A deep learning latent variable model to identify children with autism through motor abnormalities.

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.

Age-Related Differences in Psychological Distress during the COVID-19 Pandemic.

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.

Examining Predictors of Different ABA Treatments: A Systematic Review.

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.

Children on the Autism Spectrum and the Use of Virtual Reality for Supporting Social Skills.

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.

Using Technology to Identify Children With Autism Through Motor Abnormalities.

Autism is a neurodevelopmental disorder typically assessed and diagnosed through observational analysis of behavior. Assessment exclusively based on behavioral observation sessions requires a lot of time for the diagnosis. In recent years, there is a growing need to make assessment processes more motivating and capable to provide objective measures of the disorder. New evidence showed that motor abnormalities may underpin the disorder and provide a computational marker to enhance assessment and diagnostic processes. Thus, a measure of motor patterns could provide a means to assess young children with autism and a new starting point for rehabilitation treatments. In this study, we propose to use a software tool that through a smart tablet device and touch screen sensor technologies could be able to capture detailed information about children's motor patterns. We compared movement trajectories of autistic children and typically developing children, with the aim to identify autism motor signatures analyzing their coordinates of movements. We used a smart tablet device to record coordinates of dragging movements carried out by 60 children (30 autistic children and 30 typically developing children) during a cognitive task. Machine learning analysis of children's motor patterns identified autism with 93% accuracy, demonstrating that autism can be computationally identified. The analysis of the features that most affect the prediction reveals and describes the differences between the groups, confirming that motor abnormalities are a core feature of autism.

Phantom Phone Signal: why it should be of interest for psychiatry.

Phantom Phone Signal (PPS) refers to the false perception of a mobile phone ringing, vibrating and blinking, when in fact it did not. A recent literature about PPS is growing, parallel to an increasing interest about its possible psychopathological implications. The present review aims to synthesize the current knowledge about the phenomenon, and to present a conceptual framework that integrates PPS as a putative index of psychopathology. Furthermore, we propose possible directions for further research. The phenomenon seems highly prevalent, irrespective of age and gender, although estimates are still inconsistent. We have analysed possible factors associated to PPS, disentangling them in person-related (i.e. characteristics of individuals who experience PPS) and phone use-related factors (i.e., time spent using the phone, time of the mobile in vibrating mode, the carrying location of the device, average number of call/message in a day, etc). Literature regarding the association between PPS and mental illness is limited, as most of the samples are not clinical and too sectorial. Preliminary data suggest that anxiety/depression and stress-related problems seem to be the psychopathological background favouring the experience of PPS. Despite PPS is a common phenomenon, it usually do not seem to significantly impact the people's quality of life. However, they deserve attention, given the huge diffusion of phone mobiles, particularly in children and adolescents, as it may be an index for emotional or stress-related difficulties. Future studies are needed to better clarify its frequency and its possible impact on everyday life. Studies in clinical samples may further clarify its psychopathological implications.

On the Edge Between Digital and Physical: Materials to Enhance Creativity in Children. An Application to Atypical Development.

The 4 P's creativity model (person, process, press, and product) underlines how creativity is strongly connected with the materials employed to conceive and realize a creative outcome. As a multiform construct, it invites a wide variety of approaches to the study of it. One of the most promising ways to address this issue is to connect it with cognitive development and related educational pathways, as creativity can be enhanced and stimulated in every child, leading to an improvement both at personal and societal level. Even if creativity is recognized and highly valued, there is still a lack of methods which can stimulate creativity in an effective way. Useful hints may come from the outstanding contributions of Piaget and Montessori who underlined that interaction with the physical world is a fundamental building block for cognitive development. In this paper, starting from these fixed points, we describe some creativity enhancing methods for children which give importance to the edge between digital and physical materials. Digital materials open new ways to the use and integration of physical materials with hybrid platforms which can be used in educational contexts. Together with this perspective we provide a description of the application of these methodologies to enhance creativity in children with Autistic Spectrum Disorder.

Emotional Education in Early Onset Schizophrenia and Asperger's Syndrome.

In this study, we aim to verify how emotional training can improve empathy and theory of mind (ToM) in patients diagnosed with early onset schizophrenia and Asperger's syndrome. The study design includes 100 subjects divided into two experimental groups and two control groups. The two experimental groups followed a rational emotive behavior therapy (REBT) protocol. The two control groups instead underwent cognitive behavioral psychotherapy training. Analysis of Variance (ANOVA) was applied to analyze the difference between the Asperger's syndrome (AS) and early onset schizophrenia (EOS) groups, pre and post training. Our analysis shows that the AS group improved post emotional training but only when emotions were internalized, as demonstrated by the improvement of the scores in the post-treatment eye test (ET) but not in the emotional quotient (EQ) test. The EOS group instead showed post-training improvement, not only concerning skills leading to internalizing emotions but also in empathy, as demonstrated by the improvement of EQ and Reflective Functioning Questionnaire (RFQ) test scores. These scores remained lower than in the control group. Finally, our findings reveal that the value of the treatment was more considerable for the EOS group than for the AS group due to the improvement in first- and second-order ToM skills and an improvement of empathic skills in the first group, followed by the group comprising AS subjects. In the AS group, the treatment only favored the enhancement of first-order ToM skills; however, this improved quality of life and social adaptation.

Video Modeling and Social Skills Learning in ASD-HF.

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.