Background: Autism spectrum disorders (ASDs) are characterized by differences in socio-pragmatic communication. These conditions are allocated within a “spectrum” of phenotypic variability. Virtual reality (VR) is a useful tool for healthcare intervention and particularly safely advancing social abilities in children with ASD. Methods: In our study two types of intervention for improving social skills were compared: (i) emotional training obtained by the use of virtual reality (Gr1), (ii) traditional emotional training performed individually with a therapist (Gr2). We aimed to identify the intervention with the shortest acquisition time for the proposed social tasks. Results: Our findings show that both types of intervention had the same acquisition time for the recognition of primary emotions. However, for the use of primary and secondary emotions, the group using VR showed shorter acquisition times. Conclusions: These findings together with previous preliminary datasuggest that VR can be a promising, dynamic and effective practice for the support of basic and complex social skills of these individuals.

Introduction: Autism Spectrum Disorder (ASD) is a by-birth neurodevelopmental disorder difficult to diagnose owing to the lack of clinical objective and quantitative measures. Classical diagnostic processes are time-consuming and require many specialists’ collaborative efforts to be properly accomplished. Most recent research has been conducted on automated ASD detection using advanced technologies. The proposed model automates ASD detection and provides a new quantitative method to assess ASD.Methods: The theoretical framework of our study assumes that motor abnormalities can be a potential hallmark of ASD, and Machine Learning may represent the method of choice to analyse them. In this study, a variational autoencoder, a particular type of Artificial Neural Network, is used to improve ASD detection by analysing the latent distribution description of motion features detected by a tablet-based psychometric scale.Results: The proposed ASD detection model revealed that the motion features of children with autism consistently differ from those of children with typical development.Discussion: Our results suggested that it could be possible to identify potential motion hallmarks typical for autism and support clinicians in their diagnostic process. Potentially, these measures could be used as additional indicators of disorder or suspected diagnosis.

While the negative impact of COVID-19 total lockdown on mental health in youth has been extensively studied, findings collected during subsequent waves of the pandemic, in which restrictive rules were more eased, are very sparse. Here, we explore perceived psychological distress during the partial lockdown of the third wave in Southern Italy in a large sample of students, focusing on age and gender differences. Also, we assessed whether attending the type of education could have a protective role on students’ psychological well-being. An online survey was completed by 1064 southern Italian students (age range: 8–19 years; males = 368) from March to July 2021. The survey consists of a set of questions regarding general sociodemographic information as well as several aspects of students’ psychological well-being. Psychological distress was higher in high school students compared to both elementary and middle ones. In addition, we found gender differences, but only in high school students, with females reporting higher psychological distress than males. Finally, our mediation analysis showed a mediated role of face-to-face schooling in the relationship between age and psychological distress. In conclusion, this study highlights age-related differences in psychological distress during the pandemic and the protective role of school in presence for mental health in Italian students.

Autism spectrum disorders represent a heterogeneous group of clinical situations, and are mainly represented by a deficit of social communication. In this study, we compare two strategies to enhance communicative/social skills, namely self-video modeling and peer video modeling. The subjects were divided into two groups treated via the method of self-video modeling (group 1) or peer video modeling (group 2). For both groups of subjects affected by ASD-HF (Autism Spectrum Disorder-high-functioning), three different activities were proposed: (a) interacting with a salesperson while making a purchase, (b) initiating and maintaining a conversation with peers, and (c) starting and maintaining an enjoyable activity with a peer. The ability to rapidly accomplish the task was used as the main criteria to appraise the groups’ responses to the proposed activities. In group 1, the use of self-video modeling procedures demonstrated a faster and correct execution of the three proposed tasks (especially task 3) when compared to group 2. In group 2, the use of peer video modeling has instead led to a slower acquisition of abilities to process and perform the tasks. The use of self-video modeling speeds up the acquisition of skills to perform communicative/social tasks, compared to peer video modeling’s slower performance in subjects with ASD-HF. Results could be related to either the amount of time the subject is exposed to the task or to the capacity of ASD-HF subjects to self-value one’s own actions more than others. In our work, we have tried to reset the differences in exposure time. Therefore, self-video modeling is demonstrated to be more effective, as it produces a response to the signification/mirroring characteristic of ASD-HF.

In the recent literature, there is a broad consensus on the effectiveness of Applied Behavior Analysis interventions for autism spectrum disorder (ASD). Despite their proven efficacy, research in clinical settings shows that these treatments are not equally effective for all children and the issue of which intervention should be chosen for an individual remains a common dilemma. The current work systematically reviewed studies on predictors and moderators of response to different types of evidence-based treatment for children with ASD. Specifically, our goal was to critically review the relationships between pre-treatment child characteristics and specific treatment outcomes, covering different aspects of functioning (i.e., social, communicative, adaptive, cognitive, motor, global functioning, play, and symptom severity). Our results questioned the binomial “better functioning-better outcome”, emphasizing the complex interplay between pre-treatment child characteristics and treatment outcomes. However, some pre-treatment variables seem to act as prerequisites for a specific treatment, and the issue of “what works for whom and why” remains challenging. Future research should focus on the definition of evidence-based decision-making models that capture those individual factors through which a specific intervention will exert its effects.