. Unlike standard procedures that require equating the score function of the maximum likelihood problem at zero, we propose an alternative strategy where the score is instead used as an external informative constraint to the maximization of the convex Shannon&rsquo, s entropy function. The problem involves the reparameterization of the score parameters as expected values of discrete probability distributions where probabilities need to be estimated. This leads to a simpler situation where parameters are searched in smaller (hyper) simplex space. We assessed our proposal by means of empirical case studies and a simulation study, the latter involving the most critical case of logistic regression under data separation. The results suggested that the maximum entropy reformulation of the score problem solves the likelihood equation problem. Similarly, when maximum likelihood estimation is difficult, as is the case of logistic regression under separation, the maximum entropy proposal achieved results (numerically) comparable to those obtained by the Firth&rsquo, s bias-corrected approach. Overall, these first findings reveal that a maximum entropy solution can be considered as an alternative technique to solve the likelihood equation.

In benchmarking studies with simulated data sets in which two or more statistical methods are compared, over and above the search of a universally winning method, one may investigate how the winning method may vary over patterns of characteristics of the data or the data-generating mechanism. Interestingly, this problem bears strong formal similarities to the problem of looking for optimal treatment regimes in biostatistics when two or more treatment alternatives are available for the same medical problem or disease. It is outlined how optimal data-analytic regimes, that is to say, rules for optimally calling in statistical methods, can be derived from benchmarking studies with simulated data by means of supervised classification methods (e.g., classification trees). The approach is illustrated by means of analyses of data from a benchmarking study to compare two different algorithms for the estimation of a two-mode additive clustering model.

Reading is vital to every aspect of modern life, exacerbated by reliance of the internet, email, and social media on the written medium. Developmental dyslexia (DD) characterizes a disorder in which the core deficit involves reading. Traditionally, DD is thought to be associated with a phonological impairment. However, recent evidence has begun to suggest that the reading impairment in some individuals is provoked by a visual processing deficit. In this paper, we present WISC-IV data from more than 300 Italian children with a diagnosis of DD to investigate the manifestation of phonological and visual subtypes. Our results indicate the existence of two clusters of children with DD. In one cluster, the deficit was more pronounced in the phonological component, while both clusters were impaired in visual processing. These data indicate that DD may be an umbrella term that encompasses different profiles. From a theoretical perspective, our results demonstrate that dyslexia cannot be explained in terms of an isolated phonological deficit alone; visual impairment plays a crucial role. Moreover, general rather than specific accounts of DD are discussed.

Olfactory perception is affected by cross-modal interactions between different senses. However, although the effect of cross-modal interactions for smell have been well investigated, little attention has been paid to the facilitation expressed by haptic interactions with a manipulation of the odorous object’s shape. The aim of this research is to investigate whether there is a cortical modulation in a visual recognition task if the stimulus is processed through an odorous cross-modal pathway or by haptic manipulation, and how these interactions may have an influence on early visual-recognition patterns. Ten healthy non-smoking subjects (25 years ± 5 years) were trained to have a haptic manipulation of 3-D models and olfactory stimulation. Subsequently, a visual recognition task was performed during an electroencephalography recording to investigate the P3 Event Related Potentials components. The subjects had to respond on the keyboard according to their subjective predominant recognition (olfactory or haptic). The effects of haptic and olfactory condition were assessed via linear mixed-effects models (LMMs) of the lme4 package. This model allows for the variance related to random factors to be controlled without any data aggregation. The main results highlighted that P3 increased in the olfactory cross-modal condition, with a significant two-way interaction between odor and left-sided lateralization. Furthermore, our results could be interpreted according to ventral and dorsal pathways as favorite ways to olfactory crossmodal perception.