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Adolescents' mental health and well-being is a public health concern. We examined gender differences in stress, psychological distress and well-being and predictors of distress and well-being in adolescent boys and girls. A cross-sectional study with a sample of 954 Spanish adolescents aged between 13 and 17 years was conducted. All participants were assessed through questionnaires that measure psychological distress, eudaimonic well-being, life satisfaction, stress, coping styles, masculine/instrumental and feminine/expressive traits, self-esteem and social support. We find that girls scored higher than boys in psychological distress, chronic stress, minor daily hassles, social support, eudaimonic well-being and in feminine-expressive trait whereas boys scored higher than girls in detachment coping style and in masculine-instrumental trait. Hierarchical multiple regression analysis revealed that the most relevant variable in the psychological distress of both girls and boys was higher emotional coping style, followed by higher number of life events during the previous year. The most relevant variables in boys' and girls' psychological well-being were higher self-esteem and social support. Higher scores in rational coping style and in masculine/instrumental trait were also important predictors of eudaimonic well-being in adolescent boys and girls. Furthermore, in boys, older age was associated with greater distress and lower well-being and life satisfaction, while, as for the girls, a smaller number of life events and greater emotional coping style were associated with lower eudaimonic well-being and life satisfaction. Results are relevant for the design of policies and programs aimed at promoting mental health and well-being in adolescence. [ABSTRACT FROM AUTHOR]

The objective of this study was to analyze the neurostructural abnormalities of brain areas responsible for the acquisition and maintenance of fear in small animal phobia by comparing gray matter volume (GMV) in individuals with phobia and non-fearful controls. Structural magnetic resonance imaging was obtained from 62 adults (79% female) assigned to one of two groups: 31 were diagnosed with small animal phobia and 31 were non-fearful controls. To investigate structural alterations, a whole-brain voxel-based morphometry analysis was conducted to compare the GMV of the brain areas involved in fear between both groups. The results indicated that individuals with a small animal specific phobia showed smaller GMV in cortical regions, such as the orbitofrontal (OFC) and medial frontal cortex, and greater GMV in the putamen than non-fearful controls. These brain areas are responsible for avoidant behavior (putamen) and emotional regulation processes or inhibitory control (prefrontal cortex (PFC)), which might suggest a greater vulnerability of phobic individuals to acquiring non-adaptive conditioned responses and emotional dysregulation. The findings provide preliminary support for the involvement of structural deficits in OFC and medial frontal cortex in phobia, contributing to clarify the neurobiological substrates for phobias. [ABSTRACT FROM AUTHOR]

Gender and psychological well-being in older adults - ERRATUM Gender differences, social support, erratum, health aging Keywords: gender differences; social support; health aging; erratum EN gender differences social support health aging erratum 309 309 1 10/07/22 20220301 NES 220301 The above article (Matud I et al. i , 2020) published with Juan Manuel Bethencourt's name appearing incorrectly. [Extracted from the article]

Specific phobia represents an anxiety disorder category characterized by intense fear generated by specific stimuli. Among specific phobias, small animal phobia (SAP) denotes a particular condition that has been poorly investigated in the neuroscientific literature. Moreover, the few previous studies on this topic have mostly employed univariate analyses, with limited and unbalanced samples, leading to inconsistent results. To overcome these limitations, and to characterize the neural underpinnings of SAP, this study aims to develop a classification model of individuals with SAP based on gray matter features, by using a machine learning method known as the binary support vector machine. Moreover, the contribution of specific structural macro‐networks, such as the default mode, the salience, the executive, and the affective networks, in separating phobic subjects from controls was assessed. Thirty‐two subjects with SAP and 90 matched healthy controls were tested to this aim. At a whole‐brain level, we found a significant predictive model including brain structures related to emotional regulation, cognitive control, and sensory integration, such as the cerebellum, the temporal pole, the frontal cortex, temporal lobes, the amygdala and the thalamus. Instead, when considering macro‐networks analysis, we found the Default, the Affective, and partially the Central Executive and the Sensorimotor networks, to significantly outperform the other networks in classifying SAP individuals. In conclusion, this study expands knowledge about the neural basis of SAP, proposing new research directions and potential diagnostic strategies. [ABSTRACT FROM AUTHOR]